Report on current availability and methodology for natural risk map

ARMONIA PROJECT (Contract n° 511208)

APPLIED MULTI-RISK MAPPING OF NATURAL HAZARDS

FOR IMPACT ASSESSMENT

DELIVERABLE 2.1

Report on current availability and methodology for natural risk mapproduction

Zuzana Boukalova, Jakub Heller

Ceske Centrum pro Strategicka Studia (CCSS), Water Management Department

Prague, 30 June 2005

Project funded by the European Community under the:

SUSTAINABLE DEVELOPMENT, GLOBAL CHANGE AND ECOSYSTEMS

ARMONIA - Applied multi Risk Mapping of Natural Hazards for Impact Assessment

Report on current availability and methodologyfor natural risk map production (Del. 2.1)

Overview

Del. 2.1 collected the state-of-art for individual natural risk assessment

methodologies for different risk categories applied either by scientific

community or administrative end-users. Considered risks were:

o Floods

o Earthquakes

o Landslides

o Forest fires

o Volcanic activities

o Meteorological extreme events and climate change, as well as

o Possible secondary effects of natural hazard discussed by the

example of groundwater pollution.

The report on the results of the analysis consists of an introduction, the

collection of the state-of-the art for risk assessment methodologies for each

identified natural event, and a summary of state-of-the art of current

methodologies for individual risk assessment methodologies for different

risk categories.

Each singular report on a natural event is following a common structure.

The goal of the proposed research activity was to be the basis for the

further research on the harmonisation of existing methodologies, data

availability, technological tools and outputs, for the benefit of end users,

achieving a practical result that can optimise the deployment of resources

(financial, human, technological) and improve disaster mitigation and

prevention. A risk assessment process for each natural hazard event was

defined, always in the view of its integration into land planning.

Specific methodologies and spatial resolutions were identified,

corresponding to three different scales. The main differences between the

three approaches, apart from the spatial resolution, are as follows:

• the Susceptibility approach, is developed at regional scale (ranging from

1/100,000 to 1/1,000,000): definition of areas prone to impacts of

natural events and probability of occurrence in discrete categories (e.g.

high, medium, low).

• the Hazard approach, is developed at local scale (ranging from 1/2,000

to 1/10,000): the probability that a specific event may occur in a given

area within a given time window.

• the Site Engineering approach, is developed at site scale (ranging from

1/100 to 1/1000): suited to direct the work needed to reduce risk.

Main findings:

The state of art and the experience of ARMONIA Workpackage 2 in the field

of hazard and risk assessment clearly showed that spatial planning is

dealing with a multi-scale approach: spatial (regional, local general, local

detailed), return period for hazard assessment (short, medium, long),

methodology (susceptibility i.e qualitative, hazard i.e. diagnostic, site i.e.

prognostic).

ARMONIA PROJECT

Contract n° 511208

WP2: Collection and evaluation of currentmethodologies for risk map production

Del. 2.1

Report on current availability and methodologyfor natural risk map production

Project funded by the European Community under the:

SUSTAINABLE DEVELOPMENT, GLOBAL CHANGE AND ECOSYSTEMS

ARMONIA PROJECT (Contract n° 511208) Deliverable 2.1

A–II

Contract Number: 511208

Project Acronym: ARMONIA

Title:

Applied multi Risk Mapping of Natural Hazards for Impact Assessment

Deliverable N°: 2.1

Due date: 30th May 2005

Delivery date: 7th June 2005

Short Description:

Del. 2.1 is collecting the state-of-art for individual natural risk assessment

methodologies for different risk categories applied either by scientific

community or administrative end-users. Considered risks are: floods,

earthquakes, landslides, forest fires, volcanic activities, meteorological

extreme events and climate change, as well as possible secondary effects

of natural hazard discussed by the example of groundwater pollution.

Partners owning: CR4 (CCSS)

Partner contributed: CO1 (T6), CR5 (UNINA), CR7 (HRW), CR9 (EC-

JRC), CR10 (PIK), CR11 (POLIMI)

Made available to: All project partners and EC

Versioning

Version Date Name, organization

0.1 03.05.2005 First stable draft version for internal reviewers,

Zuzana Boukalova, CCSS

1.1 12.05.2005 Second stable draft version, Zuzana Boukalova,

CCSS

1.2 18.05.2005 Third stable draft version, Zuzana Boukalova,

CCSS

2.0 30.06.2006 Final version, Jakub Heller, CCSS

Quality check

Internal Reviewers:

1st Internal Reviewer: Adriana Galderisi, UNINA

2nd Internal Reviewer: Peter Bobrowsky, GSC

3rd Internal Reviewer: Daniele Spizzichino, T6


A–III

Table of contents

A. INTRODUCTION

B. STATE-OF-THE-ART FOR INDIVIDUAL RISKSASSESSMENT METHODOLOGIES FOR DIFFERENT RISKCATEGORIES

B.I Floods

B.II Earthquakes

B.III Landslides

B.IV Forest fire

B.V Volcanoes

B.VI. Meteorological extreme events and climatechange

B.VII Possible secondary effects of natural hazardsas example of groundwater pollution

C. SUMMARY - Collection and evaluation of currentmethodologies for risk map production


A–IV

A. Introduction

The main goal of WP 2 was to analyse the state-of-the art for individual

risks assessment methodologies for different risk categories.

The following natural events were studied, selected according to their

diffusion and importance throughout Europe:

• Floods

• Earthquakes

• Landslides

• Forest fire

• Volcanoes

• Meteorological extreme events and climate change

• Possible secondary effects of natural hazards as example of

groundwater pollution

Deliverable 2.1 reports on the results of the analysis and consists of the

following three main parts:

o Part A: Introduction

o Part B: Collection of the state-of-the art for risk assessment

methodologies for each identified natural event

o Part C: Summary of state-of-the art of current methodologies for

individual risk assessment methodologies for different risk categories.

For the singular reports of each natural event of Part B a common

template was used:

Template

Definition of risk (Physical definition of the natural phenomena)

• Typology

• Intensity Magnitude and Severity

Hazard assessment

• Definition of hazards

• Current methodologies for analysing representation of risks

(hazard) with respect to temporal scale

• Data typology, format and avalability

• Example of hazard maps

Element at risk and exposure (Meaning the population, buildings and

engineering works, economic activities, public services utilities,


A–V

infrastructure and environmental features in the area potentially affected

by risk)

• Typology of elements

• Definition of exposure

Analysis of vulnerability (Characteristic of a system that describes its

potential to be harmed. This can be considered as a combination of

susceptibility and value)

• Definition of vulnerability and/or consequence

• Methodologies for assessment related to structural and non-

structural elements at risk

Analysis of risk (a methodology to objectively determine risk by combining

probabilities and consequences or, in other words, combining hazards and

vulnerabilities).

• Definition of risk

• Methodologies for risk analysis assessment

• Examples of risks maps and legends

• Risk managament

Appendix:

Minimum standard (simplified model) for hazard mapping aimed at a legal

directive

o Various methodologies related to the 3 assumed scales of analysis

in the light of a potential harmonisation of hazard maps, based on a

multi-hazard perspective

Minimum standard (simplified model) for risk mapping aimed at spatial

planning

o Multi-risk assessment perspective as element of the Strategic

Environmental Assessment

o Methodologies, functions and outputs

Vulnerability and/or consequence functions

Risk functions

Legends

Specific methodologies and spatial resolutions were identified,

corresponding to three different scales. The main differences between the

three approaches, apart from the spatial resolution, are as follows:

• the Susceptibility approach, is developed at regional scale (ranging

from 1/100,000 to 1/1,000,000): definition of areas prone to

impacts of natural events and probability of occurrence in discrete

categories (e.g. high, medium, low).


A–VI

• the Hazard approach, is developed at local scale (ranging from

1/2,000 to 1/10,000): the probability that a specific event may

occur in a given area within a given time window.

• the Site Engineering approach, is developed at site scale (ranging

from 1/100 to 1/1000): suited to direct the work needed to reduce

risk.

The goal of the proposed research activity was to be the basis for the

further research on the harmonisation of existing methodologies,

data availability, technological tools and outputs, for the benefit of

end users, achieving a practical result that can optimise the deployment of

resources (financial, human, technological) and improve disaster

mitigation and prevention. A risk assessment process for each natural

hazard event was defined, always in the view of its integration into land

planning.


B–I

B. STATE-OF-THE-ART FOR INDIVIDUALRISKS ASSESSMENT METHODOLOGIESFOR DIFFERENT RISK CATHEGORIES


B.I-1

B.I Floods

Author: Darren Lumbroso, HRW

1 Definition of floods ..................................................4

1.1 Typologies....................................................................... 4

1.2 Flood magnitude, intensity and severity .............................. 4

1.2.1 Annual probability of exceedence ............................................ 4

1.2.2 Return period ....................................................................... 6

2 Hazard assessment..................................................6

2.1 Definition of flood hazard .................................................. 6

2.2 Current methods for analysing and representation of hazard

with respect to temporal scales............................................... 6

2.2.1 Background .......................................................................... 6

2.2.2 The link between flood hazard and flood risk: The Source -

Pathway - Receptor - Consequence model ............................... 6

2.3 Methods for assessing flood hazard .................................... 7

2.3.1 Information on historical floods............................................... 7

2.3.2 Soil maps ............................................................................. 7

2.3.3 Aerial photography................................................................ 8

2.3.4 Satellite imagery................................................................... 8

2.3.5 Catchment scale modelling..................................................... 8

2.3.6 Detailed hydrological and hydraulic modelling .......................... 8

2.4 Assessment of the flood hazard at different spatial scales ..... 8

2.4.1 National flood hazard assessment ........................................... 8

2.4.2 Regional or catchment scale flood hazard assessment ............... 9

2.4.3 Local scale flood hazard assessment........................................ 9

2.4.4 Assessment of coastal floods ................................................ 10

2.5 Dynamic nature of flood hazard – climate change and other

effects .......................................................................... 11


B.I-2

2.6 Data typology, format and availability .............................. 11

2.6.1 Fluvial floods ...................................................................... 12

2.6.2 Coastal floods ..................................................................... 12

2.7 Examples of flood hazard maps........................................ 12

3 Elements at risk and exposure ............................... 18

3.1 Typology of elements ..................................................... 18

3.2 Definition of exposure..................................................... 18

4 Analysis of vulnerability ........................................ 19

4.1 Definition of vulnerability and/or consequence ................... 19

4.2 Methodologies for assessment related to structural and non-

structural elements at risk............................................... 19

4.2.1 Assessment for structural elements - economic damage to

properties .......................................................................... 19

4.2.2 Assessment for non-structural elements – agriculture and people

......................................................................................... 20

4.2.3 Functions for vulnerability/consequence analysis .................... 22

4.2.4 Examples of vulnerability maps............................................. 24

5 Analysis of risk...................................................... 25

5.1 Definition of risk ............................................................ 25

5.2 Units of risk................................................................... 26

5.3 Future flood risk ............................................................ 26

5.3.1 Climate change................................................................... 27

5.3.2 Change in values of assets ................................................... 27

5.3.3 Improved flood warning ....................................................... 27

5.3.4 Changes to flood mitigation measures ................................... 27

5.3.5 Changes in land use ............................................................ 28

5.4 Methodologies for risk analysis assessment ....................... 29

5.4.1 Qualitative and quantitative methods .................................... 29


B.I-3

5.4.2 Functions of risk analysis ..................................................... 29

5.4.3 Examples of risk maps and legends....................................... 35

6 Risk management.................................................. 38

6.1 Generic risk management options .................................... 38

6.1.1 Controlling the source.......................................................... 38

6.1.2 Controlling the pathway....................................................... 38

6.1.3 Controlling the exposure ...................................................... 38

6.1.4 Examples of controlling vulnerability ..................................... 38

6.2 Significance of risk ......................................................... 38

7 Glossary of all keywords........................................ 41

8 References ............................................................ 44

Appendix: Operational standards for risk assessment

aimed at spatial planning ........................................... 45

1. Simplified model for flood hazard mapping aimed at a legal

directive ....................................................................... 45

1.1. Methodologies related to the three assumed scales of analysis

in the light of a potential harmonisation of hazard maps,based on a multi-hazard perspective.............................. 46

2. Simplified model for risk mapping aimed at spatial planning 47

2.1. Multi-risk assessment perspective as element of the Strategic

Environmental Assessment ........................................... 48

2.2. Methodologies, functions and outputs............................. 48


B.I-4

1 Definition of floodsThe term flood can be defined in many ways. In the context of this report a

flood will be defined as “a general and temporary condition of partial or

complete inundation of dry land caused by the overflow of the boundaries of

a water body or by the rapid accumulation of surface water runoff”. This can

be put more succinctly as “a temporary covering of land by water outside its

normal confines”.

1.1 TypologiesFloods may be classified by their various causes, speed of onset and

potential damage. The following broad categories of flood causes are often

recognised:

• Flash floods that build up rapidly and lowland or plains floods which

have a slower and more predictable onset;

• Floods from the precipitation in a rainfall event (pluvial floods) or from

stored water as snowmelt;

• Floods from natural events and those from the failure of flood defence

infrastructure or “dam breaks”;

• Flooding directly from raised groundwater and the contribution

antecedent moisture conditions to increasing runoff rates

• Flooding from inadequate surface water drainage in urban areas (urban

floods) and from minor watercourses and roadside ditches;

• Tidal surges and other marine conditions leading to coastal and estuarial

flooding (coastal floods).

Table 1.1 shows the major types of flood and how they may be categorised.

1.2 Flood magnitude, intensity and severityThe magnitude of a flood can be defined by its relative size and frequency.

The size of a flood is generally measured in terms of its flow or discharge.

The common unit of discharge in rivers is cubic metres per second (m3/s).

The magnitude of a flood is usually described in terms of either:

• An annual probability of exceedence;

• Return period.

It should be noted that floods are not normally described in terms of their

“intensity” or “severity”. In some parts of the world (e.g. the USA) flood

severity categories have been developed. These are qualitative categories

such as “Major flooding – extensive inundation of structures and roads.

Significant evacuation of people required”.

1.2.1 Annual probability of exceedenceThe annual probability of exceedence of a flood is the probability of a

particular condition, usually a maximum flow or water level, occurring

within any given year. For example a flood with a 1% annual probability of

exceedance has a 1 in 100 chance of occurring in any one year.

B.I-5

ARM

ON

IA P

RO

JECT (C

ontra

ct n

° 5

11208) D

eliv

era

ble

2.1

Table 1.1 Flood typologies

Type of flood Type or

frequency ofevent

Number of

propertiesaffected

Geographic distribution Type of damage Type of mitigation

Coastal Winter season 1 to 500?

Major towns andcities may give

larger numbers

Coastal

fringe/estuary/mappedflood risk zone

Flooding possible over largelengths of coast (for

example 1953 storm)

Inundation damage to buildings and contents

Possible loss of life (in excess of 3,000 in 1953)Campsites and caravan parks particularly vulnerable

Vehicles written off

Hard defence measures

Soft engineereddefences

Storm-tide warningservice

Land use regulation

River (fluvial) Winter seasonSummer storms

1 to 500?Major towns and

cities may givelarger numbers

River floodplainFlooding in one or more

river catchments at any onetime

Inundation damage to buildings and contents,vehicles written off, possible structural damage

Possible loss of life – especially in flash floods (forexample Lynmouth, 1952 or Sarno, 1997)

Deep flooding possible behind raised defencesCampsites and caravan parks particularly vulnerable

Hard defence measuresFlood storage

Flood warning serviceLand use regulation

Groundwater Prolonged seasonsof rainfall

Small clusters Certain geologies (forexample limestone, chalk)

Outside main riverfloodplain

Inundation damage to buildings and contentsespecially basements

None?

Water mains

burst

Any time Small clusters Anywhere Inundation damage to buildings and contents

especially basements

None?

Sewerage Any time Isolated or Small

clusters

Anywhere



especially basements

Asset renewal by water

service providers

Storm/

highwaydrainage

Intense storms –

especially insummer

Isolated or Small

clusters

Anywhere adjacent to roads

or urban areas


Possibly vehicle accidents

None

Overland flow Prolonged heavy

rainfall

Isolated Hills?


Inundation damage to buildings and contents None

Dam break Rare 1 to over 1,000? Specific river valleys


Inundation damage to buildings and contents,

vehicles written off, destruction of buildings,destruction of bridges, major infrastructure disrupted

Potential significant loss of life within 25 km of dam

Monitoring on-site.

Risk management byowners

Minor water-courses

1 to 20 plus? Outside main riverfloodplain

Inundation damage to buildings and contents Land use regulationHard defence measures


B.I-6

1.2.2 Return periodThe return period of a flood describes the frequency with which a particular

condition (for example maximum flow or water level) is, on average, likely

to be equalled or exceeded. It is normally expressed in years and is

therefore the reciprocal of the annual exceedence frequency. It is not a

reciprocal of the annual probability of exceedence – although this is a

reasonable approximation at higher return periods.

For example a “1 in 100 year flood” describes a flood event that has a

approximately a 1% annual probability of being equalled or exceeded in any

given year. This does not mean such a flood will occur only once in one

hundred years. Whether or not it occurs in a given year has no bearing on

the fact that there is still about a 1% chance of a similar occurrence in the

following year.

2 Hazard assessment

2.1 Definition of flood hazardA hazard may be defined as “a situation with the potential to result in

harm”. A hazard does not necessarily lead to harm, but identification of a

hazard does mean that there is a possibility of harm occurring. In the

context of flooding, a flood hazard exists in areas where flooding can occur.

2.2 Current methods for analysing and representationof hazard with respect to temporal scales

2.2.1 BackgroundTo evaluate flood hazard fully, the following is needed:

• The areal extent of the floodwater;

• The depth of the floodwater;

• Speed of onset of the flooding;

• The velocity of the flow in the floodplain;

• How often the floodplain will be covered by water;

• The length of time the floodplain will be covered by water;

• At what time of year flooding can be expected.

In many cases flood hazard maps only show the flood extent for a

particular annual probability of flooding or return period.

2.2.2 The link between flood hazard and flood risk: The Source- Pathway - Receptor - Consequence model

The method used to estimate the flood hazard is linked to the way in which

flood risk is to be assessed. For example, if the flood risk to people is to be

assessed then a flood hazard may need to be assessed in terms of flood

depths and velocities. However, if flood risk is to be estimated in terms of

economic damage to buildings then the flood hazard is usually established

in terms of the floodwater depth and the duration of the inundation.


B.I-7

To understand the link between hazard and risk it is useful to consider the

commonly adopted Source-Pathway-Receptor-Consequence model. This is a

simple conceptual tool for representing systems and processes that lead to

a particular consequence. For a flood risk to arise there must be flood

hazard that consists of a 'source' or initiator event (i.e. high rainfall); a

'receptor' (e.g. houses or people in the floodplain); and a pathway between

the source and the receptor (e.g. overland flow). This conceptual model is

shown in Figure 2.1.

A hazard does not automatically lead to a harmful outcome, but

identification of a hazard does mean that there is a possibility of

harm occurring.

Source: Reference 1

Figure 2.1 Source – Pathway – Receptor – Consequence

conceptual model

2.3 Methods for assessing flood hazardThis section will concentrate on methods that are used to assess the flood

hazard in terms of its extent and depth. It should be noted that to assess

some types of flood risk other aspects of the flood hazard such as the

floodplain velocity and the duration for which the floodplain is inundated

need to be estimated.

2.3.1 Information on historical floodsHistorical flood information from major flood events that have occurred in

the past can be used to produce flood hazard maps. Information on

historical floods may range from local to national in its coverage. Flood

hazard maps based on historical flood events often do not identify the

probability associated with a flood event.

2.3.2 Soil mapsSoil maps can provide information on soil series associated with river, lake,

wetland and tidal deposition. They can be useful in determining the

historical floodplain at geological time-scales but do not provide any


B.I-8

indication of event probability. Raised beaches provide an example of how

soil data can mislead, as these were created by isostatic uplift and may be

several metres above any current flood level.

2.3.3 Aerial photographyIf a historical flood was particularly large and of sufficient duration to permit

mobilisation of aircraft then aerial photography may have been carried out

by an organisation with an interest in flooding (for example a river

management organisation or news media). This will provide information on

areas that flooded during the particular flood being photographed although

the magnitude of the flood (expressed in terms of probability of occurrence)

may not be known.

2.3.4 Satellite imageryMicrowave and optical satellite imaging of selected river reaches can be

used to detect flood conditions and produce flood extents. The limitation of

flood maps based on historical events is described above.

2.3.5 Catchment scale modellingCatchment scale hydrological and hydraulic modelling is used when

assessing flood hazard at the scale of a hydrological catchment or river

basin. This is described in Section 2.4.2.

2.3.6 Detailed hydrological and hydraulic modellingDetailed hydrological and hydraulic modelling is usually used when

assessing the flood hazard at a relatively small scale e.g. less than

1:10,000. This approach is discussed in Section 2.4.3.

2.4 Assessment of the flood hazard at different spatialscales

2.4.1 National flood hazard assessmentAn effective method of producing national flood hazard maps is to use a

digital terrain model (DTM) of the whole country combined with estimates of

design flood water levels at various locations. In some European countries

Synthetic Aperture Radar (SAR) have been mounted on an aircraft to

produce a DTM of the whole country with a good vertical resolution (for

example ±0.5 m). A DTM produced using airborne SAR has been used to

produce a national flood hazard map of the UK showing flood extents for the

1 in 100 and 1 in 1,000 year floods.

The steps in producing a national flood hazard map via this method are as

follows:

1 Establish the magnitude of the floods to be mapped (for example the

1 in 100 year flood);

2 Estimate the peak flows for the defined floods at any point along the

rivers in the country. This could be done by catchment modelling or

statistical analysis of flow data;


B.I-9

3 Produce a DTM of the country with a sufficiently accurate vertical

resolution;

4 Estimate the water level for the defined flood at any point along the

rivers. This may require the use of a hydraulic model;

5 Use the DTM in combination with the water levels for the defined

flood to delineate the flood extent and estimate flood depths. This is

usually carried out using a Geographical Information System (GIS).

2.4.2 Regional or catchment scale flood hazard assessmentTo estimate flood hazard at a catchment or river basin level a catchment

scale model is required. The model should be able to predict water levels at

any location in the catchment for a variety of conditions. Water levels

depend on river flows, which in turn depend on inflows from sub-

catchments. The broad scale catchment model must be able to represent:

• Rainfall-runoff processes, to predict inflows from sub-catchments;

• Flood hydrographs throughout the catchment including:

- Attenuation as flood waves move along a river;

- Combination of flood hydrographs at confluences and other lateral

inflows;

• Water levels at selected points in the catchment.

Table 2.1 outlines the modelling methods to estimate catchment flood

hazard.

Table 2.1 Catchment modelling methods

Method Method for flood

flow prediction

Method for flood level

prediction

‘Simple hydrological

routing’

Rainfall-runoff

modelling and flow

routing

Rating curves, derived

from a hydrological

routing model

‘Enhanced

hydrological routing’

Rainfall-runoff

modelling and flow

routing

Rating curves, derived

from detailed hydraulic

models

‘Sparse

hydrodynamic

modelling’

Rainfall-runoff

modelling

Hydrodynamic model with

minimal number of nodes

or cross-sections

A DTM is used together with the design water levels to delineate the flood

extent and depths, within a GIS environment.

2.4.3 Local scale flood hazard assessment

At a local scale (e.g. less than 1:10,000), for example when a flood hazard

assessment is required for a new housing development, flood mitigation

scheme or small scale planning detailed hydrological and hydraulic

modelling is required. The steps in this process are summarised below.

Step 1 Topographic survey of the watercourse and floodplain


B.I-10

The upstream and downstream limits of the survey should be defined by the

objectives of the flood hazard assessment. The cross-sections surveyed

should be representative of the watercourse channel and floodplain. The

spacing between cross sections is determined by the nature of the

watercourse (for example width, channel depth, slope). Survey data of any

hydraulically significant structures are also required (for example, weirs,

bridges, flood walls).

Step 2 Hydrological assessment

A hydrological assessment of the flood flows should be made using

appropriate methodology and design inflows for the model produced. These

are usually in the form of a hydrograph.

Step 3 Construction of a hydraulic model

A full hydrodynamic model should be constructed if the area contains either

structures whose operation varies with time (for example pumps, sluices,

tidal outfalls) or a tidal estuary. In other cases, either a steady-state or

hydrodynamic model may be chosen. However, a steady-state hydraulic

model may give an overestimation of water levels where significant storage

is present.

Step 4 Calibration and verification of the modelling

Wherever practicable, the hydrological assessment and the hydraulic model

should be calibrated against recorded flows and/or water levels from

observed flood events. If calibration is carried out, at least one separate

observed event should be run through the model after the calibration to

verify the adjustment of parameters.

Step 5 Estimate the design flood water levels

The design flood water levels are estimated for the required return periods.

A commonly used return period is the 1 in 100 year flood.

Step 6 Delineate the flood extent

The flood extent and depth should then be delineated using the design flood

water levels and a DTM.

2.4.4 Assessment of coastal floods

The assessment of coastal floods is similar at national, regional and local

scales. The primary steps involved are as follows:

Step 1 Setting up tide levels and wave overtopping rates

Probability distributions of the tide levels and wave overtopping rates at

particular coasts are evaluated. After that, time series data of tide levels

and wave overtopping rates are set up to correspond to the respective

maximums in the target period for hazard maps.

Step 2 Prediction of coastal dike failure

The time of coastal dike failure is determined based on the destruction of

the defence with the time series data of wave overtopping rate.


B.I-11

Step 3 Flood simulation

Inundation depth, velocity of flood flow, and flood arrival time in coastal

zones are estimated by numerical simulation, taking the time series data of

tide level and wave overtopping rate, and the time of coastal dike failure

into account. A GIS is usually used to map the flood extent and depth.

Figure 2.2 shows a schematic diagram that outlines the method for

assessing coastal floods.

Wave

overtopping rate

Coastal

flood

dike

Inundation

depth

Inundation extent

Tidal level

Setting of tide

level and wave

overtopping rate

Figure 2.2 Example of method used to assess coastal flood extent and

depth

2.5 Dynamic nature of flood hazard – climate changeand other effects

Allowances for the affect of climate change on the flood hazard are

generally taken into account as follows:

• Fluvial floods – A factor is applied to the peak design flow. For

example, in the UK for some catchments initial research has shown that

under a “high emissions” scenario, peak flows could increase by up to

20% by the year 2050. Hence, using the precautionary principle, in the

UK peak flood flows are often increased by 20% to estimate the “worst

case” 2050 climate change fluvial flood hazard and risk scenarios;

• Coastal floods – When estimating future coastal flooding future

increases in sea level rise are taken into account. For the UK the “worst

case” sea level rise vary from 4 mm to 6 mm per year depending on the

part of the coastline. These figures are used to estimate the worst case

coastal flooding scenarios under climate change.

The flood hazard can also change for a number of other reasons for

example deterioration of flood defences, geomorphological changes such as

the reduction in capacity of a river channel owing to siltation or weed

growth, or the construction of infrastructure such as dam.

2.6 Data typology, format and availability


B.I-12

2.6.1 Fluvial floodsThe type of data required for fluvial flood hazard mapping will vary

depending on the scale at which the hazard assessment is being carried out

and how the risk is to be quantified. However, key data requirements are as

follows:

• Topographic data at a suitable resolution, for example:

- Surveyed river cross-sections;

- Surveyed floodplain sections;

- Photogrametric data or contour maps;

- Digital terrain model (DTM);

• Hydrological and hydrometric data:

- Design and historical rainfall data;

- Design and historical river flow data;

- Details of hydrological gauging stations;

• Surveys of structures that have an impact on floodwater levels,

for example:

- Weirs;

- Bridges and culverts;

- Dams and reservoirs;

- Flood defences and walls;

• Calibration and verification data from previous floods, for

example:

- Observed water levels;

- Observed flows.

The data format should be compatible with the hydrological and hydraulic

models as well as the GIS software being used to delineate the flood extent.

The availability of the above data will vary depending on the catchment and

watercourse. In some catchments the data will be readily available in others

it may have to be collected. The quantity and type of data available will

affect the method used to estimate the hazard.

2.6.2 Coastal floodsThe type of data required for coastal flood hazard mapping includes:

• Topographic data at a suitable resolution in the form of a DTM;

• Surveys of coastal flood defences if these are in place;

• Fragility curves for coastal flood defences to assess their probability of

failure;

• Extreme sea levels, for a range of return periods;

• Tidal information.

2.7 Examples of flood hazard mapsExamples of flood hazard maps are given below. Figures 2.3 to 2.13 show

examples of flood maps from England, The Czech Republic, France, Italy

and Germany that have been produced at different scales and using a

variety of different methods.


B.I-13

Source: Reference 2

Figure 2.3 Example of a national flood hazard map for the River Thames

in England showing two high return period floods

Source: Reference 3

Figure 2.4 Example of a flood map showing water depth for a flood on the

River Elbe in Prague


B.I-14

Source: Reference 4

Figure 2.5 Example of a catchment scale 1 in 100 year flood extent and

depth map using a 50 m x 50 m DTM of the catchment

Source: Reference 5

Figure 2.6 Example of a flood hazard map in London for a 1 in 1000 year

flood event with climate change used in a flood risk to people assessment


B.I-15

Legend

Probabil ity of inundation

High

Medium

Low

Source: Reference 6

Figure 2.7 Example of a qualitative flood hazard map used in England

Source: Reference 3

Figure 2.8 Example of a flood extent generated for Prague by three

different methods


B.I-16

Figure 2.9 Example of a flood extent between Belleville and Villefranche in

France for a flood that occurred on 27 March 2001 using radar data

Figure 2.10 Part of a flood map in the Tagliamento basin, Italy based on a

flood that occurred on 15 November 1996


B.I-17

Figure 2.11 Flood extent map for Dresden, Germany based on the 2002

floods with a 50 m buffer round the extent

km

Source: Reference 7

Figure 2.12 Flood map for the Hague and Rotterdam in the Netherlands

showing flood depths assuming a breach in the flood defences


B.I-18

Source: Reference 8

Figure 2.13 Coastal flood map for the Gretna in Scotland

3 Elements at risk and exposure

3.1 Typology of elementsThe elements at risk are the receptors. These can be broadly classified as

follows:

• The built environment, for example commercial and residential

properties, schools, hospitals;

• People;

• Transport links for example roads and railways;

• Agriculture including crops, land and machinery;

• Amenity and recreation facilities for example parks and footpaths;

• Natural environment for example wetlands and salt marshes.

3.2 Definition of exposureExposure refers to the receptors (for example, the people, assets and

activities) threatened or potentially threatened by a hazard. Exposure may

be defined as the “quantification of the receptors that may be influenced by

a flood (for example, number of people and their demographics, number

and type of properties)”. It is important to note that exposure typically

refers to quantities of receptors.


B.I-19

4 Analysis of vulnerability

4.1 Definition of vulnerability and/or consequenceVulnerability may be defined as the “characteristic of a system that

describes its potential to be harmed. This can be considered as a

combination of susceptibility and value”. Consequence can be defined as

“ an impact such as economic, social or environmental

damage/improvement that may result from a flood. It may be expressed

quantitatively (e.g. by. monetary value), by category (e.g. High, Medium,

Low) or descriptively”. Vulnerability is often captured in the assessment of

the consequences of flooding

The consequences of flooding are usually assessed in terms of the

following:

• Economic damage to assets, for example residential and commercial

properties, or agricultural land;

• Injuries or deaths to people.

4.2 Methodologies for assessment related to structuraland non-structural elements at risk

4.2.1 Assessment for structural elements - economic damageto properties

The economic damage caused by flooding to commercial and residential

properties is a normally assessed by estimating the flood hazard in terms of

the following two parameters:

• Depth of floodwater;

• Duration of flooding.

To estimate the economic damage for properties a relationship is required

between floodwater depth and economic damage. A generic example of

such a relationship is shown in Figure 4.1.

The data required to estimate economic damage for properties:

• Type of property (for example, school, office, library, workshop);

• Location of each property referenced to a national grid system;

• Floor area of each property;

• Threshold level of each property. This is the level at which the

property becomes inundated by floodwater;

• Floodwater level versus economic damage curve for each type of

property;

• Depth and duration of flooding for a number of design return period

floods.


B.I-20

Figure 4.1 Generic floodwater depth versus economic damage curve used

to assess economic damage to a property

It should be noted that considerable amounts of data are required to

estimate economic damage to residential and commercial properties.

4.2.2 Assessment for non-structural elements – agriculture andpeople

AgricultureThe economic damage caused to agriculture by flooding is often

several orders of magnitude less than the economic damage caused

to properties. Economic damage to an arable crop is difficult to establish

as it is a function of a number of variables including:

• Crop yield and price;

• The cost of seeds, fertilisers and agro-chemicals for the crop;

• Pollution of the land, for example by chemicals or saline water;

• The cost for the post flood clean up.

The minimum data requirements to assess agricultural economic damage

caused by floods is:

• Classification of agricultural land into different categories (for

example in terms of general crop types);

• Typical crop rotations that are used;

• Extent of flooding for a number of design return periods;

• Duration of the flooding;

• Seasonality of the flooding;

• Economic damage incurred by different agricultural land use

classes.


B.I-21

PeopleThe number of people injured or killed during a flood is another method by

which the flood risk can be assessed. A recent research project in the UK

found that the number of people injured within a given zone that is at risk

of flooding can be expressed as follows:

Ninj = function (Nz, FHR, AV, PV)

Where:

Ninj is the number of people;

Nz is the number of people in the flood hazard zone at ground or basement

level;

FHR is the flood hazard rating. This is a function of floodwater depth,

velocity and debris;

AV is the area vulnerability. This is a function of the effectiveness of flood

warning, the speed of onset of flooding and the nature of the area (for

example the type of buildings)

PV is the people vulnerability. This is a function of the age and health of the

people living in a particular flood hazard zone.

The number of fatalities caused a flood, Nfat, can be expressed as a follows:

Nfat = function (Ninj, FHR)

Hence to assess the flood risk to people the following has to be assessed:

• Flood hazard with respect to people;

• Number of people in the flood hazard zone;

• The area vulnerability;

• The people vulnerability.

To assess the risk to people posed by floods, the flood hazard is often

estimated in terms of the following:

• Depth of floodwater (m);

• Velocity of the floodwater in the floodplain (m/s)

• The amount of debris in the water.

A simple method of establishing the flood hazard rating (HR) used in the UK

is given by the formula:

HR = d(v + 1.5) + DF

Where:

HR is the flood hazard rating;

d is the depth of the floodwater in the floodplain in metres;

v is the velocity of the floodwater in the floodplain in metres/second;

DF is a debris factor. The debris factor has a value of 0, 1 or 2. The debris

factor is a function of land use, flood depth and velocity.

A flood hazard map is required that provides information on the conditions

that harm people during a flood event. The way this is done is dependent


B.I-22

on the scale at which the analysis is carried out. The flood hazard, with

respect to people, is categorised as follows:

• Low – caution;

• Moderate – dangerous for some people (for example the elderly and

children);

• Significant – dangerous for most people;

• Extreme – dangerous for all people.

Area vulnerabilityThe vulnerability of a particular area to floods, with respect to people may

be expressed as follows:

AV = function (SO, NA, FW)

Where:

AV is the Area Vulnerability;

SO is the Speed of Onset of the flood. This may vary from a few minutes to

several hours;

NA is the Nature of the Area. For example areas with mainly multi-storey

apartments would be classed as low risk areas, whereas areas comprising

parks or mobile homes would be classed as high risk;

FW is the Flood Warning and is a function of the coverage, warning time

and action taken.

People vulnerabilityVulnerability of people to flooding in a particular area may be expressed as

a function of the percentage of the residents over 75 years of age and the

percentage of residents suffering from long-term illnesses.

4.2.3 Functions for vulnerability/consequence analysis

EconomicThe flood risk in terms of economic damage is usually expressed in terms of

the Annualised Average Damage (AAD). The AAD is normally calculated

separately for properties and agriculture.

The standard procedure for this is as follows:

(i) Assess the economic damage caused by flooding for a number of

return periods to allow a sufficiently accurate probability versus

economic damage curve to be constructed.

(ii) Integrate the area under the probability versus economic damage

curve to give the annualised average damage.


B.I-23

(iii) A typical probability versus economic damage curve used to

assess annualised average damage is shown in Figure 4.2. A

number of considerations are critical to the accuracy of the

calculation of annualised average damage. These are:

• It is vital that the threshold of flooding is correctly defined. This is as the

return period at which flood damage just begins;

• It is important that the probability versus economic damage curve is

described by a number of points exceeding four, so that errors of

interpolation are not excessive.

In general it has been found that economic damage needs to be estimated

for the 1 in 5, 1 in 10, 1 in 25, 1 in 100 and 1 in 200 year return period

floods to accurately estimate annualised average damage. It should be

noted that where there is a high level of protection against flooding a higher

return period flood (for example, a 1 in 1000 year return period).

When interpreting the flood risk in terms of annualised average damage

(AAD), it should be noted that the AAD could be large in two contrasting

situations as follows:

• When the consequence (i.e. economic damage) is large but the

probability of the flood event is low. This is when high economic

damage occurs from an event with a large return period i.e. many

thousands of properties might be affected by a flood with a return period

of 1 in 1,000 years;

• When the probability of a flood occurring is high and economic

damage is low i.e. a small number of properties could be affected on a

regular basis, for example annually or biannually.

Figure 4.2 Generic probability versus economic damage curve used to

assess annualised average damage


B.I-24

PeopleThe annualised average deaths or injuries to people may be estimated in a

similar way to the annualised average damage.

4.2.4 Examples of vulnerability mapsFigures 4.3, 4.4 and 4.5 show typical examples of vulnerability maps

related to flooding.

Source: Reference 5

Figure 4.3 Area and people vulnerability maps used on the tidal River

Thames in the UK to estimate risk to people

Figure 4.4 Mapping showing consequences of flooding in terms of number

and economic damage to properties at a catchment level


B.I-25

Figure 4.5 Mapping showing social vulnerability and number of people

affected by flooding at a catchment level

5 Analysis of risk

5.1 Definition of riskTo evaluate the flood risk, consideration needs to be made of a number of

components:

• The nature and probability of the hazard (p);

• The degree of exposure of the Receptors (numbers of people and

property) to the hazard (e);

• The susceptibility of the Receptors to the hazard (s);

• The value of the Receptors (v).

Therefore:

Risk = function (p, e, s, v)

Hence vulnerability is a parameter that is taken account of in this definition

of risk. Vulnerability is a function of the susceptibility of the Receptors to

the flood hazard and the value of the Receptor. Vulnerability may be

defined as:

Vulnerability = function (s, v)


B.I-26

In practice, however, exposure and vulnerability are often captured in the

assessment of the consequences; thus risk can be viewed in simple terms

as:

Risk = Probability of flood event occurring x Consequences

5.2 Units of riskIn general, risk has units. However, the units of risk depend on how the

probability and consequence are defined. Flooding can have many

consequences, some of which can be expressed in monetary terms.

Consequences can include fatalities, injuries, damage to property or the

environment. The issue of how some of the consequences of flooding can be

valued continues to be the subject of contemporary research. However,

risk-based decision-making is greatly simplified if common units of

consequence can be agreed upon. It is, therefore, often better to use

“surrogate measures” of consequence for which data are available.

For example, “number of properties” may be a reasonable surrogate for the

degree of harm/significance of flooding and has the advantage of being

easier to evaluate than, for example economic damage or social impact. An

important part of the design of a risk assessment method is to

decide on how the impacts are to be evaluated. Some descriptions of

“consequence” are:

• Economic damage (national, community and individual;

• Number of people/properties affected;

• Degree of harm to an individual (fatalities, injury, stress etc);

• Environmental and ecological damage (sometimes expressed in

monetary terms).

5.3 Future flood riskFlood risk is unlikely to remain constant in time and it is often necessary to

predict changes in risk in the future, to make better decisions. Causes of

change to flood risk include:

• Climate (for example, greenhouse-gas induced climate change);

• Change in the value of assets at risk (for example, an increase in value

or contents of residential properties);

• Improved flood warning and response;

• Changes to flood mitigation measures (for example, construction of new

flood defences);

• Changes in land use.


B.I-27

The dynamic nature of future flood risk is shown in Figure

5.1.:

Source: Reference 1

Figure 5.1 Factors that may affect future flood risk

5.3.1 Climate changeThis has been discussed in Section 2.5.

5.3.2 Change in values of assetsChanges in the future value of assets will have an impact on the future

flood risk. Any future changes in asset value can be taken account by

modifying the economic data.

5.3.3 Improved flood warningA well designed flood warning system can reduce the impact of flood events

and as a consequence reduce flood risk. However, it is often difficult to

assess fully the impact of this in the estimation of economic damage to

properties resulting from flooding. However, it is possible to assess the

effect of improved flood warning on the flood risks posed to people resulting

from improvements in lead-times, accuracy of water level and extent

predictions and a reduction in false alarms.

5.3.4 Changes to flood mitigation measuresFuture changes to flood mitigation measures (for example such as the

construction of flood walls or flood attenuation reservoirs) will change the

flood risk. Future changes to flood mitigation measures should be

represented in hydraulic models and the reduction (or increase) in flood

hazard and risk estimated.


B.I-28

5.3.5 Changes in land useThe following changes in land use will change the level of flood risk:

• Change in the number of properties and/or people living in the

floodplain;

• An increase in the urbanisation of the catchment resulting in increased

runoff.

When estimating changes in flood risk resulting from an increase (or

decrease) in urban area in an area should initially be based on development

scenarios based on information from local, regional and national planning

authorities. These changes should be incorporated in any future

hydrological and hydraulic modelling to assess future hazard and also when

assessing the consequences of flooding (for example in terms of the

number of people or properties affected). A typical example of the urban

development scenarios that are often assessed at short and medium/long

term temporal scales are shown in Figure 5.2.

Figure 5.2 Illustration of possible urban development scenarios

Land use change other than urban developments, (for example,

aforestation/deforestation, changes in land management practice) may

occur in the future. The impacts of rural land use change on runoff

generation have not been clearly established for areas greater than 10 km2.

The difficulty in obtaining consistent evidence of the effects of land use

change on downstream flood response at this scale suggests that it is

probably relatively moderate and dependent on the exact nature of the

previous land use and local conditions (for example, climate, topography,

soils). In general it would only appear that rural land use change does not

have a major influence on influencing flood hazard and flood risk.


B.I-29

5.4 Methodologies for risk analysis assessment

Risk analysis can be defined as “a methodology to objectively determine

risk by analysing and combining probabilities and consequences”. Flood risk

assessment “comprises understanding, evaluating and interpreting the

perceptions of risk and societal tolerances of risk to inform decisions and

actions in the flood risk management process.”

5.4.1 Qualitative and quantitative methodsRisk is generally assessed in terms of a qualitative or quantitative analysis.

In terms of flood risk qualitative assessments tend to categorise flood risk

to people or buildings (for example as high, medium or low). In terms of

quantitative assessments flood risk in terms of damage to assets will be

quantified typical in economic terms ( ) and for people it is in terms of the

number of people injured or who have died.

5.4.2 Functions of risk analysisTo evaluate the flood risk, separate consideration needs to be made of the

three generic components:

• The nature and probability of the hazard;

• The degree of exposure of people and assets to the hazard;

• The vulnerability of the people and/or assets to damage or harm should

the hazard occur.

The main steps that need to be undertaken in a risk assessment are shown

in Figure 5.3.

There are a variety of flood risk assessment tools that can be applied,

ranging from high level methods to intermediate methods to detailed

methods. The appropriate level of risk analysis to use depends upon the

scale of the assessment and type of decision to be made, as shown in

Figure 5.4.


B.I-30

Source: Reference 1

Figure 5.3 Flood risk assessment process

Source: Reference 1

Figure 5.4 Appropriate level of risk analysis


B.I-31

Flood risk assessments in terms of economic damageThe process used to assess flood risk in terms of economic damage is

summarised in Figure 5.5.

Assessment of flood risk in terms of economic damage atdifferent spatial scalesMethod used to assess flood risk in terms of economic damage at different

spatial scales is summarised in Table 5.1. It should be noted that at each

scale a national property data set is required. This national property data

set would include for each residential and commercial property in the

country the data defined in Section 4.2.1 of this report.

Table 5.1 Summary of assessing flood risk in terms of economic damage

at a number of different spatial scales

Level of

assessment

Flood hazard Economic damage

National Flood extents and

depths based on a

national DTM and

flood levels

National property and agricultural data sets

together with generic water level versus

economic damage curves. Threshold level of

properties assumed to be the same as the

DTM.

Regional or

catchment

Broad scale hydraulic

modelling of the

catchment

National property and agricultural data sets

together with generic water level versus

economic damage curves.

Local Detailed one or two

dimensional hydraulic

model calibrated and

verified against a

number of observed

flood events

National property data set with detailed

water level versus economic damage for

each type of property. Detailed data on

property threshold levels.

Agricultural estimated using detailed

knowledge of crop types and damage. Farm

scale assessments carried to assess crop

damage.


B.I-32

Figure 5.5 A summary of the process for analysing flood risk in terms of

economic damage

Flood risk assessments in terms of injuries and death to peopleThe process used to assess flood risk in terms of economic damage is

summarised in Figure 5.6.

Assessment of flood risk in terms of people at different spatialscalesMethod used to assess flood risk in terms of injuries or deaths to people at

different spatial scales is summarised in Table 5.2. It should be noted that

at each scale a national property data set is required.


B.I-33

Figure 5.6 A summary of the process for analysing flood risk in terms of

injuries and deaths to people


B.I-34

Table 5.2 Summary of assessing flood risk in terms of people at a

number of different spatial scales

Level of

assessment

Flood hazard Area vulnerability People vulnerability

National Flood extents based

on a national DTM

and design flood

levels

Based on national

property data sets

Information based on

national census data

Regional or

catchment

Broad scale

hydraulic modelling

Based on national

property data sets

augmented by

information from local

government



augmented by


government

Local Detailed one or two

dimensional

hydraulic model

calibrated and

verified against a

number of observed

flood events

Based on national

property data sets

augmented by


government



augmented by


government


B.I-35

5.4.3 Examples of risk maps and legends

Examples of flood risk maps are shown below. Figure 5.7 show shows a

national flood risk map for England and Wales showing how the flood risk in

terms of economic damage may change under different economic

development scenarios by the year 2080. Figure 5.8 shows a flood risk to

people map in terms of the number of deaths that are likely to occur if a 1

in 1000 year coastal flood event occurred.

2080s

World markets

2080s

Global

sustainability

Change in average annualised economic damage under future climate change scenarios

Negligible (-£1,000 to +£1,000)

Low increase (£1,000 to £100,000)

Medium increase (£100,000 to £10 million)

High increase (Greater than £10 million)

Decrease (Less than -£1,000)

Outside floodplain

Source: Reference 9

Figure 5.7 National flood risk map for England and Wales showing

economic damage in 2080 under different development scenarios in terms

of relative average annualised damage referenced to 2002


B.I-36

Source: Reference 5

Figure 5.7 Flood risk maps showing the percentage of deaths that may

occur under a 1 in 1000 year flood event in Kinmel, Wales

Source: Reference 1

Figure 5.7 A high level flood risk map showing the economic risk in

qualitative terms at the mouth of the River Parrot in the UK


B.I-37

Figure 5.8 A local flood risk map showing the economic damage for a

flood that occurred in 1993 in Offenau in Neckar, Germany

Number of

casualties

km

Source: Reference 8

Figure 5.9 Number of expected casualties in The Hague and Rotterdam if

the flood defences are breached.


B.I-38

6 Risk management

6.1 Generic risk management optionsThere are several ways of managing and reducing the overall risk offlooding, which may be discussed in similar generic terms to the riskidentification process, broadly these are:

(i) Controlling the source;

(ii) Controlling the pathway;

(iii) Controlling the exposure;

(iv) Controlling the vulnerability.

6.1.1 Controlling the sourceExamples of source control options include:

• Use of infiltration systems to manage surface water runoff;

• Dredging and the cutting of the channel vegetation to maintain

channel capacity;

• Retention of natural flood storage on floodplains.

6.1.2 Controlling the pathwayExamples of controlling the pathway are:

• Construction of mitigation measures such as flood walls;

• Emergency operations to temporarily raise defence levels during a

flood.

6.1.3 Controlling the exposureThe exposure of receptors to floods can be controlled by:

• Implementation of land-use planning policies to limit development in

flood risk areas;

• Abandonment of buildings on the floodplain;

• Public information on reducing flood damage;

• Flood warning systems;

6.1.4 Examples of controlling vulnerabilityThe vulnerability of the Receptors can be controlled by:

• Specific building regulations on flood resistant construction in flood

risk areas;

• Ensuring safe evacuation routes;

• Installation of flood proofing devices;

• Well-practised emergency plans.

6.2 Significance of riskIntuitively it may be assumed that risks with the same numerical value

have equal significance but this is often not the case. In some cases, the

significance of a risk may be assessed by compounding the probability with

the consequence. In other cases it is important to understand the nature of


B.I-39

the risk, distinguishing between rare, catastrophic events and more

frequent less severe events. For example, risk methods adopted to support

the targeting and management of flood warning represent risk in terms of

probability and consequence, but low probability/high consequence events

are treated very differently to high probability/low consequence events.

Other factors include how society or individuals perceive a risk (a perception

that is influenced by many factors including the availability and affordability

of insurance or exposure to high flow velocities for example), and

uncertainty in the assessment.

It is thus important when considering the significance of a risk that

reference is made not only to the numerical value of the probability times

consequence, but also to how it will be perceived by society or the

individual.

A central question in risk management refers to the acceptance of risk by

the people and the decision-makers. From an engineering point of view a

general framework for acceptability criteria has been developed that is

based on a three-tier system, shown in Figure 6.1. This involves the

definition of the following elements:

• An upper-bound on individual or societal risk levels, beyond which risks

are deemed unacceptable;

• A lower-bound on individual or societal risk levels, below which risks are

deemed not to warrant concern;

• An intermediate region between (i) and (ii) above, where further

individual and societal risk reduction are required to achieve a level

deemed “as low as reasonably practicable” (the so-called ALARP

principle).

The ALARP method derives from industrial process safety applications and

thus is often seen to have an “engineering” rather than “social science”

heritage. Although this general framework gives a first impression on how

risk acceptance can be approached, it must be stated from a social science

point of view that the realms of acceptance and non-acceptance of Figure

6.1 may differ significantly between persons and that a public. Consensus

on risk acceptance may not exist. Furthermore, this framework does not

answer the question of how acceptance should be measured.


B.I-40

Source: Reference 1

Figure 6.1 Acceptable risk levels and the ALARP principle


B.I-41

7 Glossary of all keywords

Accuracy – The closeness to reality.

Annualised average damage – This is the average economic damage

from flooding that can be expected in any year.

Catchment modelling – A model that is represents the whole of the

catchment

Coastal floods – A flood generated by a high tide or storm surge in the

coastal plain

Consequence - An impact such as economic, social or environmental

damage/improvement that may result from a flood. It may be expressed

quantitatively (e.g. by. monetary value), by category (e.g. High, Medium,

Low) or descriptively.

Damage potential - A description of the value of social, economic and

ecological impacts (harm) that

would be caused in the event of a flood.

Deterministic process/method - A method or process that adopts

precise, single-values for all variables and input values, giving a single

value output

Digital elevation model (DEM) - A database of elevation data

represented by a regularly-spaced set of x,y,z locations.

Digital terrain model (DTM) – A digital representation of the height of

the earth’s surface referenced to a particular datum.

Exposure – The qualification of the receptors that may be influenced by a

flood hazard, for example, the number of people and their demographics,

number and type of properties.

Flash floods – Floods that generally occur on steep or urban catchments

with little warning and result in a rapid rise in water level.

Flood - A general and temporary condition of partial or complete inundation

of dry land caused by the overflow of the boundaries of a water body or by

the rapid accumulation of surface water runoff.

Flood hazard map – A map with the predicted or documented

characteristic (for example, extent, or velocity or depth) of flooding, with or

without an indication of the flood probability.

Flood risk map – map showing the flood risk usually in terms of economic

damage or number of injuries/deaths of people.

Flood risk zoning - Delineation of areas with different possibilities and

limitations for investments, based on flood hazard maps.

Floodplain – the area adjacent to a river that would be naturally flooded in

the absence of engineered interventions.

Hazard - A physical event, phenomenon or human activity with the

potential to result in harm. A hazard does not necessarily lead to harm.

Harm - Disadvantageous consequences.

Hydrodynamic model – A hydraulic model where the flow varies with

time.

Inundation - Flooding of land with water. (Note: In certain European

languages this can refer to deliberate flooding, to reduce the consequences

of flooding on nearby areas, for example. The general definition is preferred

here).

One dimensional hydrodynamic model – A hydrodynamic model that

provides on dimensional results.


B.I-42

Pathway – In the context of floods provides the connection between a

particular source (for example, marine storms) and a receptor (for example,

property) that may be harmed. For example, the pathway may consist of

the flood defences and flood plain between a flow in the river channel (the

source) and a housing development (the receptor).

Plains floods – Floods that are usually generated from large catchments

that have been subjected to long periods of heavy rainfall. They are

characterised by long periods of inundation and a relatively slow rise in

water level.

Probabilistic method - A method in which the variability of input values

and the sensitivity of the results are taken into account to give results in

the form of a range of probabilities for different outcomes.

Rainfall-runoff modelling – A model used to estimate runoff from an area

under various rainfall, land use and soil moisture conditions

Rating curve – The relationship between water level and flow for a given

river cross-section.

Receptor - Receptor refers to the entity that may be harmed (for example

a person, property, habitat etc.). For example, in the event of heavy rainfall

(the source) floodwater may propagate across the flood plain (the pathway)

and inundate housing (the receptor) that may suffer material damage (the

harm or consequence). The vulnerability of a receptor can be modified by

increasing its resilience to flooding.

Resilience - The ability of a system/community/society/defence to react to

and recover from the damaging effect of realised hazards.

Return period - The expected (mean) time (usually in years) between the

exceedence of a particular extreme threshold. Return period is traditionally

used to express the frequency of occurrence of an event, although it is

often misunderstood as being a probability of occurrence.

Risk - Risk is a function of probability, exposure and vulnerability. Often, in

practice, exposure is incorporated in the assessment of consequences,

therefore risk can be considered as having two components — the

probability that an event will occur and the consequence (or impact)

associated with that event. Risk = probability x consequence.

Risk analysis - A methodology to objectively determine risk by combining

probabilities and consequences or, in other words, combining hazards and

vulnerabilities.

Risk assessment - The process of judging risks that have been analysed.

Risk mapping - The process of establishing the spatial extent of risk

(combining information on probability and consequences). Risk mapping

requires combining maps of hazards and consequences. These maps usually

show the magnitude and nature of the risk.

Risk management measure - An action that is taken to reduce either the

probability of flooding or the consequences of flooding or some combination

of the two.

River basin - The area defined by the watershed limits of a system of

waters, both ground and surface, flow to a common outlet.

Routing model – A model used for routing flood flow hydrographs.

Steady-state hydraulic model – A model where the flow remains

constant i.e. it does not vary with time.

Source — The origin of a hazard (for example, heavy rainfall, strong winds,

surge).


B.I-43

Susceptibility – The propensity of a particular receptor to experience

harm.

System - In the broadest terms, a system may be described as the social

and physical domain within which risks arise and are managed.

Threshold level – The threshold level, in the context of a property, is the

level above which the property will be inundated by floodwater.

Two dimensional hydrodynamic model – A hydrodynamic model that

provides results in two dimensions.

Vulnerability - Characteristic of a system that describes its potential to be

harmed. This can be considered as a combination of susceptibility and

value.


B.I-44

8 References

1. FLOODSite (2005) Language risk project definitions, Version 4.0,

Report T32-04-01, EC project on Integrated Flood Risk Analysis and

Management Methodologies

2. Environment Agency, England and Wales website

http://www.environment-agency.gov.uk/

3. Danish Hydraulics Institute (DHI)

4. Department of the Environment Food and Rural Affairs

(Defra)/Environment Agency, UK (2004) Modelling and decision

support framework version 3.0


(Defra)/Environment Agency, UK (2005) Flood risk to people project


(Defra)/Environment Agency, UK (2004) Risk Assessment of flood

and coastal defence for Strategic Planning (RASP) project

7. Delft Hydraulics, The Netherlands

8. HR Wallingford Ltd, UK

9. UK Government Department of Science and Technology (2002)

Foresight: Future flooding


B.I-45

Appendix:Operational standards for risk assessment aimedat spatial planning

1. Simplified model for flood hazard mapping aimed ata legal directive

One of the simplest ways in which flood hazards can be displayed is in

terms of the spatial extent of the flooding. The spatial extent of the flood

should be assigned to a specific return period or annual probability. In

general the most commonly used return period is 1 in 100 years, i.e. the

flood that has an annual probability of 1% of occurring. Other commonly

mapped return periods include: 1 in 100 years, 1 in 200 years, 1 in 50

years, 1 in 20 years, 1 in 10 years and 1 in 5 years. An example of a flood

extent map is showing the flood extents without flood defences in place is

shown in Figure A1.

Figure A1 Typical national flood extent map showing two return periods

It is important to note that the way in which the hazard is to be assessed

will affect the way in which risk is to be assessed. To assess risk in terms of

economic damage or in terms of injuries or deaths to people then the depth

of the floodwater is also required. A typical local scale flood map showing

flood depths is shown in Figure A2.


B.I-46

Figure A2 Local scale flood depth map

To summarise the minimum requirement to produce flood hazard mapping

is to map the spatial extent of the flood. This should be mapped for at least

the 1 in 100 year return period flood and if possible the 1 in 1000 year

flood. The method by which this can be carried out is detailed in Section

2.4.1 of this report.

1.1. Methodologies related to the three assumed scales ofanalysis in the light of a potential harmonisation of hazardmaps, based on a multi-hazard perspective

National scale flood extent and depth map

To produce a national scale flood extent and depth map the following are

data required:

• A national digital terrain model (DTM). The vertical resolution of the

national DTM should be sufficient accurate to allow flood extents to be

produced at a national level. Typically the resolution of the DTM should

be a maximum ±5 m. The scale of the DTM grid used to map the flood

hazard is dependent on the size of the country and width of the

floodplain. A typical national DTM grid size is 50 m x 50 m. However, in

some cases a higher resolution grid may be needed.

• Estimate of flood flows. A method of estimating flood flows at a

national level is required. This is normally done by extrapolating flows at


B.I-47

gauging stations. If significant areas of the country are unguaged then a

simple method is needed to estimate flood flows. This is often based on

a simple empirical model (e.g. where flood flows are correlated against

catchment area, rainfall etc)

• Production of relationships between flood flows and flood levels.

This is often done by using a simple equation such as the Manning’s

equation that relates flow to water level.

• Production of the flood extent and depth. A Geographical

Information System (GIS) is used to produce a flood extent and depth

grid. A water surface needs to be generated. This is done by

triangulating the water levels to form a triangular irregular network

(TIN) representing the water surface. The flood extent is calculated from

the point at which the water surface intersects the DTM. A water depth

grid can be created by converting the water surface TIN to a water

surface grid. The DTM grid is then subtracted from the water surface

grid to give average depths in each grid square.

Catchment scale flood extent and depth maps

To produce a catchment scale flood extent and depth map the following are

data required:

• A digital terrain model (DTM) that covers the entire catchment;

• A broad scale hydraulic model of the catchment;

• Production of. the flood extent and depth. This has been described

above.

This is described in more detail in Section 2.4.3 of this report.

Local scale flood extent and depth maps

The method for assessing local flood extent and depths is detailed in

Section 2.4.3 of this report.

2. Simplified model for risk mapping aimed at spatialplanning

The two most commonly used receptors for flood risk assessment are:

• Direct economic damage to buildings;

• Injuries or fatalities to people.

The detailed methods and models to assess these have been described in

Section 4.2 of this report.


B.I-48

2.1. Multi-risk assessment perspective as element of theStrategic Environmental Assessment

The EU Directive on Strategic Environmental Assessment (SEA) that in

terms of natural hazards the following risk-related aspects should be

considered:

• The probability, duration and frequency of the event;

• The risks posed to human health or the environment;

• The magnitude and the spatial extent of the hazard;

• The value and vulnerability of the area.

In terms of the relationship between natural hazards and SEAs it would

appear that both the risks to properties and to people need to be assessed.

2.2. Methodologies, functions and outputs

The most common methodologies and their associated functions and

outputs for the assessment of risk to properties and to people have been

described in Chapters 4 and 5 of this report. Figures A3 and A4 show

schematic diagrams of the methods for assessing the flood risk in terms of

economic damage to properties and injuries/deaths to people respectively.

B.I-4

9

ARM

ON

IA P

RO

JECT (C

ontra

ct n

° 5

11208) D

eliv

era

ble

2.1

Figure A3 Schematic diagram showing the method to assess flood risk in terms of economic damage

B.I-5

0

ARM

ON

IA P

RO

JECT (C

ontra

ct n

° 5

11208) D

eliv

era

ble

2.1

Figure A4 Schematic diagram showing the method to assess flood risk in terms of injuries and deaths to people


B.II-1

B.II Seismic risk

Authors: Silvia Cozzi, Floriana Pergalani, Vincenzo Petrini,POLIMI

1 Physical definition of Seismic Risk ..........................3

1.1 Typologies.................................................................... 3

1.2 Intensities, Severity, Magnitude ...................................... 3

2 Hazard assessment ................................................4

2.1 Definition ..................................................................... 4

2.2 Current methodologies for analysis and data availability..... 5

2.3 Problem of scale............................................................ 6

2.3.1 Temporal scale ..................................................................... 6

2.3.2 Scale of analysis and representation ....................................... 6

3 Elements at risk, exposure and analysis ofvulnerability...........................................................6

3.1 Definition of vulnerability ............................................... 6

3.2 Current methodologies for assessment, typology of elementsat risk and most common damage potentials .................... 7

3.2.1 Analysis of vulnerability for building........................................ 73.2.1.1 Scale of analysis and representation...........................................9

3.2.2 Analysis of vulnerability for large areas ................................... 93.2.2.1 Scale of analysis and representation.........................................10

3.2.3 Analysis of bridges vulnerability ........................................... 103.2.3.1 Scale of analysis and representation.........................................11

3.2.4 Analysis of vulnerability for tunnels....................................... 113.2.4.1 Evaluation of vulnerability index ..............................................123.2.4.2 Scale of analysis and representation.........................................12

3.2.5 Analysis of vulnerability for supporting works ........................ 123.2.5.1 Evaluation of vulnerability index ..............................................123.2.5.2 Scale of analysis and representation.........................................13

3.2.6 Analysis of vulnerability for network infrastructures................ 133.2.6.1 Evaluation of vulnerability index ..............................................133.2.6.2 Scale of analysis and representation.........................................14


B.II-2

4 Analysis of risk..................................................... 14

4.1 Definition of risk.......................................................... 14

4.2 Levels of investigation ................................................. 14

4.3 Methodologies for risk assessment for different levelsof study ..................................................................... 15

4.3.1 First level studies: territorial exposure .................................. 16

4.3.2 Second level studies: damage scenario ................................. 174.3.2.1 Basic Seismic hazard..............................................................174.3.2.2 Physical vulnerability..............................................................264.3.2.3 Damage scenario evaluation....................................................29

4.3.3 Third level studies: seismic risk............................................ 314.3.3.1 Local seismic hazard assessment .............................................31

4.3.3.1.1 Methodologies for evaluating site effects ...........................314.3.3.1.2 Instability evaluation......................................................324.3.3.1.3 Scale of analysis and representation.................................32

4.3.3.2 Physical vulnerability assessment.............................................37

4.3.4 Laboratorial experiments ..................................................... 42

5 Risk management................................................. 42

5.1 Perception .................................................................. 42

5.2 Tolerance, acceptability, mitigation measures ................. 43

5.3 Preparedness, response, recovery ................................. 44

6 Glossary of all key-words ..................................... 45

7 Bibliography......................................................... 47

Appendix: Operation Standards for Risk Assessmentaimed at Spatial Planning........................................... 51

A1 Simplified model for Seismic Hazard mapping aimed at legaldirective............................................................................. 51

A1.1 Hazard methodology............................................................. 51

A1.2 Map scales........................................................................... 51

A1.3 Characteristics and use of hazard maps .................................. 54

A1.4 Data acquisition and mapping procedures ............................... 54

A2 Simplified model for risk mapping aimed at spatial planning 56

A2.1 Risk methodology, data acquisition and use ............................ 56

A2.2 Map scales........................................................................... 58

A3 Minimum standard for multi-risk assessment and mapping .. 60


B.II-3

1 Physical definition of Seismic Risk

1.1 Typologies

Earthquakes are the most evident expression of crustal breaking occurringat a variable depth ranging from a few to some hundreds kilometres.According to this hypothesis, crustal rocks are subject to deformationbecause of movements of the ground that make them accumulate energy.When in some points this level of deformation overcomes the resistance ofthe material, there occurs a breaking occurs that quickly propagates acrossa surface, called fault plane; the extension of the rupture depends on thecharacteristics of the materials and on the level of deformation of the area:the bigger the broken area is, the stronger the earthquake will be. After thebreaking, part of the energy is given back in terms of elastic waves thatpropagate in all directions.The most evident aspect of the seismic event is therefore the rapid andsometimes violent soil motion.

1.2 Intensities, Severity, Magnitude

The earthquakes “destructive power” can be described in several waysdepending on the information available at each singular event.

Data available for the study of earthquakes can be collected under threecategories, correlated with three different approaches:

a. Damage effect. The first method is based on the description of damageeffects on the built environment, on buildings and on the naturalenvironment (macroseismical effects). To this end several scales haveintroduced that allow to associate the entity of the effects with an“intensity” level. It is clear that the “intensity”, as it is defined, supplies aprecise evaluation of the earthquake, and therefore, for the same event,there are different intensity values for different places. Studyingearthquakes, “intensity” and “severity” are used as synonyms, because theyare expression of the same category of effects.

b. Seismometric registrations. A second method to measure earthquakesis provided by soil motion registrations, which are obtained thanks to theuse of seismograms (instruments able to reproduce ground motions inhorizontal or vertical direction quite faithfully)

Different kinds of waves that contribute to soil motion can be distinguishedas follows:- volume waves, divided in P-wave (from the Latin term "primae"), that

are compression waves which propagate from the source in alldirection with a sequence of compressions and dilatations; and S-wave(from the Latin term "secundae") shearing waves which causeorthogonal displacements;

- surface waves, so called because they propagate only on terrestrialsurface; they are a consequence of the interaction of P and S-waves


B.II-4

with terrestrial surface. The difference in arrival times of the waves isthe basic element for the location of the earthquake source.

c. Accelerometric registrations. The third and last method to evaluateearthquakes is through soil motion registration obtained hanks oaccelerograms, instruments capable of supplying registrations inproportion to earthquake accelerations. The simplest parameter that canbe used for this measure is the amount of the maximum recordedacceleration.

The magnitude is, instead, a value that represents the level of energyreleased by the singular considered event. This value is recorded in the“Historical recorded events catalogue” that associate the magnitude valuewith the singular earthquake took into consideration.

Fig1.1 - Earthquake of 1980.11.23Epicentre area: IRPINIA-LUCANIA (Italy) - Study POA85

2 Hazard assessment

2.1 Definition

Hazard can be analyzed in two different ways: considering it as a conceptlinked to the probability that in a specific site a certain severity event mayhappen in a predefined time-window (“probability” is the term used,

Intensity

Magnitude: 6.9


B.II-5

because an exact prevision can’t be given for the time being. Statisticanalysis of the past events that occurred in a specific site must be done inorder to obtain a right value of the hazard), or considering an individualevent (in this case a deterministic approach is followed).

A variety of methods can be classified according to different initialhypotheses, objectives and detail levels. They are divided into:

A. Probabilistic approach: they permit to obtain foresights about futureevents in a specific site, in particular they consent to define the probabilityof having an event stronger than an established severity in a given timeperiod, thanks to probabilistic analysis of past events. The result is adistribution function in the site and the determination of possible hazardindicators.

A.1. Source zone method. It is one of the most used methods for hazardassessment. It is based on two hypotheses:- uniform spatial distribution of the events in seismogenetic;- Poissonian distribution of occurrence periods.

A.2. Renewal process. This method modifies the basic hypothesis of thepreceding approach, abandoning the hypotheses of stationarity and theone about the uniform spatial distribution to calculate the time-windowbetween subsequent events.

B. Deterministic approach: damage scenario. They consider a singularevent and its propagation in surrounding areas (scenario), this will permit tostudy site effects (damage scenario).

2.2 Current methodologies for analysis and dataavailability

The procedure for hazard assessment allows to determine a level of groundmotion in an established area.To do that, knowledge of structural geology and historical seismic data canbe used.The following methodology refers to the Italian situation.

UBasic data:1 Historical recorded events catalogue. For every recorded event it is

possible to find out information including the indicators of epicentralseverity: epicentral intensity and magnitude.

2 Source zones. Those are areas that can be considered geologically,structurally and kinematically homogenous. A seismic zone is definedthrough the probabilistic distribution of the epicentral intensities.

3 Attenuation model. The evaluation of hazard is necessary to know,beside the localization and the epicentral severity, how the phenomenonpropagates from the epicentre and, as a result, the variation ofcorrelated severity parameters.- Intensity attenuation. Using the epicentral severity as indicator, the

result of the attenuation laws is still an intensity value.


B.II-6

- Magnitude attenuation. These models use as severity indicator themagnitude value.

The above data are applied to investigate how a phenomena propagates farfrom the epicentre and, consequently, they can be used to investigate thevariation of severity parameters of intensity attenuation or of magnitudeattenuation.

2.3 Problem of scale

2.3.1 Temporal scale

The time scale can be taken into consideration with respect to the as far asthe hazard and to the vulnerability.

When a probabilistic hazard is estimated, it is possible to foresee somerecurrence periods by assigning (at regular time intervals), a Pick GroundAcceleration (P.G.A.) in given time intervals and in a specific site. Obviouslythe P.G.A. value will be more or less serious according to the consideredtime-window: i.e., it can be considered more serious as far as a 1000-year-recurrence period rather than a 500-years one.

2.3.2 Scale of analysis and representation

In order to study the hazard component it is possible to map the territoryaccording to two methods: by subdividing it through the overlapping of aregular grid, or on the basis of territorial boundaries.

Anyway, seismic hazard studies can be carried out on a national scale, thatis 1:500.000 or more, but it is possible to range up to the municipal one.

3 Elements at risk, exposure and analysis ofvulnerability

3.1 Definition of vulnerability

With this term we intend to ascertain how much an object is prone to bedamaged in case of occurrence of the very event. Vulnerability is anintrinsic characteristic of an object and so it can change on the basis of thephenomena we are considering. The concept of vulnerability is closely linkedto the EXPOSURE one, which analyses the event considering theconsequence for the exposed people and goods. Therefore it seems relevantonly if there are objects that could be damaged or people who can beinvolved in the area where the event occurs. It is then important to analysethe area and verify which and how many kinds of objects and people arepresent, and how vulnerable they are.


B.II-7

3.2 Current methodologies for assessment, typology ofelements at risk and most common damagepotentials

3.2.1 Analysis of vulnerability for building

Referring to buildings, seismic vulnerability is the behavioural characteristicdescribed by a cause-effect law, where the earthquake is the cause and thedamage is the effect.

Seism and damage measures are the most widely used parameters,macroseismic intensity or soil maximum acceleration are the ones used forterritorial dimension.

Existent techniques to supply data about vulnerability can be variouslydivided:

A. Based on the results produced:1. direct techniques: just in one step they supply an effective prevision of

damages caused by earthquakes;2. indirect techniques: they consist in two steps. The first a vulnerability

index “V” is produced; then a correlation between earthquakes anddamages depending on the index is established;

3. finally, the conventional techniques produce a vulnerability index that,unlike the direct ones, is not associated to a damage forecast, but issubstantially useful to compare different buildings located in equalseismic areas.

B. Based on the measurement method used each time:1. quantitative techniques: they express damage probability or equivalent

deterministic relations in numerical terms;2. qualitative techniques: they make use of vulnerability descriptions in

terms of “low”, “middle” and “high”;

C. Using the main information source:1. based on statistic elaborations of the collected data;2. based on seismic response calculation;3. based on expert judgments;

D. Depending on the organism to which a building is assimilated:

1. typology techniques: they classify the buildings as in typological class,defined according to materials, techniques, or some other factors. Theyhave the advantage to be cheap and to require quite simple research inthe field; besides, they benefit from substantial basis of data.

On the other hand, they don’t distinguish singular buildings inside thesame class and so they don’t allow to make a list out of them; they areused to derive information about urban areas on the whole.

In particular for typology techniques Braga et al. (1982, 1984) andZuccaro et al. (1999) can be used as reference. In this case vulnerabilityis assessed by assigning a given building to a certain structural typology


B.II-8

characterized by few main features (i. e. the type of vertical orhorizontal structures), for which a probability damage matrix is defined.

An example of vulnerability assessment, carried out according to thismethod, has been carried out using data resulting from about 36.000buildings in 41 municipalities damaged by the earthquake of the Irpiniain 1980 (Braga et al., 1982; 1984) for which the following procedure wasfollowed:1) Detailed survey carried out on the basis of a card containing data

about the structural typology and damage levels of each building;2) Damage level related to thirteen different structural typologies

singled out on the basis of the kind of vertical and horizontalstructure;

3) the above mentioned thirteen typologies have been successivelygrouped in three classes (A, B, C) to make them correspond to thevulnerability classification included in the macroseismic scale MSK-76(Medvedev, 1977);

4) Statistics elaboration of damages observed in recent earthquakes todefine the relationship between the severity of the event and thecharacteristics of the building;

5) Computing of the probability that a building belonging to a specifictypology class, undergoes a certain damage level when it is hit by anearthquake of a given intensity. This can be done by considering allthe buildings which have undergone the effects of the same damagelevel within municipalities that were affected by different intensitiesdegrees;

6) damage probability matrix obtained by repeating the operation for allthe damage levels and for all three typology classes. These matrixessupply, for each vulnerability class, the probability that a specificdamage level will take place according to the macroseismic intensity.

2. mechanistic techniquesU, they substitute a theoretical mechanical modelof the building to the building itself. Such techniques allow not only toobtain results for entire urban areas, but also other results valid forsingle buildings. On the other hand, they require that in the building asufficiently clear static pattern can be recognized.

3. semeiotical technique: it considers the building vulnerability on the basisof its symptoms. In general, a certain number of vulnerability factors areintroduced, such as the general organization of the resistant system, itsquality, the global resistant of the building to horizontal actions, thestate of deterioration, etc. To every level of vulnerability degree isassigned for every building factor; the increase of the levels shows anincrease in vulnerability.

It is then possible to draw up for each building typology (like masonrybuildings), appropriate vulnerability cards (currently used by G.N.D.T. –Gruppo Nazionale per la Difesa dai Terremoti), to assess buildings seismicvulnerability, based on several information about buildings constitutiveelements.

The first level card includes general information about buildings location,geometry, and typology. In detail, the survey card consists in the following8 sections:


B.II-9

1 data about the card (building identification key, municipality, card, team,date);

2 building location (aggregate, building, toponymy, town planning bonds);3 metric data (surfaces, landing hights, maximum and minimum out of

round highs);4 use (kinds of use, state, property, users);5 building age (typologies and classes of age);6 state of the trimmings;7 structural typology (vertical, horizontal, staircase, roofing);8 damage level and expance.

The second level allows to assess vulnerability by using representative dataabout buildings propensity to be damaged by a seismic event. In particularsome factors accounts for the behaviour of the elements, structural or not,some others of the behaviour of the whole building complex.1 sort and organization of resistant system;2 quality of the resistant system;3 conventional resistance;4 position of the building and of the foundations;5 ceilings;6 planimetric configuration;7 elevation configuration;8 maximum distance between brickworks;9 roofing;10 non structural elements;11 general conditions/present state;

In order to obtain a numerical index, one of the four available classes,(from A, the best one, to D, the worst and a weight) is attached to each ofthe above mentioned parameters.

The do obtained vulnerability index constitutes a conventional measurementof the propensity to damage that should not be confused with the damageexpected for a given level of severity of the earth tremor. Therefore, tomove from the hazard assessment to the e risk valuation, it is necessary tofind a correlation between the damage level, the quality of the building andthe parameter used to measure the severity of the earth tremor.

3.2.1.1 Scale of analysis and representation

The scale of analysis for this kind of survey is the one that better highlightthe single building: 1:500 – 1: 5000 in order to allow punctual, andtherefore very in-depth researches (third level analysis).

3.2.2 Analysis of vulnerability for large areas

The most direct process to establish the built environment vulnerability is tomake use of vulnerability investigations. It is clear that is very difficult toinvestigate the whole built patrimony for large areas, but it is possible toobtain approximate evaluations for the national territory.


B.II-10

For the Italian case, the assessment of vulnerability derives from thecombined use of two data-sets: ISTAT census data (that supply, for everysingle municipality, an esteem of the number and the volume of buildings)and the data collected in different occasions using vulnerability cards byG.N.D.T. (Gruppo Nazionale per la Difesa dai Terremoti).

In short, the building heritage is subdivided in:- two classes (brickwork and reinforced concrete) on the basis of the

structural typology;- six classes on the basis of the age of construction for the brickwork

buildings (<1919, 1919-1945, 1946-1960, 1961-1971, 1972-1981,>1982) and four classes for reinforced concrete ones (<1960, 1961-1971, 1972-1981, >1982);

- two classes (good and bad maintenance state) on the basis of theefficiency of technical systems;

- two classes (since two floors or more) on the basis of the number offloors.

Once that the building patrimony has been subdivided in classes, avulnerability description for every class must be developed. To do that samecriteria adopted to classify the national buildings inventory are followed,using the archives of second level vulnerability cards.

With the support of a table or using density probability curves derived bydata regression it is possible to assign a vulnerability index value to everyclass.


To study the buildings ISTAT data are used as reference, adopting the localscale: 1:5.000 – 1:50.000. This way it is possible to proceed with simplifiedsurveys concerning vulnerability ( second level studies).

3.2.3 Analysis of bridges vulnerability

For these structures too it is possible to draw up survey cards articulated indifferent sections regarding:- identification and general information;- main dimensions, typology;- preservation condition;- detailed analysis for each component of the bridge;- marginal information in order to investigate the seismic behavior, but

useful for some other kinds of analysis.

This method is assimilable to the first level analysis; in fact, typicallystructural elements (such as foundations or frameworks) are not take intoconsideration the method is just based on a few visual noticeableparameters or on direct measures parted in the survey card. The result ofthis procedure is a vulnerability value that supplies an indication aboutbridges conditions from the point of view of the seismic response.

The model consists in the following steps:- subdivision of bridges in typological classes which are correlated to a

“basic” vulnerability value;


B.II-11

- evaluation of further factors that can increase or decrease, for everybridge, the vulnerability value compared with the one attributed on thebasis of the belonging class.


For this kind of studies, aimed at the analysis of an individual object, it ispossible to refer to the town planning scale: 1:500 – 1: 5000.

3.2.4 Analysis of vulnerability for tunnels

This kind of evaluation concerns the already existent tunnels as well asthose not accessible by means of the related project report.

In this methodology the survey is based on detectable appearance on theoutside of the gallery and on measurements on the covering by usinggeotechnical instruments.

The survey card is made up of seven different parts concerning:- general information and characteristics (sections from 2 to 4);- conditions on the inside and appearance on the outside (Section 5);- covering characteristics and stress conditions (Section 6).

The survey is then articulated in three levels:

U1. General characteristics of the work:In the sections from 2 to 4 the card notes the following data.

• Work geometry and parameters, such as:o planimetric development,o altimetrical profile of the tunnel and of his roofing,o form and section.

• Overlooking slope condition:o nature e conditions of the slope,o presence of instability,o presence of supporting works and their conditions,o presence of vegetation, etc.

• Geological characteristics of the formations crossed by the tunnel.

U2. Internal condition of the tunnel:U

The card notes the presence of:• areas with a bad state of covering,• slots in the covering,• damp areas,• systems hanged on the covering.

U3. Measures conducted on the tunnel covering:In the card are indicated:

• - the area of the measurements;• - the conglomerate appearance;• - the concrete mechanical resistance;• - the parietals stress in the covering and the modulus of elasticity.


B.II-12

3.2.4.1 Evaluation of vulnerability index

To evaluate the vulnerability index, the conditions of the slope at theentrance and the exit, of the internal covering and hanged systems of thetunnel are taken into consideration.


For this kind of studies, aimed at the analysis of the singular object, it ispossible to refer to the town planning scale: 1:500 – 1: 5000.

3.2.5 Analysis of vulnerability for supporting works

This measurement deals with already existent supporting works as well asthe ones not accessible by means of the related project report. Therefore,many technical data are not available, that is: wall width, possible armatureplan, geotechnical characteristics of foundation soil and embankment.

Analysis is thus a ‘first level’ analysis and it is based on parameters the canbe detected by means of either direct and surface measurements oroptically detectable aspects, which are recorded in the proper data form.

As technical objective data are missing, in the evaluation of the vulnerabilityindex the conditions of the building and of the surrounding environmentsmust be considered.

Main characteristics of the survey card dataThe survey card supplies information concerning:

• parameters about the state of the work, as:o develop of the plant, average height, slope of the hangings,

thickness at the head;o sort of work and covering, year of construction, presence of

drainage works;o structure and soil of foundation;o work use condition;o conditions of the work about slots, falling blocks, presence of

vegetation,• surrounding environment:

o - side of the mountain slope (towards the mount and thevalley);

o - condition of the side of the mountain;o - presence of super weights due to buildings and of barriers

against stone fallings;• Improvement or alteration operations in the structure or in the

surrounding environment.


The score is composed considering the work height and development inplane.The survey card responses are examined, homogenously grouped by theabove mentioned different aspects and put in a table with maximum and


B.II-13

minimum scores foe each group of aspects and considering the best and theworst situations.


For this kind of studies, aimed at the analysis of the singular object, it ispossible to refer to the town planning scale: 1:500 – 1: 5000.

3.2.6 Analysis of vulnerability for network infrastructures

Network infrastructures (waterworks, sewage pipes, gas network, electricnetwork, streets and railways, etc) are complex structures composed bypipes, joints and plants, sometimes strongly, sometimes loosely linked oneto the other. So, it is important to study their vulnerability not only from aphysical point of view but also considering systemic and territorial aspects.The following methodology has been proposed in Italy to defineinterventions to reduce impacts that events like the seismic one canproduce.

Analysis and evaluation procedureThe method is composed by some analysis cards and evaluation matrixrelated to the networks in the different phases of emergency andrestoration. They contain the main parameters that can most influencevulnerability. The first step consists in compiling the analysis card of thesingular network and an assessment is carried out through a weighed sumof the vulnerability scores assigned to each component. The results arecartographically represented and interpreted. Analysis cards are organised amatrix structure and, for each network, the parameters to survey aredescribed:

• Emergency phaseo performance aspectso relationship between a given network to others lifelines,;o performance invaliding parameters;o location feature;o physical continuity between networks

• Restoration phaseo big economical dependence to the networks of various fields,o possible damages induced by the earthquake


The second step is to assess the vulnerability. This way, on the basis of theinformation collected in the cards, it is possible to express a judgementabout their resistant capacity related to a seismic event.

The parameters values collected in the analysis cards must be insert in theevaluation card, so that is possible to calculate vulnerability degree:

• Intrinsic vulnerability and emergency phaseo performance and localizable aspects

• Territorial vulnerability and restoration phaseo restoration of the normal conditions.


B.II-14


In order to investigate the whole network system or just one singularnetwork on the territory, the scale to use is 1:5.000 – 1:50.000. Instead, ifa particular network junction must be studied, it is better to refer to thetown planning scale: 1:500 – 1:5000.

4 Analysis of risk

4.1 Definition of risk

Combining the above-mentioned factors (hazard and vulnerability), it ispossible to assess the risk. This term defines the entity of damagesexpected in an area due to future events and it comes from the convolutionbetween the hazard and the risk components.

Damages expected can be the result of two different approaches to the riskassessment: the probabilistic or the deterministic one. Depending on theadopted methodology it is possible to achieve different results, useful toreach different aims.

RISK = Hazard * Vulnerability

Fig. 4.1 – Definition of Risk as a convolution between hazard andvulnerability

4.2 Levels of investigation

Using the definition above mentioned, it is possible to investigate risk ondifferent levels of study, on the basis of several factors as:

- the level of investigation to carry out;- the sort of data available;- the cost to support for the research and for the implementation of

the project;- the local hazard situation (more or less serious) to investigate.

RISK

VulnerabilityHazard


B.II-15

There are three different levels of investigation connected with three scalesof analysis and representation. For spatial planning, for example, they cango from general analysis to study the territory at macro scale to carry outexpeditious studies, in the first level, to an intermediate stage for thesecond level (regional scale), to a punctual level of study for the third level,where local aspects are investigated (local scale).

Those levels of study depend also on different objective fixed in advance.

If the intend of the study is the macro-priority research aimed to establish apriority of intervention on a territory, it can be enough to carry outprobabilistic analysis in the first level of investigation.

The second level of investigation can be useful to prearrange emergencyplans, having a look at the over-local scale. To arrange urban plan, instead,it is possible to implement both probabilistic analysis and scenarioevaluations at local scale for an in-depth level of investigation.

Objective of thestudy

Type of analysisScale of

analysis andrepresentation

Level ofinvestigation

General analysis to study theterritory at macro scale to carry

out expeditious studiesNation scale First Level

Intermediate stage ofinvestigation for over-local

analysisRegional scale Second Level

Spatial planning

Punctual level of study, wherelocal aspects are investigated

Local scale Third Level

Macro-priority research aimedto establish a priority of

intervention on a territoryNational scale First Level

Prearrange emergency plans,having a look at the over-local

scaleRegional scale Second Level

Urban policyImplementation of urban plans,using both probabilistic analysis

and scenario evaluations atlocal scale for an in-depth level

of investigation.

Local scale Third Level

Tab. 4.2.1 – Different levels of investigation aimed at spatial planning andurban policies

4.3 Methodologies for risk assessment for differentlevels of study

In the European Union seismic risk has been evaluated in various ways anddifferent studies about this subject have been collected in more volumesedited by the European Commission, Environmental and ClimateProgramme Climate and natural hazards. The common aim of all the studiesis to reduce seismic risk, but there are many different ways to face thisargument.


B.II-16

The main directions that have been followed are:- experimental studies applied in one or more sites by well known

geological and seismological characteristics, both following a seismicevent, and for preventive purposes;

- laboratorial experiments and models to improve current availableengineering technologies;

- new monitoring systems implementation for large and little crustalmovements, increasing current available instrumentation by realizingnew software and past events registration systems.

Despite of the variety of pursued objectives, materials and methods usedand achieved results, the studies have been directed to reduce risk bycharacterizing and decreasing hazard or uncertainty elements, as well asprotection of more vulnerable territorial elements.

Depending on starting hypothesis assumed to define the hazard, there aremany different ways to assess risk that can be carried out on three differentinvestigation levels, from preliminary analysis to special investigations.

Working on territorial viewpoint, it means to lead studies reach tocharacterize:- areas that need analysis of expected damages, meant to territorial

seismic risk unit of measurement, for the first level of investigation;- damage areas on the basis of different scenarios, in order to conduct

intermediate level analysis;- punctual indications for special studies.

4.3.1 First level studies: territorial exposure

In this kind of analysis, the different experiments are aimed at examiningthe exposure and classifying the territory on the basis of the detectedseismic risk classification on the basis of the seismic Italian code.

The Italian legislation foreseen territorial diversification by identifying andclassifying seismic zones. The rules defining general criteria to characterizeseismic areas are the Law February, the 2, 1974, n. 64: “Measures forbuildings with particular prescription in seismic zones ” and the successiveDecree of Prime Minister March, the 20, 2003: “First elements about generalcriteria to classifying seismic areas in national territory and about technicalprovisions for building in seismic areas”.

The basic criteria for dividing regions are described in the Technical Codes,that indicate 4 horizontal acceleration values (aBgB/g) of anchoring of elasticresponse spectrum and planning and building rules to apply; so, thenumber of zones is arranged in 4.

Each area is identify on the basis of expected horizontal acceleration values(aBgB), with probability of exceeding of 10% in 50 years, as the followingtable shows:


B.II-17

Zone

Expected horizontalacceleration values with

probability of exceeding of10% in 50 years

(aBgB/g)

Horizontal acceleration values ofanchoring of elastic responsespectrum (Technical Codes)

(aBgB/g)

1 > 0,25 0,35

2 0,15 – 0,25 0,25

3 0,05 – 0,15 0,15

4 < 0,05 0,05

Tab. 4.3.1 – Identification of the basic criteria for identifying and classifyingseismic regions

What should be avoided is lack of homogeneity in border seismic areasbetween different regions. To this end, their identification must take intoaccount of a reference document at national scale. Starting from referencedocument, it is possible to estimate seismic zones lists formation and toupdate them.

4.3.2 Second level studies: damage scenario

These studies are going to value:

4.3.2.1 Basic Seismic hazard

It is by analyzed using deterministic models to investigate attended shock ina selected area.

Several experiments are based, from time to time, on different parameterssuch as seismotectonic characteristics of the area, the source energyrelease ways, the seismic waives propagation course. Starting whit theseinputs, the procedure manages to define:

- the historical seisicity, by searching in archives and historicalrecording;

- the recent seismicity, that is the one recorded byseismographes.

In the light of these data, several objectives can be pursued, like identifyingsource areas and the events characterized by different recurrence periods.In this way it is possible to calculate (using a specific attenuation model)the expected shaking at the site:

B.II- 1

8

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

Table I: Second level studies- Basic seismic hazard

PROJECTWORKING

GROUP

INVESTI-GATEDAREA

ABSTRACT OBJECTIVES MATERIAL AND METHODS RESULTS

Geodynamicmodelling of anactive region oftheMediterranean:the Apenninegeomodap

IstitutoNazionale diGeofisica,Roma, ItalyandGeoModApworking group

TheApennines

Multidisciplinary approach tomodel the recent geodynamicevolution of the Apennines,one of the most activeregions of the Mediterranean.

Definition of a geodynamic modelof the Apennines to serve as abasis for future multi-disciplinaryresearch and data collection andas a framework for immediateapplication in the assessment ofseismic hazard, earthquakesurveillance, vulnerability ofcultural heritage, protection ofcritical facilities, earthquakeprediction, land use planning,and deep fluids exploitation.

1) Definition of a geodynamic modelof the Apennines

2) Collection and processing of newGPS data in the area using existingvertices and installing new ones toincrease the coverage in the mostinteresting areas

3) Compilation of a new catalogue ofseismic moments of large historicalearthquakes

4) Definition of soil structure in depthto improve digital data quality

5) Compilation of data-base withactual stress-data

6) Two and three-dimensionalanalogical models of theApennines/Tyrrhenian system

Data elaboration for determine the forceacting in the region between theAppennines and the Adriatic/Ionianplate

A basicEuropeanearthquakecatalogue and adatabase for theevaluation oflong-termseismicity andseismic hazard(BEECD)

Istituto diRicerca sulRischioSismico, CNR,Milano, Italy

Europe Prepare a basic parametricearthquake catalogue ofEurope and a database ofprimary data, with specialreference to long-termseismicity

1) To retrieve, evaluate andmake available, in a standardformat, the considerable bodyof data existing in publishedand unpublished studies

2) To investigate, according tostandard criteria, the mainearthquake for which noprimary data is available

3) To use this material forpreparing, according torigorous and transparentprocedures a basic parametricearthquake catalogue ofEurope, to serve both as a toolfor understanding the long-term seismicity and as areliable input for seismichazard evaluation

1) Compilation of the working file

2) Evaluating the supporting data sets

3) Retrieving and improving thesupporting data sets

4) Compilation of a comprehensiveprimary dataset

5) Earthquake parametersdetermination

1) To develop a procedure which can beadopted for future implementation

2) Providing a good set of data and ofestablishing priorities for futureinvestigation

At this stage it can be predicted that theearthquakes included in the WF will bedivided into three categories:

A. Selected earthquakes for whichcomplete, good quality studies will beretrieved or produced, includingintensity data points (8-10 %)

B. Earthquakes for which the availabledata will be retrieved and evaluated,without special improvement (20-30 %)

C. Other earthquakes, for which at leastroot evaluation will be performed (60-70 %).

B.II- 1

9

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

PROJECTWORKING

GROUP

INVESTI-GATEDAREA


Earthquakesprediction intectonic activeareas usingspace techniques

UniversitaFederico II diNapoli,Napoli, Italy

UniversitätStuttgart,Stuttgart,Germany

DepartementGeophysiqueet Imageriegeologique,BRGM,Marseille,France

Campano-MoliseApennines

Study of the geodynamicsprocesses which haveaffected the chain of Matese,and on medium-short termthrough the study of thehistorical and actualseismicity and of grounddeformations which precedeand accompany earthquakes

Earthquake prediction on theMatese by:

1) monitoring of the grounddeformation and the seismicity

2) seismotectonic modelling ofthe area using historicalseismicity, tectonic andgeodynamical modelling of thearea

1) Historical and current seismicity2) Monitoring3) geological analysis4) Analysis of the deformation of

Appennine-Tyrrhenian System andgeodynamical model

5) Hypothesis for a seismotectonicmodel

In such conditions adequate results forearthquakes prediction could beachieved through the following way:1) Realization of the geodynamical

model of the regiontough which it ispossible to build the stress fieldcurrently acting

2) definition of hierarchy ofseismogenetic areas through thegeodynamical and seismotectomcmodels

3) monitoring of the deformations of thesuspect areas

High resolutionimaging of 3-dstrain in seismicand volcanicregions usingdifferential SARinterferometry

Institut dePhysique duGlobe deParis, Paris,France – IPGP

Institut furNavigation,Stuttgart,Germany –INS

CentreNationald'EtudesSpatiales,Toulouse,France –CNES

Politecnico diMilano, Milan,Italy - POLIMI

The use of multiple SARimages such as thosecurrently collected by thesatellites ERS-1 and Radarsatmakes it now possible todetect subtle changes in theEarth's land and ice surfaceover periods of days to yearswith an unprecedented scale(global), accuracy (cm level)and reliability (dayand night,all-weather). The techniqueinvolves interferometric phasecomparison of successive SARimages. SAR interferometrycan also generate highresolution topographic maps

1) The goal of this project is toassess the accuracy of thedifferential SAR interferometrytechnique to measure crustaldeformations in a realenvironment

2) Calibrating the differential SARinterferometry technique indifferent environments. Thiscalibration phase is the centralpart of the present study. Thecharacteristic signature,amplitude and spatialdistribution of each of theseeffects on SAR compleximages and SAR interferogrammust be investigated ondifferent sites representativeof different conditions anddifferent geophysicalprocesses, namelyearthquakes, volcanoes andlandslides.

Experiment in the following selectedsites:1) The Campi Flegrei and Vesuvius, in

Italy which provide a good exampleof critical interferometricconditions: small displacements,rugged topography, low coherence(urban area). Yet, this area is ofmajor interest, given the riskinvolved for the population ofPozzuoli and Napoli.

2) The Etna volcano where a widerange of observations are availablefor a long period of time

3) The Saint-Etienne-de-Tinee areawhere a major landslide is movingat the impressive rate of Icm/day.This provides an example of largedisplacements with high spatialvariability over a very small area(of the order of 1km).

4) The Antarctic which provides anexample of SAR interferometryapplied to the ice-shelf

In this study, SAR interferometry hasdemonstrated its capability to producelarge scale digital elevation models or todetect small displacements of variousorigins, such as surface deformationproduced by a volcano, a landslide or Amoving ice-shelf. Other studies detectedthe effect of earthquakes, tides onglaciers, or phase surface changes. Thiscapability provides several fields ofapplication with revolutionary toolswhich chance the accuracy of the studyregardless of the accessibility or groundinstrumentation.

B.II- 2

0

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

PROJECTWORKING

GROUP

INVESTI-GATEDAREA


*Genesis andimpact oftsunamis on theEuropean coast -GITEC - anEuropean effortto foster tsunamiresearch

Dipartimentodi Fisica,Settore diGeofisica,University ofBologna,Bologna, Italy

Europeanareas

The project is structured infour main areas of researchand activity embracing: 1-tsunami generation, 2-tsunami potential, 3- tsunamipropagation 4 - tsunamiwarning and risk mitigation

Illustrate the main resultsattained by the project GITECand the basic methods used inorder to achieve them

1) European tsunami catalogue2) Study and simulation of

earthquake-induced tsunami cases3) Study and simulation of landsides-

induced tsunami cases4) Assembling of bathymetric data5) Recognition of tsunami deposits

through geological methods6) Tsunami warning system7) Epilot land management study

Tsunamis are produced by submarineand coastal earthquakes, by submarinelandslides and by volcanic eruptions.Though it is clear that the generationprocess must involve a suddendisplacement of a large volume of oceanwater, it is presently recognized thatthere are still many aspects of thisprocess that are uncertain and deserveinvestigation, which makes tsunamigeneration one of the key problems oftsunami research.

*Southern Europenetwork foranalysis ofseismic data

IstitutoNazionale diGeofisica,Roma, Italia

IstitutoGeograficoNacional,Madrid

NationalObservatoryofAthens, Atene

Finsiel s.p.a.,Roma

In this paper we present theresults of the Project"Southern Europe Network forAnalysis Seismic Data"sponsored by the EuropeanCommunity. The project isstructured in four themes ofseismological interestdeveloped by three National Institutes (Greece,Italy and Spain) working ingeophysical fields, andsupported by high technologycompanies as Digital, Finsieland Telecom.

1) A telematic system for seismicdata exchange by means of aprivate satellite network wascreated and a standardprotocol for seismic dataexchange between the threeseismic national networksconnected by the satellitenetworks was realized

2) recovery of old waveformsrecordings of the mainearthquakes occurred at thebeginning of this century.

3) 3D Tomography and aninternational Workshop wasorganized in the frame of theSouthern Europe Network forAnalysis of Seismic Dataproject

1) 3-D model of seismic wave velocity of the mediterranean area2) data-bank connection to the MEDNETnetwork3) digitization of historical seismograms

B.II- 2

1

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

PROJECTWORKING

GROUP

INVESTI-GATEDAREA


*Rapidtransfrontierseismic dataexchangenetwork:Transfrontiergroup

TransfrontierGroup

Understanding the sourcesand reasons for our seismicityand the hazards we areexposed to dependsfundamentally on good dataand, for Europe, which isdivided politically into smallregions in relation to itstectonics, it is essential thatgood data exchange isachieved

1) Establish the definition of"significant earthquake";

2) Install a computer bollettinboard at each partecipant'slaboratory which will showdata acquired during theprevious three monthstogether with an 'earthquakealert' area containinginformation on immediatesignificant earthquakes;

3) Develop or adopt standarddata exchange formats to beused for computer-to-computer transfer of waveformdata;

4) Implement waveformexchange between participantsfor significant earthquakes;

5) Transmit data continuouslyacross selected borders wherethis proves to beadministratively possible;

6) Upgrade the seismicmonitoring network in Portugaland add key monitoringstations in border regions ofother participants whereappropriate.

Establishment of a network of institutions with national or quasi-nationalresponsibilities for earthquake monitoring

The adoption and gradual implementation of the e-mail based softwaredeveloped at ETH, Zunch (Auto Data Request Manager, ADRM) is speeding updata transfer and is placing participants on a convergent path with other relatedactivities in Europe and more widely.

New seismc stations have been installed to improve border region coverage anda modern digital, remote data access network is now functioning in southernPortugal

Measurement ofstrong groundmotion in Europe (MASGE)

Imperialcollege ofScienceTechnology &Medicine,London

Europeanarea

Present the current status ofthe MASGE project for thedevelopment of predictiverelationships for peak groundacceleration and spectralordinates for the Europeanarea for engineering purposesand, at the same time, todiscuss the experience gainedfrom this exercise.

Attenuation relationships forpeak and response spectra forground accelerationsincorporating site conditionsprovide an estimate of groundshaking at a given distance froman earthquake of specifiedmagnitude. For practicalengineering applications suchrelationships:1) must be based on reliable

observational data2) must be relatively simple3) must involve design variables

that can be assessed by theengineer with some confidence

1) strong-motion records2) seismological parameter3) source distance4) station location5) focal depth6) magnitudes7) moment magnitude8) local soil condition9) dataset10) attenuation model

1) Regression test for zero-periodhorizontal acceleration

2) Depth controlled test of horizzontalacceleration

3) Site effects test4) Magnitude dependent shape test5) Attenuation of zero-period

horizontal acceleration6) Effect of site condition7) Attenuation of spectral ordinates for

horizontal acceleration with siteeffects

8) Attenuation of zero-period verticalacceleration

9) Site effects10) Attenuation of spectral ordinates for

vertical accelerations with siteeffects

B.II- 2

2

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

PROJECTWORKING

GROUP

INVESTI-GATEDAREA


Long periodearthquake riskin Europe

EQEInternational,London

Europe Quantification of this seismichazard regime

Attention has also beendirected towards the practicalengineering implications forthe seismic safety ofstructures vulnerable to longperiod, long duration,excitation

Establish a sound empirical andtheoretical basis for theassessment of long periodearthquake risk in Europe. Thishas involved pursuit of a numberof seismological research studies,each of which affords insight intothe characteristics of long periodmotion

1) analysis of empirical seismograms2) numerical simulation of seismograms3) optimization of 2D laterally heterogeneous complete synthetics programs4) stochastic modelling long period motion5) rayleigh wave propagation6) long period earthquake effects

Time dependenthazard estimatebased on amulti-parametergeophysicalobservatorysystemSCENARIO

ISMES,Bergamo

NationalGeophysicsInstitute,Roma

NationalObservatory,Athens

Development of a softwaresystem which supports thereduction of seismic risk inearthquake-prone zones. Thesystem implements possiblescenarios through theintegration of models anddata layers. A patternrecognition system, linkedwith a multiparametergeophysical observatorysystem, provides timedependent evidences forpossible seismic events andfollowing damage scenarios.

1) A data base of measurementdata coming from a multi-parameter data acquisitionnetwork (the Poseidon centreinstalled in Sicily), has beendeveloped and methods ofrecognising these patternshave been devised.

2) A real time patterns andtrends recognition system hasbeen implemented whichsearches for identifiedprecursors for events ingeophysical data coming fromthe automatic acquisitionsystem of the Poseidon centre.

3) Models of expected damage interm of macroseismic intensitymaps, due to seismic eventswhich incorporate parametersderived from the incominggeophysical data at the centrehave been implemented.

1) damage scenarios2) precursor analysis3) software implementation

The SCENARIO system can be directlyapplied in various fields related to civilprotection activities, and severaldevelopments may be envisioned

The same technology may be used inthe emergency phase, when completeinformation about actual damages is notavailable and the best possible estimateis required to cope with unforeseensituation.

The main foreseen development of theproject is the integration with damagemodelling systems at a different scale

B.II- 2

3

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

PROJECTWORKING

GROUP

INVESTI-GATEDAREA


Seismic hazardzonation: amultidisciplinaryapproach usingfluid-geochemistrymethod (GSZ)

University ofRome 'LaSapienza'

IstitutoNazionale diGeofisica,Italy

University ofExeter, EarthResourcesCentre (ERC)

ThessalonikiUniversity(AUT)

CNRS Nancy(CRG)

Italy,Greece,UnitedKingdom

Development of amultidisciplinary approachmainly based on fluidgeochemistry data coupledwith geological andgeophysical information.Surveys were planned indifferent geological, structuraland seismotectonic scenariosto test the reliability of suchan approach in locating activefault systems and evaluatingtheir seismogenic potential

1) to refine seismic hazardzonation by fluid geochemistrymodelling and monitoring in afew selected test-sites

2) to understand better the pre-seismic processes , seismicsources and seismic stress-strain phenomena linked torising fluid

3) to develop a multidisciplinaryapproach to seismic zonation

4) to enhance the basicknowledge of geochemicalearthquake prediction studies

The GSZ research is divided into thefollowing steps:1) the comprehensive investigation of

water-rock-gas interactionmechanisms characterising thegeological and seismo-tectonicsetting of the investigated areas(i.e. geochemical modelling);

2) the location in the surveyed areasof potentially seismo-related;

3) fault systems characterised bydeep input and minimalcontamination by shallow aquifers.

University of Rome subcontractors:1) soil-gas surveys in the Fucino and

Gargano area2) stable isotopes geochemestry in

Gargano groundwater3) gravity features in the Gargano area4) structural geologicy survey in the

Gargano area

CNRS Nancy:1) rare cases isotopic ratio in the

Gargano fluids

Exeter University, U.K.:1) structural model geology of the study

areas in Devon and Cornwall2) review of fluids seismicity3) seismic hazard of the area4) soil gas mapping5) structural analysis from topographic

features

ING and subcontractors:1) geological review and geochemical

survey in Sardinia2) geological and geochemical survey in

the Gargano area3) interdisciplinary GIS data

management4) the development of the geochemical

monitoring system (GMSII)

Genesis andimpact oftsunamis on theEuropean coaststsunami warningand observations- GITEC TWO -

Dipartimentodi Fisica,Settore diGeofisica,University ofBologna,Bologna, Italy

Atlantic,Ionian Sae,easternMediterranean

GITEC-TWO is the acronym ofan international projectinvolving nine partners ofsevenEuropean countries: France,Greece, Italy, Norway,Portugal, Spain and UnitedKingdom.

1) tsunami warning systems2) new techniques to model

tsunami genesis3) new techniques to model

tsunami propagation4) tsunami observations5) tsunami risk

1) tsunami warning systems2) tsunami generation3) tsunami propagation and run-up4) tsunami observation

One of the final products will be a'Tsunami risk management-preventionand mitigation measures' map that willsummarise the tsunami risk analysisand the proposed counter-measures

B.II- 2

4

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

PROJECTWORKING

GROUP

INVESTI-GATEDAREA


Satellite seismicnetwork

IstitutoNazionale diGeofisica ofRome

IstitutoGeograficoNadonal ofMadrid

NationalObservatoryof Athens

The Argo project representsthe first European digitalseismic network on datatransmission via satellite.This project connects twoindependent networks usedfor emergencycommunication (ECN) andenvironmental data collection(ADCN), respectively, withthe following institutions:control centre of the ItalianCivil Defence Department, theIstituto Nazionale di Geofisica(ING) and the volcanologicaland hydrological centres.

- Assigns the capacity of transmission to the peripheral stationsaccording to the kind of probes used in each station.

- Sends to the peripheral stations a time mark reference to the timing ofthe acquired data.

- Controls the satellite link between the peripheral stations and data-collection centre

- Forms with 30 packets received from specific peripheral stations aunique packet which is forwarded again by a satellite relaunching, tothe qualified data-processing centre

The expected results of this project areas follows:1) The creation of a distributed system

for the real-time monitoring of thenetwork area seismicity

2) ) The analysis of at least 10 importantseismic events with the highestmagnitudes occurring in this century,based on the original instrumentaltracks from stations in variouscountries, which will allow asubstantial improvement of thepresent seismic catalogue of theMediterranean area

3) The creation of an infrastructure andthe study of common methods for thedetermination, the selection and theexchange of seismic data betweenEuropean countries via satellite link

4) The creation of a common databasewhere a suitable choice of the datarepresenting the main seismic eventsmonitored by the southern Europenetwork stations will be cumulated

5) The elaboration of a three-dimensional kinematic model of theMediterranean Sea through thecomparison of the differenttomography techniques currentlystudied by the scientific partners

B.II- 2

5

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

PROJECTWORKING

GROUP

INVESTI-GATEDAREA


*Time-dependenthazard estimatebased on a multiparametergeophysicalobservatorysystem

ISME5,Bergamo,Italy

NationalGeophysicsInstitute,Rome, Italy

NationalObservatoryof Athens,Athens,Greece

Development of a softwaresystem which supports thereduction of seismic risk inearthquake-prone zones. Thesystem implements possiblescenarios through theintegration of models anddata layers.

The objective of this project is toreduce the seismic risk bydeveloping a software system tosupport the civil defenceauthorities in planning theirresponse to an earthquake

1) A database of patterns and trendsof anomalies related toearthquakes in data coming from amultiparameter data-acquisitionnetwork (the Poseidon centreinstalled in Sicily) will bedeveloped, then methods ofrecognizing these patterns will bedevised.

2) A real-time patterns and trendsrecognition system will beimplemented, which will search foridentified precursors for events ingeophysical data coming from theautomatic acquisition system of thePoseidon centre. The system willhave a semiautomatic learningfacility for enlarging the databasedescribed above

3) Models of expected damage interms of macroseismic intensitymaps, due to seismic events, whichincorporate parameters derivedfrom the incoming geophysicaldata at the centre will beimplemented.

The benefits of this project lie inreducing loss of life and damage to theinfrastructure through seismicprotection procedures and an efficientcivil defence response after the event.Moreover, the system described wouldimprove the ability to manage the riskto the environment associated withseismic events.

Legend:

* Project relevant for spatial planning


B.II-26

4.3.2.2 Physical vulnerability

It is analyzed by using direct methods as vulnerability surveys or by meansof approximate evaluations combining different available data.

In this way is possible to subdivide the heritage to value on the basis ofmore factors (such as the structural typology, the age of building, the stateof maintenance) and reach at defining a vulnerability index for differentstructures considered.

B.II- 2

7

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

Table II: Second level studies- Physical vulnerability

PROJECT WORKINGGROUP

INVESTIGATEDAREA


*Earthquakeprotection forhistoric towncentres TOSQUA

School ofArchitecture andCivilEngineering,University ofBath, U.K.

The MartinCentre,CambridgeUniversityArchitectureDepartment,Cambridge, U.K.

Lisbon, Naples,Rhodes andCastiglioneCasauria

The present project addressesthis issue with particularreference to historic towncentres in areas of Europewhere the seismic hazard isrelatively high while thearchitectonic and urbanheritage is of unquestionablevalue, for it is unique.

1) Verify current and developnew vulnerabilityassessment techniques atpurpose for historic towncentres

2) Produce guidelines for localauthorities on the subject ofcost effective andunobtrusive upgradingstrategy, which will improvethe seismic behaviour of theexisting building whilepreserving their historic andarchitectonic character

1) assembling data on thevulnerability of the historicbuilding stock for the four casestudies

2) comparing existing methods ofearthquake vulnerabilityassessment

3) developing a new method toevaluate buildings which haveundergone typical renovationand structural strengtheningand do not show damagedirectly related to seismiccauses

4) identifying general strategies forcost-effective retrofitstrengthening of key types ofbuildings such as multi-storeyresidential blocks

5) disseminating these findingslocally to professional andadministration officers

The importance of comparativestudies in the field of seismicvulnerability of historic centres.The distinctive character andhistory through which each of thecase studies has developed to thepresent state, as it would be forany other historic centre, make anygeneral assumption on assessmentmethods an almost futile exercise.The European TOSQA projecttherefore represented a uniqueoccasion to identify crucialparameters that should be takeninto account when devising avulnerability methodology,providing the opportunity to testthem on different cases.

**Experimentalevaluation oftechnicalinterventions toreduce seismicvulnerability of oldexisting buildings

ISMES (Bg)

NationalTechnicalUniversity ofAthens / LEE,Athens (Greece)

Results of a largeexperimental programmecarried out on 15 models,scaled 1:2, of which fourteentwo-storey regular masonrybuildings and one three-storey irregular building. Aftersuffering damage, the modelshave been repaired andstrengthened and againtested. A total number of 25buildings have thus beensubjected to test by theshaking table facilities ofISMES and NTUA/LEE

Provide a better insight into theactual seismic response ofexisting masonry buildings andto experimentally assess theefficiency of practicaltechniques for upgrading theirearthquake resistance capacity

Seismic shaking-table tests havebeen carried out on 14 two-storeymasonry housing models:1) The structural models have

been subjected to realearthquake-like dynamicexcitation up to appearance ofsignificant damage

2) then they were repaired byapplication of retrofittingtechniques

3) Subsequently, the repairedhousing models have beenagain subjected to earthquake-like shaking, in order to assessthe actual effects and efficiencyof the applied retrofittingtechniques

The results have been collected ina table

Italian researchprogrammes inearthquakeengineering

National Groupfor theEarthquake LossReduction, Italy

Emilia Romagna,Italy

Description of the present situation of research in earthquake engineering in Italy and to the future scientific applied activities, deal withtwo aspects: further research but also dissemination of knowledge and preparation of concrete tools for an effective policy of seismicprotection.

B.II- 2

8

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1


INVESTIGATEDAREA


**

An expert systemto supportretrofitting ofmasonry buildings

M, Cadei, P.Panzeri, A.Peano, P.SalvaneschiISMES,Bergamo, Italy

A mobile laboratorysupporting the seismicassessment and planning ofretrofitting for masonrybuildings has been designedand implemented in ISMES. Itis equipped with devicesallowing experimental tests tobe performed for theacquisition of data related tothe physical properties of thematerials and to the structuralfeatures of the buildings. It isalso provided with softwaresystems for data acquisitionand management and, inparticular, with a knowledge-based system for supportingthe evaluation and planningprocess.

Support the procedures leadingto the seismic assessment ofmasonry buildings and theplanning of precautionaryoperations on them

1) generate all the input datarequired by the seismicassessment software

2) ensure reliable and reallyinteresting information

3) provide quick and low-cost testsand analysis

4) limit weight and volume ofrelated devices

5) limit electric power required6) allow execution of the tests on

site, particularly on a building inan old urban nucleus

The whole mobile laboratory hasbeen used in seismic assessmentto three buildings in an old Italianurban nucleus

Seismicvulnerabilityassessment ofmasonry gravitydams

C. Noret, A.Carrere

Develop the methodology andquantitative tools for seismicvulnerability assessment ofmasonry gravity dams

1) Detection of the key factorsinfluencing the dynamicresponse of water-retainingmasonry structures

2) Prediction of permanentdeformations occurring as aresult of the seismicresponse of masonry gravitydams

3) Gaining an improvedengineering knowledgeenabling the seismicvulnerability of masonrygravity dams to be reduced

1) Survey of the materials commonly used in the construction of existingEuropean masonry gravity dams

2) Definition of a constitutive law for stone masonry used in damconstruction

3) Laboratory testing on large-scale internal filling material specimens4) Full-scale dynamic experimental investigation on a typical masonry

gravity dam5) Numerical modelling of seismic behaviour of gravity dams6) Improvement and validation of simplified methods7) Safety criteria, seismic vulnerability evaluation and upgrading

possibilities

Legend:

* Project relevant for spatial planning** Laboratory experiments


B.II-29

4.3.2.3 Damage scenario evaluation

A more relevant approach for planning purpose, thought less considered instudies carried out until today, concerns the evaluation of the damagescenario that can supply useful elements for emergency management andto arrange emergency programs.

This kind of evaluation can supply indicators about damage scenarioregarding:

- the cost of buildings direct damages (physical and economic);- the number of the buildings expose to collapse risk (for

planning emergency operations);- the number of potential victims and wounded people (for

estimate the impact of the event on the damaged population)

Having P.G.A. and vulnerability values for each event, it is possible to findout the damages costs expected value for unit of volume, which could becompared to the entity of the physical damage too.

The number of victims and injured can be calculated by the following steps:- evaluation of the number of collapsed buildings;- evaluation of the number of present inhabitants in collapsed buildings;- evaluation of the number of victims as an equal to 50% of present

inhabitants;- evaluation of the number of injured as an equal to 30% of present

inhabitants in collapsed buildings and as an equal from 0 to 50% ofinhabitants of buildings where the damage is bigger than 30%.

B.II- 3

0

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

Table III: Second level studies- Damage scenario

Legend:

* More relevant project relevant for spatial planning

PROJECT WORKING GROUP INVESTIGATEDAREA


*Seismic risk evaluationthrough integrated useof geographicalinformation systems andartificial intelligencetechniques SERGISAI

S. Menoni, V. Petrini, G.Zonno Istituto di Ricercasul Rischio Sismico,Milan, Italy with thecontribution of theSergisai working group

The project Sergisai hasdeveloped a computerprototype in which amethodology for seismic riskassessment has beenimplemented

1) Probabilistic model forecasting the future seismic activityin the area to be studied

2) Deterministic methods for assessing the hazard input3) Probabilistic methods for assessing the hazard input4) Models and codes selected for vulnerability assessment5) Method to assess the vulnerability of buildings6) Developing a model to assess the vulnerability of urban

systems7) Definition and application of the prototype to test areas

(Toscana, Garfagnana, Barcelona)8) Use of the prototype in decision-making process

An ideal prototype shouldallow end-users to carry outa complete risk assessmentand evaluation of preventivestrategies communicatingthrough a friendly userinterface. The riskassessment should addressnot only all the parametersdefining the hazard but alsogive a complete picture ofthe vulnerability of the mostimportant sub-systems thatare part of the life of humansettlements.

*A rapid warning systemfor earthquakes in theEuropean-Mediterraneanregion

European-MediterraneanSeismological Centre(EMSC), Bruyeres-le-Chatel,France

Institute GeograficoNacional (IGN), Madrid,Spain

British Geological Survey(BGS), Edinburgh, UnitedKingdom

University of Thessaloniki(AUTH.GL),Thessaloniki,Greece

GeoForschungsZentrum(GFZ), Potsdam,Germany

Istituto Nazionale diGeofisica (ING), Rome,Italy

MediterraneanSea

This project intends onimproving the existing systemin use at the European-Mediterranean SeismologicalCentre (EMSC) whichfederates several seismicnetworks. New networks aregoing to be connected to thesystem and automatic dataprocessing will be improved inorder to achieve higheraccuracy in the determinationof the earthquake focalparameters

1) Releasing accuratelocation informationwithin one hour ofany event ofmagnitude 5.0 inEurope

2) Providing detailedsource analysis forthese events within afew hours

1) Enhance the geographical coverage of short periodseismological station transmitting data in real time

2) Increase the number of seismological observatoriescentralising their regional/national data and locating in quasi-real-time earthquakes in the European-Mediterranean areas

3) Realise information for events magnitude greater than 5.04) Carry out a study for defining better propagation model for

the European-Mediterranean region5) Carry out a study for designing a better location software

integrating automatic depth evaluation6) Integrate the automatic computation of the scalar seismic

moment and Mm magnitude7) Develop/enhance techniques for fast moment tensor inversion


B.II-31

4.3.3 Third level studies: seismic risk

Those are typically engineering and technical studies, aimed at studing aspecific area.

4.3.3.1 Local seismic hazard assessment

First the basic seismic hazard is valued, and then local seismic hazard isinvestigated. Local seismic hazard effects can change on the basis ofparticular geological and morphological conditions characterizing a specificarea (e.g. topological irregularity, deposits, landslides). For areas that canproduce local effects (and so potentially dangerous) their response todifferent shock levels must be investigated.

Geological and geomorphological particular conditions in one area, when aseismic event is occurring, can produce different effects that must be takeninto consideration for the local seismic hazard assessment.

These effects are called “local effects” and can be distinguished in:

- instability effects: collapses or movement of big soil massesincompatible with structure stability, which are different depending oncondition present in site;

- site effects: represented by the interaction of seismic waves withparticular local condition, that can modify the characteristics ofsuperficial seismic movement compared with the shaking in the bedrock.Local conditions are represented by superficial and buried morphologies(topography) and by particular geological and stratigraphical soilcharacteristics, that can generate local amplifications of seismic actionstransmitted by terrain and by resonance phenomenon due to the specificterrain and structure under investigation.

These analyses constitute the seismic microzoning study that obviously isan interdisciplinary analysis, including geological and seismological studies,and also geotecnical and structural engineering studies.

4.3.3.1.1 Methodologies for evaluating site effects

To evaluate site effects there are different procedures depending on theadopted methodologies and on the attended result:

- qualitative approach: it is the first step to characterize generally theproblem of local effects;

- semi-quantitative approach: it represents a very clear and useful guide,from the methodological point of view, for the development of seismicmicrozoning studies, illustrating, for each category of phenomenonassociated with a seismic event, some zoning methodologies subdividedin three levels of investigation, related to the extension of the areaunder examination, the available data and the detail level of theenclosed cartography;

- quantitative approach: it represent a detail study for limited localsituations, so they are individualized physical size useful to quantifyinglocal effects.


B.II-32

Quantitative evaluation

The quantitative evaluation is subdivided in:

a. instrumental approach: based on analysis and elaboration of recordedseismic data in site. The most diffuse and used methods are theNakamura Method (1989) and the spectral ratio method (Kanai eTanaka, 1961).

b. numerical approach: based on numerical analyses of real situations bysuitable and detailed geometrical and mechanical site characterizationand evaluating the local seismic response by using calculation codes. Inorder to carry out a numerical analysis the following steps must be takeninto consideration:

1. Construction of geological section;2. Definition of input movement;3. Definition of geotechnical parameters;4. Selection of calculation programmes: monodimensional,

bidimensional, tridimensional;5. Choice of the sort of result to supply.

4.3.3.1.2 Instability evaluation

The evaluation of landslides hazard (such as slides and flows or as falls)triggered by earthquakes, consists in landslide stability analysis or in slopestatic condition analysis, both in pseudostatic conditions and, then, indynamic conditions.

The first step is to recognise unstable areas, by means of a geological studyin appropriate scale, whose result can be the preparation of:

1. A geological map, a geomorphological map, a lithotecnical map, and inparticular a landslides and subject to landslides areas map;

2. A cataloguing of these areas in order to store characteristic data(typology, activity, geology, morpholocical elements, etc.) (Scheda IFFI,2001);

3. Landslides movements evolution control, both by means of traditionaltechniques such as inclinometers, piezometers, etc, and by means ofinnovative techniques as SAR interferometry, etc.

Following the characterization and identification of landslide movements,you must procede quantifying them, meaning the assessment of stabilityindex in static, pseudostatic and dynamic conditions.

4.3.3.1.3 Scale of analysis and representation

To analyse local effects the scale to take into consideration is the detail one(1:500 – 1:5.000), that permits to microzone the area. This way it ispossible to characterize the individual phenomenon, such as a land subjectto landslides or a deposit.

But if the aim of the analysis is to characterize the phenomenon at aregional level, the regional scale up to 1:10.000 can be used. Above thisthreshold the phenomenon in examination cannot be characterizedanymore.

B.II-3

3

Table IV: Third level studies - Local seismic hazard assessment


INVESTIGATEDAREA


Short term earthquakepredictionmeasurements inGreece at sitessensitive toobservation of seismicelectric signals -SES

Solid StateSection,Department ofPhysics,University ofAthens

Western Greece(Lefkada),Chalkidiki,Northern Greece(Grevena-Kozani)and CentralGreece (Eratini-Egion)

During the period June1994 - May 1995,significant earthquakeactivities occurred inWestern Greece (Lefkada),Chalkidiki, Northern Greece(Grevena-Kozani) and inCentral Greece (Eratini-Egion). They were precededby SES electrical activitiesthat led to predictionsissued well in advance.These predictions containedinformation concerning:

1) the time-window

2) epicentral area

3) magnitude of theimpending earthquakes

1. investigation ofwhether a SES verticalcomponent exists

2. investigation of theinfluence of local andregional inhomogeneities(of the geoelectricalstructure in general) on thesensitivity of "a site" forSES collection

3. investigation ofprecursor changes, if any inthe impedance tensor thatinterrelates the variationsof the magnetic and theelectric field of the earth

4. laboratoryinvestigation of theemission of electricalprecursory phenomena

The electrotelluric measurementshave been carried out:1) in three remote SES sensitive

stations in Greece2) using several dipoles with

lengths ranging between fiftymeters and several kilometers

3) measuring the verticalelectrotelluric componentusing pairs of electrodesinstalled at each of twoindependent boreholes withdepths of around 50m

4) using a sampling rate of theorder of 1 sample/sec

1) The big earthquakes whichoccurred in Greece during theperiod June 1994-May 1996,were preceded by significantSES activity

2) The vertical component of anSES is not always observed.For example, the SES electricalactivity that preceded thestrongest EQ in Greece duringthe last 10 years, did not showany vertical component.

3) Laboratory experiments showthat the rock rupture ispreceded by transient electricchanges similar to SES.

Observation andmodeling ofheterogeneities inseismic sources andcrustal structures forseismic hazardassessment aroundactive faults in themediterranean region.

Institut de Physiquedu Globe de ParisInternational Centerfor TheoreticalStudies, TriesteIstituto di Geodesia eGeofisia, TriesteUniversity of OxfordUniversidadComplutense MadridInstitute GeograficoNational, MadridInstitute SuperiorTecnico, LisbonAristotele Universityof ThessalonikiNational KapodistrianUniversity of AthensNational Observatoryof Athens

Mediterraneanregion

Seismic hazard assessmentin the Mediterranean regionto contribute to theunderstanding and propersimulation of thiscomplexity, in order toconstrain the physicalprocesses at work duringthe rupture of a fault, andto better assess the seismichazard in tectonically activezones

1) tectonic and seismologicalresults obtained from fieldwork and data acquisition,giving evidence for anddescribing the earthquakesource complexity

2) develop more refined dataanalysis and numericalsimulations, concerning bothsource and propagationeffects

3) seismic hazard andengineering application

1) tectonic study of active faultsystem multidisciplinary studyof destructive earthquakes

2) seismic source analysis fromseismic records in theMediterranean Area

3) modelling the complexity ofseismic source

4) complexity of wavepropagation

5) a seismic hazard andengineering application

B.II-3

4


INVESTIGATEDAREA


Euro-seistest: volvi-thessaloniki: aEuropean test site forengineeringseismology,earthquakeengineering andseismology.

COMMISSION OFTHE EUROPEANCOMMUNITIESDirectorateGeneral XII forScience, Research& Development

Alluvial valley 30km northeast ofThessaloniki, onthe active fault ofthe largeearthquake(Ms=6.5) of June20. 1978

The objective of theEUROSEISTEST R&D projectis to establish in aseismically active area aEuropean Test Site in orderto study various problemsin the field of EngineeringSeismology, EarthquakeEngineering andSeismology.

Produce, for a long period oftime, a high qualityinstrumental in-situ data whichare extremely well controlledregarding their seismological,geological, geotechnical andstructural backgrounds, so thatthey can validate variousmethods and analytical -numerical - empirical toolsused in seismology (predictionof ground motion, site effectsetc) and earthquakeengineering (buildingresponse, soil-structureinteraction, lifeline problemsetc).

1) site description2) seismological networks3) temporary seismic survey4) geodetic survey5) geophysical and geotechnical

investigation6) instrumentation -

accelerometric network, freefield

7) prediction studies of strongmotion

8) processing of site effects9) instrumentation and testing

over a structural model

1) Create an area perfectly wellknown from seismological,geological and geodynamicalpoint of view that is a highquality experimental site inorder to study differentproblems related to theaforementioned subjects.

2) The strong motion networkinstalled is operational since1994. The temporary seismicsurvey injunction with theinstrumental structure offers agood possibility to theresearch engineers andscientists in European orinternational level, to testtheir methods to validate theircodes and to develop newmethods and codes moreprecise and applicable.

Earthquake-predictionresearch in a naturallaboratory PRENLAB

Prenlab group Iceland Multinational project ofearthquake predictionresearch at reducingseismic risk;

High quality earthquakedata acquisition andevaluation system

1) to develop methods forautomatic extraction of allinformation available in thefrequent micro-earthquakerecordings, including faultmapping, rock stress tensorinversion, and monitoring ofcrustal instability

2) to make use of informationfrom micro-earthquakes,geological information,historical as well as olderseismological information forphysical interpretation ofand modelling the tectonicprocesses leading toearthquakes

3) to improve theunderstanding of the spaceand time relationshipbetween earthquakes andother observable featuresassociated with crustaldeformation

4) to apply this knowledge forimproved real-timeevaluations and alertsystems and for improvedhazard assessments

1) extension of the monitoringnetworks

2) acquisition, evaluation andstoring of data

3) to search for time and spacepatterns in the multilpidy ofthe information of the SIL data

4) introduction of new algorithmsinto the alert system andother evaluation of the SILsystem

5) retrieving of data and otherpreparatory work formodelling destructiveearthquakes

6) development of methods usingmicro-earthquakes formonitorig crustal instability

7) monitoring stress changebefore earthquakes usingseismic shear wave splitting

Two models are being prepared:1) a scheme comprising the main

ridge parts in Iceland and theNorth Atlantic Ridge to thenorth and to the south ofIceland

2) a model of the SISZ and theadjacent part of the easternrift zone

B.II-3

5


INVESTIGATEDAREA


3d site effects and soil-foundation interactionin earthquake andvibration riskevaluation (TRISEE)

Politecnico diMilano, Italy

Universita diCagliari, Italy

EC Joint ResearchCentre, Ispra

NationalTechnicalUniversity, Athens

Royal Institute ofTechnology,Stockholm,Sweden

New 3D/2D wavepropagation tools forinvestigating site andsource effects inearthquake and vibrationenvironments, applicationto significant engineeringproblems, large laboratorycyclic tests on non-linearsoil-foundation interaction,and development of anartificial intelligenceapproach to assess site-dependent risk based onnumerical simulations andactual observations

The model can be used to:1) investigating site effects and

source effects of earthquakeand environmentalvibrations

2) apply model to solverelevant engineeristicproblems

3) laboratory cyclic tests onnon-linear soil-foundationinteraction

4) develop an artificialintelligence approach toassess site-dependent risk

1) numerical tools2) experimental data and field

observation

• Codes created for wavepropagation and soil-structureinteraction

• Validation and applications ofnumerical tools

• Experimental results fromlarge scale laboratory test

• Preliminary recommendationon site-dependent riskassessment for earthquakecodes

A European test sitefor earthquakeprecursors and crustalactivity: the Gulf ofCorinth, Greece

GAIA:GeotectonicActivity,Instrumentationand Analysis P.Bernard et al.

Gulf of Corinth,Greece

The project will contributeto defining optimalmethodologies in terms ofinstruments, site selection,data analysis, and physicalmodelling for the detectionand understanding ofseismic and a seismiccrustal instabilities

The objective of the GAIAproject is to install around theGulf of Corinth a network ofmultiparameters sites withcontinuous monitoring ofseismicity, grounddeformation, hydrogeology,and electromagnetism, forrecording and modelling thegeophysical processes relatedto the seismic and a seismicdeformation in the faultsystem of the rift

Several dozen sensors havebeen already been set up inmultiparameter sites withcontinuous monitoring. Incomingdata are being analysed atpresent for noise removal, anddecorrelated from meteorologicalfactors:1) seismicity2) crustal deformation3) radon and groundwater4) electromagnetism

A large part of the multipara-meter equipment planned in theGAIA project is now installed.The analysis of the incoming datais just starting for most of thestations: correlation of recordedsignals to meteorological factorsand the tide will be the first step;intercorrelation between variousgeophysical parameters andvarious sites, as well as with thelocal seismic activity, will then becarried out.

Active faulting andseismic hazard inAttica (Greece)SEISFAULTGREECE

Université JosephFourier, GrenobleInstitut dePhysique duGlobe, ParisAristotleUniversity ofThessaloniki

NationalKapodistrianUniversity, AthensNational TechnicalUniversity ofAthensUniversity ofCambridge

Gulf of Evia andthe Aegean

The project concerns amultidisciplinary study ofthe active faulting aroundthe Gulf of Evia and aseismological study of theAegean to mitigate betterthe seismic hazard aroundAthens (Greece)

- Deploy a network of 30 broad-band seismological stations over the Aegean. This network willrecord local, regional and distant earthquakes that will be used for the study of the local seismicity,the structure of the crust and the upper mantle

- Conduct a seismological survey to the Gulf of Evia to study the seismicity and the velocity structureof a very active extensional region

- Geodetic survey and a tectonic survey

B.II-3

6


INVESTIGATEDAREA


Euro-seistest — Volvi,Thessaloniki: aEuropean test site forengineeringseismology,earthquakeengineering andseismology

K. D. Pitilakis,Professor,AristotleUniversity ofThessaloniki(Coordinator)

D. HatzidimitriouAristotleUniversity ofThessaloniki

G. Manos 1. T. S.A. K, Thessaloniki

P. Y. Bard L. G. 1.T., Grenoble

D. Jongmans L.G. 1. H., Liege

Valley nearThessaloniki,where the majorearthquake'sepicentre of June1978 was located

Establish in a seismicallyactive area a European testsite for engineeringseismology, earthquakeengineering and seismology

Produce — for a long period oftime — high-qualityinstrumental in situ data,which are extremely wellcontrolled, regarding theirseismological, geological,geotechnical, structuralbackgrounds, so that they canground valid tests and checksof methods already used inengineering seismology(prediction of ground motion,site effects) and earthquakeengineering (concerningbuilding behaviour, soil-structure interaction, lifelineproblems, etc.) and calibratenew methods to be developed.

1) seismological survey2) geotecnichal and geo phisical

survey3) free-field strog motion

instrumentation4) strong motion instrumentation

of model structure5) data retrieving and processing6) data analysis

Euro-Seistest will generate:• for a long period of time• a high-quality databasefrom weak and strong motionmeasurements. This databaseand the analysis that will bemade throughout this project willbe extremely useful forimproving methods of estimatingthe site effects and the seismicbehaviour of buildings. It alsoprovides valuable data toimprove the methods for thelocalization of seismic events aswell as the determination of theirfocal mechanism.

*Realistic modelling ofthe seismic input

Universita degliStudi di Trieste,Istituto di Geo-desia e Geofisica

InternationalCentre forTheoreticalPhysics

CNR — GruppoNazionale per laDifesa daiTerremoti

Institut furOeophysik, ETHHoenggerbergZurich

Italy, Ethiopia,and BulgariaMicrozoning oflarge, medium-sized and smalltowns: MexicoCity, Rome,Naples,Benevento, Buia

Computation of syntheticseismograms, and makes itpossible, as required by arealistic modelling, to takesource and propagationeffects into account, fullyutilizing the large amountof geological, geophysicaland geotechnical dataalready available

The optimization of techniquesaimed at prevention will beone of the basic themes of thedevelopment of seismic zoningin the 21st century.

1) seismic zoning in the 21stcentury

2) examplemof deterministiczoning using sintheticseismograms

3) European projects inframework of EPOCH

The computation of realisticsynthetic seismograms, usingmethods that make it possible totake source and propagationeffects into account, utilizing thehuge amount of geological, geo-physical and geotechnical dataalready available, gives a verypowerful and economically validscientific tool for seismic zona-tion and microzonation. Themethod provides a economicallyand scientifically valid procedurefor the immediate, first-orderseismic microzonation of anyurban area, where the geotech-nical data are available. Thepossibility to model the seismicinput also at long period suppliesa useful tool for the engineeringdesign and for the retrofitting ofspecial objects, with relativelylong free periods that is acquir-ing a continuously increasing im-portance, due to the widespreadexistence in the built environ-ment of special objects.

Legend:

* More relevant project relevant for spatial planning


B.II-37

4.3.3.2 Physical vulnerability assessment

This aspect is lacking in European studies. Different physical structures areexposed to various magnitude of earthquake. The elements contributing tomake the structures vulnerable are numerous and can change on the basisof the considered structure, of its function, of surrounding environment, andalso on others main characteristic of the building, like age, condition,materials, irregularities, reported damages and repairs. It is possible tocollect every kind of information in specific evaluation cards for eachstructure (bridges, supporting works, tunnels).

B.II- 3

8

Table V: Third level analysis- Physical vulnerability assessment



Monuments underseismic action acontribution to theunderstanding ofstructuralbehaviour and tothe improvement ofrestorationtechniques

AMTE Consulting Engineers,Athens, Greece

Parthenon inAthens as aclassical temples

St. Pierre'sCathedral atBeauvais as agothic cathedral

The Project aims at investigating methods for analysing thestructural response under seismic action of discontinuous"blocky" structures, such as old and ancient monuments.Two sites representative of Classical temples and Gothiccathedrals have been selected and investigated forcollecting geometrical and structural history data

1) collect and record informations about the two sites and abouthistorical response of the strctures

2) test materials and connect their properties for developmodels

3) obtain response by simulations that can be used to derive ageneral approach

4) try to investigate the actual methodology of response forstructural analysis of discontinuous "blocky" structures

Vulnerability ofburied pipe-linesunder seismicloading (VULPIP)

Institute of StructuralAnalysis and AseismicResearch (ISAAR), NTUA,Athens, Greece

Centre Experimental deRecherchcs et d'Etudes duBatiment and des TravauxPubliques (CEBTP), SaintRemy les Chevreuse, France

GreekFrance

Investigation of the wavepropagation effects onlong buried pipelines

The behaviour of long, straightjointed buried pipelinessubjected to excitations due toseismic wave propagation isinvestigated in order to assesstheir vulnerability and providerecommendations to improvetheir overall design. Theseismic environment isquantified by consideringimposed ground axial strainsand imposed ground rotations.Different sets of experimentsare performed to establish themechanical behaviour of jointsand the soil-pipelineinteraction parameters. Themost prevailing PVC and castiron pipelines with joints inFrance and Greece areinvestigated.

1) pipeline systems2) quantification of the

seismic environment3) mechanical properties of

bare pipelines4) determination of soil-

pipeline parameters5) structural analysis of the

pipeline system6) vulnerability of pipelines

Under the maximum anticipatedearthquake in the studiedregions, wave propagationeffects are not negligible. Morespecifically, an avoidablecontact between jointedsegments will always occurunder compression. Resultsunder tension indicate that asafer design for the PVCpipelines could be attained byaltering the ductility of theirrubber joints

Seismicvulnerabilityassessment ofmasonry gravitydams

Noret, Da Rin, Aubry • Spain• France• Germany

Materialscommonly usedin theconstruction ofmasonry dams

Develop a methodology and quantitative tools for theassessment of the seismic vulnerability of masonry gravitydams

1) history of Europeanmasonry dams

2) materials commonly usedin the construction ofmasonry dams

3) constitutive law for stonemasonry used in damconstruction

4) laboratory testing of large-scale specimens of internalfilling material

Bibliographical research led todetermination of the maincharacteristics of the masonrymaterial used in the core of thedams and to definition of anappropriate constitutive law forthe material. Preliminarylaboratory tests of the materialshowed different failuremechanisms.

B.II- 3

9



**Pseudodynamictesting of large-scale models ofcivil engineeringstructures at Elsa

European Commission JointResearch Centre, Ispraestablishment

Pseudodynamic testmethod at the ELSAreaction-wall facility.

1) Description of innovativehardware and softwareaspects related to theimplementation of the PSDtest method at the ELSAfacility. presented of thetesting activity at largescale conducted since theopening of the laboratoryin 1992.

2) Presentation of the testingactivity at large scaleconducted since the openingof the laboratory in 1992.

Tests realised using severaltypology of structures

Tests realised for updatingactual knowledge aboutantiseismic constructiontechniques

*Research anddevelopment needsfor post-earthquakeemergency damageand usabilityassessment ofbuildings

Department of CivilEngineering University ofPatras, Greece

1) Post-earthquakedamage evaluation andassessment of buildingsafety for emergencymeasures necessaryfor mitigating theconsequences ofdamaging earthquakesas well as savinghuman life frompossible aftershocks.

2) Assessment of abuilding's safety,involving estimates ofits resistance to lateralforces in relation to theobserved damage andthe expected futureseismic activity.

1) to save properties byidentifying emergencystrengthening needs andmeasures

2) to record damages forsubsequent repair andstrengthening and thusprovide the basis forallowing use of as manybuildings as possible, assoon as possible and at anacceptable level of risk

3) to collect the data necessaryfor obtaining estimates ofthe disaster that will allowauthorities to take reliefmeasures, formulatedisaster mitigation policiesand allocate availableresources

1) organizational aspects2) legal aspects3) research and development

needs

Policy for mitigation ofearthquake risks should bedirected along two lines ofaction:1) increasing the safety of

construction, future andexisting, and another aimedat predisaster planning

2) preparedness for coping withthe emergency created by acatastrophic event

**A Europeanresearchprogramme toimprove theassessment of steelbuildings behaviourduring earthquakes 'STEELQUAKE'

Department of structuralengineering, Politecnico ofMilano Milan, italyJRC - Ispra Italy ISMESBergamo, ItalyInstitut Du Genie Civil,Universite De Liege BelgiumNTUA - Lee Athens, Greece

The attention ofresearchers has beenfocused on the problem ofthe brittle collapse ofbeam to columnconnections in momentresisting steel frames

Experimental testingprogramme which has beenplanned with the purpose ofcontributing to a deeperknowledge of the followingproblems:1) the low cycle fatigue

behaviour of welded joints2) the implications of brittle

failure in weldedconnections on the globalframe response.

Analysis of the behaviour of civil engineering steel structures,of the moment resisting category, under earthquake loads. Theoverall objective is to provide a better insight into the actualbehaviour of civil engineering steel structures, of the momentresisting category, under earthquake loads, implementing insuch an analysis a quantitative reference to the failure ofconnections in terms of low cycle fatigue, considering theduration of the earthquake and the corresponding number ofcycles supported in dissipative (plastic) zones.

B.II- 4

0



General guidelinesand specificationsfor repair andstrengthening ofold masonrystructures againstseismic actions

P. Carydis Laboratory forEarthquake Engineering,National Technical, Athens,Greece

Two old masonrymonuments inGreece: theKnight's Palaceon Rhodos islandand the oldpalaces on Corfuisland.

Necessary actions andstudies that must becarried out for the repairand strengthening of oldmasonry structuresagainst seismic actionsare exposed

1) investigation fordetermining the origin ofthe materials

2) structural details and anyother character of thestructure up to theverification methods forproving the success and theeffect of the interventions tothe whole structure

1) assessment of existing situation2) logic of the selection of the various intervention3) interventions4) verification procedure monitoring

*Evaluating thevulnerability ofEurope's historictown centres

Robin Spence, Dina D'AyalaCambridge University,Department of Architecture,Cambridge, United Kingdom

This project bringstogether six institutions'with relevant experienceand skills in different partsof Europe to studyvulnerability of Europe'shistoric town centres inrelation to the differinglocal situations, upgradingstrategies for each of thefollowing criteria:1) life safety for occupants2) limitation of damage

from futureearthquakes

3) limitation of alterationsto the appearance andfabric of the buildings

4) responsiveness toeconomic needs

Develop better ways ofassessing the effectiveness ofalternative strengtheningmethods for the buildings inhistoric centres of Europeantowns and cities, and to pro-vide a reference document onthe subject to guide city andconservation authorities indevising appropriateearthquake protectionstrategies for these buildings

1) assemble data on the vulnerability of four historic towncentres

2) compare existing methods of earthquake vulnerabilityassessment for historic buildings and centres by applicationto case-study areas within these town centres

3) develop these methods to make them applicable tobuildings which have undergone typical renovation andstructural strengthening

4) identify general strategies for cost-effective retrofitstrengthening of key types of buildings: principallymultistorey residential blocks

5) communicate such strategies to the key non-technicaldecision-makers and planners involved

6) disseminate these findings locally and through a majorpublication

Seismic behaviourand vulnerability ofburied lifelines

Gesellschaft furSchwingungsuntersuchungenund dynamischePrüfmethoden mbHMannheimD'Appolonia, GenoaUniversite Libre de BruxellesAristotle University ofThessalonikiNational KapodistrianUniversity of Athens

Fictitious buriedpipeline

Methodologies for theassessment of seismichazard to buried pipelinesare developed

Design a new pipeline byutilizing the developed toolsand methodologies or at leastredesign or requalify anexisting pipeline, such a taskwould clearly break the limitsof a research

1) Investigation of seismic hazard2) local effects description3) analysis methodology and tools4) risk analysis

B.II- 4

1



Vulnerability ofburied pipelinesunder seismicloading

Institute of StructuralAnalysis and AseismicResearch (ISAAR), NTUA,Athens

Centre experimental derecherches et d'etudes dubatiment and des travauxpubliques (CEBTP), Saint-Remy-les-Chevreuse

The behaviour of longstraight jointed buriedpipelines subjected toexcitations due to seismicwave propagation isinvestigated. A structuralmodel is developed toanalyse the pipelinesystem.

1) Assessing the vulnerabilityof buried pipelines on thebasis of the criticalparameters, as well as atproviding recommendationsthat will improve the overalldesign of pipeline systems.

2) Investigation of the wavepropagation effects on longburied pipelines. Theseeffects occur during anearthquake and can act ona large area around theepicentre.

1) pipelines systems2) quantification of the seismic environment3) mechanical properties of bare pipelines4) determination of soil-pipeline parameters5) structural analysis of the pipeline system6) vulnerability of pipelines

*Evaluation ofvulnerability andretrofittingstrategies for ahospital building

Camillo Nuti, Giorgio Monti Hospital ofCastel di Sangro,Abruzzi region,Italy

Evaluation of the seismicvulnerability of a hospitalbuilding, based on thelogic of the infrastructurefunctional system, thecorresponding minimalcut-set description isobtained and theprobability of failure iscalculated for differentpeak groundaccelerations. The methodpermits a rationalevaluation of differentintervention strategies onboth structural and non-structural components aswell as on installationsand equipment.

Obtain useful indicationsconcerning the effectivevulnerability of Europeanhospitals as well as possiblestrategies for their seismicimprovement

1) description of case-studyhospital

2) local seismicity3) vulnerability of operating

theatre system

The method proved to be veryeffective in allowing the relativequantification of efficiency ofdifferent intervention strategies,on structural and non-structuralcomponents as well as onequipment. Absolute estimatescan be carried out as well, andit has been found that thehospital has a very largevulnerability also at moderateseismic intensities. Simple andcheap interventions cansensibly reduce vulnerability,even though to obtain relevantlevels of seismic protectionstructural retrofitting isunavoidable.

Legend:

* Project relevant for spatial planning** Laboratory experiments


B.II-42

4.3.4 Laboratorial experiments

Other European studies, less concerned with territorial planning, consist inlaboratorial experiments. In fact they are more relevant in technical-engineeristic area, so they became useful for planning just in a second step.They are physical structures models carried out to investigate the materialsresistance to different shock degrees (seismic simulations) in order toincrease the endurance and also to elaborate improvement and successfulrepairs.

These kind of experiments are helpful to plan emergency programs and toevaluate physical vulnerability and of people exposition level.

The importance of the dialogue between different subjects involved in riskassessment comes out in order to reduce and monitor hazard andvulnerability elements as well as to plan and manage emergency programsby mutual data exchanging, database updating, and many other solutions.

5 Risk management

5.1 PerceptionThe perception of an existent risk on a territory can be dealt with differentpoints of view: in particular in sociological or technical way.

The sociological perception of a risk regards the involved population andhow it is disposed to cohabit with the natural hazard. In this way differentsociological studies have been carried out by various authors. The followingbibliography reports some of them:

• Stallings R., Promoting Risk. Contructiong the earthquake threat, Aldinede Guyter, New York, 1995;

• Joh H., Disaster stress of the 1995 Kobe earthquake, in “Psychologia –An International Journal of Psychology in the Orient”, vol. XL, n.3,September 1997;

• Berke Ph. anf Beatley T., Planning for earthquakes. Risk, politics andpolicy. The Johns Hopkins University Press, Baltimore, 1992;

• Bogard W.C., Bringing social theory to hazard research. Conditions andconsequences of the mitigation of environmental hazards, in"Sociological Perspectives", vol.31, n.2, April 1988;

• Drabek T., Human System response to disaster. An inventory ofsociological findings, Springer-Verlag, New York, 1986;

• Mushkatel A., J. Nigg, Effect of objective risk on key actor support forseismic mitigation policy, in "Environmental Management", vol. 11, n.1,January 1987;

• Mushkatel A., J. Nigg, Opinion congruence and the formulation of seismicsafety policies, in "Policy Studies Review" vol. 6, n.4, May 1987.


B.II-43

5.2 Tolerance, acceptability, mitigation measures

Risk management foresees two main phases: emergency phase and normaltime. Mitigation measures can be implemented just in planning phase andnot in the emergency one.

Elements to act on to start implementing mitigation measures are:

- Vulnerability: making buildings and lifelines safer;- Exposure: avoiding exposure in the most critical areas;- Hazard: in this case is possible to act just on local hazard and

not on basic hazard, by measures as safety measures for slope,good planning measures for building areas, etc.

Acting on these parameters it can be possible to reduce the risk, but it isimpossible to reach the “zero risk level”, because it always remain aresidual threshold of risk, that can be more or less critical in the wake of themitigation measures to undertake on the basis of several economical andsociological factors. Those strategies can be differently accepted by theinvolved population according to their level of comprehension of thephenomena and on their availability to accept to cohabit with the residuerisk, depending on the efficacy of the undertook mitigation measures. Afactor whose presence is determinant to modify those aspects depends onthe way the risk is transmit to the involved population an how the availableinformation is managed by the scientific community and the publicadministration.

Mitigation measures to undertake are decided in the wake of suitableanalysis, the most appropriate of which is the Cost/Benefit Analysis, thatcan quantify both costs for mitigation measure and benefits that thisimprovement can produce. Comparing costs and benefits is possible todefine the acceptable level of risk: if costs exceed benefits, the acceptablelevel will be high; vice versa, if benefits are exceeding costs, the toleranceto cohabit with an hazard is very low and so planning mitigation measuresis appropriate.

This kind of analysis allows to look at the question following the double wayof the cost of the work and its benefits.

The knowledge of these parameters is useful:

• To valuate the order of preference of the mitigation measurecompared with other interventions for land management;

• To valuate if costs to support brings substantial benefits;• To apply Cost/Benefit Analysis to value seismic risk compared whit

other natural or technological hazards existent on a territory.

In this way is possible to know damages level and so making aredevelopment.

In practice, mitigation measures are building and engineering interventions,which are different depending on the site, the work and the level of risk thatinterests the structure, but they also depend on the availability of thesociety to accept the costs needed for decrease different levels of thevulnerability component. In fact, every vulnerability degree reduction has aspecific cost, and the ways to manage and undertake mitigation measures


B.II-44

can be differently accepted by the population, and so the reduction of thevulnerability can change depending on it.

5.3 Preparedness, response, recoveryPreparedness implicate the arrangement of emergency plan, clear and easyto consult, which gives indications about:

1. the first actions to undertake after the impact: what to do (or not),where to go and how;

2. how to manage the emergency phase and, for plan managers part,how to organize this;

3. early prepare risk-expose population to know how to behave in caseof emergency. A good and complete information is helpful to avoidwarped information and panic, which should make difficult themanagement of the situation.

In order to prepare the emergency plan, the following points must be takeninto consideration:

• more escape ways, well distributed on the territory;• areas to establish collection centres and recover centres for the

escaped population;• centre of operations to manage the emergency, in a due distance

from the devastated area;• available territorial resources (as hospitals, fire brigades stations,

etc.) and different ways to reach them.

The first aim to achieve is to get population safe, and in particular:

• to save as more people as possible;• to manage the emergency trying to avoid the spread of panic and

chaos;• to offer prompt shelter.

The arrangement of emergency plan depends on several factors, which aredifferent for every considered territory. Main territorial characteristics totake into consideration in planning the emergency are: physical geography,local town planning, sort of resource present, etc. So it is clear that isimpossible to draw up an emergency plan universally useful.


B.II-45

6 Glossary of all key-words

Earthquake: this phenomenon is the most evident expression of crustalbreaking happening in changeable depth from a few to some hundredkilometres.

Hazard: this concept can be analyzed in two different ways: considering itas a concept linked to the probability that in a specific site a certain severityevent may happen in a predefined time-window (“probability” is the termused, because an exact prevision can’t be given for the time being. Statisticanalysis of the past events occurred in a specific site must be done in orderto obtain a right value of the hazard), or considering an individual event.Different methods can be classified on the basis of different startinghypothesis, objectives and detail level.They are divided into Probabilistic approach and Deterministicapproach (damage scenario).

Vulnerability: this terms means how much an object can be damaged incase of occurrence of the very event. Vulnerability is an intrinsiccharacteristic of an object and so it can change on the basis of thephenomena we are considering. The concept of vulnerability is closely linkedto the exposure one, which analyses the event considering theconsequence for the subjects and the objects exposed.

Risk: Combining hazard and vulnerability, is possible to establish the risk.This term defines the entity of damages attended in a data area because offuture events. It is measured in the basis of the sort of damage to evaluate.Depending on starting hypothesis assumed for define hazard, there aremany different ways to assess risk that can be carried out on three differentinvestigation levels, from preliminary analysis to special investigation.

First level studies - basis seismic hazard: In this kind of analysis, thedifferent experiments are aimed to examining the exposure and classifyingthe territory on the basis of the detected seismic risk classification on thebasis of the seismic Italian code (the Italian code considers four zones).

Second level studies- damage scenario: these studies are going to value the Basic Seismic

Hazard, by using deterministic models to investigate attended shock in aselected area. They consider a singular event and his propagation insurrounding areas (scenario), this will allow to study site effects(damage scenario).

- physical vulnerability: it is analysed by using direct methods asvulnerability surveys or by means of approximate evaluations combiningdifferent available data.

Third level studies- local seismic hazard. local seismic hazard effects can change on the

basis of particular geological and morphological conditions whocharacterize a specific area (e.g. topological irregularity, deposits,


B.II-46

landslides). For areas who can produce local effects (and so potentiallydangerous) their response to different shock level must be investigated

Geological and geomorphological particular conditions in one area, when aseismic event is occurring, can produce different effects that must be takeninto consideration for the local general seismic hazard assessment.- physical vulnerability assessment: different physical structures are

exposed to various magnitude of earthquake. The elements contributingto make the structures vulnerable are numerous and can change on thebasis of the considered structure, of its function, of surroundingenvironment, and also on others main characteristic of the building, likeage, condition, materials, irregularities, reported damages and repairs. Itis possible to collect every kind of information in specific evaluationcards for each structure (bridges, supporting works, tunnels).

Laboratorial experiments: they are physical structures models carriedout to investigate the materials resistance to different shock degrees(seismic simulations) in order to increase the endurance and also toelaborate improvement and successful repairs.These kind of experiments are helpful to plan emergency programs and toevacuate physical vulnerability and of people exposition level.

Source zones: they are areas which can be considered geologically,structurally and kinematically homogenous. The seismic zone is definedthrough the probabilistic distribution of the epicentral intensities.

Earthquake shaking data: data available to study earthquakes. They aredivided into:- Shock effect on antropic environment, on buildings and on natural

environment (macroseismical effects);- Seismometric registrations of soil motions;- Accelerometric registrations of soil motion registration by using

accelerograms, instruments capable to supply registrations proportionalto earthquake accelerations.

Maximum recorder acceleration value: it is the most simple parameterused to measure the strength of an earthquake.


B.II-47

7 Bibliography

• Floriana Pergalani, Vincenzo Petrini, Scheda tecnica per la valutazionedello scenario di danno e del rischio sismico, Dicembre 2003;

• Floriana Pergalani, Vincenzo Petrini, Massimo Compagnoni, Dipartimentodi Ingegneria Strutturale, Politecnico di Milano, Valutazione della rispostasismica locale di piccoli centri a scala nazionale – Illustrazione dei metodidi valutazione degli effetti di sito -, Convenzione tra Servizio SismicoNazionale, Dipartimento della Protezione Civile e Dipartimento diIngegneria Strutturale del Politecnico di Milano, Novembre 2002;

• V. Petrini, S, Menoni, F. Pergalani, M.P. Boni, M. Mandelli, Vulnerabilitàsismica delle infrastrutture a rete, da Ingegneria Sismica n°2, 2000;

• Regione Lombardia, Settore Ambiente ed Energia, Servizio Geologico eConsiglio Nazionale delle Ricerche- Istituto di Ricerca sul Rischio Sismico,Determinazione dei rischio sismico a fini urbanistici m Lombardia,Milano, Giugno 1996;

• Maria Pia Boni, Scira Menoni, Floriana Pergalani, Vincenzo Peti-ini ,Scenario sismico di danno delle tnfrastruttijre a rete in una zonacampione della Regione Lombardia, da Ingegneria Sismica 2/2002);

• European Commission, Environmental and climate programme,

• Seismic and volcanic risk. Proceedings of the workshop ‘Monitoring andresearch for mitigating seismic and volcanic risk’ held at ReykjavìkIceland, from 20 to 22 October 1994, Edited by B. Thorkelsson, M.Yeroyianni, Directorate-General Science, Research and Development;

• European Commission, Environmental and climate programme Climateand natural hazards;

• Collaborative European research activities for seismic risk prevention andreduction. Proceedings of the workshop held at Bergamo, Italy from 9 to11 November 1994, Edited by M. Yeroyianni, A. Peano, P. Panzeri,Directorate-General Science, Research and Development;


• Seismic risk in the European Union (Volume I). Proceedings of therewiew meetings held in Brussels on 2-3 and 23-24 May 1996, Edited byA. Ghazi, M. Yeroyianni, Directorate-General Science, Research andDevelopment;


• Seismic risk in the European Union (Volume II). Proceedings of therewiew meetings held in Brussels on 27 and 28 November 1997, Editedby M. Yeroyianni, Directorate-General Science, Research andDevelopment;

• Historical Investigation of European Earthquakes, Materials of the CECproject. Rewiew of Historical Seismicity in Europe 1, Edited byMassimiliano Stucchi, CNR – Istituto di Ricerca sul Rischio Sismico;


B.II-48

• Historical Investigation of European Earthquakes, Materials of the CECproject. Rewiew of Historical Seismicity in Europe 2, Edited by PaolaAlbini and Andrea Moroni, CNR – Istituto di Ricerca sul Rischio Sismico;

• Starr, C., Social benefit versus technological risk, Science, 165,September 1969;

• Petrini, V. and Scirocco, F., Procedimento per la costruzione di una cartasismica italiana su basi statistiche, Istituto Lombardo (Rend. Sc.), A 110,1976;

• Grandori, E. and Grandori, G., An application of decision theory toseismic zoning, Sixth world Conference on Earthquake Engineering, NewDelhi, January 1977;

• Boore, D. M., The effect of simple topography on seismic waves:implications for the accelerations recorded at Pacoima Dam, SanFernando Valley, California. Bulletin of the Seismological Society ofAmerica, Vol. 63, No. 5, pp. 1603-1609, 1973;

• Faccioli, E. e al., Elementi per una guida alle indagini di MicrozonazioneSismica. Quaderni de "La Ricerca Scientifica" N. 114. CNR, Roma, 1986;

• Gèli, L, Bard, P.Y., Jullien, B., The effect o topography on earthquakeground motion: a review and new results. Bulletin of the SeismologicalSociety of America, Vol. 78, No.1, 1988;

• Lucantoni, A., Bosi, V., Bramerini, F., De Marco, R., Lo Presti, T., Naso,G., Sabetta, F., Il Rischio sismico in Italia. Ingegneria sismica, XVIII, N.1, pp. 5-36+CD allegato, 2001;

• Regione Lombardia, CNR-IRRS, Determinazione del rischio sismico ai finiurbanistici in Lombardia, 1996.

• Ambraseys N., Srbulov M.. Earthquake induced displacement of slopes.Soil Dynamics and Earthquake Engineering, 14, pp 59-71, 1995;

• Bieniawski Z.T., Rock Mass classifications in rock engineeringapplications. Fourth International Congress on Rock Mechanics,Montreaux, 1979;

• Bishop A.W., The use of the slip circle in the stability analysis of slopes.Geotechnique, 5, pp 7-17, 1955;

• Callerio, A., Petrini, V., Pergalani, F., ELCO, A program for two-dimensional analyses using boundary element method. RapportoTecnico, IRRS, Milano, 2000;

• Casadei, F., Gabellini, E., Implementation of a 3D coupled spectral-element/finite-element solver for wave propagation and soil-structureinteraction simulation. Technical report, Joint Research Centre, Ispra,Italy, 1997;

• Cividini A., Pergalani F., Petrini V., La risposta dei versanti ad azionisismiche attraverso un modello semplificato, Ingegneria Sismica, annoVIII, 3, pp 28-44, 1991;

• Cividini A., Pergalani F., On some aspects of the numerical evaluation ofpermanent displacements, Proceeding of French-Italian conference on


B.II-49

"Slope stability in seismic areas", Bordighera (Imperia), Italia, pp 167-180, 1992;

• Farmer I.W., Engineering behaviour of rocks. Chapman and Hall ltd.,1983;

• Grandori G., Perotti F., Tagliani A., On the Attenuation of MacroseismicIntensity with Epicentral Distance, Ground Motion and EngineeringSeismology, A.S. Cakmak Ed., Elsevier, 1987;

• Graham J., Methods of stability analysis. Slope Instability, ed. D.Brunsen & D.B. Prior. Wiley and Sons, New York, pp 523-602, 1984;

• Gruppo di Lavoro CPTI 1999 - ING, GNDT, SGA, SSN, CatalogoParametrico dei Terremoti Italiani, Bologna, pp 92, 1999;

• Gruppo di Lavoro 2004, Redazione della mappa di pericolosità sismicaprevista dall’Ordinanza PCM 3274 del 20 marzo 2003. Rapportoconclusivo per il Dipartimento di Protezione Civile, INGV, Milano-Roma,pp 65 + 5 appendici, aprile 2004;

• Guagenti E., Petrini V., Il caso delle vecchie costruzioni: verso una nuovalegge danni-intensità, Proceedings of the 4P

thP Italian National Conference

on Earthquake Engineering, Milano, Volume I, pp 145-153, 1989;

• Jibson R.W., Harp E.L., Michael J.A., A method for producing digitalprobabilistic seismic landslide hazard maps: an example from the LosAngeles, California, area. US Geological Survey O-F Report, pp 98-113,1998;

• King J.L., Tucker B.E., Observed variations of earthquake motion acrossa sediment filled valley. Bull. Seism. Soc. Am., 74, pp. 137-151, 1984;

• Luzi L., Pergalani F., Application of statistical and GIS techniques toslope instability zonation (1:50.000 Fabriano geological map sheet), SoilDynamic and Earthquake Engineering, Elsevier Science, vol. 15, pp 83-94, 1996;

• Luzi L., Pergalani F., Slope instability in static and dynamic conditions forurban planning: the “Oltre Po Pavese” case history (Regione Lombardia-Italy), Natural Hazard, 20, pp 57-82, 1999;

• Luzi L., Pergalani F., A correlation between slope failures andaccelerometric parameters: the 26 september 1997 earthquake (Umbria-Marche, Italy), Soil Dynamic and Earthquake Engineering, ElsevierScience, vol. 20, pp 301-313, 2000;

• Malagnini L., Tricarico P., Rovelli A., Hermann R.B., Opice S., Biella G.,de Franco R., Explosion, earthquake, and ambient noise recording in aPliocene sediment-filled valley: interferences on seismic responseproperties by reference and non-reference-site techniques. Bull. Seism.Soc. Am., 86, pp. 670-682, 1996;

• Malagnini L., Herrmann R,B., Di Bona M., Ground motion scaling in theApennines (Italy). Bull. Seism. Soc. Am., 90, 4, pp 1062-1081, 2000;

• Malagnini L., Akinci A., Herrmann R,B., Pino N.A., Scognamiglio L.,Characteristics of the ground motion in northeastern Italy. Bull. Seism.Soc. Am., 92, 6, pp 2186-2204, 2002;


B.II-50

• Margottini C., Molin D., Serva L., Intensity versus ground motion: a newapproach using Italian data, Engineering Geology, 33, pp 45-58, 1992;

• Newmark N. M., Effects of earthquake on dams and embankments.Géotechnique, 23, 1965;

• Pergalani, F., Romeo, R., Luzi, L., Petrini, V., Pugliese, A., Sanò, T.,Seismic microzoning of the area struck by Umbria-Marche (central Italy)Ms 5.9 earthquake of the 26 september 1997. Soil Dynamic andEarthquake Engineering, Elsevier Science, 18, pp. 279-296, 1999;

• Pergalani, F., Compagnoni, M., Petrini, V., Valutazione degli effetti di sitodi alcuni centri dell’Alta Valtiberina Umbra tramite modellazionenumerica, Ingegneria Sismica, 1, pp. 44-56, 2002;

• Pergalani, F., de Franco, R., Compagnoni, M., Caielli, G., Valutazionedegli effetti di sito tramite analisi numeriche e sperimentali nell’abitato diCittà di Castello: analisi, confronti e utilizzo dei risultati, Ingegneriasismica, 1, pp. 66-77, 2002;

• Pergalani F., Compagnoni M., Petrini V., Evaluation of site effects insome localities of “Alta Val Tiberina Umbra” (Italy) by numericalanalysis, Soil Dynamic and Earthquake Engineering, Elsevier Science, 23,2, pp 85-105, 2003;

• Regione Lombardia, Consiglio Nazionale delle Ricerche, Analisi di stabilitàin condizioni statiche e pseudostatiche di alcune tipologie di frane dicrollo finalizzata alla stesura di modelli di indagine e di intervento,Milano, 2001;

• Romeo R., Seismically-induced landslide displacements: a predictivemodel. Proc. XXIII General Assembly of European Geophysical Society,Nice, 1998;

• Sabetta F., Pugliese A. Attenuation of peak ground acceleration andvelocity from italian strong motion record, Bulletin of Seismic Society ofAmerica, 77, pp. 1491-1513, 1987;

• Sabetta F., Pugliese A., Estimation of response spectra and simulation ofnonstationary earthquake ground motions, Bulletin of the SeismologicalSociety of America, 86, pp. 337-352, 1996;

• Scheda IFFI, Scheda di censimento dei fenomeni franosi, Presidenza delConsiglio dei Ministri, Dipartimento per i Servizi Tecnici Nazionali,Servizio Geologico, 2001;

• Spencer E., A method of analysis of the stability of embankmentsassuming parallel interslice forces. Geotechnique, 17, pp 11-26, 1967;

• Stucchi M., Camassi R., NT4.1.1 Un catalogo parametrico di terremoti diarea italiana,GNDT, 1998.


B.II-51

Appendix:Operation Standards for Risk Assessment aimedat Spatial Planning

A1 Simplified model for Seismic Hazard mappingaimed at legal directive

A1.1 Hazard methodology

To study hazard in order to obtain a simplified model we have to recourse toa deterministic model.

Minimum data required for increase this model are:

1) Historical recorded events catalogue. For every recorded event it ispossible to find out information including the indicators of epicentralseverity: epicentral intensity and magnitude.

2) Source zones. Those are areas that can be considered geologically,structurally and kinematically homogenous. A seismic zone is definedthrough the probabilistic distribution of the epicentral intensities.

3) Attenuation model. The evaluation of hazard is necessary to know,beside the localization and the epicentral severity, how the phenomenonpropagates from the epicentre and, as a result, the variation ofcorrelated severity parameters:

• Intensity attenuation. Using the epicentral severity asindicator, the result of the attenuation laws is still an intensityvalue.

• Magnitude attenuation. These models use as severity indicatorthe magnitude value.

The above data are applied to investigate how phenomena propagates farfrom the epicentre and, consequently, they can be used to investigate thevariation of severity parameters of intensity attenuation or of magnitudeattenuation.

A1.2 Map scales

The choice of the scale to study spatial planning is conditioned bymultifaceted factors. Out of all these the most influential are:

- the depth level chosen to lead the analysis;- the object of the study (infrastructure network, building, landslide,

etc.);- the sort of approach to use (preliminary study, cognitive survey,

detailed survey, etc.).

In particular, there are three different detail levels to investigate:


B.II-52

1. The Local scale: it allows to analyse in depth the local hazard presentin one or more municipalities (1:500 – 1: 5000).

In the map, the local hazard is represented by P.G.A. values, thatdecrease getting away from the epicentre.

Fig. A1.1 – Example of Local Hazard Map: an earthquake near GardaLake (Lombardia Region), the epicentre is in the municipality of Salò.

2. The Regional scale: at this scale it is possible to investigate thehazard for areas including a big number of municipalities that can berepresented at 1:5.000 – 1:50.000 scale.

ROE`VOLCIANO

VILLANUOVA SUL CLISI

GAVARDO

GARDONE RIVIERA

TOSCOLANO MADERNO

GARGNANO

VOBARNO

SALO`r

Lago

di G

arda

2.75

0.850.951.051.151.251.35

1.451.551.65

1.751.85

1.95

2.052.15

2.252.352.45

2.552.65

+ -

Legend: P.G.A. values


B.II-53

Fig. A1.2 – Example of Regional Hazard Map: Expected MaximumAcceleration values (Amax (g)) for different Return Periods in the Lombardia

Region

3. The National scale: with this scale of representation it is possible tohave a full picture of the national hazard (1:500.000 or more).

Fig. A1.3. – Seismic Hazard Map of the national territory (Italy) with areturn period of 475 years (National Institute of Geophysic and

Vulcanology)

Return Period = 72years




B.II-54

A1.3 Characteristics and use of hazard maps

Having three different levels of detail to produce hazard maps, meanshaving different ways to use them.

In particular, the national scale is useful to classify the national territory inseismic areas or not; while the regional one, apart from this function (butmore in detail that in the national scale), is of use for draft a more or lesshazardous areas list.

The local scale is the most detailed one and it is used to zoning the regionin study or to give indications about the buildings protection levels to adopt.

A1.4 Data acquisition and mapping procedures

Data available for the study of earthquakes can be collected under threecategories, correlated with three different approaches:

a. Damage effect. This method describes the damage effects on the builtenvironment, on buildings and on the natural environment (macroseismicaleffects).

b. Seismometric registrations. This method is provided by soil motionregistrations, which are obtained thanks to the use of seismograms(instruments able to reproduce ground motions in horizontal or verticaldirection quite faithfully)

Different kinds of waves that contribute to soil motion can be distinguishedas follows:

• volume waves, divided in P-wave (from the Latin term "primae"),that are compression waves which propagate from the source in alldirection with a sequence of compressions and dilatations; and S-wave (from the Latin term "secundae") shearing waves which causeorthogonal displacements;

• surface waves, so called because they propagate only on terrestrialsurface; they are a consequence of the interaction of P and S-waveswith terrestrial surface. The difference in arrival times of the waves isthe basic element for the location of the earthquake source.


B.II-55

c. Accelerometric registrations. The third and last method to evaluateearthquakes is through soil motion registration obtained hanks oaccelerograms, instruments capable of supplying registrations in proportionto earthquake accelerations. The simplest parameter that can be used forthis measure is the amount of the maximum recorded acceleration.

The data so obtained are implemented and acquired using G.I.S.(Geographic Information Systems).

GNDT

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

0 5 10 15 20 25 30

Time (s)

Pg

a (g

)


B.II-56

A2 Simplified model for risk mapping aimed at spatialplanning

A2.1 Risk methodology, data acquisition and use

To define a simplified model for risk mapping is necessary to work on thehazard and vulnerability components. As far as the minimum standard forthe hazard component, is concerned to use a deterministic input model (asexplained above). So, only vulnerability component remains to be analysed.Vulnerable elements are distinct between the ones inferable from ISTATcatalogues and the ones that involved population and buildings or otherstructures.

Summarizing, a simplified model for risk mapping needs of twocomponents:

1. a deterministic input to define the hazard.

To do that Basic Seismic Hazard is used to investigate the attended shock ina selected area.

Several experiments are based, from time to time, on different parameterssuch as seismotectonic characteristics of the area, the source energyrelease ways, the seismic waives propagation course. Starting whit theseinputs, the procedure manages to define:

- the historical seisicity, by searching in archives and historicalrecording;

- the recent seismicity, that is the one recorded by seismographes.

In the light of these data, several objectives can be pursued, like identifyingsource areas and the events characterized by different recurrence periods.In this way it is possible to calculate (using a specific attenuation model)the expected shaking at the site.

2 . the vulnerability from ISTAT data to assess the vulnerabilitycomponent.

Physical vulnerability is analysed by using direct methods as vulnerabilitysurveys or by means of approximate evaluations combining differentavailable data.

In this way is possible to subdivide the patrimony to value on the basis ofmore factors (such as the structural typology, the age of building, the stateof maintenance) and reach at define a vulnerability index for differentstructures considered.


B.II-57

Fig. A2.1 – Vulnerability map for buildings at local level for the municipalityof Salò (Lombardia Region)

Fig. A2.2 – Vulnerability map for infrastructure network at local level for themunicipality of Salò (Lombardia Region)


B.II-58

A2.2 Map scales

1. The Local scale: these kind of analysis are appropriately feasible on anintermediate detail scale, such as the local one (1:500 – 1: 5000).

Fig. A2.3 – Example of Local Risk Map: Values of risk in the municipality ofToscolano Maderno (Lombardia Region)

Legend:

Damage level ratio:cost of damage / value of the new building

2. The Regional scale: for the regional scale too (1:5.000–1:50.000), it ispossible to carry out studies and maps about seismic risk.

D > 0,01

0,001 < D < 0,01

D < 0,001


B.II-59

Fig. A2.4 - Example of Regional Risk Map: Values of risk in the ToscanaRegion (Italy)

(C.N.R. – G.N.D.T, 1998)

Legend:

Damage level ratio:cost of damage / value of the new building

3. The National scale: at present, for the Italian case, the production ofseismic risk map concerns only the local and the regional levels; so there isnot a risk map for the whole national territory.

< 0,01%

0,01 – 0,09%

0,09 – 0,20%

O,20 – 0,40%

> 0,40%


B.II-60

A3 Minimum standard for multi-risk assessment andmapping

In order to achieve a simplified model for multi-risk assessment to use it asan element of Strategic Environmental Assessment, it is necessary to have,for every natural events considered, an univocal definition of risk in termsof attended damages. This way, having the same terms of comparison forevery kind of hazard, it is possible to compare different nature risks, andthen to define a “multi-risk” approach.

For this case too, the choice of the scale is linked to the sort of study tocarry out. For a simplified model, where isn’t possible to achieve a highlevel of detail, also the scale of analysis and representation couldn’t enterinto detailed levels.


B.III-1

B.III Landslides

Authors: Giuseppe Delmonaco, Daniele Spizzichino, T6

1 Definition of Landslide..................................................... 4

2 Landslides classification .................................................. 4

2.1 Material type ............................................................................5

2.2 Landslide activity ......................................................................6

2.2.1 State of activity.........................................................................6

2.2.2 Distribution of activity ................................................................8

2.2.3 Style of activity .........................................................................8

2.3 Landslide causes .......................................................................9

3 Intensity or Magnitude (I)............................................. 10

3.1 Velocity.................................................................................. 10

3.2 Dimension.............................................................................. 12

3.3 Energy................................................................................... 13

3.4 Consequences......................................................................... 13

3.5 Hybrid ................................................................................... 14

4 Return period of landslides............................................ 15

4.1 Geomorphological criteria or qualitative analysis......................... 15

4.2 Analysis of temporal series related to effects.............................. 15

4.3 Analysis of temporal series related to causes ............................. 16

4.3.1 Precipitation............................................................................16

4.3.2 Earthquakes............................................................................17

4.4 Monitoring.............................................................................. 18

4.4.1 Mechanical approach ................................................................18

4.4.2 Kinematics approach ................................................................18

5 Hazard assessment (H) ................................................. 19

5.1 Basic concepts ........................................................................ 19

5.2 Prediction of landslide types ..................................................... 20

5.3 Prediction of landslide intensity................................................. 20

5.4 Prediction on landslide affected area ......................................... 21

5.4.1 Methods of relative hazard analysis ............................................21

5.4.1.1 Qualitative methodologies...................................................21

5.4.1.1.1 Field geomorphologic analysis .........................................21

5.4.1.1.2 Combination of index maps or heuristic approach...............22

5.4.1.2 Quantitative methodologies.................................................23

5.4.1.2.1 Statistical analysis .........................................................23

5.4.1.2.2 Geotechnical models ......................................................25

5.5 Temporal prediction ................................................................ 27

5.5.1 Analysis of return time .............................................................27

5.5.2 Analysis of intensity/magnitude .................................................29

5.6 Prediction of evolution ............................................................. 29


B.III-2

5.6.1 Prediction of run-out ................................................................30

5.6.2 Prediction of retrogression limits ................................................30

5.6.3 Prediction of lateral expansion ...................................................30

6 Landslide hazard mapping............................................. 30

6.1 Introduction ........................................................................... 30

6.2 Susceptibility and hazard mapping............................................ 31

6.3 Hazard zoning scales ............................................................... 33

6.4 Landslide Hazard map types..................................................... 33

6.5 Approaches to landslide mapping.............................................. 34

6.5.1 The Inferential Approach...........................................................34

6.5.2 The Statistical Approach ...........................................................34

6.5.3 The Process-Based Approach.....................................................35

6.6 The mapping unit for GIS Technique ......................................... 35

7 Element at Risk (E) or exposure .................................... 36

7.1 Definition ............................................................................... 36

7.2 Cartography related to the element at risk - Map of Exposure -.... 37

7.3 Economic value of element at risk............................................. 37

7.3.1 Human life Value .....................................................................38

7.3.2 Goods and activities value.........................................................38

7.3.3 Global Value ...........................................................................39

8 Vulnerability (V) ............................................................ 39

8.1 Vulnerability: some web definitions ........................................... 40

8.2 Conceptual approach: vulnerability assessment.......................... 40

8.2.1 Definition ...............................................................................40

8.2.2 Vulnerability components..........................................................41

8.3 Human life vulnerability ........................................................... 42

8.4 Vulnerability of good and activities............................................ 42

9 Analysis of Risk (R) ....................................................... 45

9.1 Definition ............................................................................... 45

9.2 Qualitative analysis ................................................................. 45

9.2.1 Damage propensity..................................................................45

9.3 Quantitative analysis ............................................................... 46

9.3.1 Total risk................................................................................46

9.3.2 Potential damage (WL)..............................................................47

9.3.2.1 Rigorous assessment .........................................................48

9.3.2.2 Simplified assessment. .......................................................49

9.3.3 Specific Risk (Rs) .....................................................................50

9.4 Probability of acceptable rupture............................................... 50

10 Risk management.......................................................... 52

10.1 Introduction ........................................................................... 52

10.2 Framework for landslide risk management ................................ 53

10.2.1 General framework ..................................................................53

10.2.2 Increasing of social acceptable threshold risk...............................54


B.III-3

10.3 Acceptable and tolerable risk from landsliding............................ 55

10.3.1 General issues.........................................................................55

10.4 Treatment.............................................................................. 57

10.4.1 Risk mitigation through structural action and measures.................58

10.4.2 Risk mitigation with non-structural action and measures ...............58

10.5 Public Awareness, Education and Capacity Building .................... 59

10.6 Emergency Preparedness Plan.................................................. 59

10.6.1 Before the Landslide ................................................................59

10.6.2 When it Rains..........................................................................60

10.6.3 Key Considerations ..................................................................61

10.6.4 What Can You Do If You Live Near Steep Hills ..............................61

10.6.4.1 Prior to Intense Storms: .....................................................61

10.6.4.2 During Intense Storms:......................................................61

10.6.5 After the Disaster ....................................................................62

10.7 The Phases of emergency Plan (planning, response, recovery) .... 62

10.7.1 Emergency Phases...................................................................62

10.7.2 Planning Phase........................................................................62

10.7.3 Response Phase ......................................................................63

10.7.3.1 Initial Response.................................................................63

10.7.3.2 Extended Response............................................................64

10.8 Recovery Phase ...................................................................... 64

11 Glossary of all keywords................................................ 64

12 Bibliography .................................................................. 70

13 Appendix: Operational Standards for Risk Assessment

aimed at Spatial Planning................................................... 92

13.1 Minimum standard (simplified model) for hazard mapping

aimed at a legal directive................................................................. 92

13.1.1 Various methodologies related to the 3 assumed scales of analysis

in the light of a potential harmonisation of hazard maps, based on a multi-

hazard perspective...............................................................................92

13.2 Minimum standard (simplified model) for risk mapping aimed at

spatial planning .............................................................................. 98

13.2.1 Multi-risk assessment perspective as element of the Strategic

Environmental Assessment....................................................................98

13.2.2 Methodologies, functions and outputs .........................................99

13.2.2.1 ........................................................................................ 101

13.3 Minimum Standard for Landslide Risk Maps ............................. 106

13.3.1 Local Scale mapping ( 1: 10.000) .......................................... 106


B.III-4

1 Definition of LandslideThe term "landslide" describes a wide variety of processes that result in the

downward and outward movement of slope-forming materials including

rock, soil, artificial fill, or a combination of these (UNESCO, 1984).

A landslide event is defined as "the movement of a mass of rock, debris or

earth down a slope" (Cruden 1991). The word 'landslide' also refers to the

geomorphic feature that results from the event. Other terms used to refer

to landslide events include 'mass movements', 'slope failures', 'slope

instability' and 'terrain instability'.

Limits and uncertainties

There is a conceptual confusion in the term landslide since it is referred

both to landslide deposit (displaced mass) and the movement of material

along a slope.

2 Landslides classificationIn spite of the simple definition, landslide events are complex

geological/geomorphological processes and are therefore difficult to classify.

An adequate classification system should be based on parameters and/or

features that can be measured and observed in the field. At the same time,

a classification system should satisfy requisites of uniqueness, rationality,

homogeneity and readiness of application, though the detection of classes

mutually exclusive.

The classification system, most commonly used worldwide, and proposed

for this report, is modified from Varnes (1978). The classification is based

upon material type and type of movement, and is similar to the updated

classification of slope movements suggested by Cruden and Varnes(1996).

This is based on the movement, with a special attention to the spatial

distribution of displacements and their velocity as well as to the shape of

the failure and landslide body.

The Cruden & Varnes classification can be resumed in the following landslide

types:

1. Falls: take place rapidly by free-fall, bouncing, or rolling, and may

develop into either slides or flows.

2. Topples: consist of the rapid rotation of a unit of rock or soil about

some pivot point. Toppling may not lead to either falls, slides or flows.

3. Slides: involve the movement along one or more distinct surfaces.

Slides are subdivided into 'rotational slides' and 'translational slides',

depending upon the shape of the failure plane.

a . Rotational slides: also referred to as slumps, involve movement

along a curved failure plane. Often the failure plane did not exist


B.III-5

before movement occurred. Rotational slides usually involve relatively

few distinct rock or soil units.

b. Translational slides: involve the movement of many rock or soil

units along a plane. If few distinct units are involved, the movement

is referred to as a 'translational block slide'. Often the failure plane

existed before movement occurred.

4. Lateral spreads: are dominated by lateral extension of the ground,

accompanied by shear or tensile forces, and a general subsidence of the

ground surface. They generally occur relatively slowly.

5. Flows describe movement that resembles a viscous fluid. Some flows

occur slowly, others occur rapidly. Velocity within the flowing mass is

usually decreases with depth and laterally. In most cases, water is an

integral component. Creep is a type of flow that occurs very slowly.

6. Complex landslides involve the combination of two or more types of

movement. Commonly one type of movement starts the material

moving, such as a debris slide, and once underway the material takes on

the character of another type of movement, such as a debris flow. The

name of the complex movement is a combination of the types of

movement, in order of occurrence, such as a debris slide-debris flow.

The rate of movement depends on the types of movements and material

types involved.

According to WP/WPLI (1990-1994), complex landslides should be classified

following the types of movement involved related to the genetical and

temporal sequence of the single types that compose the phenomenon.

2.1 Material type

The material involved in a landslide should be classified according to its

state before the initiation of the movement or, if the movement changes in

the time, according to the state that characterizes the material before the

movement where such a change occurs

The material involved in a landslide is classified into two groups, 'bedrock'

and 'soil'. Soil, which is generally unconsolidated superficial material, is

further subdivided into 'debris' and 'earth' depending upon its texture.

Rock refers to earth materials that have lithified by some rock-forming

process. Its strength depends not only on the rock type but also on the

degree of weathering and the density and orientation of the discontinuities,

which are generally the planes of weakness in the rock mass.

Debris is composed of predominantly coarse grained soil, or as mentioned

above, can also include highly fractured bedrock. The strength of coarse

grained soil is generally derived from friction between the grains.

Earth refers to predominantly fine grained soil (primarily of silt and clay

sized materials). The strength of fine grained soil is generally derived from

cohesion, the chemical and electrical bonding between the small particles.


B.III-6

2.2 Landslide activity

The activity defines the temporal evolution of a landslide, through the

analysis of movement, displaced materials and areas involved. The activity

can be regrouped under three headings:

1. State of activity, that is related to the timing of a landslide

2. Distribution of activity, that describes the area where a landslide is

moving

3. Stile of activity, that indicates the contribution of single movements to

the landslide

2.2.1 State of activity

The state of activity is defined as follows Cruden & Varnes, 1996):

active: landslide currently moving;

suspended: landslide moved within the last annual cycle of seasons, but

not presently moving;

reactivated: landslide that is again active after being inactive;

inactive: landslide that moved more than one annual cycle of seasons

ago.

Inactive landslides can be subsequently divided in:

dormant: if the causes of movement remain apparent;

naturally stabilised: inactive landslide protected by its original causes

without human interventions;

artificially stabilised: inactive landslide protected by its original causes

with artificial remedial measures;

relict: inactive landslides developed under geomorphologic and climatic

setting, considerably different from present conditions.

The geomorphological information of the state of activity are generally

related to the type and state of preservation of some diagnostic elements,

as reported in Table 2.1.

Active Inactive

Scarps, terraces and crevasses with sharp bordersScarps, terraces and crevasses with roundedborders

Crevasses and depressions without secondaryfilling

Crevasses and depressions with secondary filling

Secondary mass movements on scarpsAbsence of secondary mass movements onscarps

Fresh striae over the failure surface and marginalshear planes

Absent or weathered striae over the failuresurface and marginal shear planes

Fresh crack surfaces on blocks Weathered crack surfaces on blocks

Irregular drainage system, diffuse ponding anddepressions with internal drainage

Well preserved drainage system

Pressure crests at the contact with sliding margins Abandoned marginal cracks and banks

Absence of soil on the exposed portion of the failuresurface

Growth of soil on the exposed portion of thefailure surface

Presence of rapid-growing vegetation Presence of slow-growing vegetation

Different vegetation between internal and externallandslide areas

No difference of vegetation between internal andexternal landslide areas

Tilting trees without vertical growthTilting trees with vertical growth in the portions

succeeding the tilted part

Table 2.1. Geomorphic criteria for field survey of landslide state of

activity (Crozier, 1984, modified)


B.III-7

The state of activity of a landslide and its geomorphologic characteristics

are strictly depending on climate conditions, as reported in Figure 1.

Fig. 1. Block diagrams of morphologic changes with time of idealized

landslide (a) in humid climate: A, active or recently active (dormant

– historic) landslide features are sharply defined and distinct; B,

dormant – young landslide features remains clear but are not

sharply defined owing to slope wash and shallow mass movements

on steep scarps; C, dormant – mature landslide feature are

modified by surface drainage, internal erosion and deposition, and

vegetation; D, dormant – old landslide features are weak and often

subtle. (Turner & Schuster, 1996).


B.III-8

2.2.2 Distribution of activity

The distribution of activity describes where the landslide is moving and

permits to predict the type of landslide evolution in the space. Following the

distribution of activity a landslide is:

advancing: if the surface of rupture is extending in the direction of

movement;

retrogressive: if the surface of rupture is extending in the direction

opposite the movement of the displaced material;

progressive or multi-directional: if the surface of rupture is enlarging

in two or mode directions;

diminishing: if the volume of displaced material is decreasing with

time;

confined: landslide with a scarp but no visible surface of rupture in

the foot of the displaced mass;

constant: if the displaced mass continues to move without

considerable change of the rupture surface and volume of the

displaced mass;

enlarging: if the rupture surface is developed on one or both lateral

margins of the landslide.

2.2.3 Style of activity

The style of activity is the way in which different movements contribute to

the landslide. Following the style of activity a landslide can be defined as:

complex: characterised by the combination, with time, of at least two

types of movement (fall, topple, slide, expansion, flow);

composite: characterised by the combination, with time, of at least

two types of movement (fall, topple, slide, expansion, flow)

simultaneously in different areas of the displaced mass;

successive: characterised by a movement of the same type to an

earlier and adjacent landslide, where displaced masses and rupture

surfaces are clearly distinct;

single: characterised by a single movement of the displaced mass;

multiple: characterised by repeated movements of the same type,

often following enlargement of the failure surface.

In order to characterise the type of evolution of a landslide it can be very

useful to refer to the frequency of reactivations instead of the state of

activity detected during field survey. On this subject the distinction

proposed by Del Prete et al. (1992) among continuous, seasonal and

intermittent (pluriannual or pluridecennial return time) landslides or what

proposed by Bisci & Dramis (1991) and Flageollet (1994) reported in Table

2.2.

State of activity Recurrence Return time Last activation

ACTIVE Continuous - Presently moving

Seasonal > 1 year Recent

Short-term recurrence 1 - 10 years Recent history

QUIESCENT Medium-term recurrence 10 - 100 years Recent history

Long-term recurrence 100 - 1000 years Recent or ancient history

STABILISED Very long-term recurrence > 1000 years Ancient history and prehistory

Tab. 2.2 – Landslide activity (BISCI & DRAMIS, 1991 and

FLAGEOLLET, 1994, modified).


B.III-9

2.3 Landslide causes

Landslide causes analysis consists in examining the various factors that

contribute to slope instability, in their parameterisation and subdivision in

classes and, finally, in their representation as thematic maps.

A list of major predisposing factors, derived by literature (Terzaghi, 1950;

Carrara & Merenda, 1974; Cotecchia, 1978; Varnes, 1978; Hansen, 1984;

Esu, 1984; Crozier, 1986; Canuti et al., 1992; Amanti et al., 1992; Cruden

& Varnes, 1994; Hutchinson, 1995) is reported in the following table:

LITHO-STRATIGRAPHYa) lithological characteristics (i.e. weak materials, presence of clayey

particles);b) stratigraphical characteristics (i.e. rheological contrast: rigid

material over ductile material;c) textural characteristics (i.e. porosity, materials with metastable

texture);d) primary structures (layers, schistosity, fissility);e) mineralogical, petrographical, geochemical characteristics (i.e.

typology of clayey minerals, weathering).

TECTONICa) secondary structures (joints, faults, folds, shear bands, bending);b) tectonic setting of the area;c) neo-tectonic uplift and/or e/o tilting;

QUATERNARY GEOLOGYa) weathering (physical and/or chemical);b) depth of soil, regolith and degradation covers;c) climatic fluctuations;d) eustatic fluctuations;e) melting of glaciers (i.e. unloading of pressures);f) melting of permafrost;g) glacio-eustasy and glacio-isostasy;h) ancient or relict landslides.

HYDROGEOLOGYa) hydrography and springs;b) permeability, contrast of permeability;c) drainage conditions;d) characteristics of groundwater (i.e. free, suspended, confined,

semi-confined aquifers);e) pore pressure in soils and discontinuities;f) filtration;g) capillarity and negative pore pressures;h) evapotranspiration, runoff and infiltration;i) groundwater geochemistry;

GEOTECHNICS AND GEOMECHANICSa) granulometry;b) index properties (i.e. Atterberg limits, point load);c) cementation (i.e. content of CaCO3);d) density (with natural water content, dry, saturated);e) shear strength of material (peak, critical condition, residual;

drained or undrained);f) tensile strength;g) geometrical characteristics of discontinuities (i.e. orientation,

spacing, persistence, roughness);h) mechanical characteristics of discontinuities (i.e. shear strength);i) presence of pre-existing shear surfaces;j) presence of organic matter;k) sensitivity (change in strength with remoulding);l) fragility and progressive rupture;m) cracking and softening;n) swelling and consolidation;o) stress history (i.e. pressure and overconsolidation ratio);p) in situ tensional state;

SEISMICITYa) neotectonics, regional geodynamic model;b) historical and instrumental seismicity, seismotectonic model;c) characteristics of the source (recurrence, maximum expected

magnitude, hypocentral depth, geometry of the source);d) attenuation law;e) seismic macrozoning: ground shaking (i.e. intensity, peak

acceleration, response spectrum)f) seismic microzoning: local seismic response (i.e. amplification),

dynamical effects on terrain properties (liquefaction; dynamicaleffects on pore pressure and shear strength).

VOLCANIC ACTIVITYa) steam emission and subsequent condensation;b) tephra accumulation;c) hydrothermal alteration;d) ice and snow melting;e) volcanic uplift;f) diversion of hydrographic network.

GEOMORFOLOGYa) slope morphometry (i.e. slope angle, height, length, shape,

orientation);b) morphometry of catchments and channels;c) relief energy;d) erosion (i.e. fluvial, marine, glacial) on the foot of the slope;e) superficial erosion (diffuse or concentrated runoff);f) underground erosion (i.e. solution, karst, piping);g) slope loading;h) deforestation (natural causes);

CLIMATOLOGY, METEOROLOGY E HYDROLOGYa) rainfall pattern;b) frequency, intensity and duration of extreme events (i.e. intense

rainfall, extremely prolonged rainfall);c) thermal pattern (ice/snow melting, freezing of spring waters);d) fluctuation of hydrographical level (lakes or rivers);e) fluctuation of sea level;f) thermal excursion (freeze-thaw cycles);g) fluctuation of soil humidity (imbibition / desiccation).h) pre-existing mass movements and frequency of reactivations.

VEGETATION AND LAND USEa) pedologic characteristics (i.e. soil type, texture, structure, depth,

organic matter, content in carbonates);b) agricultural land use (i.e. crop, tree crop, specialised cultures,

grassland, bush, forest)c) type and state of vegetation (i.e. leave cover, depth and strength

of roots, weight of vegetation);d) agricultural techniques (i.e. superficial tillage, strip, terrace).

HUMAN FACTORSa) excavation on the slope or slope toe;b) overloading on slope or crest;c) fluctuation of piezometric levels of artificial basins (i.e. critical

height; rapid emptying);d) deforestation and forestation;e) irrigation;f) mining activity;g) artificial vibrations;h) water leakage (reservoirs, aqueducts, sewage systems).

Tab.2.3 – Causative factors of landslides.


B.III-10

3 Intensity or Magnitude (I)Geometrical and mechanical severity of a landslide. It may be expressed as

a relative scale or as one or more landslide parameters (i.e. velocity,

volume, energy).

A conceptual distinction between magnitude and intensity is reported in

Hungr (2001) in the dynamic analysis of fast-moving landslides (flows and

slides). The magnitude is a parameter that describes the scale of an event.

As a general rule, the volume of the involved material can express the

magnitude of a landslide. The initial volume (i.e. the volume of a rock mass

before the detachment) should be distinguished from the volume of a

landslide deposit, that can be larger due to swelling or erosion phenomena,

or smaller due to partial deposition or diversion of material during the

travel.

Therefore, the magnitude defines the total volume of the displaced mass, as

a sequence of connected episodes, considered as a single event. The

intensity, as for earthquakes, is not a single parameter but a spatial

distribution of different characteristics that describe, qualitatively or

quantitatively, the impact of a landslide in different sites. Velocity, duration

of movement, height of displaced mass, depth of deposits are some of

quantitative parameters of intensity. These parameters are a function of the

areas involved by a landslide and tend to annul at lateral and distal margins

of the path, defining in such a way the extension of the impact zone. With

respect to other field such as seismicity and flood where the intensity may

be clearly defined (i.e. magnitude of an earthquake, height or discharge of

water flow) the definition of the severity of a landslide (in terms of intensity

or magnitude) is a very difficult task for experts due to the objective

difficulty in the assessment of the various parameters. In addition, the

expression of intensity related to potential damage or losses should be

avoided being depending on vulnerability of potential exposed element.

3.1 Velocity

Hungr (1981) proposed a scale of landslide intensity based on classes of

velocity related to a scale of damage. This scale has been partially modified

by Cruden & Varnes (1996) as shown in Table 3.1.

Class Description Potential damage Velocity (mm/s)

7 Extremely rapidCatastrophe of major violence; buildings destroyed by impact ofdisplaced material; many deaths; escape unlikely.

5 m/s 5 x 103

6 Very rapidSome lives lost; velocity too great to permit all persons toescape

3m/min 5 x 101

5 RapidEscape evacuation possible; structures, possessions andequipment destroyed

1.8 m/h 5 x 10-1

4 ModerateSome temporary and insensitive structures can be temporarilymaintained

13m/month

5 x 10-3

3 Slow

Remedial construction can be undertaken during movement;insensitive structures can be maintained with frequentmaintenance work if total movement is not large during aparticular acceleration phase

1.6m/year

5 x 10-5

2 Very slow Some permanent structures undamaged by movement15

mm/year5 x 10

-7

1 Extremely slowImperceptible without instruments; construction possible withprecautions

Table 3.1. Scale of landslide intensity based on velocity and induced

damage (Cruden & Varnes, 1996)


B.III-11

The assessment of velocity of a landslide is generally a difficult task; it may

be assessed approximately considering the typology and activity of a

landslide (Varnes, 1978) (Tab 3.2).

CLASSES OF VELOCITY

1 2 3 4 5 6 7

Fall

Topple

Rock slide (F)

Rock slide (R)

Debris slide

Earth slide (F)

Earth slide (R)

Lateral expansion of rock mass

Lateral expansion of rock mass overlaying clay bedrock

Lateral expansion due to liquefaction

Rock flow

Debris flow

Cohesive earth flow (F)

Cohesive earth flow (R)

Tab. 3.2 - Landslide velocity (referred to the classes proposed by

Cruden & Varnes, 1996) based on typology, material and state of

activity; F =first-triggered landslide; R = reactivation

A similar approach has been proposed by Canuti & Casagli (1996), based on

landslide typology, involved material and state of activity (first-triggered or

reactivated landslides) (Tab. 3.3).

Typology Fall Slide Flow

Material Rock Rock Debris Earth Rock Debris Earth

State of activity - F R - F R - - -

Class of velocity 6-7 5-6 1-5 1-6 5-6 1-5 1-2 1-7 1-4

Table 3.3. Landslide velocity proposed by Canuti & Casagli (1996)

based on typology, material and state of activity. F =first-triggered

landslide; R = reactivation

The relationship between movement and velocity is quite evident: a debris

flow or a rock fall are generally very rapid or extremely rapid, while an

earth flow is usually slow or very slow. Generally a first-triggered landslide

exhibits a higher velocity than a reactivation, except for some cases

discussed by Hutchinson (1987). The former is characterised by a fragile

rupture mechanism while the latter by a ductile rupture mechanism where

the shear strength is proximate or equal to residual values.

Another way to assess landslide intensity, based on velocity, can be done

comparing the surface area of present or potential landslides with their

estimated velocity (Tab.3.4 and 3.5). The potential unstable areas are

assessed taking into account landslide phenomena that are developing over

slopes with similar geological and morphological setting.

VELOCITY

Class V0 V1 V2 V3

Values - < 10-6 m/s

(< m/month)10

-6 - 10

-4m/s

(m/month - m/h)> 10

-4 m/s

(>m/h)

Class Values Description NEGLIGIBLE SLOW MODERATE RAPID

A0 - NEGLIGIBLE I0 I0 I0 I0

A1 < 103 m

2SMALL I0 I1 I2 I3

A2 103 - 10

5 m

2MEDIUM I0 I1 I2 I3

AREA A3 > 10

5 m

2LARGE I0 I2 I3 I3

Tab. 3.4– Diagram for simplified assessment of intensity


B.III-12

Intensity Description

I0 NEGLIGIBLE Stable or potentially stable areas

I1 SMALL Areas with small or potentially small landslides

I2 MEDIUM Areas with intermediate or potentially intermediate landslides

I3 LARGE Areas with large or potentially large landslides

Tab. 3.5 – Classes of intensity referring table 3.4

3.2 Dimension

Landslide intensity can be also estimated through the dimension of the

displaced mass (Fell, 1994) (Tab. 3.6).

Intensity (I) Description Volume (m3)

7 Extremely large > 5 x 106

6 Very large 1 x 106 ÷ 5 x 10

6

5 Large 2.5 x 105 ÷ 1 x 10

6

4 Medium 5 x 104 ÷ 2.5 x 10

5

3 Small 5 x 103 ÷ 5 x 10

4

2.5 Very small 5 x 102 ÷ 5 x 10

3

2 Extremely small < 5 x 102

Table 3.6 - Scale of intensity of landslides based on the volume of

the displaced mass (Fell, 1994)

The estimation of the displaced mass is often difficult to calculate;

therefore, the intensity may be preferably expressed as landslide area.

The assessment of intensity, based on dimension, should take into account

the different landslide typologies. DRM (1990) has proposed to associate

the volume of displaced mass following landslide types (Tab. 3.7) compared

with intensity levels and consequent damage on human life and economy.

The intensity of slides is evaluated through the depth of phenomena since

the estimation of volumes, for this type of landslides, is rather difficult.

FALLS AND TOPPLES

Volume (m3) Description

H1 E1 < 102

Fall of isolated blocks

H2 E2 102 - 10

4Fall, topple or sliding of blocks

H3 E3 104 - 10

6Large fall of blocks

H3 E4 > 106

Catastrophic fall or sliding

FLOWS

Volume (m3) Description

H1 E1 < 5 x 102

Mud flow or mud slide

H2 E2 5 x 102 - 10

4Mud or debris flow

H3 E3 104 - 10

6Rapid debris flow

H3 E4 > 106

Exceptional mass movement

SLIDES

Depth (m) Description

H0 E1 < 2 Superficial slide or solifluxion

H0 E2 2 – 10 Localised slide

H0 E3 10 – 50 Slide of a slope

H0 E4 > 50 Exceptional slide

Table 3.7 - Relationship between intensity and physical

characteristics of landslides (DRM, 1990)

In the table 10 the distinction between intensity and consequences on

human setting (H0 – H3) and economic setting (E1 – E4) has been kept. With

respect to the velocity of movements, the scales of intensity referred to falls

and slides (rapid movements) are the same; as regarding slides, that are

generally slow movements, the intensity, referred to human setting, is


B.III-13

equal to zero (H0) independently from landslide dimension. This definition

includes an analysis of social and economic vulnerability. Finally, the

symbols H and E are referred to the French terminology humaine and

économique (human and economic respectively) and not to the UNESCO

terminology H (Hazard) and E (Element at risk).

3.3 Energy

As reported by Morgenstern (1985) and Cruden & Varnes (1996), small and

very rapid landslides may be more disastrous than large slow-moving

landslides due to their high kinetic energy.

Intensity may be considered as equal, or proportional, to the kinetic energy

developed by landslides. The energy is variable with the time: equal to zero

at the initial conditions, increasing up to the highest value after the

landslide triggering, then decreasing up to zero again. Landslide intensity

can be measures as the maximum kinetic energy or the average value

developed by a landslide.

An assessment of the energy balance may be done following the sled

model, proposed by Heim (1932) and after by Scheidegger (1973), Hsü

(1975) and Sassa (1988), based on the assumption that all the energy of

the movement is lost for friction.

3.4 Consequences

Another way of assessing landslide intensity is to relate the event with the

potential damage. This approach has been proposed by the French project

PER (Plan d’Exposition aux Risques) (DRM, 1988, 1990) where the intensity

levels are defined with respect to the potential damage for human lives

(Tab. 3.8) and economy (Tab. 3.9).

Degree Intensity Potential consequences Landslide types

H0 Very lowImprobable damage (except induceddamage)

Slow-moving landslides

H1 Medium Isolated damage Isolated falls

H2 High Some victims Falls, slides or mud flows

H3 Very high Catastrophe (some tens victims)Catastrophic falls and slides,rapid mud/debris flows

Table 3.8 - Scale of landslide intensity with respect to potential

consequences on human life (DRM, 1990)

Degree Intensity Potential consequences Example

E0 Low10% of worth of an individual singlehouse

Detachment of unstable blocks

E1 MediumTechnical intervention on few houses orsmall lots

Rock detachment or fallingrock barriers; drainage ofsmall unstable areas

E2 HighHigh qualified technical intervention of alarge area, with relevant costs

Stabilisation of a largelandslide; consolidation of arock slope

E3 Very highAny technica l intervention hasunacceptable costs for populations

Catastrophic fall or slide

Table 3.9 - Scale of landslide intensity with respect to potential

economic losses (DRM, 1990)


B.III-14

3.5 Hybrid

Landslide intensity can be assessed using different parameters as velocity,

kinetic energy, depths and heights of landslide deposits, applied, following

their suitability, for different landslide types. This approach is adopted in the

guidelines for landslide hazard and risk assessment in Switzerland (Raetzo

et al., 2002). Indicative values of these parameters are used to subdivide

potential unstable areas or risk areas in three different intensity classes:

high, medium, low (Tab. 3.10). The criterion for assessing landslide

intensity is applied on the most diffuse landslide types, distinguishing for

each one those parameters that properly characterise the intensity.

Landslide types Low intensity Average intensity High intensity

Rock falls E < 30 kj 30 < E < 300 kj E > 300 kj

Rock avalanches E > 300 kj

Slides v 2 cm/year v: dm/year (> 2 cm/year) Large differential movements: v >0.1 m/day for superficial slides;displacement > 1 m per event

Earth/debris flow

Potential e < 0.5 m 0.5 m < e < 2 m e > 2 m

Real - h < 1 m h > 1 m

Table 3.10 - Criteria for intensity assessment. E = kinetic energy; v

= long-term average velocity; e = depth of unstable mass; h =

height of deposit (Raetzo et al., 2002)

The BUWAL method (1998), used for the assessment of hazard in

Switzerland, provides an intensity analysis by defining the magnitude as

product of velocity vs. geometrical severity. The velocity is compared with

velocity classes provided by Cruden & Varnes (1996) (see table 3.11).

Class Description Velocity Potential damage for peopleVelocityBUWAL

7 Extremely rapid 5 m/s

6 Very rapid 3m/minSevere injury and/or death 3

5 Rapid 1.8 m/h

4 Moderate 13m/monthModerate injury 2

3 Slow 1.6 m/year

2 Very slow 16 mm/year

1 Extremely slow

Minor/no injury 1

Table 3.11 - Landslide intensity scale following BUWAL (1998)

compared with intensity scale from Cruden & Varnes, 1996

The geometrical severity is defined through the following table.

Falls Slides and flows Geometrical severity

Diameter of blocks > 2 m Depth > 10 m 3

Diameter of blocks 0.5 - 2 m Depth 2 - 10 m 2

Diameter of blocks < 0.5 m Depth < 2 m 1

Table 3.12 - Landslide intensity scale following BUWAL (1998) based

on geometrical severity compared with different landslide types

The magnitude is the product of geometrical severity by velocity (Tab 3.13)

Potential damage to structures Magnitude

Severe (disruption) 6-9

Functional 3-4

Minor 1-2

Table 3.13 - Landslide intensity expressed as total magnitude

(BUWAL, 1998)


B.III-15

4 Return period of landslidesThe most common criteria for the assessment of landslide return times are

the following:

a) Geomorphological criteria or qualitative analysis;

b) Analysis of temporal series related to effects: the analysis of temporal

series of mass movements enables to define directly the return times of

landslides;

c) Analysis of temporal series related to causes: the correlation between

landslides and long-time records of possible triggering elements (i.e.

rainfall, seismicity) permits to define critical thresholds and associated

return times;

d) Monitoring: the instrumental observation of piezometric levels or slope

displacement for single landslides allows the prediction of slope

movements through the comparison with thresholds or models calibrated

on the observed unstable or potentially unstable areas.

4.1 Geomorphological criteria or qualitative analysis

The recurrence of landslides can be assessed subjectively from general or

qualitative information such as historical, geomorphological and

geotechnical analyses. The direct analysis, using geomorphological and

geotechnical information, in case of lack of historical data, can provide a

probabilistic estimation on landslide occurrence. This approach, although

subjective, is an effective way for assigning relative probability of return

times of landslides in a given area. For instance, a lower probability of

landslide occur in slope that exhibit rounded and vegetated crown areas

while higher probability can be associated to steep slopes with tension

cracks.

4.2 Analysis of temporal series related to effects

Historical analysis is the main source for assessing landslide return times.

The main sources are:

a) Multi-temporal analysis of maps (i.e. geomorphological maps, landslide

inventory maps);

b) Multi-temporal analysis of aerial photos or satellite images;

c) Newspapers;

d) Direct observations;

e) Scientific publications;

f) Technical reports.

Long-term activity of landslides can be analysed with datation methods,

commonly used in Earth’s Sciences, such as radiocarbon, lichenometry and

dendrocronology methods (Starkel, 1966; Schoeneich, 1991; Corominas et

al., 1994).

The annual frequency f(N) of landslides in a period of N years, is the ratio

between the number of events n and the number N of observed years. If N

is quite long, f(N) is an estimation of the annual probability of occurrence P.

Landslide hazard can be calculated as follows:

H(N) = 1 - (1 - P)N = 1 - (1 - 1/T)N (4.1)


B.III-16

When landslide events are very low compared to the time under analysis,

namely N << T, the equation is:

H(N) NP = N/T (4.2)

4.3 Analysis of temporal series related to causes

Return time of landslides can be estimated through the recurrence of critical

threshold related to specific triggering causes. These are mainly related to

precipitation, human activity and, subordinately, seismicity.

Theoretically, the probability of a landslide occurrence is the sum of

probabilities related to different triggering causes (Fell, 1994):

P = Pr + Pa + Ps (4.3)

The problems related to landslide hazard assessment associated to human

activity regard the prediction stage and should be analysed in the phase of

spatial planning and risk management.

4.3.1 Precipitation

Precipitation can be considered the most common triggering cause of

landslides. The effect of precipitation is the increasing of pore pressure u

that cause a decreasing of shear strength. This, for saturated terrains, is

expressed by:

’ = - u (4.4)

where and ’ represent respectively total and effective strength. Such a

reduction results in decreasing of shear strength, following the Mohr-

Coulomb’s failure criterion:

f = ’ tan ’ + c’ (4.5)

In literature numerous studies on landslide-induced precipitation are

available. Generally pluviometric data are available for areas where

pluviometric stations are working; therefore, rainfall data can be effectively

used both for implementing landslide hazard models (forecasting) and for

prevention scopes (e.g. alarm systems for risk mitigation).

The possible approaches may be summarised in 7 different cathegories,

starting from empirical to quantitative models (Polemio & Petrucci, 2000):

1. empirical correlations aimed at detecting possible triggering thresholds

based on rainfall duration-intensity functions vs. landslides;

2. reconstruction of cumulated and antecedent rainfall vs. landslides;

3. long-term precipitation vs. landslides;

4. methods for analysis of effective precipitation

5. hydrological simplified methods,

6. integrated methods for precipitation-slope stability analysis;

7. complete slope stability methods.

These approaches can be grouped in 3 categories:

a) statistical or empirical models (black-box models): where a direct

correlation between rainfall height, in a defined time interval, and slope


B.III-17

movements is analysed without implementing physical laws that rule the

transformation rainfall-infiltration-piezometric response;

b) deterministic models: where hydrological models are use for analysis of

various parameters (rainfall, run-off, effective infiltration) and

hydrogeological models for analysis of piezometric height and aquifer

recharge;

c) hybrid models: where the above approaches are usually coupled (e.g.

aquifer recharge through a hydrological model and piezometric response

by means of a statistical analysis).

4.3.2 Earthquakes

The influence of earthquakes on slope stability is still quite controversial

and, often, overestimated.

The effects of an earthquake on a slope can be direct or indirect. The former

may cause slope movements during the seismic event; the former may

occur from some hours to some days after an earthquake (Hutchinson,

1993).

The main effect results in increasing of destabilizing stresses through the

application of a transient horizontal inertial stress (F = KW), where W is the

weight of the potential unstable mass and K is the coefficient of seismic

acceleration. Such a stress is generally assumed in the calculation of limit

equilibrium for the assessment of the safety factor under pseudo-static

conditions. Since the wavelengths of strong earthquakes, in most of

terrains, are some tens meters, the effects of direct destabilization may

occur only along short slopes, with length generally < 30m (Ambraseys,

1977; Hutchinson, 1987). For longer slopes, in fact, the destabilizing

acceleration produced toward the external part of slopes is balanced by a

stabilizing acceleration, with opposite direction, caused by the succeeding

waves. The highest synchronous acceleration, associated to the maximum

peak of K, results for landslides that have a dimension equal to half

wavelength.

Rock falls, debris flows and earth flows are the most common landslide

types triggered by earthquakes, especially under saturated conditions of

terrains. Re-activation of slides and flows may occur also in cohesive

materials (Hutchinson & Bhandari, 1971).

Another important effect of earthquakes, affecting saturated loose granular

soils, is the dynamic liquefaction (Seed & Idriss, 1967; Seed, 1968; Valera

& Donovan, 1977; Crespellani et al., 1988). An earthquake can cause a

consolidation of soils due to a structural collapse and, consequently,

promote critical pore pressure values that result in liquefaction. In this case,

the shear strength of soils can decrease abruptly causing sliding also along

gentle slopes. Many landslide-induced earthquakes are generally associated

to liquefaction (Seed, 1975). Moreover, since ground failure is fragile,

landslides generated by liquefaction are characterised by high velocity and

long run-out, constituting very hazardous phenomena. The assessment of

potential liquefaction of a soil is based on seismic parameters (e.g.

magnitude, duration, number of cycles, distance from epicentre, maximum

site acceleration) as well as on geotechnical parameters (e.g. grain-size

distribution, uniformity, relative density, SPT test, initial stress state).


B.III-18

The indirect effects, generally, cause the re-activation of pre-existing

landslides, also large landslides in cohesive soils, due to the cyclic load on

pore pressure regime. Some investigations (Lemos et al., 1985; Sassa,

1992) have shown that the application of rapid cyclic loads in special shear

ring apparatus can cause, in some cohesive materials, a progressive

decreasing of residual shear strength after an initial peak. Such a behaviour

can explain the delay between the seismic shake and landslide trigger.

The triggering thresholds of landslides can be assessed as local seismic

response parameters (i.e. intensity, peak acceleration) or as earthquake

source parameters (i.e. magnitude). A common adopted methodology is to

implement a deterministic analysis (i.e. pseudo-static slope stability

analysis) to calculate the critical acceleration that produce a safety factor

equal to 1. Another method is to compare empirically landslides occurrence

with site intensity of magnitude at the source.

4.4 Monitoring

The assessment of landslides occurrence based on monitoring provides the

most detailed and reliable information, especially in landslide hazard and

risk analysis at local/site scale.

Two distinct approaches can be adopted in landslide hazard analysis

through monitoring: mechanical and kinematical approaches.

4.4.1 Mechanical approach

Theoretically, the prediction of landslide movements or potentially unstable

slopes can be done through the monitoring of all parameters, variable in

time, that define the safety factors such as pore pressure, slope

morphology, geotechnical parameters of terrains, loads.

In practical terms, pore pressure is the parameter that exhibits a large

uncertainty as well as a wide variability in time. Therefore, the mechanical

approach is essentially based on piezometric measures.

Generally, 1-2 years of piezometric observations are used to deduce a

possible correlation between rainfall and groundwater fluctuation. The

prediction of hazard can be done through a statistical analysis of

precipitation. Estimated pore pressures can be used as input in slope

stability models for assessing the safety factor; in addition, their

probabilistic assessment through the analysis of annual extremes enables to

associate a return time to each safety factor value (hazard analysis).

A wide scientific literature is available on the prediction of piezometric

fluctuation related with rainfall and other meteorological parameters, based

on empirical, deterministic and hybrid approaches applied to slope stability

assessment.

4.4.2 Kinematics approach

A direct approach for predicting the time of failure of a slope is based on

displacement monitoring, through topographic, extensometric or

inclinometric measures.


B.III-19

5 Hazard assessment (H)Hazard is defined as the probability that a landslide with a given intensity

may occur in a specific time and area. It can be expressed as annual

probability or return time of a landslide. Landslide hazard is to be referred

to a well defined intensity:

H = H (I)

5.1 Basic concepts

As a basis for landslide hazard assessment and zoning any methodology

should be referred to the following four fundamental assumptions, widely

accepted by landslide experts (Varnes et al., 1984; Carrara et al., 1991;

Hutchinson & Chandler, 1991; Hutchinson, 1995; Turner & Schuster, 1995):

• Landslides will always occur in the same geological, geomorphological,

hydrogeological and climatic conditions as in the past;

• The main conditions that cause landsliding are controlled by identifiable

physical factors and laws that can be empirically, statistically and

deterministically defined;

• The degree of hazard can be evaluated;

• All types of slope failures can be identified and classified.

On this basis a complete assessment of landslide considers prediction of the

following parameters (Hartlén & Viberg, 1988):

• Typology: prediction of the landslide type that may occur in the

considered area;

• Affected area: prediction of where a landslide may occur;

• Return time: prediction of when a landslide may occur;

• Intensity: prediction of dimension (area and/or volume), velocity or

energy of a landslide;

• Evolution: prediction of run-out, retrogression limits and/or lateral

expansion of a landslide.


A rigorous landslide hazard assessment needs a large amount of

information on the various parameters. In addition, considering that reliable

scenarios should be done at local/site scale, this implies a time and money-

consuming activities for analysis and mapping.

The basic principle for which past and present unstable areas will be

affected by landslides in the future can be valid for factors that are constant

in time, such as geological, structural and geotechnical setting. A correct

landslide hazard assessment should take into account the variability of

those factors that may play a role in slope stability like climate and land use

modifications.

Due to the objective conceptual and operational limits, most of landslide

hazard maps should be defined as landslide susceptibility maps.

Limitations of landslide hazard analysis mainly include:

o Spatial and temporal discontinuity of landslides,


B.III-20

o Objective difficulty in the prediction of causes, triggering

factors and cause-effect relations,

o Long-term and exhaustive historical records on landslides and

potential triggering factors (i.e. long-term climatic records).

5.2 Prediction of landslide types

The prediction of landslide types that may occur in an area can be done

starting from an accurate landslide inventory map. In this case, the spatial

and temporal prediction of landslides can be differentiated according to

Cruden & Varnes classification.

As concerning potentially unstable areas, the expected landslide type can be

assessed on the basis of the typologies occurring in areas with similar

geological, geomorphological, geotechnical and land use characteristics.

5.3 Prediction of landslide intensity

The prediction of the landslide intensity is mainly depending on the amount

and quality of information from landslide inventory. Landslide hazard, or the

probability of occurrence, should be differentiated according to the

intensity, in order to have an estimation of consequences (risk analysis).

On this issue, some authors (i.e. Fell, 1994) provide a different definition of

landslide hazard that can be expressed as the product of intensity (I) and

probability of occurrence (P).

The methodology proposed by Fell (1994) considers the product of an index

of intensity by an index of probability associated to intensity and hazard

classes (Tab. 5.1).

INTENSITY PROBABILITY HAZARD

I Description Volume (m3) P Description P (annual) H = I P Description

7 Extremely high > 5 x 106

12 Extremely high 1 30 Extremely high

6 Very high1 x 10

6 ÷ 5 x

106

8Very high 0.2

20-29Very high

5 High2.5 x 10

5 ÷ 1 x

106

5High 0.05

10-19High

4 Medium5 x 10

4 ÷ 2.5 x

105

3Medium 0.01

7-9Medium

3 Small5 x 10

3 ÷ 5 x

104

2Small 0.001

3-6Small

2.5 Very small5 x 10

2 ÷ 5 x

103

1Very small 0.0001

2Very small

2Extremely

small< 5 x 10

2

Table 5.1 - Assessment of landslide hazard with prediction of

intensity (Fell, 1994)

The approach proposed by DRM (1990) for PER implementation is more

correct since it provides the definition of the probability of occurrence

depending on different levels of intensities. Anyway, in the implementation

of PER sometimes the local authorities have used operational criteria where

landslide hazard is not properly expressed as combination of probability by

intensity (Perrot, 1988).


B.III-21


The expression of hazard as I x P is not coherent with the UNESCO

terminology and can present some problems. In fact, an event of small

dimensions and very frequent can have the same hazard of a very large and

less frequent landslide event. In addition, the vulnerability is already related

to landslide intensity. This implies that intensity is taken into account two

times in the risk assessment. To overcome this problem Fell defines the

specific risk as the product of probability by vulnerability.

5.4 Prediction on landslide affected area

The spatial prediction of hazard consists in the assessment of relative

hazard. This is the degree of hazard of a slope compared with other slopes,

without indicating the probability of occurrence of landslides (temporal

occurrence), generally based on historical and present instability.

5.4.1 Methods of relative hazard analysis

The methods for the assignment of the different hazard levels can be

qualitative or quantitative, direct or indirect:

• Qualitative methods are subjective and describe the hazard zoning in

terms substantially descriptive;

• Quantitative methods provide numerical estimations, in terms of

probability, on landslide occurrences for each hazard class;

• Direct methods produce essentially geomorphological mapping of

landslide hazard (Verstappen, 1983);

• Indirect methods are essentially carried out through distinct stages. First

of all, these require a field analysis and a landslide inventory map in the

study area or in a subset area (training area). The second step is the

detection and mapping of a set of physical factors that are directly or

indirectly related to slope instability (predisposing factors). Finally, an

assessment of the relative contribution of the various predisposing

factors for landsliding and a hierarchisation of landslide hazard in areas

with distinct hazard degree (hazard zoning).

5.4.1.1 Qualitative methodologies

In general qualitative approaches are based entirely on expert judgement.

The input data are usually derived from assessment during field trips,

possibly integrated by aerial photo interpretation. These methodologies can

be divided into two types: field geomorphological analysis and combination

or overlaying of index maps (heuristic approach).

5.4.1.1.1 Field geomorphologic analysis

This approach is a direct and qualitative method based on the experience of

the earth scientist in assessing present and potential landsliding without any

specific indication of rules that have led to the assessment and/or zoning. In

this case the stability maps are directly evolved from detailed

geomorphological maps. The assessment of slope stability takes into

consideration a very large number of factors. They can be used successfully

at any scale and adapted to specific local requirements. The field

geomorphological analysis does not require the use of a Geographical


B.III-22

Information System which, in this case, is simply a drawing tool. Examples

of geomorphological-based hazard analysis are very frequent in scientific

literature of the 70s and 80s.

Perhaps one of the most comprehensive projects reported in the literature is

the French ZERMOS (Zones Exposées à des Risques aux MOuvements du

Sol et du sou-sol) procedure which involves two main phases: analysis and

extrapolation. In the first phase, all the predisposing factors are examined,

both permanent (e.g. topography, geology, hydrogeology) and temporary

(e.g. climate, land use and other man-made factors). Active and/or inactive

landslides may be analysed. In the following phase all the factors are

extrapolated by the author to areas with similar physical conditions, thus

enabling zoantion of the area into three sections with varying degrees of

hazard (defined as risque):

• null or low hazard, areas in which no instability should occur;

• potential or uncertain hazard, areas with potential instability of uncertain

nature and extent;

• ascertained hazard, areas with declared instability and certain threat of

failure.

The hazard calculated is of a relative nature and the authors acknowledge

that the various hazard categories cannot be compared from one area to

another. The choice of three classes is inspired to the necessity to let the

hazard maps comprehensive by stakeholders and end users (Public

Administration)


The main disadvantages of such approaches are:

• The subjectivity in the selection of both the data and the rules that

govern the stability of slopes or the hazard of instability; this fact makes

it difficult to compare landslide hazard maps produced by different

investigators or experts;

• Use of implicit rather than explicit rules hinders the critical analysis of

results and makes it difficult to update the assessment as new data

become available;

• Lengthy field surveys are required.

5.4.1.1.2 Combination of index maps or heuristic approach

In this approach, the expert selects and maps the factors that affect the

slope stability and, based on personal experience, assigns to each a

weighted value that is proportionate to its expected relative contribution in

generating failure. The following operations should be carried out:

• subdivision of each parameter into a number of relevant classes;

• attribution of a weighted value to each class;

• attribution of a weighted value to each of the parameters;

• overlay mapping of the weighted maps;

• development of the final map showing hazard classes.

The advantages of such a methodological approach are that it considerably

reduces the problem of the hidden rules and enables total automation of the

operations listed above through appropriate use of a GIS. Furthermore, it

enables the standardisation of data management techniques, from

acquisition through final analysis. This technique can be applied at any


B.III-23

scale. In order to provide a better coherence to physical processes, the

attribution of weights can be supported by statistical analysis on the

assessment of the contribution of single predisposing parameters to slope

instability.


The major disadvantage is the lengthy operations involved, especially where

large areas are concerned. In addition, the reliability of heuristic methods

depends largely on how well and how much the investigator understands

the geomorphological processes acting upon the terrain. Since this

knowledge can be formalised into rules, the method could take into account

local geomorphological variability or specific conditions leading to slope

failures. Major limitations refer to the fact that in most cases the available

knowledge on the causal relations between environmental factors and

landslides is inadequate and, most importantly, is essentially dependent on

the experience of the investigator. At present, maps obtained by this

method cannot be readily evaluated in terms of reliability or certainty.

Additionally, landslide hazard is not directly expressed in terms of

probability, limiting the use for risk evaluation and economic estimates.

5.4.1.2 Quantitative methodologies

5.4.1.2.1 Statistical analysis

The attribution of weighted values on a subjective basis to the numerous

factors governing slope stability represents the main limitation in all the

methods described above. The solution to this problem could be to adopt a

statistical approach that compares the spatial distribution of landslides with

the parameters that are being considered. The results could then be applied

to areas currently free of landslides but where conditions may exist for

susceptibility to future instability. The major difficulty consists in

establishing the slope failure processes and in systematically identifying and

assessing the different factors related to landsliding. One of the principal

advantages is that the investigator can validate the importance of each

factor can validate the importance of each factor and decide on the final

input maps in an interactive manner. The use of GIS makes these

operations much easier and to a large extent explains the increasing

adoption of the statistical approach which closely parallels the ever-

increasing application of GIS techniques.

Statistical analyses can be either bivariate or multivariate.

Bivariate statistical analysis

In bivariate statistical analysis each individual factor is compared to the

landslide map. The weighted value of the classes used to categorise every

parameter is determined on the basis of landslide density in each individual

class. The following operations are required:

• selection and mapping of significant parameters and their categorisation

into a number of relevant classes;

• landslide mapping;

• overlay mapping of the landslide map with each parameter map;


B.III-24

• determination of density of landslides in each parameter class and

definition of weighted values;

• assignment of weighting values to the various parameter maps;

• final overlay mapping and calculation of the final hazard or susceptibility

value of each identified land unit.

The simplest models consider the determination of threshold value of slope

angle, for each lithological type, that may cause potential slope instability.

The models are based on a series of empirical functions that relate two or

more significant parameters, such as slope height or slope angle of

landslide areas.

The bivariate statistical approach is widely employed by the earth scientists

and numerous parameters may be taken into consideration: lithology, slope

angle, slope height, land use, distance from major structures, drainage

density, relief morphology, closeness of the facet to a river, attitude of

lithotypes. This approach has been successfully employed by researchers

mapping hazard of superficial failures that affect prevalently weathered and

soil covers, triggered by heavy rainfall.

Multivariate statistical analysis

Although the multivariate statistical approach had already been successfully

applied in several areas of applied geology, such as petroleum exploration,

the application of this technique to landslide hazard assessment began since

the second half of 70s. The so-called black-box statistical approaches are

based on the analysis of functional links among the various predisposing

factors and present and past landslide distribution.

The procedure involves several preliminary steps which are undertaken in a

test area. Once the results achieved have been verified, they are extended

to the entire area under examination. The following steps are required.

1. Classification of the study area into land units.

2. Identification of significant factors and creation of input maps.

The input variables include information concerning the landslides (i.e.

typology, degree of activity) and geo-referencing. Several attributes are

automatically derived from statistical operations performed on the basic

parameters (mean, standard deviation, maximum or minimum values). An

important aspect is the conversion of various parameters from nominal to

numeric, such as geological composition or vegetation cover. This can be

done through the creation of dummy variables or by coding and ranking the

classes based on the relative percentage of the area affected by landsliding.

The two methods are similar but the latter is to be preferred.

3. Construction of a landslide map.

4. Identification of the percentage of landslide-affected areas in every land

unit and their classification into unstable and stable units.

The threshold value of this classification is fixed every time on the basis of

two requirements: a) in areas with high landslide density, the threshold

should be based on relatively high percentages in order to achieve two

statistically representative groups; b) however, even a relatively low

landslide density must be taken into consideration as it could represent a


B.III-25

risk for human activities. In general, the decision to carry out the analysis

on two groups only (unstable and stable land units) simplifies the problem

from a statistical point of view but hinders the identification of various

combinations of factors related to different hazard types.

5. Combination of the parameter maps with the land unit map and creation

of an absence/presence matrix of a given class of a given parameter within

each land unit.

6. Multivariate statistical analysis.

The statistical analysis most frequently used are discriminant analysis or

regressive multiple analysis which are often employed in parallel within the

same project. It is preferable to apply discriminant analysis (stepwise or

canonical discriminant analysis) with continuous variables, while the

regressive analysis can be used even with nominal variables.

7. Reclassification of land units based on the results achieved in the

previous phase and their classification into susceptibility classes.

In the discriminant analysis for example, the inspection of the standardised

discriminant coefficient allows the contribution of various parameters in

causing slope instability to be quantified and, as a result, enables objective

reclassification of the study area. By transforming the classification function

scores into probabilities, the susceptibility map can then be converted into a

hazard map.


• Black-box are conceptually simple but, due to the great complexity in

identifying the slope failure processes and the difficulty in systematically

collecting the different factors related to landsliding, the task of creating

a geomorphological predictive model enabling actual/potential unstable

slopes to be identified over large areas, is difficult operationally.

• Errors in mapping past and present landslides will exert a large and not

readily predictable influence on statistical models, particularly if errors

are systematic in not recognizing specific landslide types.

• Additionally, being data-driven, a statistical model built up for one region

cannot readily be extrapolated to the neighbouring areas.

5.4.1.2.2 Geotechnical models

Deterministic analysis

This type of approach involves analysing specific sites or slopes in

engineering terms. The main physical properties are quantified and applied

to specific mathematical models and the safety factor is calculated. These

models (mono, bi- and tri-dimensional) are commonly used in soil

engineering for slope-specific stability studies. The approach is widely

employed in civil engineering and engineering geology and has been applied

to landslide hazard assessment and mapping, especially after the

introduction of GIS. Accuracy and reliability is improved as detailed

knowledge of the area of application increases. A deterministic approach

was traditionally considered to be sufficient for both homogenous and non-

homogenous slopes. The index of stability is the well known safety factor,

based on the appropriate geotechnical model. The calculation of the safety


B.III-26

factor, F, requires geometrical data, shear strength parameters and

information on pore water pressure. Moreover, decisions must be made on

whether to use peak shear strength values or residual shear strength values

(or values in between) for specific parts of the slip surface. For these

reasons such methods are normally applied only in small areas and at

detailed scales. Calculations of the safety factor must be made for each

individual slope or area before a hazard map can be prepared.

The safety factor enables the evaluation on the slope stability degree and

an objective comparison among different slopes. Usually the probability of

occurrence of a landslide is not calculated unless the safety factor is related

to the temporal occurrence of the possible triggering factor (i.e. critical

precipitation return time). A reference for assessing the relative hazard

based on F has been proposed by Ward (1996).

Tab.5.2 - Hazard classes related to safety factor F (Ward, 1976).

Probabilistic analysis

For decades, geotechnical modelling and analysis within a deterministic

framework has facilitated the quantification of safety or reliability. However,

performance indicators such as the factor of safety, F, do not take into

account the variability of geotechnical parameters of terrains such as

cohesion c, angle of internal friction and the undrained shear strength su

some of which may also vary in magnitude with time. The spatial and

temporal variability of pore water pressure is again very important but is

not reflected in the calculated values of the conventional factor of safety.

The probability of failure is defined as the probability that the performance

function has a value below the threshold value. Considering the factor of

safety, F, as the performance function, the threshold value is 1 and

probability of failure pf may, therefore, defined as:

pf = P[F<1] (5.1)

The probability of success or the reliability ps is therefore the complement

of pf:

ps = 1 - pf (5.2)

In order to calculate the probability of failure, the probability density

function of the performance function is required. Thus it is recognised that F

is not a single-valued function. Its probability distribution may be

characterised by means of at least two statistical parameters, the mean or

central value F and the standard deviation F.

It is often useful to define a reliability index which combines the mean and

standard deviation of the performance function. Thus, if F is the

performance function

= (F – 1)/ F (5.3)

Hazard F

High < 1.2

Medium 1.2 - 1.7

Low > 1.7


B.III-27

The numerator gives the extent to which the average value is above the

threshold value and the denominator reflects the dispersion from this

average value.

Three commonly used methods of probability calculation are:

• First Order Second Moment Method (FOSM);

• Point Estimate Method;

• Monte Carlo Simulation Method.

The availability of GIS can facilitate the use of a deterministic or a

probabilistic geotechnical approach as part of a methodology of landslide

hazard assessment. For example, after subdivision of an area or region into

elements or small areas, the factor of safety of individual sloping areas may

be computed and then mapped. Alternatively, using a probabilistic

framework, the probability of failure of individual slopes could be computed

and then mapped. Depending on the adopted hazard assessment approach,

this information could be used on its own or combined with other factors or

factor maps to produce susceptibility maps and/or hazard maps.


The deterministic models that provide safety factor calculation usually do

not provide return time of landslide phenomena.

Systematical uncertainties derive from the following considerations:

o a soil mass can only be investigated at a finite number of points;

o the number of field and laboratory tests conducted to determine soil

parameters is limited by financial and time constraints;

o the testing equipment and methods are not perfect.

Other uncertainties are associated with geotechnical models, landslide

mechanisms, their occurrence and impact.

A deterministic analysis of landslide hazard can be done only for single

slopes or limited areas where a large and detailed geotechnical data are

available.

Reliable mechanical models are not yet available for several types of

structurally complex rock units.

5.5 Temporal prediction

The temporal prediction of landslide hazard is essentially based on definition

of the probability of occurrence of landslides. While spatial prediction

provides a relative hazard of different slopes, the temporal prediction

provides an absolute hazard.

For some authors the term absolute hazard is not referred to the probability

of occurrence, but to the definition of the safety factor (F) that, as already

discussed, indicates only a relative zoning of a slope-failure propensity and

not a probabilistic estimate of occurrence.

5.5.1 Analysis of return time

If P is the annual probability of occurrence of a landslide, the return time T

of the event is given by 1/P.


B.III-28

The probability of occurrence of m events in a period of N years is given by:

P m NN

m N mP Pm N m( , )

!

!( )!( )= 1

In case of rare events compared with the available temporal scale (for

N>30 or P<0.02 the error is <1%) the binomial distribution can be

represented by Poisson’s distribution:

( )P m N

NP e

m

m NP

( , )!

=

Hazard, H, is defined as the probability of occurrence of at least one

landslide in a period of N years or:

H N P m N( ) ( , )= =1 0

Therefore, on the basis of binomial distribution the equation is:

H N PT

N

N

( ) ( )= =1 1 1 11

while following Poisson’s distribution:

H N e eNP N T( ) /= =1 1

As concerning rarer events compared with the analysed temporal scale (for

NP<0.02 the error is <1%) the equation can be approximated to:

H N NPN

T( ) =

The probability of occurrence can be calculated both in absolute terms

(annual probability or return times) or following nominal scales (e.g. high

probability, low probability).

In literature, the interpretation of recurrence of slow-moving re-activated

landslides is illustrated in the following tables.

Class Hazard T (years) Landslide movement1 Very high > 2 Continuous or seasonal

2 High 2-5 Periodical

3 Medium 5-20 Periodical

4 Low 20-50 Periodical

5 Very low >50 Periodical

Table 5.3 - Landslide hazard classes based on return time (Del Prete

et al., 1992)

Hazard T (years) P (annual)Extremely high 1 1

Very high 5 0.2

High 20 0.05

Medium 100 0.01

Low 1000 0.001

Very low 10000 0.0001

Table 5.4 - Landslide hazard classes based on return time (Fell,

1994)


B.III-29

5.5.2 Analysis of intensity/magnitude

The BUWAL method (1998) is used for the analysis of landslide hazard. This

is calculated through a matrix between intensity, expressed as velocity

(Tab. 5.5) and magnitude (Tab. 5.6), vs. return times of potential

landslides.

Velocity Return time (years) Probability (annual) Hazard1 < 1 (active) 1 11 1-30 0.03 31 30-100 0.01 2

1 100-1000 0.001 2

2 < 1 (active) 1 32 1-30 0.03 42 30-100 0.01 32 100-1000 0.001 22 > 1000 0.0001 1

3 < 1 (active) 1 4

3 1-30 0.03 43 30-100 0.01 43 100-1000 0.001 33 > 1000 0.0001 2

Table 5.5 - Potential landslide hazard related to velocity and return

time (BUWAL, 1998)

Magnitude Return time (years) Probability (annual) Hazard1-2 < 1 (active) 1 2

1-2 1-30 0.03 31-2 30-100 0.01 2-31-2 100-1000 0.001 2

3-4 < 1 (active) 1 33-4 1-30 0.03 3-43-4 30-100 0.01 33-4 100-1000 0.001 2-3

3-4 > 1000 0.0001 1

6-9 < 1 (active) 1 46-9 1-30 0.03 46-9 30-100 0.01 46-9 100-1000 0.001 36-9 > 1000 0.0001 1-2

Table 5.6 - Potential landslide hazard related to magnitude and

return time (BUWAL, 1998)

Since vulnerability is proportional to landslide phenomena, the levels of

landslide hazard, when associated to the elements at risk, correspond to

specific risk (Cruden & Varnes, 1996).

5.6 Prediction of evolution

The prediction of landslide evolution consists in the detection of the area

that can be directly or indirectly affected by a landslide, through the

analysis of:

o prediction of run-out;

o prediction of retrogression limits;

o prediction of lateral expansion.


B.III-30

5.6.1 Prediction of run-out

Current an past research into the run-out calculation of a fast-moving

landslide (i.e. rock falls, debris flows, rock avalanches) can generally be

grouped into three categories. The first includes empirical models aimed at

providing practical tools for predicting the run-out distance and distribution

of landslide accumulation. The second category includes simplified analytical

models that describes the physical behaviour of mass movement, based on

lumped mass approaches in which the mass is assumed as a single point.

The third includes numerical simulations of conservation equations of mass,

momentum and energy that describe the dynamic motion of landslide mass,

and/or a rheological model to describe the material behaviour of sliding

mass.

5.6.2 Prediction of retrogression limits

The prediction of retrogression limits is essentially based on the analysis of

geomorphologic evidences on the field that define the distribution of activity

(i.e. tension cracks, counter slopes). Some landslide typologies are

generally characterised by a retrogressive evolution such as rotational and

translational slides, rock topples/falls affecting jointed rocks. In most cases,

the ultimate limit is represented by the catchment’s divide so that the

analysis, although conservative, can be carried out simply by using

topographical information.

5.6.3 Prediction of lateral expansion

The prediction of lateral expansion is important in the analysis of earth

flows or liquefaction phenomena, when the displaced mass is very fluid and

may expand to the slope toe. The prediction is very complex and mostly

depends on slope morphology, grain-size and water content of soils, shear

strength of materials, pore pressure and lateral stress coefficient.

6 Landslide hazard mapping

6.1 Introduction

The identification and map portrayal of areas highly susceptible to

damaging landslides are first and necessary steps toward loss-reduction”

(Zeizel, 1988). There are four general categories of potential users of

landslide hazard information (Wold and Jochim, 1989):

o scientists and engineers who use the information directly;

o planners and decision makers who consider landslide hazards among

other land-use and development criteria;

o developers, builders, and financial and insuring organizations;

o interested citizens, educators, and others with little or no technical

experience.

Members of these groups differ widely in the kinds of information they need

and in their ability to use that information (Wold and Jochim, 1989).

Most local governments do not have landslide hazard maps and do not have

funding available for mapping activities, and such communities usually look

to a higher level of government for mapping. The U.S. Geological Survey

(USGS) has provided maps in some areas (e.g., demonstration


B.III-31

mapping of San Mateo County, California; Brabb et al., 1972), but in

general, landslide hazard mapping by the USGS has had limited geo-

graphic coverage. Although most local communities look to their state as

the primary source of maps, few states have undertaken significant

landslide hazard mapping programs. However, there are important

exceptions. California and Oregon, for example, have undertaken landslide

hazard mapping at standard USGS mapping scales. These maps provide an

excellent starting point for local communities and, importantly, form the

basis for state laws that require a certain level of compliance with the

information they provide.

The considerable variability among state geological agencies, particularly in

terms of their existing mapping capabilities and projected funding

environments, makes it difficult to provide detailed commentary and

suggestions regarding the partnerships between the USGS and states for

landslide hazard mapping and assessment. Historically, there have been

strong ties between the USGS and state geological surveys in the realm of

mapping (e.g., Ellen et al., 1993; Coe et al., 2000b) and, to a lesser extent,

for the identification and mitigation of natural hazards. The suggestion in

the national strategy proposal (Spiker and Gori, 2000) of mapping

partnerships, using a model based on competitive grants and matching

funds (as with the existing National Geologic Cooperative Mapping

Program), would undoubtedly provide resources for a considerable amount

of much-needed mapping. However, such a model raises the possibility that

hazard mapping assessed as having a high priority might not be possible if

state matching funds are not available.

It is important that the details of the cooperative mapping partnership be

worked out carefully, in close consultation with state geologists, as the

national strategy implementation plan is being developed. Landslide hazard

zonation is commonly portrayed on maps. Preparation of these maps

requires a detailed knowledge of the landslide processes that are or have

been active in an area and an understanding of the factors that may lead to

an occurrence of potentially damaging landslides.

Accordingly, this is a task that should be undertaken by geoscientists. In

contrast, vulnerability analysis, which assesses the degree of loss, requires

detailed knowledge of population density, infrastructure, economic

activities, and ecological and water quality values and the effects that a

specific landslide would have on these elements. Specialists in urban

planning and social geography, economists, and engineers should perform

these analyses.

Because landslides both leave a topographic signature when they occur and

are driven largely by topographic effects, improved sources of high-

resolution topographic information have the potential to greatly increase the

accuracy of landslide hazard maps.

6.2 Susceptibility and hazard mapping

A national strategy (Spiker and Gori, 2000) should identify three activities

that are required to provide the maps, assessments, and other information

needed by officials and planners to reduce landslide risk and losses:


B.III-32

1. Develop and implement a plan for mapping and assessing landslide

and other ground failure hazards nationwide.

2. Develop an inventory of known landslide and other ground failure

hazards nationwide.

3. Develop and encourage the use of standards and guidelines for

landslide hazard maps and assessments.

The landslide inventory and landslide susceptibility maps are critically

needed in landslide prone regions of the nation. These maps must be

sufficiently detailed to support mitigation action at the local level. To cope

with the many uncertainties involved in landslide hazards, probabilistic

methods are being developed to map and assess landslide hazards” (Spiker

and Gori, 2000, p.13). Hazard zoning may be mapped at various scales;

user requirements and the intended applications determine the appropriate

scale. Because a clear understanding of the different types of landslide

hazard maps is critical for successful implementation of a national strategy.

In the absence of accepted national standards for landslide hazard maps, a

variety of mapping styles have been employed for each type of map. This

even applies to landslide inventory maps—the most basic type of landslide

map. These document the locations and outlines of landslides that have

occurred in an area during a single event or multiple events. Small-scale

landslide inventory maps may show only landslide locations and general

outlines of larger landslides, whereas large-scale maps may distinguish

landslide sources from landslide deposits, classify different kinds of

landslides, and show other pertinent data.

The quantitative definition of hazard or vulnerability requires analysis of

landslide-triggering factors, such as earthquakes or rainfall, or the

application of complex models. Both tasks are extremely difficult when

dealing with large areas. Consequently, the legends for most landslide

hazard maps usually describe only the susceptibility of certain areas to

landslides, or provide only relative indications of the degree of hazard, such

as high, medium, and low. Not all methods of landslide zonation are equally

applicable at each scale or for each type of analysis. Some require very

detailed input data that can be collected only for small areas because of the

required levels of effort and the high cost.

Consequently, selection of an appropriate mapping technique depends on

the type of landslide problems occurring within an area of interest and the

availability of data and financial resources, as well as the duration of the

investigation and the professional experience of the experts involved. When

carefully applied by well-qualified experts, the inferential approach may

describe the real causes of slope instability, based on scientific and

professional criteria.

However, due to the scale and complexity of slope instability factors, the

basic inferential approach is unlikely to be definitive over large areas when

mapping is conducted at small scales. For such applications, the

combination of expert inference and qualitatively weighted contributing

parameters greatly improves the objectivity and reproducibility of the

zoning. Combined statistical and process based approaches may efficiently

provide reliable regional landslide zoning over large areas, by classifying the

terrain into susceptibility classes that reflect the presence and intensity of

causative factors of slope instability.


B.III-33

For detailed studies of small areas, large amounts of data may become

available, and in such cases, simple process-based models become

increasingly practical for establishing landslide hazard zoning. They allow

variations in the safety factor to be approximated and, thus, yield

information useful to design engineers.

6.3 Hazard zoning scales

Characteristics and Use Data Acquisition and Mapping Procedures

• National zoning maps:Provide a general inventory of problem areas forthe landslide inventories nation with a low level ofdetail. These maps are useful to national policy

makers and the general public.

National summary of regional landslide and mapproducts

• Regional zoning maps:Provide engineers and planners an overview ofpotential landslide impacts on large projects orregional developments during initial planningphases. The areas investigated are quite large andthe required map detail is low.

Detailed data collection for individual factors(geomorphology, lithology, soils, etc.) is not a cost-effective approach. Data gathered fromstereoscopic satellite imagery combined withregional geologic, tectonic, or seismic data shoulddelineate homogeneous terrain units.

• Local zoning maps:Identify land sliding zones for large engineeringstructures, roads, and urban areas. Theinvestigations may cover quite large areas; yet aconsiderably higher level of detail is required.Slopes adjacent to landslides should be evaluatedseparately and may be assigned different hazardscores depending on their characteristics.

Data collection should support the production ofdetailed multi temporal landslide distribution mapsand provide information about the variousparameters required in statistical analysis.

• Site-specific zonation maps:Used during site investigations to provide absolutehazard classes and variable safety factors as afunction of slope conditions and the influence ofspecific triggering factors.

Data collection should relate to the parametersneeded for slope stability modelling (e.g., materialsequences and geotechnical properties, seismicaccelerations, hydrologic data).

Table 6.1 –Hazard zoning scales

6.4 Landslide Hazard map types

A landslide inventory map shows the locations and outlines of landslides.

A landslide inventory is a data set that may represent a single event or

multiple events. Small-scale maps may show only landslide locations,

whereas large-scale maps may distinguish landslide sources from deposits,

classify different kinds of landslides, and show other pertinent data.

A landslide susceptibility map ranks slope stability of an area into

categories that range from stable to unstable. Susceptibility maps show

where landslides may form. Many susceptibility maps use a colour scheme

that relates warm colours (red, orange, and yellow) to unstable and

marginally unstable areas and cool colours (blue and green) to more stable

areas.

A landslide hazard map indicates the annual probability (likelihood) of

landslides occurring throughout an area. An ideal landslide hazard map not

only shows the chances that a landslide may form at a particular place, but

also the chances that a landslide from farther upslope may strike that place.

A landslide risk map shows the expected annual cost of landslide damage

throughout an area. Risk maps combine the probability information from a

landslide hazard map with an analysis of all possible consequences

(property damage, casualties, and loss of service).


B.III-34

6.5 Approaches to landslide mapping

6.5.1 The Inferential Approach

This approach is very common and relies on visual analysis of aerial

photographs, and other remote-sensing images, topographic and geologic

maps, and field observations and historical data, to create interpretative

maps of the extent and relatively activity of landslide features. Four major

classes of maps may be produced by the inferential approach:

1. Landslide inventory maps show the spatial distribution of mass

movements, represented either as affected areas to scale or as point

symbols (Wieczorek, 1984).

2. Landslide density maps show landslide distributions by landslide

isopleths (Wright et al., 1974).

3. Landslide activity maps are usually based on interpretation of aerial

photographs taken at different times.

4. Qualitative combination maps result when a scientist uses individual

expert knowledge to assign weights to a series of parameter maps

and then sums these to produce a series of relatively homogeneous

slope instability zones (Stevenson, 1977).

Limitations

Maps produced by the inferential approach, while rooted in direct

observation, are strongly dependent on the experience and skill of the

mapmaker. Inventory, density, and activity maps are costly to create and

require repeated updating after major landslide-producing storms.

Qualitative combination maps may be unreliable when insufficient field

knowledge of the important factors prevents the proper establishment of

factor weights, leading to unacceptable generalizations.

6.5.2 The Statistical Approach

The statistical approach consists of mapping a large number of parameters

considered to potentially affect landslides, and subsequent (statistical)

analysis of all potential contributing factors. This analysis hopefully

identifies conditions leading to slope failures. The advent of digital elevation

data has encouraged the use of two distinct statistical approaches:

1. Bivariate statistical analysis evaluates each factor map (e.g., slope,

geology, land-use) in turn with the landslide distribution map, and

weighting values based on landslide densities are calculated. Brabb et al.

(1972) provided an early example of such an analysis. USGS personnel in

Menlo Park, California later applied geographic information system (GIS)

techniques to statistical landslide mapping (Newman et al., 1978; Brabb,

1984, 1987; Brabb et al., 1989). Subsequently several statistical methods

have been applied to calculate the weighting values (van Westen, 1993).

2. Multivariate statistical models for landslide hazard zonation have been

developed in Italy, mainly by Carrara (1983, 1988) and his colleagues

(Carrara et al., 1991, 1992). All relevant factors are evaluated spatially

within grid cells or by morphometric units. The statistical model is built up

in a “training area,” where the spatial distribution of landslides is well

known. Then the model is extended to the entire study area, based on the


B.III-35

assumption that the factors that cause slope failure in the target area are

the same as those in the training area. Bernknopf et al. (1988) applied

multiple regression analysis to a GIS data set, using presence or absence of

landslides as the dependent variable and the factors used in a slope stability

model (soil depth, soil strength, slope angle) as independent variables.

Limitations. Statistical approaches have the advantage of using an objective

procedure for hazard delineation and are relatively inexpensive to create

once the digital data are available and statistical analyses have been

performed. Good results are found in homogeneous zones or areas with

only a few types of slope instability processes. In more complex situations,

very large data sets may be required because the methods do not make use

of selective criteria based on professional experience. Another disadvantage

of the statistical approach is that specific empirical relationships may be of

limited generality; hence statistical relationships have to be determined for

each study region, the boundaries of which are not clear.

6.5.3 The Process-Based Approach

This approach uses a deterministic or process-based analysis to delineate

relative landslide potential. Quantitative theory for slope instability is

applied using digital elevation data and other digital information, such as

geologic attributes and vegetation cover. The slope instability theory is

commonly coupled to process-based hydrologic models. This approach

emerged in the past 10 years and is undergoing rapid evolution, driven in

part by new observational technology (see below). Despite problems related

to collection of sufficient and reliable input data, deterministic models are

increasingly used for hazard analysis over larger areas, especially with the

aid of GIS techniques, which can handle the large number of calculations

involved when determining safety factors over large areas. Yet this

approach is applicable only when the geomorphic and geologic conditions

are fairly homogeneous over the entire study area and the landslide types

are simple.

Limitations. The main problem with process-based methods is their high

degree of simplification. Slope stability is often strongly dependent on local

conditions, such as planes of weakness in bedrock, root strength, or

groundwater conductivity, which are at present nearly impossible to map at

the resolution needed over a large area. Hence, the controlling parameters

in processed-based models can be difficult to estimate, and considerable

uncertainty must be accepted in model results.

6.6 The mapping unit for GIS Technique

Evaluation of landslide hazard requires the preliminary selection of a

suitable mapping unit, according to data availability, scale of analysis and

representation and potential landslide hazard methodological approach to

be implemented.

The mapping unit refers to a portion of the land surface which contains a

set of ground conditions that differ from the adjacent units across definable

boundaries (Hansen, 1984). At the scale of the analysis, a mapping unit

represents domain that maximises internal homogeneity and between-units

heterogeneity. Various methods have been proposed to partition the


B.III-36

landscape for landslide hazard assessment and mapping (Meijerink, 1988;

Carrara et al., 1995). All methods fall into one of the following five groups:

1. grid-cells;

2. terrain units;

3. unique-condition units;

4. slope units;

5. topographic units.

Grid-cells, preferred by raster-based GIS users, divide the territory into

regular squares of pre-defined size which become the mapping unit of

reference. Each grid-cell is assigned a value for each factor (e.g.

morphology, lithology, geotechnical parameters) taken into consideration.

Alternatively, a stack of raster layers, each mapping a single instability

factor, is prepared.

Terrain units, traditionally used by geomorphologists, are based on the

observation that in natural environments the interrelations between

materials, forms and processes result in boundaries which frequently reflect

geomorphological and geological differences. Terrain units are the base of

the land-system classification approach which has found application in many

land resources investigations.

Unique-condition units imply the classification of each slope-instability

factor into a few significant classes which are stored into a single map, or

layer. By sequentially overlying all the layers, homogeneous domains

(unique conditions) are singled out whose number, size and nature depend

on the criteria used in classifying the input factors.

Slope-units, automatically derived from high-quality DTMs, partition the

territory into hydrological regions between drainage and divide lines.

Depending on the type of instability to be investigated the mapping unit

may correspond either to the sub-basin or to the main slope-unit. Slope-

units can be further subdivided into topographic units defined by the

intersections of contours and flow tube boundaries orthogonal to contours.

For each topographic unit, local morphometric variables and the cumulative

drainage area of all up-slope elements are computed.

Selection of an appropriate mapping unit depends on a number of factors

such as: the type of landslides under analysis; the scale of investigation;

the quality, resolution, scale and type of the thematic information required;

the availability of the adequate information management and analysis tools.

Each technique for tesselling the territory has advantages and limitations

that can be stressed or reduced choosing the appropriate hazard evaluation

method.

7 Element at Risk (E) or exposure

7.1 Definition

Elements at risk can be defined as “Population, property, economic activity,

public services or environmental goods situated in a location exposed to

danger”. In landslide risk assessment, finalised on spatial planning, the

main topic is not only calibrated on the existing activities and goods but also

on the scenario provide by development plane.


B.III-37

7.2 Cartography related to the element at risk - Map ofExposure -

The map of element at risk (map of exposure), constitute one of the most

important start data, not only for a complete landslide risk analysis

(forecasting applications), but also for the mitigation measurements

planning and for preparedness of emergency plan.

Data available for the production of an exposure map could be provided by

public stakeholders (i.e. municipality, region, province, district) trough their

planning and urbanisation instruments (i.e. strategic regional plan,

preparatory land-use planning, detailed land-use planning)

A correct and exhaustive exposure map could be containing the inventory of

all settlement, structure and infrastructure element exposed at risk like:

a ) Urban settlement, commercial, industrial and agriculture activities,

organized by human density, buildings typology and function;

b) Transport infrastructure and in particular the more sensitive area, in

order to prevent the problems of services interruption; the infrastructure

exposed at fall and occlusions;

c) Services infrastructure like hydro drinkable distributions net, lifelines in

general and pipelines in general; in order to pointed out the more

sensitive tract and point;

d ) Public structures (i.e. school, barrack, city hall) and rescue and

emergency structures (i.e. hospital, fire department, civil protection)

e) Technological and industrial plant potentially pollutant;

f) Cultural heritage, historical, artistic, cultural, environmental and

landscape goods.

7.3 Economic value of element at risk

For each single typology of element at risk could be defined the economic

value W or number of units of each element at risk situated in a given

location:

W = W(E)

The value of element at risk could be expressed in terms of number N or

quantity of exposed unity (i.e. number of persons, buildings) or in terms of

exposed area S (i.e. hectares of terrain) or in alternative in monetary

terms. The value is a specific function of every single element at risk:

W = N otherwise W = S

For the comparison between different element at risk sometimes is usefull

to express the value in monetary terms, simply multiply the number N o

element or the surface S by a unitary cost w

W = N x w otherwise W = S x w

The expression of the value in monetary terms is particularly indicated for

the risk analysis of elements with difficult parametrisation. For examples in

the national France project PER, risk is been calculated separately between

human life and socio economical settlement.


B.III-38

7.3.1 Human life Value

The economic value of element at risk, in terms of human life proposed by

DRM (1990) is showed below in the table.

The monetary value is normalized with the assumption that 1 is the medium

cost of the human life. The high value linked to injured is strictly connected

by the highest social cost for the permanent invalidity with respect the

dead.

Dead Injured Homeless

1 2 - 3 0.2 - 1

Tab.7.1. - Relative costs about human life at risk in France (DRM,

1990)

7.3.2 Goods and activities value

The economic value of goods and activities should be evaluated for each

homogeneous area of land use (tab 7.2)

The monetary value is normalized with the assumption that 1 is the medium

cost of the losses of one hectares of agricultural terrain

As been carried out a different relative costs depending on typologies of

goods and activities developed into.

Land use zone Goods Activities

Agricultural zones 1 0.5

Isolated houses 6 2

Groups of houses 10 1

Big urban areas 23 8

Industrial, artisan, commercial area 8 28

Urban centre 16 30

Tab.7.2. - Relative costs per hectares linked by land use in France

(DRM, 1990)

In the experiences of Province of Modena & GNDCI (1994), focused on the

risk assessment in urban area, the socio – economical value for the element

at risk has been estimated trough an empirical scale as shown below.

Cost: High Medium Low

Weight: 1 0.7 0.3

Buildings

Civil habitations, publicbuildings, cemetery,agricultural areas, hoteland residence

Civil habitations, touristhabitations, stalls

Service infrastructurecommercial and artisaninfrastructure

StreetsRoad conditions: publicprimary road

Public secondary road Minor road system

Aqueduct Reservoir, main collector

Electro ductPower station, cabin oftransformation

Urban power station

Gas duct Reservoir, Main pipelines

Variousinfrastructures

Architectonic emergencyPhone lineDrainage system

Sports center, touristinfrastructure

Tab.7.3 - socio – economic value for the element at risk in urban

area (Province of Modena & GNDCI U.O. 2.9, 1994a e 1994b)


B.III-39

7.3.3 Global Value

In same cases could be useful to express a global value taking into account

all the element at risk in a particular area

In monetary terms, the global value is given simply by the sum of the single

cost of each different element at risk.

Del Prete et alii (1992) propose, as an example, the use of the following

expression for the evaluations of the total value of the element at risk

W = [Rm(Mm-Em)] Nab + Ned Ced + Cstr + Cmorf

where:

Rm is the medium income of the inhabitants;

Mm is the medium age of dead of inhabitants;

Em is the medium age of inhabitants;

Nab is the number of inhabitants;

Ned is the number of buildings;

Ced is the medium costs of buildings;

Cstr is the costs of structures and infrastructures;

Cmorf is the costs of morphological modifications.

In the correct definitions of risk, the total value W could be multiply to an

appropriate index of vulnerability.

8 Vulnerability (V)Vulnerability is the degree of loss produced on specific element or group of

element at risk as a consequence of a natural phenomena of a specific

intensity.

In other terms is the propensity of a society to experience damage,

disruption and causalities as a result of a natural hazard.

The vulnerability should be expressed by a scale starting from 0 (nobody

loss) to 1 (total loss) and is a function of intensity of the phenomena and

typology of element at risk.

V=V(I;E)

More in details the concept of vulnerability define the correlations between

the intensity of a specific phenomena with his possible consequences.

Formally the vulnerability concept should be expressed in terms of

dependent probability (Einstein, 1988):

V = P(damage event)

In other words: the probability that the element at risk suffers a specific

damage due to the occurrence of a landslide of a specific intensity.

In the same time the vulnerability concept should be include a

measurement of severity of damage.

Using Morgan et al.(1992) definition, the complete evaluation of

vulnerability is expressed by the simple product of several quantity

(everyone defined trough a relative scale from 0 to 1):

V = VS x VT x VL


B.III-40

where:

• VS is the probability of spatial impact: define the probability that a

certain element at risk is involved by a landslide, (e.g. the probability

that a rapid debris flow involve a specific building ).

• VT is the probability of temporal impact: define the variability of

characteristics of the element at risk trough the time (e.g. the

probability that a specific building is occupied in during the landslides

occurrence).

• VL is the probability of loss of human life of each occupant of the

element, or in otherwise the value portion injured that could be lose.

In addition of the intensity of the phenomena and typologies of the element

at risk, in the definitions of the vulnerability, several factors, with difficult

parametrisation, are involved. This parameters are linked to social

organisation of the area test (Panizza, 1988).

The vulnerability, with parity of other conditions, is minor in that country

equipped with prevention and emergency plan

The evaluation of vulnerability could be based on statistic method, in the

specific case of frequent and repeatable phenomena’s. For example, in the

case of rock fall is possible to estimate, on statistical base, the probability

that a rock detachment produce a specific damage on a specific building.

8.1 Vulnerability: some web definitions

In the following table various definitions of vulnerability are listed:

Source Definition

http://www.geocities.com/CapitolHill/Lobby/6075/Glossary.htm

Likely to be damaged or disrupted

http://www.ben.edu/semp/htmlpages/glossaryh1.html Susceptibility of a population

http://www.mmeirs.org/glossary.html The degree to which a socio-economicsystem, for example, is either susceptible orresistant

International Agreed Glossary of Basic Terms Related toDisaster Management (1992) UN-DHA, IDNDR

Degree of loss

http://www.reliefweb.int/library/mcda/refman/glossary.html

The extent to which a community, structure,service or geographic area is likely to bedamaged or disrupted

American Heritage College Dictionary, 3 rd edition Susceptibility to a physical injury or attack.

Fema (2001) How exposed or susceptible to damage anasset is.

Tab.8.1 - Definitions of vulnerability

8.2 Conceptual approach: vulnerability assessment

8.2.1 Definition

Vulnerability assessment poses problems of understanding the interaction

between this phenomenon and the exposed element.

This interaction can be expressed by so-called damage functions, or by

extension, vulnerability functions. These enable a structuring of the various

components of the vulnerability concept, which is the first step towards

vulnerability assessment (Leone et al., 1996).


B.III-41

8.2.2 Vulnerability components

Three main groups of exposed elements susceptible to damage are defined:

• property or land, including any structures on it, but also whole areas

or land use means;

• people;

• various activities and functions.

Each group has its corresponding specific type of damage function:

• a structural-damage function for material assets;

• a corporal-damage function for people;

• an operational-damage function for the various activities and

functions

Vulnerability of a structural asset depends on the intensity of the

phenomenon and the resistance of the structure to the mechanical stress by

the phenomenon.

Vulnerability of a person also depends on the intensity of the phenomenon,

plus the intrinsic and extrinsic sensitivity of the person concerned:

Intrinsic sensitivity is made up of:

• perceptive factors (level of danger perception);

• cognitive factors (knowledge of how to protect oneself);

• mobility factors (level of mobility when faced with danger).

Extrinsic sensitivity is made up of:

• factors of physical protection (provided by the surrounding

structures);

• technical and functional circumstances (efficiency of the ways and

means of raising the alarm, evacuation, emergency aid, treatment,

e.g.).

Functional vulnerability depends on the:

• damage level of the material assets (technical factors);

• people (human factors);

• secondary functions that ensure the activity in question (functional

factors) as well as the ability of the disaster-struck society to restore

this activity (social, economic and institutional factors).

The specificity of landslide phenomena is essentially manifested by

structural and corporal damage. Such functions are difficult to formalize

from an analytical point of view due to the:

• diffuse character of the phenomena,

• complexity of the type of associated damage,

• rarity of “consolidated balance sheets” to the damage.

To progress, it is vital to collect and compare historical data of the damage-

recording.

The result is the progressive development of damage matrices, after

drawing up:

• suitable typologies for the processes,

• modes of occurrence,

• and damage rate that are specifically caused by landslides.


B.III-42

In general the estimations of vulnerability in large part is based on

objectives assessment methodologies.

A lot of researchers includes in the vulnerability evaluation, a sort of

implicitly estimation of phenomena unpredictability.

It’s our opinion, for a correct evaluation of every single parameters, in the

risk assessment procedure, to remain separate the concept of hazard, value

of element at risk and vulnerability.

It’s opportune discriminate the vulnerability evaluations in terms of typology

of element at risk, because the vulnerability depends of the intensity of the

phenomena.

In particular different approach are developed depending from the typology

of element at risk (e.g. human life vulnerability or goods and activities

vulnerability)

8.3 Human life vulnerability

In the real case in which the element at risk is mainly represented by

human life, the vulnerability should be expressed by the probability of dead,

injured or homeless after the occurrence of a specific landslide of a specific

intensity.

The vulnerability in that case is directly dependent by the populations

density in an exposed area (Fell, 1994).

In the scope of PER projects, the value of probability of dead, injured and

homeless is fixed by the DRM (1990), in relationship by the intensity of

landslides phenomena (see tab. 8.2).

That kind of value of probability could be used directly to express

vulnerability.

Damage H0 H1 H2 H3

dead 0 10-5

10-3

10-2

injured 0 10-4

10-2

10-1

homeless 0 10-4

10-1

10-1

Tab. 8.2. - Probability in terms of effects on human life for different

scale of intensity. (DRM, 1990)

If we are able to define the intensity in terms of displacement velocity, the

edge of human life vulnerability (possibility of dead or injured) has been

fixed by Hungr (1981) and Morgenstern (1985) in 1 m/s, corresponding to

human run velocity.

Del Prete et al. (1992) propose to halve that threshold, considering the time

of reaction of all the people involved. Cruden & Varnes (1996) reduce the

threshold to 0.05 m/s (about 3 m/min), in order to consider the possibility

of totally evacuation of the risk area.

8.4 Vulnerability of good and activities

In the situations of a particular element at risk, for example good and or

activities, the vulnerability express the percentage of the economic value

that could be loss after the occurrence of a landslides phenomena.


B.III-43

Depending on the scale of work the vulnerability of each building could be

detected and evaluated or in alternative the vulnerability of an

homogeneous land use.

In the case of a single building the vulnerability evaluation is based on the

estimation of damage. A preview estimation of damage is given by the

economic commitment useful to restore and re establish the situation before

the landslide occurs.

In a very preliminary approach the damage could be evaluated by:

• aesthetical;

• functional;

• structural.

Scale of damage severity about buildings has been developed and adopted:

• by Tomlinson et al. (1978), in particular referred to foundations

problems;

• by Alexander (1989) for damages due to different typologies of

landslides; and

• by Ragozin & Tikhvinsky (2000) linking deep of foundations and slip

surfaces (tab 8.3).

Depth of foundations (m) Depth of slip surface (m) Vulnerability

2 < 2 1.0

> 2 < 2 0

Minor than slip surface 2 – 10 1.0

10 –13 2 – 10 0.5 – 1.0

> 13 2 – 10 0 – 0.5*

Every depth > 10 1.0**

Tab.8.3 - Vulnerability value respect to depth of foundations and

slip surfaces (Ragozin & Tikhvinsky, 2000)

Note: (*) the value are grater than 0 for the slip surface landslides major than the depth of

foundations, the displacements velocity Vs the building is more than 1 m/s and the volume is

grater than 100 m3, (**) not including special foundations

Scale of damage severity in terms of percentage of building cost, is given

by DRM (1990) and shown in the tab 8.4.

Degree ofdamage

% of buildingvalue

Kind of damage

1 some % Light damage and non structural. The stability is uncompromised.

2 10 – 30 Crack on the walls.

3 50 – 60 Important deformations. Crack open. Evacuation is necessary.

4 70 – 90 Partial floor subsidence and walls disarticulations. Immediate evacuation.

5 100 Total disruption: Restoration is impossible.

Tab.8.4 - Conventional scale of damage severity (inspired to

Mercalli scale) (DRM, 1990)

The damage degree is strictly linked by the intensity of phenomena and

structural typologies (tab. 8.5).


B.III-44

Intensity Typology A B C1 C2

Sliding 5 3 – 4 2 1 – 2

Flow 2 – 5 1 – 3 1 – 2 1E1

Fall 4 – 5 3 – 5 3 – 5 2 – 3

Sliding 5 5 3 – 5 3 – 5

Flow 3 – 5 1 – 4 1 – 3 1E2

Fall 5 5 5 4 – 5

Sliding 5 5 4 – 5 4 – 5

Flow 5 3 – 5 1 – 5 1 – 5E3

Fall 5 5 5 5

Sliding 5 5 5 5

Flow 5 5 5 5E4

Crollo 5 5 5 5

Tab.8.5 - Relative damage evaluation due to different landslide

typology and intensity correlated to building structural typology

(DRM, 1990)

A = old buildings, mediocre quality, without foundations, in that categories belong the B

typology with a particular level of decay; B = normal and traditional buildings in masonry or

light structure without concrete (small cottage and so on ); C = Good quality buildings in

concrete or CAP. The categories is divided in two sub classes:; C1 = single buildings of small

dimension; C2 = buildings with more than three floor .

At spatial planning level, for examples at the municipality scale, it is very

difficult to evaluate the vulnerability for each single building. It is more

reasonable trying to define percentage of damage in homogeneous areas of

land use in function of the landslides intensity.

For that kind of vulnerability map always in DRM (1990) is useful the

tab.8.6.

Land use area E1 E2 E3

Agricultural area 70 90 100

Isolated building 60 90 100

Group of buildings 36 80 100

Village 10 60 90

Commercial and industrial areas 40 80 100

Urban areas 50 80 90 – 100

Tab.8.6 - Damage degree divided in percentage of homogeneous

area of land use and intensity of landslide (DRM, 1990)

Fell (1994) gives a relative and descriptive scale for the vulnerability

associated to property loss tab. 8.6 That kind of scale could be used to link

a numerical value to an empirical evaluation of degree of loss

Vulnerability of good andactivity

Vulnerability

Extremely high V 0.9

high 0.5 V < 0.9

medium 0.1 V < 0.5

low 0.05 V < 0.1

Very low V < 0.05

Tab 8.7 - Vulnerability scale of good and activity (Fell, 1994)


B.III-45

9 Analysis of Risk (R)

9.1 Definition

Risk: A combination of the probability or frequency of occurrence of a

defined hazard and the magnitude of the consequences of the occurrence.

More specifically, risk is defined as the probability of harmful consequences,

or expected loss (e.g. lives, injured people, property, livelihoods, economic

activity disrupted or environment damaged) resulting from interactions

between natural or human-induced hazards.

The evaluation of landslide risk is the combination and parameterisation of

several different factors (e.g. socio economical factors, environmental –

geological factors).

The definition of those parameters involves different competences and skills

(e.g. geologists, engineers, spatial planners, stakeholders).

The three different components of risk (Hazard, Vulnerability and Worth of

elements at risk) should be defined with different degree of detail

depending on data availability and experiences from expertises and

scientific communities.

In some cases, it could be necessary to develop only a simple and partial

synthesis of information, evaluating the specific risk rather than total risk.

During the risk assessment procedure, a fundamental priority is the

“acceptable risk” threshold definition, because it is possible to define the

critical interpretation of the results and further activities (i.e. risk

assessment, zoning).

The acceptable risk definitions permit the discrimination of a list of priority

in order to assess mitigation measurements.

Depending on the objectives of the analysis and data availability, the

acceptable thresholds risk could be defined as total or specific risk.

9.2 Qualitative analysis

This is the most simple expression of landslide risk assessment. This

considers the acquisition of information on landslide hazard, elements at

risk and their vulnerability, by expressing them with qualitative

classifications (i.e. low, medium, high risk) based on expert judgement.

9.2.1 Damage propensity

The definition of the damage propensity or risk susceptibility considers only

a part of the base elements or simply defining them qualitatively or semi-

quantitatively. In the landslide risk analysis a typical approach of damage

propensity can be implemented by, for instance, overlapping the elements

at risk with landslide inventory maps or landslide susceptibility maps.

Due to the objective difficulty to undertake an exhaustive and quantitative

landslide risk analysis, almost all the existing literature and applications on

landslide risk assessment can be considered as damage propensity analysis.


B.III-46

For instance, the Italian Law 180/98 on landslide risk assessment is a

typical example of damage propensity analysis. This takes into account the

following steps:

a) Landslide inventory mapping;

b) Overlapping of landslide areas with the potential elements at risk;

c) Definition of 4 distinct risk classes (R1-R4), defined qualitatively

according to the social and economic consequences.

9.3 Quantitative analysis

The general framework of a quantitative landslide risk assessment is a

typical multi-discipline approach based on the following tasks:

a) Landslide hazard assessment, namely the probability of occurrence

and characteristics of potential landslides;

b) Identification of elements at risk, as number and characteristics;

c) Analysis of vulnerability of the various elements at risk;

d) Risk evaluation.

9.3.1 Total risk

Expected loss of human lives, injured, damage to the property and

economic activities caused by a landslide event. It can be expressed as

annual cost or number or amount of lost units per year. It is a function of

the elements at risk E and a given intensity I of the landslide:

R(I;E) = H(I) V(I;E) W(E)

According to the considered element at risk, the following risk typologies

can be identified:

a) Induced risk on human life: expected number of deaths, injured or

homeless per year, or their economic worth caused by a landslide;

b) Induced risk on properties: expected number of damaged houses per

year or lost land surface per year, or expected cost of damage caused

by a landslide;

c) Induced risk on economic activities: expected cost of direct and

indirect damage on economy caused by a landslide;

d) Induced risk on goods of public interest: expected cost of damage on

facilities and environment caused by a landslide.

By expressing all the quantities as money it is possible to define a global

risk given by the algebraic sum of the costs associated to each simple

component.

The a priori definition of the total risk applied to spatial planning is quite

problematic. The choice of the risk levels should be done at local level

taking into account the specific socio-economic condition of each zone.

Nevertheless, this differentiation at local level determines some difficulty in

comparing various risk maps designed in distinct areas. For this scope it can

be useful to identify some general criteria for the choice, time by time, of

the risk classes to adopt for landslide risk zoning.

This approach has been adopted for the implementation of PER in France

that identify three distinct landslide risk classes (tab. 9.1). The cost for

prevention measures equal to 10% of the worth of the element at risk is the

acceptable risk threshold.


B.III-47

Class Description Prevention measures

Red Zone Prone to landslide with high intensityand high probability of occurrence

Protection measures cannot be implemented.Constructions are not allowed.

Blu Zone Prone to landslide with moderateintensity and probability of occurrence

Landslide risk mitigation measures can beimplemented for structures done before the publicationof the Plan; the cost of measures cannot exceed 10%

of the worth of goods.

White Zone No expected hazard. No prescriptionadopted.

Landslide mitigation measures are not necessary.

Tab.9.1 – Classes of risk zoning in the project PER (DRM, 1988)

Another general scheme is proposed in table 9.2 where risk is classified in 4

classes. Where a quantitative assessment of the various components of risk

cannot be undertaken, it is possible to adopt nominal scales, as proposed in

9.1 to utilise combining hazard, following table 9.4, and potential damage

assessed with table 9.5.

Risk Description

R0 NUL Negligible risk

R1 LOW Socially tolerable riskNo prevention activities

R2 MEDIUM Socially intolerable riskPrevention activities are necessary

R3 HIGH Catastrophic riskUrgent prevention activities to implement

Tab. 9.2 – Total risk classes

WL0 WL1 WL2 WL3

H0 R0 R0 R0 R0

H1 R0 R1 R1 R2

H2 R0 R1 R2 R3

H3 R0 R2 R3 R3

Tab.9.3 – Scheme for risk assessment based on hazard and

potential damage

9.3.2 Potential damage (WL)

Potential amount of losses caused by a landslide with a given intensity. It

can be expressed as number or amount of exposed units or as monetary

worth. For a given typology of element at risk E and a given intensity I the

potential damage is:

WL(I;E) = W(E) V(I;E)

Potential damage WL takes into account the worth of elements at risk and

their potential degree of loss or damage, as a function of the element

characteristics and landslide intensity. Thus, the assessment of potential

damage requires only general information on landslide intensity (that

affects vulnerability) and is mostly based on the characteristics of the

elements at risk. Such an assessment can be done, therefore, by urban

planners and administrators.

The unit of the loss worth is the same of the worth of the elements at risk,

namely the number or area of damageable units, or the expected cost for

damage.


B.III-48

The risk can be estimated from potential damage, starting from

assumptions on landslide hazard (recurrence intervals) using the following

equation:

R(I;E) = WL(I;E) H(I)

In the following sub-chapters, two distinct methodologies for the

assessment of potential damage are reported: the former is based on a

direct application of the definition where vulnerability and worth of elements

at risk are calculated separately; the latter is a simplified assessment based

on the typology of the element at risk and landslide intensity (taking into

account, implicitly, vulnerability and worth of the elements at risk).

The choice between the two methodologies is substantially based on the

level of analysis and data availability.

9.3.2.1 Rigorous assessment

The risk assessment methodology adopted in the project PER (DRM, 1985,

1988, 1990) considers a detailed definition of potential losses (defined, not

properly, as vulnerability) vs. one or more landslide events with given

hazard and intensity.

In general, potential damage can be expressed as money loss:

WL = N w V (9.1)

Where N is the number of exposed elements, w their unitary worth and V

their vulnerability.

The assessment of potential damage is differentiated according to the

different typologies of element at risk:

a) potential damage for human life WLh: possibility that a landslide can

cause deaths, injured or homeless;

b) potential damage for goods and economic activities WLe: economic

worth of damage to goods and employment;

c) potential damage on goods of public interest: damage on public

structures and infrastructures.

Each component of potential damage is assessed separately following

different landslide intensities, as defined in the Tables 6 and 7. In addition,

the potential damage is assessed for each homogeneous land area defined

by the Municipality Plans. The potential damage at municipality scale can be

obtained by summing the values referred to the different homogeneous

areas.

The potential damage associated to human life can be calculated with the

following function:

WLh (zone) = N [(w V)deaths + (w V)injured + (w V)homeless] (9.2)

where N is the number of residents in the considered zone, w the monetary

worth of each element at risk (Tab. 16) and V their vulnerability (Tab. 19).

The potential damage of goods and economic activities WLe is calculated

with the following equation:

WLe (zone) = S [(w V)goods + (w V)activities] (9.3)


B.III-49

where S is the area of the zone, w the worth of elements at risk per area

(Tab. 16) and V their vulnerability (Tab. 23).

The potential damage for goods of public interest WLp is calculated with the

following equation:

WLp (zone) = k WLe(zone) + D (9.4)

where k is a coefficient that depends on landslide intensity and D a

coefficient that takes into account the number and worth of public facilities

in the zone.

The potential damage at municipality scale is given by, respectively:

WLh(municipality) = [WLh(zone) A] human life;

WLe(municipality) = [WLe(zone) C] goods and economic activities;

WLp(municipality) = WLp(zone) goods of public interest;

where A is a coefficient that takes into account the additional presence of

people in tourist areas (1.3 in tourist areas and 1 in non-tourist areas) and

C is a coefficient that considers the density of facilities vs. municipality

population.

9.3.2.2 Simplified assessment.

The analysis is based on a schematic classification of the territory in

homogeneous urban and land use areas. For each zone, the potential

damage is calculated following the type of element at risk, considering its

relative worth, and landslide intensity.

Four general classes of elements at risk are proposed, combined with the

four classes of intensity defined in tab. 9.4 and tab. 9.5, provide four

classes of potential damage.

Intensity

Elements at risk I0 I1 I2 I3

E3 Urban areas, large industrial and commercial areas,architectural, historical and artistic goods, main roads, relevantsocial facilities

WL0 WL2 WL3 WL3

E2 Small urban areas, minor industrial, artisan and commercialareas, secondary roads WL0 WL1 WL2 WL3

E1 Isolated houses, minor roads, agricultural areas, public parksWL0 WL1 WL1 WL2

E0 Uninhabited or unproductive areasWL0 WL0 WL0 WL0

Tab. 9.4 – Scheme for simplified assessment of potential damage)

Danno Descrizione

WL0 NUL No damage

WL1 LOW Aesthetic or minor functional damage on buildings that are neither affecting humanlife safety nor the continuity of socio-economic activities

WL2 MEDIUM Functional damage to buildings, possibility of homeless and occasional accidents,possible breakdown of socio-economic activities

WL3 HIGH Severe damage to buildings, possibility of deaths and injured, disruption of socio-economic activities

Tab. 9.5 – Classes of potential damage


B.III-50

9.3.3 Specific Risk (Rs)

Expected degree of loss as consequence of a landslide with a given

intensity. It is expressed as annual probability. For each typology of

element at risk E and a given landslide intensity I the specific risk is:

Rs(I;E) = H(I) V(I;E)

The specific risk, unlike potential damage, is a parameter mainly based on

landslide characteristics. The assessment of specific risk, hence, is typically

undertaken by landslide specialists.

The total risk can be estimated by the specific risk using the information on

elements at risk worth:

R(I;E) = Rs(I;E) W(E)

The assessment of the specific risk is very important since it allows to

estimate the consequences of landslides independently from the number

and worth of the element at risk.

The specific risk can be used, in specific cases, for the definition of the

acceptable risk (see chapter 10).

Tab. 9.6 – Scale of specific risk of goods and activities (Fell, 1994)

9.4 Probability of acceptable rupture

In the framework of reliability analysis, there are well defined levels of

probability of acceptable rupture. These values can be differentiated

according to the typology and amount of elements at risk and, therefore,

the vulnerability is implicitly taken into account. For this reason they can be

considered as measures of acceptable risk.

Anyway, the temporal factor is not directly considered. In fact, the

acceptable thresholds are directly compared with the values of probability of

rupture calculated with probability analysis (probability that the safety

factor is lower or equal to 1). The uncertainty of the safety factor is only a

consequence of the uncertainties of the various input parameters in slope

stability calculation. Hence, the probability of rupture cannot be directly

associated to a probability of occurrence (landslide return time).

In civil engineering, different criteria for the calculation of probability

tolerable rupture are adopted. CIRIA (Construction Industry and Research

Information Association) in USA has proposed the following criteria:

Social criteria: P Kn

na s s

d

r

( ) (%)=1000

where:

Ks is a constant depending on work typology and its social use;

nd is the service time of the system;

nr is the number of individuals exposed to risk in the time nd.

Specific risk Rs (annual)

Extremely high Rs 0.1

High 0.02 Rs < 0.1

Medium 0.005 Rs < 0.02

Low 0.001 Rs < 0.005

Very low Rs 0.001


B.III-51

Economic criteria: Pb

C Ea e

i

( ).

(%)= 10023

where:

b is a constant depending on population standard of living (0.06 in USA for

1982-83);

Ei is the initial cost (USD) of the structure;

C is a coefficient referred to the cost of a rupture consequence related to

the initial cost of the structure (namely a measure of the vulnerability).

Socio-economic criteria: P bK

q na se

s

d

( ).

(%)= 10023 2

where:

q is the average value (USD) established by the insurance system for

human life (100 000$ in USA for 1982-83).

Kirsten & Moss (1985) have adapted the criteria of CIRIA to rock slope

stability criteria, providing the values of the input coefficients and risk

thresholds following an empirical classification of slopes based on service

time, social use and surveillance required.

Cat. Service time Social use Surveillancerequired

Ks nd

(ys)nr Pa(s)

(%)Pa(se)

(%)

1 ZERO Accessforbidden

Continuousmonitoring withhigh-techsystems

12000 0.4 0.064

75 75

2 EXTREMELYSHORT(temporary openmines)

Accessstronglyforewarned


5600 1 0.16 35 5.6

3 VERY SHORT(temporary slopes inopen mines)

Accessactivelyforewarned


2400 2.5 0.4 15 0.38

4 SHORT(semi-temporaryslopes in open mines,quarries, civil works

Accessforewarned

Continuousmonitoring withsimple systems

1200 6.25 1.0 7.5 0.018

5 MEDIUM(semi-permanentslopes)

Accessdiscouraged

Intentionallysuperficialobservation

460 16 2.56 2.5 0.031

6 LONG(almost-permanentslopes)

Accesspermitted

Occasionalobservation 160 40 6.4 1.0 10

-4

7 VERY LONG(permanent slopes)

Free access No control30 100 16 0.19 3 10

-6

8 VERY LONG(impact onenvironment andthreat for human life)

Free access No control6 250 40 0.003

810

-7

9 EXTREM. LONG(high impact onenvironment; seriousthreat for human life

Free access No control1 625 100 0.006

32.6 10

-

9

Table 9.7 – Criteria for the assessment of the probability of

acceptable rupture for rock slopes (from Kirsten & Moss, 1985). The

probability of the acceptable rupture following an economic criterion

is independent from the slope category and is equal to

Pa(e)=0.00013%.

Priest & Brown (1983) have proposed some criteria for the interpretation of

rock slope stability probabilistic analysis. According to the typology of slope


B.III-52

and elements at risk, they have defined different threshold values for the

average value of the safety factor E(F), rupture probability P(F<1), and

probability that F<1.5 (Table 9.8). If one, two or all three criteria are

satisfied, the authors provide an interpretation of the slope behaviour,

suggesting risk mitigation strategies (Table 9.10).

CRITERIA

Class Consequences Element at risk E(F) P(F<1.0) P(F<1.5)

1 Slight Quarry terracesModest excavation (H<50m) far fromroads

1.3 0.1 0.2

2 Moderate Permanent or semi-permanent slopes 1.6 0.01 0.1

3 Severe Medium-high slopes (H>50m) nearroads or below structures

2.0 0.003 0.05

Table 9.8 - Acceptable risk assessed following probabilistic analysis

(from Priest & Brown, 1983)

CRITERIA

E(F) P(F<1.0) P(F<1.5) Interpretation

V V V STABLE

VV

FV

VF

Risk can be or cannot be acceptable; the risk level can be decreasedwith monitoring

F V V The risk level can be decreased with a modest re-shape of the slope

FFF

VFF

FVF

UNSTABLE: the risk level can be decreased only with a substantial re-shape of the slope, or with reinforcement of the rock slope; monitoringcan be necessary

Table 9.10 – Interpretation of the risk level and mitigation

strategies following the criteria proposed in Table 3.5 (from Priest &

Brown, 1983): V = criterion satisfied; F = criterion not satisfied.

10 Risk management

10.1 Introduction

Landslide and slope engineering have always involved some form of risk

management although it was seldom formally recognised as such. This

informal type of risk management was essentially the exercise of

engineering judgement by experienced engineers. Recent advances in risk

analysis and risk assessment are beginning to provide systematic and

rigorous processes to formalise the engineering judgements and enhance

slope engineering practice.

Landslide risk management, like many other forms of risk management of

natural and/or civil engineering hazards, is a relatively new discipline with

evolving analysis techniques.

Risk management is relatively well established in other industries,

particularly the nuclear and hazardous process industries, where standards

for risk analysis and risk management have been developed. Within the

societal context, safety regulation involves achieving an appropriate balance

between cost and safety over a range of diverse activities. If it is possible to

achieve this balance, either in part or in full, then consistent methods of

evaluation across the entire range of activities will be required.

In developing landslide risk management methods, it is important to keep in

mind the wide range of landslide and slope stability problems which need to


B.III-53

be considered. The systems need to be capable of handling landslides which

are:

• small, (e.g. single boulders) through to very large (several million m3)

• extremely slow moving (mm per year) to extremely rapid (>100 km/hr)

• from natural slopes (eg. boulder falls, debris flows, avalanches), and

man-made slopes (e.g. cuts and fills, for highways, behind buildings,

houses)

• a hazard to property and life.

The systems also need to recognise that there are many levels of detail and

different methods which can be used depending on the situation, e.g.

detailed probabilistic analysis may be appropriate for slopes with detailed

engineering investigation, but observational methods using geomorphology

and expert judgement may be appropriate for assessment of natural slope.

10.2 Framework for landslide risk management

10.2.1 General framework

The risk management process comprises three components:

1. Risk analysis

2. Risk assessment

3. Risk management

Risk analysis and risk assessment are sub-sets of risk management and risk

analysis is a subset of risk assessment.

In contrast, in an engineering standards approach, the level of safety is not

known, rather those design, construction and maintenance standards that

have proven to be successful in the past, form the bases for decision-

making. Standards usually increase if a standards based engineered facility

fails, because failure of an engineered facility, represents to many, failure of

engineering. In terms of standards-based approaches, the engineering

profession is almost completely in control of the level of safety of

engineered facilities. We use the term “almost” to indicate that engineering

standards are not solely decided by engineers, the requirements of the

courts, economics and public expectation also play a role. Unfortunately,

there is no unified framework to integrate all of the components of the

standards-based approach, and the engineering profession often finds itself

trying to balance the often conflicting interests of owners, who pay the

engineers fees and the public who would be affected by the failure of the

facility. One consequence of this is the enormous legal liability carried by

engineers, a liability that in many cases is rather more onerous than that

associated with other professions that deal with matters of public safety.

Conversely, risk-based methods involve acceptance of failure as an

inevitable consequence of society’s need for engineered facilities. Failure is

permissible provided the risks (probability of failure x consequences) are

tolerable. Risk based methods, when used for safety evaluations of existing

facilities do not involve the concept of “designing for failure”, and many of

the criticisms of risk-based engineering do not apply.

Risk management techniques provide an integrated approach to safety

decision-making and have the advantage that the engineer is not faced with


B.III-54

having to determine what is an appropriate level of safety, this is done by

those policy makers who are responsible for these matters. The engineers

perform the risk analysis, and provide a measure of how safe a facility is.

How safe it needs to be is determined by the owner and the government

body that represents the public (regulators). Engineers can provide various

risk management related services in addition to analysing risk; they can

even assist decision makers in developing decision analysis techniques and

in choosing appropriate decision criteria, without being responsible for the

actual decision.

One of the most important knowledge base for the risk assessment and

management is the hazard zoning; that specific step is structured by the

interpretation and the possible framework of operational decision for the

risk reduction and mitigation.

The risk management aspect phase is typically under the influence of

political and administrative approach; nevertheless fundamental should be

the rules of scientist and experts of the scientific communities in order to

define the priority of actions and mitigations strategies.

One of the most important example of risk management comes from the

experiences of Plans d’Expòsition aux Risqué (PER, DRM 1987), in France.

PER instruments are integrated document, of spatial planning and urban

standard, regulating, land use and territory development.

Three possible prevention strategies are individuated:

1) increasing of social acceptable threshold risk;

2) mitigation of risk through structural action to hazard reduction;

3) mitigation of risk through non structural action to potential damage

reduction;

The total risk evaluation, (in terms expected annual cost of damage),

permits to choose through different mitigations strategies with cost-benefit

analysis.

By every single cost of each action, a benefit in terms of risk reduction

should be associated, expressed by the reduction of annual cost of landslide

damage.

In this view it is possible to define the minimum number of years in which

the total cost could be amortized.

10.2.2 Increasing of social acceptable threshold risk

The increasing of social acceptable threshold risk could be obtained through

the population information and responsibility. It is widely demonstrated that

the awareness of tolerable risk thresholds are in general higher than the

unconscious ones.

It is possible to encourage a campaign of information in the highest risk

areas, not only in the emergency phase, but also preventively , in order to

let the population aware of risk.

Instruments for that kind of campaign could be:

a) use of mass media communication;


B.III-55

b) diffusion of informative brochures that describe the kind of risk and the

behaviour to assume in case of alarm and emergency;

c) assemblies and meetings with administrations and stakeholders;

d) installation of hazard signage;

e) stipulation of insurance for damage coverage.

The informative activities for the risk tolerance increasing is a very low-cost

approach and could be adopted for large areas.

10.3 Acceptable and tolerable risk from landsliding

10.3.1 General issues

There is an implied level of acceptability and tolerability of landslide risks in

every jurisdiction where slope instability poses a problem. Unfortunately,

there is rarely, if ever, any indication of what this level of tolerable risk

actually is. Landslide risk analysis can be carried out, albeit with difficulty,

without the requirement to define what is tolerable whereas such a

definition is required for landslide risk management. There have been a

number of initiatives to define acceptable risks for engineered facilities,

unfortunately few have been accepted by policy makers (the nuclear

industry and hazardous chemical industries are the exceptions). There are

several reasons why this is so.

These include but are not limited to the following:

1. Apparent reluctance of policy makers to deal with the issues.

2. Apparent unreasonableness of court decisions concerning hazardous

activities.

3. Apparently unreasonable public expectations.

4. Possibly an unreasonably high standard of duty of care assumed by

some professional bodies responsible for public safety, or imposed on

them by the courts.

5. Lack of suitable framework to deal with such complex decision

making processes.

6. Apparent unwillingness of stakeholders to invest the time and

resources necessary to develop a sound and logical process.

7. Shortage of suitably trained and experienced individuals and groups

to develop the processes, even if the resources were available.

8. A prevailing attitude that the problem of developing rational methods

of risk management is so enormous that it is a hopeless task which is

simply not worth the effort.

9. Shortage of data necessary for precise estimates of probabilities.

10. Lack of engineering analysis tools developed for predicting failure,

and so on.

While Fell (1994), Hungr, Sobkowicz and Morgan (1993) and Morgan et al

(1992) have discussed acceptable risk criteria for landsliding, there have

been no acceptable risk criteria established for landslides established by a

government authority, National or International Technical Society in the

way that has been done for hazardous industries or other like dam.

Some example of acceptable risk diagram as shown in the following figures:


B.III-56

Starr (1999), according to statistical data on accidents and diseases,

propose a standard level of acceptable specific risk of Rs=10-6 per year. Fell

(1994) observes that public opinion seem to tolerate high levels of risk

(Rs=10-2÷10-4 per year) when voluntarily exposed to risk (e.g. road

accidents, work or sport accidents) while when prone to unintentional risk

(e.g. fires, natural hazards, engineering works collapse) it tolerates much

lower levels (Rs=10-5÷10-6 per year).


B.III-57

For landslides developed in natural slopes, when the population is aware of

risk, the tolerance is high, comparable with the tolerance of voluntary risk.

In those situations Whitman (1984) indicates an acceptable specific risk of

10-2 per year. Fell (1994) estimates an acceptable specific risk of 10-2 per

year, for damage to properties, and 10-3 for human life. In artificial slopes,

the tolerable risk is like those for unintentional risk (Rs = 10-5 per year).

This value, or slightly lower, should represent also the acceptable risk for

landslides developed on reinforced slopes.

A further consideration, associated to the concept of voluntary or

unintentional risk, is the distinction between the acceptable specific risk of a

single individual in a landslide hazardous area, and the acceptable specific

risk of the whole population. For instance, according to the data provided by

the Italian Ministry of Public work (Catenacci, 1992), the global probability

of death caused by landslides in Italy, in the period 1945-1990, is about 10-

6 per year per person. This is comparable with the acceptable unintentional

specific risk thresholds. Nevertheless, in landslide areas, the population is

exposed, almost consciously, to risk levels of some orders higher.

Fell (1994) has proposed a scale of specific risk of damage to properties

that can be used for interpreting the results of a risk zoning or to compare

risk levels calculated for different scopes.

10.4 Treatment

At the end of the evaluation procedure, it is up to the client or policy

makers to decide whether to accept the risk or not, or to decide that more

detailed study is required. The landslide risk analyst can provide

background data or normally acceptable limits as guidance to the decision

maker, but as discussed above, should not be making the decision. Part of

the specialist advice may be to identify the options and methods for treating

the risk.

Typical treatment options would include:

Accept the risk; this would usually require the risk to be considered to be

within the acceptable or tolerable range.

Avoid the risk; this would require abandonment of the project, seeking an

alternative site or form of development such that the revised risk would be

acceptable or tolerable.

Reduce the likelihood; this would require stabilisation measures to

control the initiating circumstances, such as re-profiling the surface

geometry, groundwater drainage, anchors, stabilising structures or

protective structures etc. After implementation, the risk should be

acceptable or tolerable.

Reduce the consequences; this would require provision of defensive

stabilisation measures, amelioration of the behaviour of the hazard or

relocation of the development to a more favourable location to achieve an

acceptable or tolerable risk.

Monitoring and warning systems; in some situations monitoring (such

as by regular site visits, or by survey), and the establishment of warning

systems may be used to manage the risk on an interim or permanent basis.

Monitoring and warning systems may be regarded as another means of

reducing the consequences.


B.III-58

Transfer the risk; by requiring another authority to accept the risk or to

compensate for the risk such as by insurance.

Postpone the decision; if there is sufficient uncertainty, it may not be

appropriate to make a decision on the data available. Further investigation

or monitoring would be required to provide data for better evaluation of the

risk.

10.4.1 Risk mitigation through structural action and measures

The landslide probability occurrence (hazard) in certain risk area should be

minimized through the following structural action:

a) reduction of the triggering factors (previous mentioned in chapther 4 and

5), for example by land use reclamations and hydrological and geological

environmental restoration work, or through rationalisation of land use

and agricultural activities;

b) direct intervention on actives landslides in order to prevent remobilisation

and control the evolution. This is possible by means of stabilisation

works. These can be designed to reduce the mobilisation forces (slope re-

profiling, detachment of unstable blocks) or increase resistant forces (i.e.

drainage, chemical and physical treatment, concrete injection, walls,

nails, anchors, bolts, piling)

Structural actions and measures have often high costs and are usually

adopted for the risk mitigation of unstable slope where other strategies

cannot be promoted (i.e. urban areas, Cultural Heritage, strategic

structures).

10.4.2 Risk mitigation with non-structural action and measures

The non-structural actions are oriented to the reduction of the potential

damage. This can be done by acting on the elements at risk an their

vulnerability.

The reduction of the worth and importance of the elements at risk have to

be assessed during the spatial planning activities.

The action of reducing value of the element at risk can be summarised in:

a) transfer of the element at risk from landslide prone areas to stable

areas (delocalisation);

b) limitation of urban expansion (restrains and limits);

c) land use definition of unstable areas;

The vulnerability should be reduced through the implementation of technical

measures or restrains according to the social characterisation of the

territory.

Some actions are summarised below:

a) reinforcement of buildings with reduction of the potential damage;

b) implementation of mitigation measures (stabilising structures or

protective structures i.e. anchors, rails, tunnels, trenches), in

order to prevent or reduce the possibility that the element at risk

could be affected by a landslide; with no constrain for the

occurrences and magnitude of the event;


B.III-59

c) setting up of monitoring systems and early warning systems to

reduce potential losses (human lives and goods)

d ) organisation of prevention, emergency and recovery plans, in

order to reduce the effects and damage.

The non-structural actions and measures are more flexible than structural

measures; in addition, the former usually have lower costs. This kind of

measures are strongly recommended in high landslide risk areas.

10.5 Public Awareness, Education and CapacityBuilding

Before individuals and communities can reduce their risk from landslide

hazards, they need to know the nature of the threat, its potential impact on

them and their community, their options for reducing the risk or impact,

and how to carry out specific mitigation measures.

Achieving widespread public awareness of landslides hazards will enable

communities and individuals to make informed decisions on where to live,

where to purchase property, or locate a business. Local decisions and

critical facilities to reduce the potential damage from landslides hazard are:

Develop public awareness, training, and education programs

involving land-use planning, design, landslide hazard curricula,

landslide hazard safety programs, and community risk reduction;

Evaluate the effectiveness of different methods, messages, and

curricula in the context of local needs;

Disseminate landslide hazard related curricula and training modules

to community organizations, universities, and professionals societies

and associations.

10.6 Emergency Preparedness Plan

A landslide usually occur without warning. The energy of a landslide mass

moving down a slope can devastate anything in its path. The emergency

prepardeness plan are generally structured in this form:

1. Before landslide occur;

2. During disaster event;

3. After the event.

Two simple example of preparedness plan developed by the F.E.M.A. is

reported below.

10.6.1 Before the Landslide

You can reduce the potential impacts of land movement by taking steps to

remove yourself from harm's way. Assume that burn areas and canyon,

hillside, mountain and other steep areas are vulnerable to landslides and

mudslides. Build away from steep slopes. Build away from the bottoms or

mouths of steep ravines and drainage facilities. Consult with a soil engineer

or an engineering geologist to minimize the potential impacts of landslides.

Develop a family plan that includes:

• Out-of-state contact

• Place to reunite if family members are separated


B.III-60

• Routes to evacuate

• Locations of utility shut-offs

Store the following emergency supplies:

• Food

• Water

• First aid kit

• Flashlights and batteries

• Battery-operated radios

• Special medications/eye care products

Store an evacuation kit that includes:

• Cash (small bills and change)

• Important documents (Birth certificates, insurance policies, marriage

certificates, mortgage documents)

• Irreplaceable objects

• Games, toys for children

Purchase supplies to protect your home:

• Hammer

• Nails

• Plywood

• Rain gauge

• Sand

• Sandbags

• Shovel

Limit the height of plants near buildings to 18 inches. Use fire-retardant

plants and bushes to replace chaparral and highly combustible vegetation.

Water landscape to promote early growth. Eliminate litter and dead and dry

vegetation. Inspect slopes for increases in cracks, holes and other changes.

Contact your local public works department for information on protection

measures.

10.6.2 When it Rains

Monitor the amount of rain during intense storms. More than three to four

inches of rain per day, or 1/2-inch per hour, have been known to trigger

mudslides or debris flows.

Look for geological changes near your home:

• New springs

• Cracked snow, ice, soil or rocks

• Bulging slopes

• New holes or bare spots on hillsides

• Tilted trees

• Muddy waters

Listen to the radio or watch television for information and instructions from

local officials. Prepare to evacuate if requested to do so. Respect the power

of the potential mudslide. Remember, mudslides move quickly, can cause

damage and kill. Prioritize protection measures:

• Make your health and safety and that of family members the number

one priority.

• Make your home the number two priority.


B.III-61

• Make pools, spas, patios and other elements the next priority.

Implement protection measures when necessary:

• Place sandbags

• Board up windows and doors

10.6.3 Key Considerations

• Use permanent measures, rather than sandbags, if possible.

• Deflect, rather than stop or dam debris.

• Use solutions that do not create problems for your neighbours.

10.6.4 What Can You Do If You Live Near Steep Hills

10.6.4.1 Prior to Intense Storms:

1. Become familiar with the land around you. Learn whether debris flows

have occurred in your area by contacting local officials, State geological

surveys, or departments of natural resources, and university departments

of geology. Slopes where debris flows have occurred in the past are likely to

experience them in the future.

2. Support your local government in efforts to develop and enforce land-use

and building ordinances that regulate construction in areas susceptible to

landslides and debris flows. Buildings should be located away from steep

slopes, streams and rivers, intermittent-stream channels, and the mouths

of mountain channels.

3. Watch the patterns of storm-water drainage on slopes near your home,

and note especially the places where runoff water converges, increasing

flow over soil-covered slopes. Watch the hillsides around your home for any

signs of land movement, such as small landslides or debris flows or

progressively tilting trees.

4. Contact your local authorities to learn about the emergency-response

and evacuation plans for your area and develop your own emergency plans

for your family and business.

10.6.4.2 During Intense Storms:

1. Stay alert and stay awake! Many debris-flow fatalities occur when people

are sleeping. Listen to a radio for warnings of intense rainfall. Be aware that

intense short bursts of rain may be particularly dangerous, especially after

longer periods of heavy rainfall and damp weather.

2. If you are in areas susceptible to landslides and debris flows, consider

leaving if it is safe to do so. Remember that driving during an intense storm

is hazardous.

3. Listen for any unusual sounds that might indicate moving debris, such as

trees cracking or

boulders knocking together. A trickle of flowing or falling mud or debris may

precede larger flows. If you are near a stream or channel, be alert for any

sudden increase or decrease in water flow and for a change from clear to

muddy water. Such changes may indicate debris flow activity upstream, so


B.III-62

be prepared to move quickly. Don’t delay! Save yourself, not your

belongings.

4. Be especially alert when driving. Embankments along roadsides are

particularly susceptible to landslides. Watch the road for collapsed

pavement, mud, fallen rocks, and other indications of possible debris flows.

10.6.5 After the Disaster

Stay away from the slide area as there may be additional danger from

further slides or flows;

Check for injured or trapped victims and give first aid if you're trained;

Check on neighbours, especially elderly or special needs victims;

Listen to radio or television for emergency information;

Flooding can occur after a mudflow or landslide;

Check for damaged utility lines, building foundations and surrounding

damage;

Replant damaged areas as soon as possible since erosion can cause

addition flooding and slides;

Have the area inspected by geo-technical experts to evaluate the area

for additional risks.

10.7 The Phases of emergency Plan (planning,response, recovery)

10.7.1 Emergency Phases

Emergency management activities are often conducted within three

generally defined phases. However, because each disaster is unique,

individual disasters may not include all indicated phases:

Planning;

Response;

Recovery.

10.7.2 Planning Phase

The planning phase involves activities that are undertaken in advance of an

emergency or disaster. These activities assess threats, develop operational

capabilities and design effective responses to potential incidents. Planning

activities include:

o Completing hazard analyses;

o Designing and implementing hazard mitigation projects consistent

with the hazard analyses;

o Developing and maintaining emergency plans and procedures;

o Developing mutual aid agreements;

o Conducting general and specialized training;

o Conducting exercises;

o Improving emergency public education and warning systems.


B.III-63

10.7.3 Response Phase

The response phase includes increased readiness, initial and extended

response activities upon receipt of a warning or the observation that an

emergency situation is imminent or likely to occur.

Incidents that may trigger increased readiness activities include:

Receipt of a flood advisory or other special weather statement;

Conditions conducive to wild land fires, such as the

combination of high heat, strong winds, and low humidity;

A hazardous materials incident;

Information or circumstances indicating the potential for acts

of violence or civil disturbance.

Increased readiness activities may include, but are not limited to the

following:

Increasing public information efforts;

Accelerating training efforts;

Inspecting critical facilities and equipment, including testing warning

and communications systems;

Warning threatened areas of the population;

Conducting precautionary evacuations in potentially impacted areas;

Mobilizing personnel and pre-positioning resources and equipment.

10.7.3.1 Initial Response

The County’s initial response activities are primarily performed at the field

response level. Emphasis is placed on minimizing the effects of the

emergency or disaster. Support and coordination activities take place in the

Emergency Management Center with operational links to field response

units.

Examples of initial response activities include:

Making all necessary notifications, including County

departments and personnel, local cities;

Disseminating warnings, emergency public information, and

instructions to the citizens of Santa Cruz County;

Declaration of a local emergency;

Conducting evacuations and/or rescue operations;

Caring for displaced persons and treating the injured;

Road clearing, debris removal, flood fight

Conducting initial damage assessments and surveys;

Assessing need for mutual aid assistance;

Restricting movement of traffic/people and unnecessary access to

affected areas;

Developing and implementing Initial Action Plans;

Securing incident sites

Conducting search and rescue operations;

Fire suppression.


B.III-64

10.7.3.2 Extended Response

Extended response operations involve the coordination and management of

resources and information necessary to facilitate the transition to recovery.

Although not a specific action, but rather an evolutionary transition in the

response timeline, extended operations generally begin 72 hours after the

initial disaster incident.

Examples of extended response activities include:

Coordination with state and federal agencies working within

the local agencies;

Preparing initial damage assessments;

Operating mass care facilities;

Conducting coroner operations,

Procuring, allocating and monitoring resources required to

sustain operations;

Coordinating mutual aide resources;

Restoring essential services;

Initiating advance planning activities;

Documenting expenditures;

Developing and implementing Action Plans for extended

operation; and

Disseminating emergency public information.

10.8 Recovery Phase

Recovery activities involve the restoration of the affected area(s) to pre-

emergency conditions. Recovery activities may be both short-term and

long-term, ranging from restoration of essential utilities such as water and

power, to implementation of mitigation measures designed to minimize the

impact of future occurrences of a given threat.

Examples of recovery activities include:

Restoring utilities and infrastructure;

Reinstating autonomy for displaced persons

Reconstruction of damaged property;

Conducting residual hazard analyses;

Coordination of Federal, State, public and private assistance;

Determining and recovering costs associated with response

and recovery.


Absolute Risk: Pure risk without the mitigating effects of Internal Controls.

See also Managed Risk.

Acceptable Risk – A risk for which, for the purposes of life or work, we are

prepared to accept as it is with no regard to its management. Society does

not generally consider expenditure in further reducing such risks justifiable.

Aleatoric Probability: Relating to the uncertain outcome of an event (such

as the role of a die) in a generally predictable distribution; also known as

pure chance.


B.III-65

Assurance: A system of Corporate Governance that provides feedback on

the efficiency and effectiveness of operations, compliance with laws and

regulations, and accuracy and reliability of financial information. Both

Internal Audit and Risk Management are part of the assurance process.

Avoiding Risk: A Risk Management technique of redesigning the task to

deal with a different set of risks (usually lower). Not to be confused with

Eliminating Risk.

Behavioral Risk Assessment: The assessment of Risk to an organization

as a result of examining its culture, structure, employee attitudes, and

mechanisms to relieve employees of stress.

Chief Risk Manager: The manager or executive who reports to senior

management on the organization's risk exposures and alternative

management actions required to deal with them.

conditional analysis: technique, based on Bayes theorem (Morgan, 1968),

according to which frequency data (such as landsliding area or number of

landslides) can be used to calculate probabilities that depend on knowledge

of previous events.

Containment: The Risk Management strategy that attempts to limit the

negative Consequences of a Risk Event. This strategy can include Internal

Controls and/or Contingency Planning.

Consequence – The outcomes or potential outcomes arising from the

occurrence of a landslide expressed qualitatively or quantitatively, in terms

of loss, disadvantage or gain, damage, injury or loss of life.

Control: That functional part of a system that provides Feedback on how

the system is accomplishing its purpose or objectives. See Internal Control.

Control Framework: A Model or recognized System of Control categories

that covers all internal controls expected in an organization. Control

frameworks include COSO, CoCo, Cadbury, and the like. See also, Risk

Frameworks.

Control and Risk Self Assessment: Abbreviated CRSA. See Control Self

Assessment.

Control Self-Assessment: Abbreviated CSA. A class of techniques used in

an audit or in place of an audit to assess risk and control strength and

weaknesses against a Control Framework. The "self" assessment refers to

the involvement of management and staff in the assessment process, often

facilitated by internal auditors. CSA techniques can include

workshop/seminars, Focus Groups, Structured Interviews, and survey

questionnaires.

Control Risk: The tendency of the Internal Control system to lose

effectiveness over time and to expose, or fail to prevent exposure of, the

assets under control.

Cost/Benefit Analysis: A Risk Management tool used to make decisions

about Accepting Risk or using some other risk management technique.

discriminant analysis: a multivariate statistical method aimed at

maximizing the distance (separation) between two or more predefined

groups of objects on the basis of a linear combination (discriminant

function) of a set of known variables (discriminating variables).

drainage-divide networks: streamlines and corresponding watersheds

usually automatically derived form a DTM.


B.III-66

DTM (digital terrain model) or DEM (digital elevation model): any

digital representation of the continuous variation of ground relief over

space.

Elements at Risk – Meaning the population, buildings and engineering

works, economic activities, public services utilities, infrastructure and

environmental features in the area potentially affected by landslides.

Expected Loss or Expected Value Approach: The evaluation of Risk

based on the dollar variation that results as a Consequence to the risky

Events.

Exposure: The susceptibility to loss, perception of Risk, or a Threat to an

asset or asset-producing process, usually quantified in dollars. An exposure

is the total dollars at risk without regard to the probability of a negative

event. A measure of importance.

Exposure Approach: The approach to Risk Assessment from the

perspective of the four classes of assets (physical, financial, human,

intangible) and their size, type, portability, and location.

factor: any characteristics, natural or man-induced, of the environment

which is directly or indirectly related to the causes of landsliding in a given

region.

Frequency – A measure of likelihood expressed as the number of

occurrences of an event in a given time. See also Likelihood and Probability.

Global Risks: External or Environment risks that are outside of the

immediate political or government regulatory risk boundaries.

Hazard – A condition with the potential for causing an undesirable

consequence (the landslide). The description of landslide hazard should

include the location, volume (or area), classification and velocity of the

potential landslides and any resultant detached material, and the likelihood

of their occurrence within a given period of time.

heuristic (model): a method of solving a problem in which several

approaches are attempted and progresses toward a solution are evaluated

after each attempt.

Individual Risk – The risk of fatality or injury to any identifiable (named)

individual who lives within the zone impacted by the landslide; or who

follows a particular pattern of life that might subject him or her to the

consequences of the landslide.

Insurance: A contract to finance the cost of risk. Should a named risk

event (loss) occur, the insurance contract will pay the holder the contractual

amount. See Risk Financing.

Integrated Risk Management: The consideration of Risk at all levels of

the organization, from the Strategic to the day-to-day job of the customer-

facing employee. Integrating risk management into internal auditing means

adopting Risk-Based Auditing and using risk management tools to plan

internal audits.

landslide hazard zonation: the division of the land surface into

homogeneous areas or domains and their ranking according to different

degrees of hazard due to mass-movement (see Varnes et al. , 1984).

landslide hazard: the probability of occurrence within a specific period of

time and within a given area of a potentially damaging landslide (see

Varnes et al., 1984.


B.III-67

Landslide Intensity – A set of spatially distributed parameters related to

the destructive power of a landslide. The parameters may be described

quantitatively or qualitatively and may include maximum movement

velocity, total displacement, differential displacement, depth of the moving

mass, peak discharge per unit width, kinetic energy per unit area.

landslide inventory: the systematic mapping, through various techniques

(i.e., field surveys, aerial-photointerpretation, site measurements, historical

records, etc.) of past and recent landslides in a region.

landslide susceptibility (or propensity): an estimate of the slope-

instability conditions of a region mainly based on the qualitative judgment

of the investigator.

Likelihood – used as a qualitative description of probability or frequency.

logistic regression analysis: a multivariate statistical method aimed at

estimating the probability of a dichotomous outcome variable on the basis

of a set of independent, variables measured in any scale. The model

assumes the form: Pr(event) = 1/(1 + exp(-(B0 + B1*X1 + B2*X2 + ......

+ Bm*Xm))).

Long-Term: The planning or Time Horizon that deals with events beyond

the Short-Term and Mid Term, typically from two to twenty years, though

most often two to five or seven years.

Loss: A negative outcome.

Matrix Approach: In Risk Assessment, an approach that matches system

components with risks, threats or controls with the object of measuring and

examining the combinations of the two axes.

Mean: The average value in a distribution.

Median: The value in a distribution where 50% of the distribution values

are greater than or less than the median value.

Mode: A measure of statistical central tendency that notes the most

frequent value in the distribution of values. The mode is also the peak

(highest) value of the curve. See Normal Curve.

model: a mathematical or physical system, obeying certain specific

conditions, whose behavior is used to understand a physical (or biological or

social) system to which is in some way analogous

multiple regression analysis: a multivariate statistical method aimed at

estimating a (dependent) variable on the basis of a linear combination of a

set of known (independent) variables.

multivariate model: a model which aims to predict or explain the behavior

of a dependent variable on the basis of a set of known independent

variables.

Planning Risk: The risk that the planning process is flawed. In Risk

Assessment, it is the risk that the assessment process is inappropriate or

improperly implemented.

predictive (model): a statistical or heuristic model which aims to forecast

the occurrence in space or time of an event on the basis of the values of a

set of variables or factors.

Probability – The likelihood of a specific outcome, measured by the ratio of

specific outcomes to the total number of possible outcomes. Probability is

expressed as a number between 0 and 1, with 0 indicating an impossible

outcome, and 1 indicating that an outcome is certain.


B.III-68

raster (structure): an array of cells (pixel) referenced by a raw and

column number; each cell is independently addressed with the value of an

attribute; it is one of the fundamental ways of representing and storing

spatial data (see vector structure).

Residual Risk: The remaining Risk after Risk Management techniques have

been applied.

Risk – A measure of the probability and severity of an adverse effect to

health, property or the environment. Risk is often estimated by the product

of probability x consequences. However, a more general interpretation of

risk involves a comparison of the probability and consequences in a non-

product form.

Risk Analysis – The use of available information to estimate the risk to

individuals or populations, property, or the environment, from hazards. Risk

analyses generally contain the following steps: scope definition, hazard

identification, and risk estimation.

Risk Estimation – The process used to produce a measure of the level of

health, property, or environmental risks being analysed. Risk estimation

contains the following steps: frequency analysis, consequence analysis, and

their integration.

Risk Evaluation – The stage at which values and judgements enter the

decision process, explicitly or implicitly, by including consideration of the

importance of the estimated risks and the associated social, environmental,

and economic consequences, in order to identify a range of alternatives for

managing the risks.

Risk Assessment – The process of risk analysis and risk evaluation.

Risk Control or Risk Treatment – The process of decision making for

managing risk, and the implementation, or enforcement of risk mitigation

measures and the re-evaluation of its effectiveness from time to time, using

the results of risk assessment as one input.

Risk Management – The complete process of risk assessment and risk

control (or risk treatment).

Risk Prioritization: The relation of acceptable levels of risks among

alternatives. See also Risk Ranking.

Risk Ranking: The ordinal or cardinal rank prioritization of the risks in

various alternatives, projects or units.

Risk Reduction: Application of Risk Management principles to reduce the

Likelihood or Consequences of an Event, or both.

Risk Response: Management's decisions and actions when risks are

revealed. See also Risk Management.

Risk Retention: Intentional (or unintentional) retaining the responsibility

for loss or Risk Financing within the organization.

Risk Scenarios: A method of identifying and classifying risks through

creative application of Probabilistic events and their Consequences. Typically

a Brainstorming or other creative technique is used to stimulate "what

might happen." See also Threat Scenarios.

Risk Transfer: Shifting the responsibility or Risk Financing burden to

another party.

Risk Treatment: Another term for Risk Management.

sampling unit: terrain-unit treated as a case in any statistical analysis.


B.III-69

slope-unit: the right or left side of a sub-basin of any order into which a

watershed can be partitioned, usually by means of a computer algorithm

which enables the automatic detection of stream lines and related divides

(see drainage-divide networks).

Scenario-Building (Scenario Building): The exercise of developing

Scenarios.

Scenario Planning: The use of Scenarios in (usually) Strategic Planning.

Scenario Plots: Various standard forms of organizing the Scenario-Building

process. Typical plots are: Winners and Losers (either/or), Lone Ranger (us

against them), Challenge and Response (both/and), Good News/Bad News

(worst thing), Tectonic Change (structural alteration), etc.

Scenarios: Narrative descriptions of assumptions, risks and environmental

factors and how they may affect operations. Scenarios attempt to explore

the effect of changing several variables at once with objective analysis and

subjective interpretations. See also Risk Scenarios and Threat Scenarios.

Societal Risk – The risk of multiple fatalities or injuries in society as a

whole: one where society would have to carry the burden of a landslide

causing a number of deaths, injuries, financial, environmental, and other

losses.

Specific Risk: The type of risk that is found in specific activities. The level

of this risk is expected to vary from activity to activity, even though all

activities may have it.

Strategic Planning: Long-term plans based on the organizations overall

business objectives. Strategic plans are typically multiple years and reach

out 5 or 10 years (or more) using Scenarios or other planning methods that

identifies Assumptions, Risks, and Environmental factors.

Temporal Probability – The probability that the element at risk is in the

area affected by the land sliding, at the time of the landslide.

terrain-unit (or mapping unit or homogeneous domain): that portion

of land surface which contains a set of ground conditions which differ from

the adjacent units across definable boundaries (Hansen, 1984). By

definition, the terrain-unit must be mappable at effective cost over the

entire region through criteria which are as objective as possible.

TIN (triangulated irregular network): a relief representation consisting

of a continuous set of connected triangular facets based on a Dalauny

triangulation of irregularly spaced nodes or elevation points.

Tolerable Risk – A risk that society is willing to live with so as to secure

certain net benefits in the confidence that it is being properly controlled,

kept under review and further reduced as and when possible. In some

situations risk may be tolerated because the individuals at risk cannot afford

to reduce risk even though they recognise it is not properly controlled.

Transfer Risk: A Risk Management technique to remove risk from one area

to another or one party to another. Insurance transfers risk of financial loss

from insured to insurer. Partial transfers are known as Sharing Risk.

Triggers: In planning, these are external decisions or events that create

the need (or perecption) that a project must be planned.

uncertainty (certainty): the estimated amount by which an observed or

calculated value may depart from the true value.


B.III-70

union (of sets): a set consisting of those elements which are members of

at least one set in a given family of sets.

unique-condition unit: terrain-unit obtained by the sequential overlay of a

set of base maps portraying slope-instability factors (Chung et al. , 1995).

vector (structure): a set of graphic data that can be ultimately

decomposed into point locations described by generally absolute

coordinates; it may include points, lines (a set of related points) and areas

(a line or set of lines defining a polygon); it is one of the fundamental ways

of representing and storing spatial data (see raster structure).

Vulnerability: The degree of loss to a given element or set of elements

within the area affected by the landslide hazard. It is expressed on a scale

of 0 (no loss) to 1 (total loss). For property, the loss will be the value of the

damage relative to the value of the property; for persons, it will be the

probability that a particular life (the element at risk) will be lost, given the

person(s) is affected by the landslide.

12 BibliographyAhlberg P., Stigler B., Viberg L. (1988). Experiences of landslide risk

considerations in land use planning in Sweden. Proc. 5th Int. Symp. on

Landslides, Lausanne, 2, 1091-1096.

Aleotti P., Baldelli P., Polloni G. (1996). Landsliding and flooding event

triggered by heavy rains in the Tanaro basin (Italy). Proc. Int. Congr.

Interpraevent 1996, 1, 435-446.

Aleotti P. , Baldelli P., Polloni G. (1998). Soil slips, rock-block slides and

stream hydraulic processes caused by heavy rains: their interaction

and relevant hazard. Proc. of the 2nd Conf. Environ. Management

ICEM2, Wollongong, 10-13 Feb 1998, 1, 553-564.

Alexander E.D. (1989). Urban landslides. Progress in Physical Geography,

13, 157-191.

Alexander E.D. (1995). A survey of the field of natural hazards and disaster

studies. In: Carrara A., Guzzetti F. (Eds.), Geographical Information

Systems in Assessing Natural Hazards. Kluwer Academic Publisher,

Dordrecht, The Netherlands, 1-19.

Amadesi E., Vianello G., Bonfatti G., Pignone R. & Preti D. (1977) - Guida

alla realizzazione di una carta della stabilità dei versanti. Regione

Emilia Romagna. MB T6. Ed.Pitagora., Bologna, 72pp.

Amadesi E. & Vianello G. (1978). Nuova guida alla realizzazione di una carta

della stabilità dei versanti. Mem. Soc. Geol. It., 19, 53-60.

Amanti M., Carrara A., Castaldo G., Colosimo P., Gisotti G., Govi M.,

Marchionna G., Nardi R., Panizza M., Pecci M. & Vianello G. (1992).

Linee guida per la realizzazione di una cartografia della pericolosità

geologica connessa ai fenomeni di instabilità dei versanti alla scala

1:50.000. Versione Preliminare. Presidenza del Consiglio dei Ministri.

Servizio Geologico. Progetto CARG 53pp.

Ambraseys N.N. (1977). On the response of structures to travelling waves.

Proc. CENTO Seminar on Earthquake Hazard Minimization, Teheran,

410-414.

Ambraseys N.N. (1983). Evaluation of seismic risk. In: Ritsema A.R. &

Gurpinar A. (ed.), Seismicity and seismic risk in the offshore North Sea

area. Reidel Pub. Co., Dordrecht, 317-345.


B.III-71

Ambraseys N.N. (1988). Engineering Seismology. Earthquake Engineering &

Structural Dynamics, 17, 1-105.

Antoine P. (1977). Réflextions sur la cartographie ZERMOS et bilan des

expériences en cours. Bulletin Bureau Recherche Geologique et

Mineraire, 3 (2), 1-2 ; 9-20.

Attewell P.B. (1987) - Aspects of risk assessment in engineering geology

and geotechnics. Memoir of the Geological Society of China, 9, 335-

365.

Attewell P.B. & Farmer I.W. (1973) - Principles of Engineering Geology.

Chapman & Hall, London.

Azimi C., Desvarreux P., Giraud A., Martin-Cocher J. (1982). Méthode de

calcul de la dinamique des chutes de blocs: application à l’étude du

versant de la Montagne de la Pale (Vecors). Bull. Liason Labor. Ponts et

Ch., 122, 93-102.

Baynes F.J., Lee, M. (1998). Geomorphology in landslide risk analysis, an

interim report. Proceedings of the 8th Congress of the Int. Assoc. of

Engineering Geologists, Moore and Hungr (Eds.), Balkema, pp.1129-

1136.

Baecher G. (1983). Applied geotechnical reliability analysis - reliability

theory and its applications in Structural and Soil Mechanics. In: Thoft-

Christensen P. (ed.), NATO Series 70 ASI, 237-270.

Baeza C. & Corominas J. (1996). Assessment of shallow landslide

susceptibility by means of statistical techniques. Proc. 7th Int. Symp. on

Landslides, Trondheim, 1, 147-152.

Barton M.E. & Thompson R.I. (1986) - A model for predicting groundwater

response to meteorological changes. Groundwater in Engineering

Geology. Geol. Soc. Eng. Group. Spec. Pub., 3, 299-311.

Bernknopf, R.L., Campbell, R.H., Brookshire, D.S., Shapiro, C.D. (1988). A

probabilistic approach to landslide hazard mapping in Cincinnati, Ohio,

with applications for economic evaluation. Bull. Am. Ass. of Eng. Geol.,

25 (1), 39-56.

Bertini T., Cugusi F., D'elia B. & Rossi-Doria M. (1984) - Climatic conditions

and slow movements of colluvial covers in central Italy. Proc. 4th Int.

Symp. on Landslides, Toronto (Canada), 1, 367-376.

Bertocci R., Canuti P., Casagli N., Garzonio C.A. & Vannocci P. (1995) -

Landslides on clay and shale hillslopes in Tuscany (Italy). In: Haneberg

W.C. & Anderson S.A. (eds.) “Clay and Shale Slope Instability”,

Geological Society of America Rewievs in Engineering Geology,

Boulder, (Colorado, USA) v.10, 107-119.

Bertozzi E. & Broili L. (1978). Considerazioni sui criteri di progettazione

delle opere di difesa nei processi di scoscendimento massi. Mem. Soc.

Geol. It., 19, 187-195.

Bieniawski Z.T. (1974) - Geomechanics Classification of rock masses and its

application in tunnelling. Proc. 3rd Cong. ISRM, Denver, 2A, p.27.

Bishop A.W. & Morgenstern N.R.(1960) - Stability coefficients for earth

slopes. Géotechnique, 10, 129-150.

Blanc R.P. & Cleveland G.B. (1968) - Natural slope stability as related to

geology, San Clemente Area Orange and San Diego counties,

California. California division of Mines And Geology Special Report, 98,

19pp.

Bonham-Carter G.F. (1994). Geographic Information Systems for

Geoscientists: Modelling with GIS. Pergamon, Ottawa, 398 pp.


B.III-72

Bosi C. (1978). Considerazioni e proposte metodologiche sulla elaborazione

di carte della stabilità. Geol. Appl. e Idrogeol., Bari, 13, 246-281.

Bosi C., Dramis F., Gentili B. (1985). Carte geomorfologiche di dettaglio ad

indirizzo applicativo e carte di stabilità. Geol. Appl. e Idrogeol., Bari, 20

(2), 53-62.

Bernknopf R.L., Campbell R.H., Brookshire D.S., Shapiro C.D. (1988). A

probabilistic approach to landslide hazard mapping in Cincinnati, Ohio,

with application for economical evaluation. Bull. American Assoc.

Engin. Geologists, 25 (1), 39-56.

Brabb E.E. (1984). Innovative approaches to landslide hazard mapping.

Proc. 4th Int. Symp. on Landslides, Toronto, 1, 307-324.

Brabb E.E. (1995). The San Mateo County California GIS project for

predicting the consequences of hazardous geologic processes. In:

Carrara A., Guzzetti F. (Eds.), Geographical Information Systems in

Assessing Natural Hazards. Kluwer Academic Publisher, Dordrecht, The

Netherlands, 234-299.

Brabb E.E., Harrod, B.L. (Eds.) Landslides: Extent and Economic

Significance. Balkema Publisher, Rotterdam, 385 pp.

Brabb E.E., Pampeyan E.H. & Bonilla M.G. (1972) - Landslide susceptibility

in San Mateo County, California. USGS Misc. Field Investigation Map,

MF-360.

Brand E.W. (1988). Landslide risk assessment in Hong Kong. Proc. 5th Int.

Symp. on Landslides, Lausanne, 2, 1059-1074.

Brand E.W., Styles K.A., Burnett A.D. (1982). Geotechnical land use maps

for planning in Hong Kong. Proc. 4th Congress IAEG, New Delhi, 1, 145-

153.

Brand E.W. & Hudson R.R. (1982) - CHASE, an empirical approach to the

design of cut slopes in Hong Kong soils. 7th Southeast Asian

Geotechnical Conference, Hong Kong, 1, 1-16.

Brand E.W., Premchitt J., Phillipson H.B. (1984). Relationship between

rainfall and landslides. Proc. 4th Symp. on Landslides, Toronto, 1,

BiTech Publishers, Vancouver, Canada, 377-384.

Broili L. (1973). In situ tests for the study of rockfall. Geologia Applicata e

Idrogeologia, 8(1).

Bromhead E.N. (1997). The treatment of landslides. Proc. of Institution of

Civil Engineers, Geotechnical Engineering, 125, 85-96.

Brugner W. & Valdinucci A. (1972). Schema di cartografia tematica relativa

alla stabilità dei terreni ed esempio della sua applicazione nel territorio

di Alpago (Prov. di Belluno). Boll. Serv. Geol. D’It., 93, 189-194.

Brunsden, D. (1993). Mass movements; the research frontier and beyond: a

geomorphological approach. Geomorphology, 7, 85-128.

Bunce C.M., Cruden D.M., Morgenstern N.R. (1995). Hazard assessment for

rock fall on a highway. Proc. of the Canadian Geotechnical Conference,

Vancouver, 449-508.

Burnett A.D., Brand E.W., Styles K.A. (1985). Terrain classification mapping

for a landslide inventory in Hong Kong. Proc. 4th Int. Conf. And Field

Workshop on Landslides, Tokyo, 63-68.

Caine N. 1980 - The rainfall intensity-duration control of shallow landslides

and debris flows. Geografiska Annal, 62A, 23-27.

Campbell R.H. (1973). Isopleth map of landslide deposits, Point Dume

quadrangle, Los Angeles County, California. U.S. Geol. Surv. Misc. Map

MF-535.


B.III-73

Cancelli A. & Nova R. (1985) - Landslides in soil and debris cover triggered

by rainfall in Valtellina (Central Alps-Italy). Proc. Iv Int. Conf. & Field

Workshop on Landslides, Tokio, 267-272.

Cannon S.H. & Ellen S.D. (1985). Rainfall conditions for abundant debris

avalanches, San Francisco Bay region, California. California Geology,

38 (12), 267-272.

Cannon S.H. & Ellen S.D. (1988) - Rainfall that resulted in abundant debris

flow activity during the storm. In: “Landslides, floods and marine

effects of the storm of Jan 3-5, 1982, in the San Francisco Bay region,

California”. USGS Prof. Papers., 1434, 27-35.

Cannon S.E., Savage W.Z. (1988). A mass change model for debris flow.

The Journal of Geology, 96, 221-227.

Canuti P. & Casagli N. (1996). Considerazioni sulla valutazione del rischio di

frana. Da: Fenomeni franosi e centri abitati. Atti del Convegno di

Bologna del 27 maggio 1994. CNR-GNDCI-Regione Emilia Romagna.

Pubbl. n. 846, 58 pp.

Canuti P., Dramis F. & Esu F. (1992). Le condizioni di instabilità dei pendii

nei centri abitati. Principi e criteri generali ad uso degli Uffici Tecnici di

Enti Pubblici. CNR-GNDCI Pubbl. n. 544, Tecnoprint, Bologna, 100 pp.

Canuti P., Focardi P., Garzonio C.A., Rodolfi C., Zanchi C. (1984). Analysis

of the dynamic of a mass movement on silty clayey lacustrine deposits

in north-central Italy - Proc.IV ISL, Toronto, A.A.Balkema, pp XX.

Canuti P., Focardi P., Garzonio C.A. (1985). Correlation between rainfall and

landslides. Proc. 27th I.G.C., Moscow. Bull. IAEG., 32, 49-54.

Canuti P., Garzonio C.A., Rodolfi G., Vannocci P. (1985). Stabilità dei

versanti nell'area rappresentativa di Montespertoli (Firenze). Carta di

attività delle forme e di densità dei fenomeni franosi. Tipografia

S.EL.CA. Firenze.

Capecchi F & Focardi P. (1988). Rainfall and landslides: research into a

critical precipitation coefficient in an area of Italy. Proc. 5th Symp. on

Landslides, Lausanne, 1131-1136.

Carrara A. (1983). A multivariate model for landslide hazard evaluation.

Mathematical Geology, 15, 403-426.

Carrara A. (1988). Drainage and divide networks derived from high-fidelity

digital terrain models. In: Chung C.F. (Ed.) Quantitative Analysis of

Mineral and Energy Resources. Reidel, Dordrecht, NATO-ASI Series,

581-597.

Carrara A. (1989). Landslide hazard mapping by statistical methods: a

"black-box" model approach. Proc. of the Workshop on Natural

Disasters in European-Mediterranean Countries, Perugia, CNR-US NFS,

427-445.

Carrara A., Guzzetti F. (Eds.) (1995), Geographical Information Systems in

Assessing Natural Hazards. Kluwer Academic Publisher, Dordrecht, The

Netherlands, 353 pp.

Carrara A. & Merenda L. (1974). Metodologia per un censimento degli

eventi franosi in Calabria. Geol. Appl. & Idrogeol., 9, 237-255.

Carrara A. & Merenda L. (1976). Landslide inventory in northern Calabria,

southern Italy. Geol. Soc. Am. Bull., 87, 1153-1162.

Carrara A., D’Elia B., Semenza E. (1985). Classificazione e nomenclatura dei

fenomeni franosi. Geol. Appl. Idrogeol., 20, 223-243.


B.III-74

Carrara A., Catalano E., Sorriso-Valvo M., Reali C., Ossi I. (1978). Digital

Terrain Analysis for land evaluation. Geol. Appl. e Idrogeol., 13, 69-

127.

Carrara A., Cardinali M., Detti R., Guzzetti F., Pasqui V. & Reichenbach P.

(1990). Geographical Information Systems and multivariate model in

landslide hazard evaluation. In: A. Cancelli (ed.) “Alps 90”. 6th Int.

Conf. & Field. Workshop on Landslides. Milano., 17-28.

Carrara A., Cardinali M., Detti R., Guzzetti F., Pasqui V., Reichenbach P.

(1991). GIS techniques and statistical models in evaluating landslide

hazard. Earth Surface Processes and Landsform, 16, 427-445.

Carrara A., Cardinali M., Guzzetti F. (1992). Uncertainty in assessing

landslide hazard and risk. ITC Journal, The Netherlands, 2, 172-183.

Carrara A., Cardinali M., Guzzetti F., Reichenbach P. (1995). GIS technology

in mapping landslide hazard. In: Carrara A., Guzzetti F. (Eds.),

Geographical Information Systems in Assessing Natural Hazards.

Kluwer Academic Publisher, Dordrecht, The Netherlands, 135-175.

Carrara A., Bitelli G., Carlà R. (1997). Comparison of techniques for

generating digital terrain models from contour lines. International

Journal Geographical Information System, 11, (in stampa).

Carson M.A. & Kirkby M.J. (1972). Hillslope form and process. Cambridge

University Press, Cambridge, 475 pp.

Casagli N. & Pini G. (1993). Analisi cinematica della stabilità di versanti

naturali e fronti di scavo in roccia. Atti 3° Convegno Nazionale dei

Giovani Ricercatori di Geologia Applicata. Potenza.

Casagli N. & Rinaldi M. (1994). Meccanismi di instabilità delle sponde

nell’alveo del Fiume Sieve (Toscana). Atti del IV Convegno dei Giovani

Ricercatori del Gruppo Nazionale Geologia Applicata. Riccione, 18-21

Ottobre, 1994. Tecnoprint, Bologna.

Casagli N., Pini G. & Tarchiani U. (1994) - Valutazione del rischio di frana

nella falesia di Talamone (GR). Atti del IV Convegno Nazionale dei

Giovani Ricercatori del Gruppo Geologia Applicata. Riccione, 18-21

Ottobre, 1994. Tecnoprint, Bologna.

Casagrande A. (1971). On liquefaction phenomena: report of a lecture.

Géotechnique, 21, 197-202.

Cascini L. & Versace P. (1986). Eventi pluviometrici e movimenti franosi.

Atti XVI Conv. Naz. di Geotecnica, Bologna, 3, 171-184.

Cascini L. & Versace P. (1988). Relationship between rainfall and landslide

in a gneissic cover. Proc. 5th Int. Symp. on Landslides, Lausanne, 1,

565-570.

Catenacci V. (1992). Il dissesto geologico e geoambientale in Italia dal

dopoguerra al 1990. Servizio Geologico Nazionale. Mem. Descr. Carta

Geologica d’Italia, 301pp.

Chandler R.J. (1984) - Recent european experience of landslides in over-

consolidated clays and soft rocks. Proc. 4th Int. Symp. on Landslides,

Toronto, 1, 61-78.

Chandler R.J. & Peiris T.A.(1989). Further extension to the Bishop &

Morgenstern stability charts. Ground Engineering, May 1989, 33-38.

Chandler R.J. & Skempton A.W. (1974). The design of permanent cutting

slopes in stiff fissured clays. Géotechnique, 24 (4), 457-466.

Chowdhury R.N. (1984). Recent developments in landslides studies:

probabilistic methods. Proc. 4th Int. Symp. on Landslides, Toronto, 1,

209-228.


B.III-75

Chowdhury R.N., Flentje, P.N. (1998). A landslide database for landslide

hazard assessment. Proc. 2nd Int. Conf. on Environmental

Management. Feb.10-13. Wollongong, Australia. Sivakumar, M.,

Chowdhury, R.N. (Eds.), Elsevier, London,1229-1239.

Chung C.H., Fabbri A.G. (1995). Multivariate regression analysis for

landslide hazard zonation. In: Carrara A., Guzzetti F. (Eds.),



Chung C.H., Fabbri A.G. (1999). Probabilistic prediction models for landslide

hazard mapping. Photogrammetric Engineering and Remote Sensing,

65 (12), 1389-1399.

Clerici A. & Dall’Olio N. (1995). La realizzazione di una carta della stabilità

potenziale dei versanti mediante tecniche di analisi statistica

multivariata e un Sistema d’Informazione Geografica. Geologia Tecnica

& Ambientale, 4, 49-57.

CNR-GNDCI & Regione Emilia Romagna (1993). Atlante dei centri abitati

instabili dell’Emilia Romagna. Inquadramento generale. CNR, Roma, 66

pp.

Cooke R.U. & Doornkamp J.C. (1974). Geomorphology in environmental

management, an introduction. Claredon Press, Oxford, 413pp.

Corominas J. (1996). The angle of reach as a mobility index for small and

large landslides. Canadian Geotechnical Journal, 33, 260-271.

Corominas J., Weiss E.E.J., Van Steijn H., Moya J. (1994) - The use of

dating techniques to assess landslide frequency, exemplified by case

studies form European countries. In: Casale R., Fantechi R. &

Flageollet J.C. (1994) “Temporal Occurrence and Forecasting of

Landslides in the European Community”. Programme EPOCH. Final

Report, 1, 71-94.

Cotecchia V. (1978). Evoluzione dei versanti, fenomeni franosi e loro

controllo (P.F. "Conservazione del suolo": S.P."Fenomeni franosi").

Mem.Soc.Geol.It., 19, 29-51.

Cotecchia V. (1978). Systematic reconnaissance mapping and registration

of slope movements. IAEG Bull., 17, 5-37.

Cotecchia V., Lenti V., Salvemini A. & Spilitoro G. (1986). Reactivation of

the large Buoninvente slide by the Irpinia earthquake of 23 Nov. 1980.

Proc. Int. Symp. on Engineering Geology Problems in Seismic Area,

Bari, Geol. Appl. Idrogeol., 21 (4), 217-243.

Crespellani T., Nardi R. & Simoncini C. (1988). La liquefazione del terreno in

condizioni sismiche. Zanichelli, Bologna, 185 pp.

Crozier M.J. (1984). Field assessment of slope instability. In: Brunsden &

Prior (Eds.) Slope Instability, John Wiley & Sons Ltd., Chichester, chp.

4, 103-142.

Crozier M.J. (1986). Landslides: Causes, Consequences and Environment.

Croom Helm Pub., London.

Cruden D.M. (1991). A simple definition of a landslide. IAEG Bull., 43, 27-

29.

Cruden D.M. (1997). Estimating the risk from landslide historical data. In:

Cruden D.M. & Fell R. (Eds.) Landslide Risk Assessment. Proc. Int.

Workshop on Landslide Risk Assessment, Honolulu, 19-21 Feb. 1997,

Balkema, Rotterdam, 177-184.

Cruden D.M. & Varnes D.J. (1996). Landslides Types and Processes. In:

Turner A.K. & Schuster R.L. (Eds.) Landslides: Investigation and


B.III-76

Mitigation. Transportation Research Board Special Report 247. National

Academy Press, WA, 36-75.

Cruden D.M. & Fell D.J. (1997). Landslide risk assessment. IUSG Working

Group on Landslides, Committee on Risk Assessment, Workshop,

Honolulu 19-21 Feb. 1997, Balkema, 371 pp.

Cruden, D.M. (1997). Estimating the risks from landslides using historical

data; in “Landslide Risk Assessment”, Cruden D.M., Fell R. (Eds.),


Dai F.C., Lee C.F. (2001). Frequency-volume relation and prediction of

rainfall-induced landslides. Engineering Geology, 59 (3/4), 253-266.

Dai F.C., Lee C.F., Ngai Y.Y. (2002). Landslide risk assessment and

management:an overview. Engineering Geology, 64 (1), 65-87.

Davies T.R.H. (1982). Spreading of rock avalanche debris by mechanical

fluidization. Rock Mechanics, 15, 9-24.

DeGraff J.V. (1985). Using isopleth maps of landslides deposits as a tool in

timber sale planning. Bull. Am. Ass. of Eng. Geologists, 22, 445-453.

DeGraff J.V.& Agard S.S. (1984). Defining geologic hazards for natural

resources management using tree-ring analysis. Environmental

Geology and Water Sciences, 6 (3), 147-155.

DeGraff J.V. & Canuti P. (1988). Using isopleth mapping to evaluate

landslide activity in relation to agricultural practices. IAEG Bull., 38,

61-71.

D’Elia B., Esu F., Pellegrino A. & Pescatore T.S. (1985). Some effects on

natural slope stability induced by 1980 Italian earthquakes. Proc. 11th

ICSMFE, San Francisco, 4, 1943-1949.

Delaunay J. (1981). Carte de France des zones vulnérables a des

glissements, écroulements, affaissements et effrondrements de terrain.

Bureau des Recherches Géologiques et Minières. 81 SGN 567 GEG, 23

pp.

Delmonaco G., Margottini C., Trocciola A. (1998). The hydroclimatic sceario

of the Tiber river basin. In: Casale R. Pedroli G.B. and Samuels P.

(Eds.) Hydrological and hydrogeological risks. Proc. of the 1st Ribamod

Workshop, Delft, 13-15 Feb. 1997. EUR 18019 EN, 195-210.

Delmonaco G., Leoni G., Margottini C., Puglisi C., Spizzichino D. (2001).

Methodological approaches applied to debris flow susceptibility and

hazard assessment of geological formations of the Vezza River basin.

TEMRAP - The European Multi-hazard Risk Assessment Project, Final

Report, (in stampa).

Del Prete M., Giaccari E., Trisorio-Liuzzi G. (1992). Rischio da frane

intermittenti a cinematica lenta nelle aree montuose e collinari

urbanizzate della Basilicata. Pubbl. n 841-GNDCI, 84 pp.

Descourdes F. & Zimmermann T.H. (1987). Three-dimensional dynamic

calculation of rockfalls. 5th Int. Congr. Rock Mechanics, Montreal (CA),

337-342.

Dietrich E.W., Reiss R., Hsu M.L., Montgomery D.R. (1995). A process-

based model for colluvial soil depth and shallow landsliding using

digital elevation data. Hydrological Process, 9, 383-400.

Dikau R., Brunsden D., Schrott L., Ibsen M.L. (1996). Landslide recognition.

Identification, movements and causes. Wiley, Chichester, England, 251

pp.

Dikau R., Cavallin A., Jager S. (1996). Databases and GIS for landslide

research in Europe. Geomorphology, 15 (3/4), 227-239.


B.III-77

DRM-Délégation aux Risques Majeurs (1985). Catalogue de mesures de

prévention, mouvements de terrains. Plan d’Exposition aux risques.

Rapport administratif et technique provisoire. Premier Ministre. 443 pp.

DRM-Délégation aux Risques Majeurs (1985). Mise en œuvre des Plan

d’Exposition aux Risques naturels prévisibles. Plan d’Exposition aux

risques. Rapport administratif et technique provisoire. Premier Ministre.

DRM- Délégation aux Risques Majeurs (1987). Clauses réglementaires -

Fiches informatives. Mouvements de terrain. Plan d'Exposition aux

risques. Ministère de l'Environnement. Direction de l'Eau et de la

Prévention des Pollutions et des Risques. La Documentation Française.

119pp.

DRM- Délégation aux Risques Majeurs (1987). Mesures de prévention.

Mouvements de terrain. Plan d'Exposition aux risques. Ministère de

l'Environnement. Direction de l'Eau et de la Prévention des Pollutions et

des Risques. La Documentation Française. 529pp.

DRM-Délégation aux Risques Majeurs (1988). Evaluation de la vulnerabilite.

Plan d’Exposition aux risques. Ministére de l’Environnement. Direction

de l’Eau et de la Prévention des Pollutions et des Risques. La

Documentation Française. 112 pp.

DRM-Délégation aux Risques Majeurs (1990). Les études préliminares à la

cartographie réglementaire des risques naturels majeurs. Secrétariat

d’Etat auprés du Premier ministre chargé de l’Environnement et de la

Prévention des Risques technologiques et naturels majeurs. La

Documentation Française. 143 pp.

Dunne T. (1991). Stochastic aspects of the relations between climate,

hydrology and landform evolution. Transaction Japanese

Geomorphological Union, 12, 1-24.

Edil T.B. & Shultz M.N. (1983) - Landslide hazard potential determination

along a shoreline segment. Eng. Geology, 19, 159-177.

Einstein H.H. (1988). Special lecture: landslide risk assessment procedure.

Proc. 5th Int. Symp. On Landslides, Lausanne, 2, 1075-1090.

Einstein H.H. (1997). Landslide risk – systematic approaches to assessment

ad management. In: Cruden, D.M., Fell, R. (Eds.), Landslide Risk

Assessment. Proc. Int. Workshop on Landslide Risk Assessment,

Honolulu, 19-21 February 1997, Balkema, Rotterdam, 25-50.

Esu F. (1977). Behaviour of slopes in structurally complex formations. Int.

Symp. on the Geotechnics of Structurally Complex Formations, Capri 2,

292-304.

Esu F. (ed.) (1991). Frane costiere. Università La Sapienza, Roma. CNR-

GNDCI, Pubblicazione Speciale.

Evans S.G. (1997). Fatal landslides and landslide risk in Canada. In: Cruden

D.M. & Fell R. (Eds.) Landslide Risk Assessment. Proc. Int. Workshop

on Landslide Risk Assessment, Honolulu, 19-21 Feb. 1997, Balkema,

Rotterdam, 185-196.

Evans S.G. & Hungr O. (1993). The assessment of rockfall hazard at the

base of talus slopes. Can. Geotech. J., 30, 620-636.

Falcetta J.L. (1985). Etude cinematique et dynamique de chutes de blocs

rocheaux. These, INSA, Lyon.

Fell R. (1994). Landslide risk assessment and acceptable risk. Can.

Geotechn. J., 31 (2), 261-272.


B.III-78

Fell R., Chapman T.G. & Maguire P.K. (1991). A model for prediction of

piezometric levels. In: R.J. Chandler (ed.) "Slope Stability

Engineering", ICE, London. 37-42.

Fell R., Mostyn G., O’Keeffe L., Maguire P. (1988). Assessment of the

probability of rain induced landsliding. 5th Australia-New Zealand

Conference on Geomechanics, pp.72-77.

Fell R., Finlay P.J., Mostyn, G.R. (1996). Framework for assessing the

probability of sliding of cut slopes. Proc. 7th Int. Symp. on Landslides,

Trondheim. Balkema, Rotterdam, The Netherlands, 1, 201-208.

Fell R., Walker B.F., Finlay P.J. (1996). Estimating the probability of

landsliding. Proc. 7th Australia New Zealand Conf. on Geomechanics,

Adelaide. Institution of Engineers Australia, Canberra, 304-311.

Fell R., Hartford, D. (1997). Landslide Risk Management. In: Landslide Risk

Assessment, Cruden D.M., Fell R. (Eds.), Balkema, Rotterdam, pp.51-

110.

Fenti V., Silvano S., Spagna V. (1979). Methodological proposal for an

engineering geomorphological map. Forecasting rock-falls in the Alps.

IAEG Bull., 19, 134-138.

Finlay P.J., Fell R., Maguire P.K. (1997). The relationship between the

probability of landslide occurrence and rainfall. Canadian Geotechnical

Journal 34 (6), 811-824.

Flageollet J.C. (1994). The time dimension in the mapping of earth

movements. In: Casale R., Fantechi R. & Flageollet J.C. (1994)

“Temporal Occurrence and Forecasting of Landslides in the European

Community”. Programme EPOCH. Final Report, 1, 7-20

Flentje P.V., Chowdhury R.N. (1999). Quantitative Landslide Hazard

Assessment in an Urban Area. Proc. 8th Australia New Zealand Conf. on

Geomechanics. Vitharana N. (Ed.), Hobart, Tasmania. Institution of

Engineers, Australia.

Focardi P. (1982). Considerazioni cinematiche sul percorso di massi

provenienti da frane di crollo. Geologia Tecnica, 4, 13-23.

Fookes P.G., Dale S.G., Land J.M. (1991). Some observations on a

comparative aerial photography interpretation of a landslipped area.

Quarterly Journal of Engineering Geology, 24, 249-265.

Fukuzono T. (1985). Proc. 5th Int. Conf. & Field Workshop on Landslides,

Tokio, 145-150.

Genevois R. & Tecca P.R. (1987). Analisi probabilistica della stabilità dei

versanti : applicazione per la realizzazione di una carta della

pericolosità nella media valle del Fiume Tammaro (BN). Mem. Soc.

Geol. It., 37 (1), 157-170.

Genevois R., Romeo R.W., & Scarascia Mugnozza G.M. (1987). Un approccio

probabilistico all’analisi di stabilità di versanti in roccia. Geologica

Romana, 26, 262-286.

Giani G.P. (1992). Potenzialità dei metodi di analisi nella previsione del

moto di caduta massi lungo versante. 4° Ciclo Conf. Meccanica e

Ingegneria delle Rocce, MIR, Politecnico di Torino, 11.1-11.12.

Glade T. (1998). Establishing the frequency and magnitude of landslide-

triggering rainstorm events in New Zealand. Evironmental Geology, 35,

2-3.

GNGFG (1987). Cartografia della pericolosità connessa ai fenomeni di

instabilità dei versanti. A cura di Carrara A., Carton A., Dramis F.,

Panizza M. & Prestininzi A. Boll. Soc. Geol. It., 106, 199-221.


B.III-79

Godefroy P. & Humbert M. (1983). La cartographie des risques naturales

liés aux movements de terrain et aux séismes. Hydrogéologie-Géologie

de l’Ingénieur, 2, 69-90.

Goodman R.E. (1976). Methods of Geological Engineering in Discontinuous

Rocks. West Publ. Co., St. Paul (USA), 472 pp.

Goodman R.E. (1980). Introduction to Rock Mechanics. John Wiley & Sons

Ltd., New York, 562 pp.

Goodman R.E & Bray J.W. (1976). Toppling of rock slopes. Proc. Speciality

Conf. on Rock Engineering for Foundations & Slopes. ASCE, Boulder

(Colorado), 2, 201-234.

Govi G. (1977). Photo interpretation and mapping of landslides triggered by

the Friuli earthquake. IAEG Bull., 15, 67-72.

Govi M. & Sorzana P.F. (1977). Effetti geologico del territorio: frane. In: B.

Martinis (ed.), “Studio Geologico dell’area maggiormente colpita dal

terremoto friulano del 1976”. Progetto Finalizzato Geodinamica. Rivista

Italiana di Paleontologia e Stratigrafia, 83 (2), 329-368.

GSEGWP - Geological Society Engineering Group Working Party (1972). The

preparation of maps and plans in terms of Engineering Geology.

Q.J.Engng Geol., 5, 295-382.

Guerricchio A. & MelidoroG. (1979). Fenomeni franosi e neotettonici nelle

argille grigio-azzurre calabriane di Pisticci (Lucania). Geol. Appl. E

Idrogeol., 14, 105-138.

Guida D., Guida M., Iaccarino G., Lambiase S., Metacalf G., Salzano G.,

Vallario A., Vecchio V., Zicari G. (1979). Proposta per l'elaborazione di

cartografia tematica inerente alla dinamica dei versanti. Mem. Soc.

Geol It., 19, 170-198.

Gupta R.P., Joshi B.C. (1989). Landslide hazard zoning using the GIS

approach – a case study from the Ramganga catchment, Himalayas.

Engineering Geology, 28, 119-131.

Govi M. & Sorzana P.F. (1980) - Landslide susceptibility as a function of

critical rainfall amount in Piedmont basins (NW Italia). Studia

Geomorphologica Carpatho-Balcanica, 14, 43-61.

Gumbel E.J. (1967) - Statistics of extremes. Columbia University Press, New

York.

Gutemberg B. & Richter C.F. (1954). Seismicity of the Earth and associated

phenomena. Her Pub. Co.

Guzzetti F., Cardinali M. (1990). Landslide inventory map of the Umbria

Region, Central Italy. In: Cancelli, A. (Ed.) ALPS 90, 6th Int. Conf. and

Field Workshop on Landslides, Milano, 273-284.

Guzzetti F., Cardinali M., Reichenbach P. (1994). The AVI Project: A

bibliographical and archive inventory of landslides and floods in Italy.

Environmental Management, 18 (4), 531-555.

Guzzetti F., Cardinali M., Reichenbach P. (1996). The influence of structural

setting and lithology on landslide type and pattern. Environmental and

Engineering Geology, 2 (4), 623-633.

Guzzetti F., Carrara A., Cardinali M., Reichenbach P. (1999). Landslide

hazard evaluation: a review of current techniques and their application

in a multi-scale study, Central Italy. Geomorphology, 31, 181-216.

Haneberg W. (1991). Observation and analysis of pore pressure fluctuations

in a thin colluvial landslide complex near Cincinnati, Ohio. Engineering

Geology, 31,159-184.


B.III-80

Hansen A. (1984). Landslide hazard analysis. In: Brunsden D., Prior D.B.

(Eds.), Slope Instability. Wiley, New York, 523-602.

Hansen A., Franks C.A.M., Kirk P.A., Brimicombe A.J., Tung F. (1995).

Application of GIS to hazard assessment, with particular reference to

landslides in Hong Kong. In: Carrara A., Guzzetti F. (Eds.),



Harr M.E. (1987). Reliability based design in civil engineering. McGraw Hill

Book Co., New York.

Hartlén J. & Viberg L. (1988). General Report: Evaluation of landslide

hazard. Proc. 5th Int. Symp. On Landslides, Lausanne, 2, 1037-1058.

Heim A. (1932). Bergstruz und Menschenleben. Fretz und Wasmuth, Zurich,

218 pp.

Ho K., Leroi E., Roberts B. (2000). Keynote lecture: quantitative risk

assessment: application, myths and future direction. Proc. Int. Conf.

on Geotechnical and Geological Engineering, GEOENG 2000,

Melbourne, Australia, 1, Technomic, Lancaster, 236-312.

Hoek E. & Bray J.W. (1981). Rock Slope Engineering. Institution of Mining

and Metallurgy, London, 357 pp.

Hollingsworth R. & Kovacs G.S. (1981). Soil slumps and debris flows:

prediction and protection. Bull. Am. Ass. of Eng. Geologists, 18 (1), 17-

28.

Horlick-Jones T., Amendola A., Casale R. (Eds.) (1995). Natural risk and

civil protection. Commission of the European Communities, E&FN Spon,

London, 554 pp.

Howard A.D., 1994. A detachment-limited model of drainage basin

evolution. Water Resources Research, 30 (7), 2261-2285.

Hsü K. (1975). Catastrophic debris stream (sturzstorm) generated by

rockfalls. Bull. Geol. Soc. of America, 86, 129-140.

Hudson J.A. & Harrison J.P. (1994). Principles of Engineering Rock

Mechanics.

Humbert M. (1976). La cartographie en France des zones exposées a des

risques liés aux mouvements du sols. Cartes ZERMOS. Lnternational

Association Engineering Geology Bulletin, 16, 80-82.

Humbert M. (1977)(a). Risk mapping of areas exposed to movements of soil

and sub-soil: French “Zermos” maps. IAEG Bull., 16, 80-82.

Humbert M. (1977)(b). La cartographie ZERMOS. Modalités d’établissement

des cartes de zones exposées a des risques liés aux movements du sol

et du sous-sol. Bulletin Bureau Recherche Geologique et Mineraire, 3,

5-8.

Hungr O. (1981). Dynamics of rock avalanches and other types of mass

movements. PhD Thesis. University of Alberta.

Hungr O. (1995). A model for the runout analysis of rapid flow slides, debris

flows and avalanches. Canadian geotechnical Journal, 32, 610-623.

Hungr O., Yau H.W., Tse C.M., Cheng L.F., Hardingham A.D. (1999).

Natural slope hazard and risk assessment framework. In: Clarke B.

(Ed.), Urban ground Engineering. Thomas Telford, london, 332-353.

Hungr O. (2001). Analytical models for slides and flows. Kyoto

Hutchinson J.N. (1969). A reconsideration of the costal landslide at

Folkestone Warren, Kent. Géotechnique, 19(1), 6-38.

Hutchinson J.N. (1970) - A coastal mudflow on the London Clay cliffs at

Beltinge, North Kent. Géotechnique, 20, 412-438.


B.III-81

Hutchinson J.N. (1973). The response of London clay cliffs to differing rates

of toe erosion. Geol. Appl. & Idrogeol., 8, 221-239.

Hutchinson J.N. (1986). A sliding-consolidation model for flow slides.

Canadian Geotechnical Journal, 23, 115-126.

Hutchinson J.N. (1987). Mechanisms producing large displacements in

landslides on pre-existing shears. 1st Sino-British Geol. Conf., Taipei,

Memoir of the Geological Survey of China, 9, 175-200.

Hutchinson J.N. (1988). General report : morphological and geotechnical

parameters of landslides in relation to geology and hydrology. Proc. 5th

Int. Symp. On Landslides, Lausanne, 1, 3-35.

Hutchinson J.N. (1993). Some aspects of the morphological and geotechical

parameters of landslides, with examples drawn from Italy and

elsewhere. Atti 2° Conv. Naz. Giovani Ricercatori Geologia Applicata,

Viterbo, Geologica Romana.

Hutchinson J.N. (1995). Keynote paper : landslide hazard assessment. In

Bell (Ed.), Landslides. Balkema, Rotterdam, 1805-1841.

Hutchinson J.N. & Bhandari R.K. (1971). Undrained loading, a fundamental

mechanism of mudflows and other mass movements. Géotecnique, 21,

353-358.

Hutchinson J.N. & Chandler M.P. (1991). A preliminary hazard zonation of

the Undercliff of the Isle of Wight. In: Chandler R.J. (ed.): "Slope

Stability Engineering", Thomas Telford, London, 197-205.

Hutchinson J.N. & Gostelow T.P. (1976) - The development of an

abandoned cliff in London clay at Hadleigh, Essex. Phil. Trans. Roy.

Soc. London A283, 557-604.

IAEG - Commission on Engineering Geology Mapping (1981). Rock and soil

description and classification for engineering geological mapping. IAEG

Bull., 24, 235-274.

Ibsen M.L. & Brunsden D. (1996). The nature, use and problems of

historical archives for the temporal occurrence of landslides, with

specific reference to the south coast of Britain, Ventnor, Isle of Wight.

Geomorphology, 15, 241-258.

IDNHR, Advisory Committee (1987). Confronting Natural Disasters. An

International Decade for Natural Hazard reduction. National Academy

Press. WA, 60 pp.

IUGS Working Group on Landslides, Committee on Risk Assessment (1997).

Quantitative risk assessment for slopes and landslides: the state of the

art. In: Cruden D., Fell R. (Eds.), Landslide Risk Assessment. Balkema,

Rotterdam, 3-12.

Iverson R.M. & Major J.J. (1987) - Rainfall, groundwater flow and seasonal

movement at Minor Creek Landslide, NW California: physical

interpretation of empirical relations. Geol. Soc. Am. Bull., 99, 579-594.

Ives J.D. & Messerli B. (1981). Mountain Hazard Mapping in Nepal :

Introduction to an Applied Mountain Research Project. Mountain

Research and Development, 1, 223-230.

Jade S. & Sarkar S. (1993). Statistical models for slope stability

classification. Engineering Geology, 36, 91-98.

Jibson R.W. (1989). Debris flows in Southern Puerto Rico. Geol. Soc. Am.

Spec. Pub., 236, 1-13.

John K.W. (1968). Graphical stability analysis of slopes in jointed rock. J.

Soil Mech. Found. Div Proc. ASCE, 94, SM2, 497-526.


B.III-82

Keefer D.K. (1984). Landslides caused by earthquakes. Bull. Soc. Geol.

Am., 95, 406-421.

Keefer D.K., Wilson R.C., Mark R.K., Brabb E.E., Brown W.M., Ellen S.D.,

Harp F.L., Wieczoreck O.F., Alger C.S., Zatkin R.S. (1987). Real time

landslide warning during heavy rainfall. Science, 238, 921-925.

Kienholz H. (1978). Maps of Geomorphology and Natural Hazard of

Griendelwald, Switzerland, scale 1:10.000. Artic and Alpine research,

10, 169-184.

Kienholz H., Hafner H., Schneider G., Tamrakar R. (1983). Mountain

hazards mapping in Nepal’s Middle Mountains. Maps of land use and

geomorphic damages (Kathmandu-Kakani area). Mountain Research

and Development, 3 (3), 195-220.

Kienholz H., Schneider G., Bichsel M., Grunder M., Mool P. (1984). Mapping

of mountain hazard and slope stability. Mountain Research and

Development, 4, 247-266.

Kirsten H.A.D. & Moss A.S.E. (1985). Probability applied to slope design -

case histories. Rock Masses: Modeling of Underground openings.

Probability of failure. Fracture of intact rock (edited by C.H.

DOWDING). ASCE, New York, 106-121.

Klugman M.A. & Chung P. (1976). Slope-stability study of the regional

municipality of Ottawa-Carleton, Ontario, Canada. Ontario Geol.

Survey Misc. Paper, MP 68, 13pp.

Kockelman W.J. (1986). Some techniques for reducing landslide hazards.

Bull. Am. Ass. Eng. Geologists, 23 (1), 29-52.

Koirala N.P., Watkins, A.T. (1988). Bulk appraisal of slopes in Hong Kong.

In: Bonnard C. (Ed.) Landslides, Proc. 5th Int. Symp. on Landslides,

Lausanne, Switzerland. Balkema, Rotterdam, 2, 1181-1186.

Komar P.D. (ed.) (1983). Handbook of Coastal Processes and Erosion. CRC

Press, Florida.

Körner H.J. (1981). The energy line method in the mechanics of avalanches.

Journal of Glaciology, Vol. 26, No 94.

Leone F., Aste J.P., Leroi E. (1996). Vulnerability assessment of elements

exposed to mass-moving: working toward a better risk perception. In:

Senneset (Ed.), Landslides. Balkema, Rotterdam, 263-269.

Lerner D.N. (1986) - Predicting piezometric levels in steep slopes.

Groundwater in Engineering Geology. Geol. Soc. Eng. Group. Spec.

Pubb., 3, 327-333.

Leroueil S., Locat J., Vaunat J., Picarelli L., Lee H., Faure R. (1996).

Geotechnical characterisation, risk assessment and mitigation. In:

Maric B., Lisac L., Szavits-Nossan A. (Eds.), Geotechnical Hazards.


Lemos L., Skempton A.W. & Vaughan P.R. (1985). Earthquake loading of

shear surface in slopes. Proc. 11th ICSMFE, San Francisco, 4, 1955-

1958.

Leroi E. (1996). Landslide hazard – Risk maps at different scales:

objectives, tools and developments. In: Senneset (Ed.), Landslides.

Balkema, Rotterdam, 1, 35-52.

Li K.S. (1992). Some common mistakes in probabilistic analysis of slopes.

Proc. 6th Int. Symp. on Landslides, Christchurch, 1, 475-480.

Li Tianchi (1983). A mathematical model for predicting the extent of a

major rockfall. Z.Geomorph., 27, 473-482.


B.III-83

LPC - Laboratoire des Ponts et Chaussées (1978) - Eboulements et chutes

de pierres sur les routes. Méthode de Cartographie. Group d’Etudes des

Falaises (GEF). Laboratoire Central des Ponts et Chaussées. Rapport de

Recherche No.80, 63pp.

Lucini P. (1969) - Un metodo grafico per la valutazione della franosità.

Mem. Note Ist. geol. Appl. , Napoli, 2, 1-14.

Lumb, P. (1975). Slope failures in Hong Kong. Quarterly Journal of


MacKay C.H. (1997). Management of rock slopes on the Canadian Pacific

Highway. In: Cruden D.M., Fell R. (Eds.) Landslide Risk Assessment,

Balkema, 271-276.

Maione U. & Moisello U. (1981). Appunti di idrologia. La Goliardica Pavese,

2^ Edizione, 251 pp.

Mahr T. & Malgot (1978) -Zoning Maps for regional and urban development

based on slope stability. Proc. 3rd Int. Congr. IAEG, Sec.I, 1, 124-137.

Major G., Ross-Brown D. & Kim H.J. (1978) - A general probabilistic analysis

for three-dimensional wedge failures. Proc. 19th U.S. Rock Mech.

Symp, Mackay School of Mines, Nevada, 45-56.

Malgot J., Baliak F., Cabalova D., Mahr T., Nemcock A. (1973) - Mapa

svahovych deformacii Handlovskej kotliny. A. Záklandá mapa; B.Mapa

ingeniersko-geologickeho rajonovania.

Mark R.K. (1992). Map of debris flow probability, San Mateo County,

California, scale 1:62.500. US Geological Survey Miscellaneous

Investigation Map, I-1257-M.

Mark R.K. & Ellen S.D. (1995). Statistical and simulation models for

mapping debris-flows hazard. In: Carrara A., Guzzetti F. (Eds.),



Markland J.T. (1972). A useful technique for estimating the stability of rock

slopes when the rigid wedge sliding type of failure is expected.

Imperial College Rock Mechanics Research Report, 19.

Margottini C. & Fantucci R. (1993). Dendrogeomorphology in landslide

analysis: state of art. RT/AMB/93/20, ENEA, Roma, 22 pp.

Matheson G.D. (1983). Rock stability assessment in preliminary site

investigations – Graphycal Methods. Transport and Road Research

Laboratory Report, 1039, 30 pp.

Matheson G.D. (1989). The collection and use of field discontinuity data in

rock slope design. Q. J. Eng. Geol., 22, 19-30.

Matichard Y. & Pouget P. (1988) - Pluviométrie et comportament de

versants instables. Proc. 5th Int. Symp. on Landslides, Lausanne, 1,

725-728.

McMahon B.K. (1975). Probability of failure and expected volume of failure

in high slopes. Proc. 2nd Australia-New Zealand Conf. Geomechanics,

Brisbane, 308-317.

Meherota G.S., Dharmaraju R., Kanungo D.P. (1994). Landslide hazard

zonation - a tool for environmental development and protection of hilly

terrain. In: Man and Mountain 94, primo convegno internazionale per

la protezione e lo sviluppo dell'ambiente montano, 101-113.

Mejìa-Navarro M., Wohl E.E., Oaks S.D. (1994). Geological hazards,

vulnerability and risk assessment using GIS: model for Glenwood

Springs, Colorado. Geomorphology, 10, 331-354.


B.III-84

Meijerink A.M.J. (1988). Data acquisition and data capture through terrain

mapping unit. ITC Journal, 1, 23-44.

Meneroud J.P. (1978) - Cartographie des risques dans les Alpes-Maritimes

(France). Proc. 3rd Cong. IAEG, Sec.I, 2, 98-107.

Montgomery D.R., Wright R.H., Booth T. (1991). Debris flow hazard

mitigation for colluvium-filled swales. Bull. Am. Ass. of Eng. Geologists,

28 (3), 303-323.

Montgomery D.R. & Dietrich W.E. (1994). A physically based model for the

topographic control of shallow landsliding. Water Resource Research,

30 (4), 1153-1171.

Moon A.T., Olds R.J., Wilson R.A., Burman, B.C. (1992). Debris flow zoning

at Montrose, Victoria. In: Bell D.H. (Ed.) Landslides. Proc. 6th Int.

Symp. on Landslides, Christchurch, New Zealand. Balkema, Rotterdam,

2, 1015-1022.

Moon A., Robertson M., Davies, W. (1996). Quantifying rockfall risk using a

probabilistic toppling failure model. In: Senneset (Ed.), Landslides.

Balkema, Rotterdam.

Morgan G.C., Rawlings G.E., Sobkowicz J.C. (1992). Evaluating total risk to

communities from large debris flows. Geotechnique and natural hazard.

BiTech. Publishers, Vancouver B.C., 225-236.

Morgenstern N.R. (1985). Geotechnical aspects of environmental control.

Proc. 11th ICSMFE, San Francisco, 1, 155-186.

Morgestern N.R. (1997). Toward landslide risk assessment in practice. In:

Cruden D, Fell R. (Eds.), Landslide Risk Assessment. Balkema,

Rotterdam, 15-23.

Moser m. & Hohensinn f. (1983) - Geotechnical aspects of soil slips in alpine

regions. Engineering Geology, 19, 185-211.

Mostyn G.R., Fell R. (1997). Quantitative and semiquantitative estimation of

the probability of landsliding. In: Cruden D, Fell R. (Eds.), Landslide

Risk Assessment. Balkema, Rotterdam, 297-315.

Mulder H.F.H.M. (1991). Assessment of landslide hazard. Profschrift ter

Verkrijging van Graad van Doctor an de Rijkuniversiteit te Utrecht,

University of Utrecht, 150 pp.

Murk B.W., Skinner B.J., Porter S.C. (1997). Dangerous Earth. An

Introduction to Geological Hazards. Wiley, New York, 300 pp.

Nardi R., puccinelli A., D'Amato Avanzi G. & Trivellini M. (1987). Valutazione

del rischio da frana in Garfagnana e nella Media Valle del Serchio

(Lucca). 2): Carta geologica e carta della franosità degli elementi

"Sillico", "Castelnuovo Garfagnana", "Cascio", "Castelvecchio Pascoli",

"Gallicano", "Barga", "Fornaci di Barga" e "Ghivizzano" (scala

1:10.000). Boll. Soc. Geol. It., 106, 819-832.

Neeley M.K. & Rice R.M. (1990). Estimating risk of debris slides after timber

harvest in northwestern California. Bull. Am. Ass. of Eng. Geologists,

27 (3), 281-289.

NERC-National Environment Research Council (1975). Flood studies report,

Vol 1.

Neuland H. (1976). A prediction model of landslips. Catena, 3, 215-230.

Newmark N.W. (1965). Effects of earthquakes on dams and embankments.

Géotechnique, 25, 4.

Nicoletti P.G., Sorriso-Valvo M. (1991). Geomorphic controls of the shape

and mobility of rock avalanches. Geol. Soc. of America Bull., 103 (10),

1366-1373.


B.III-85

Nieto A.S. (1989). Mechanical models and geological observations: closing

the prediction gap. Proc. of the Workshop on Natural Disasters in

European-Mediterranean Countries, Perugia, CNR-US NFS, 145-164.

Nilsen T.H. & Brabb E.E. (1977). Slope stability studies in the San Francisco

bay region, California. Geological Society of America, Reviews in


Nilsen T.H., Wright R.H., Vlasic C., Spangle W.E. (1979). Relative slope

stability and land-use planning in the San Francisco Bay region,

California. US Geological Survey Professional Paper 944, 104 pp.

Okimura T. & Kawatani T. (1987). Mapping of the potential surface-failure

sites on granite slopes. In: Gardiner E. (Ed.), International

Geomorphology 1986, Part I. Wiley, Chichester, 121-138.

Okunishi K., Okumura, T. (1987). Groundwater models for mountain slopes.

In: Anderson M.G., Richards K.S. (Eds.) Slope Stability. Wiley, 265-

285.

Oliver G. & Renet J.P. (1976). Essai de cartographie des risques liés à des

mouvements de terrain dans la région de Saint-Martin-de-Belleville.

Bull. Liason Lab. P. et Ch., spécial, mars 1976, 40-55.

Ollier C.D. (1977). Terrain classification: methods, applications and

principles. In: J.R. HAILS (ed.) “Applied Geomprphology”, Elsevier,

Amsterdam, 277-371.

O'Loughlin E.M. (1986). Prediction of surface saturation zones in natural

catchments by topographic analysis. Water Resources Research, 22

(5), 794-804.

Olshansky R. (1990). Landslide hazard in the United States. Case studies in

planning and policy development. Garland Publishing, New York, 178

pp.

Omura H., Hicks D. (1992). Probability of landslides in hill country. In:

Landslides. Proc. 6th Int. Symp. on Landslides, Christchurch, New

Zealand. Balkema, Rotterdam.

Onofri R. & Candian C. (1979). Indagine sui limiti di massima invasione dei

blocchi rocciosi franati durante il sisma del Friuli del 1976.

Considerazioni sulle opere di difesa. Reg. Aut. friuli Venezia Giulia,

Cluet, Trieste, 1-42.

Osman A.M. & Thorne C.R. (1988). Riverbank stability analysis. Part I:

Theory. Journal of the Hydraulics Division, American Society of Civil

Engineers, 114, 125-150.

Paiola A. (1978). Movimenti franosi in Friuli. comportamento dei corpi che

cadono su di un pendio e calcolo del limite di espandimento potenziale.

Tecnica Italiana, 6.

Panizza M. (1988). Geomorfologia Applicata. La Nuova Italia Scientifica.

Papani G. & Tellini C. (1983) - Metodo elementare per elaborare

uniformemente carte della stabilità potenziale dei terreni. Studio della

parte media della Valle Tresinaro. Ateneo Parmense. Acta Naturalia, 9

(2).

Paronuzzi P. (1989). Probabilistic approach for design optimization of

rockfall protective barriers. Q.J. Engineering Geology, 22, 175-183.

Pasquero M. (1987). Dinamica della caduta massi rocciosi nello studio della

stabilità dei versanti. Tesi di Laurea, Politecnico di Torino.

Pellegrino A., Guerricchio A., Lazzari S., Nora B. & Valentini G. (1993). La

previsione delle frane ed i piani di emergenza. CNR-GNDCI. Rapporto

interno.


B.III-86

Perla R., Cheng T.T., McClung D.M. (1980). Rockslides and avalanches:

Basic principles and perspectives in the realm of civil and mining

operations. In: Rockslides and avalanches, Vol. 2, 1-92, (Voight B.,

ed.), Elsevier.

Perrot A. (1988). Cartographie des risques de glissements en Lorraine.

Proc. 5th Int. Symp. on Landslides, Lausanne, 2, 1217-1222.

Pike R.J. (1988). The geometric signature: quantifying landslide-terrain

types from digital elevation models. Mathematical Geology, 20 (5),

491-511.

Piteau D.R. & Clayton R. (1977). Discussion on paper : “Computerised

design of rock slopes using interactive graphics for the input and

output of geometrical data” of Cundall P.A., Voegele M.D. & Fairhurst

C. Proc. 16th Symp. on Rock Mechanics. University of Minnesota. ASCE,

62-63.

Piteau D.R. & Peckover F.L. (1978). Egineering of Rock Slopes. In: Turner

A.K. & Krizek R.J. (Eds.) Landslides analysis and control.

Transportation Research Board Special Report 176. National Academy

of Sciences 218-225.

Polemio M. & Petrucci O. (2000). Rainfall as a landslide triggering factor: an

overview of recent international research. In: Bromhead E., Dixon N. &

Ibsen M.L. (Eds.) Landslides in research, theory and practice. Proc. 8th

Int. Symp. on Landslides, Cardiff, Thomas Telford, London, 2000,

1219-1226.

Pomeroy J.S. (1979). Map showing landslides and areas susceptible to

sliding in Beaver County, Pennsylvania. US Geological Survey

Miscellaneous Investigation Map I-1160.

Premchitt J., Brand E.W., Chen, P.Y.M. (1994). Rain-induced landslides in

Hong Kong 1972-1992. Asia Engineer, June, 43-51.

Priest S.D. & Brown E.T. (1983) - Probabilistic analysis of rock slopes.

Trans. Inst. Min. Metall., A92(1), A1-A12.

Provincia di Modena & GNDCI U.O. 2.9 (1994). Proposta di una carta del

rischio da frana per il centro abitato di Sestola (Appennino modenese).

CNR-GNDCI – Linea 2 “Previsione e Prevenzione di eventi franosi a

grande rischio” – Programma Speciale SCAI. 37 pp.

Provincia di Modena & GNDCI U.O. 2.9 (1994). Proposta di una carta del

rischio da frana per il centro abitato di Lama Mocogno (Appennino

modenese). CNR-GNDCI – Linea 2 “Previsione e Prevenzione di eventi

franosi a grande rischio” – Programma Speciale SCAI. 46 pp.

Radbruch-Hall D.H. & Crowther K.C. (1973). Map showing areas of

estimated relative amounts of landslides in California. U.S. Geol.

Survey Misc. Inv. Map, MF-771.

Radbruch-Hall D.H. & Varnes D.J. (1976). Landslides: causes and effect.

IAEG Bull., 14, 205-216.

Radbruch-Hall D.H., Colton R.B., Davies W.E., Skipp B.A., Lucchitta I., &

Varnes D.J. (1976) - Preliminary landslide overview map of the

Conterminous United States. U.S. Geol. Survey Misc. Field Studies

Map, MF-771.

Raetzo H., Lateltin O., Bollinger D., Tripet J.P. (2002). Hazard assessment

in Switzerland – Codes of Practice for mass movements. Bull. Eng.

Geol. Env., 61, 263-268.

Ragozin A.L. & Tikhvinsky O. (2000). Landslide Hazard, Vulnerability and

Risk Assessment. In: Bromhead E., Dixon N. & Ibsen M.L. (Eds.)


B.III-87

Landslides in research, theory and practice. Proc. 8th Int. Symp. on

Landslides, Cardiff, Thomas Telford, London, 2000, 1257-1262.

Rennolls K., Carnell R. & Tee V. (1980). A descriptive model of the

relationships between rainfall and soil water table. Journal of

Hydrology, 47, 103-114.

Rib H.T. & Liang T. (1978). Recognition and identification. In: Schuster R.L.

& Krizek R.J. (Eds.), Landslides analysis and control. Washington

Transportation Research Board, Special Report 176. National Academy

of Sciences, WA, 34-80.

Ritchie A.M. (1963). Evaluation of rockfall and its control. Highway Research

Record, 17, 13-28.

Roberds W.J. (1990). Methods for developing defensible subjective

probability assessments. Proceedings of the Transportation Research

Board, No. 1288, National Research Council, Washington DC, 183-190.

Romana M. (1985) - New adjustment ratings for application of Bieniawski

classification to slopes. Int. Symp. on the Role of Rock Mechanics.

Zacatecas. 49-53.

Roth R.A. (1983). Factors affecting landslide suceptibility in San Mateo

County, California. IAEG, 20 (4), 353-372.

Sangrey D.A., Harrop-Williams W., Klaiber J.A. (1984) - Predicting

groundwater response to precipitation. J. Geotech. Eng.ing, ASCE,

110(7), 957-975.

Sarma S.K. (1979). Stability analysis of embankments and slopes. Proc.

ASCE, 105, GT5, 1511-1524.

Sassa K. (1988). Special lecture: Geotechnical model for the motion of

landslides. Proc. 5th Int. Symp. on Landslides, Lausanne, 1, 37-55.

Sassa K. (1992). Access to the dynamic of landslides during earthquakes by

a new cyclic loading high-speed ring apparatus. Proc. 6th Int. Symp. on

Landslides, Christchurch (New Zealand), Balkema, 3, 1919-1937.

Sassa K. (1993). Landslide volume - apparent friction relationship in the

case of rapid loading on alluvial deposits. Landslide News, 6, 16-19.

Scavia C., Barla G. & Vai L. (1988). Analisi di tipo probabilistico. Atti dei cicli

di conferenze “Meccanica e Ingegneria delle Rocce”. Politecnico di

Torino, 12, 1-27.

Scheidegger A.E. (1973). On the prediction of the reach and velocity of

catastrophic landslides. Rock Mechanics, 5, 231-236.

Scheidegger A.E. (1994). Hazards: singularities in geomorphic systems.


Schuster R.L. (1995). Keynote paper: recent advances in slope stabilisation.

In: Bell (Ed.) Landslides. Balkema, Rotterdam, 1715-1745.

Schuster R.L. (1996). Socio-economic sisnificance of landslides. In: Turner

A.K. & Schuster R.L. (Eds.) Landslides: Investigation and Mitigation.

Transportation Research Board Special Report 247. National Academy

Press, WA, 12-35.

Schuster R.L., Fleming R.W. (1986). Economic losses and fatalities due to

landslides. Bulletin of American Association Engineering Geologists, 23

(1), 11-28.

Schuster R.L. & Krizek R.J. (1978). Landslides Analysis and Control.

Washington Transportation Research Board, Special report 176.

National Academy of Sciences, WA, 234 pp.


B.III-88

Schoeneich P. (1991) - La datation des glissements de terrain. Proc. VI Int.

Symp. on Landslides, Christchurch (New Zealand), 1992, Balkema, 1,

205-212.

Seed H.B. (1968). Landslides during earthquake due to soil liquefaction.

Terzaghi lecture, J. Soil Mech. Found. Div., ASCE, 94, SM5.

Seed H.B. (1975). Earthquake effects on soil foundation systems. In: Fang

H.Y. Foundation engineering Handbook, 2nd ed., 1991. Van Nostrand

Reinhold, New York.

Seed H.B. & Idriss I.M. (1967). Liquefaction of saturated sands during cyclic

loading. Proc. ASCE, 92, SM6, 69-84.

Seeley M.W. & West D.O. (1990). Approach to geologic hazard zoning for

regional planning, Inyo National Forest, California and Nevada. Bull.

American Association of Eng. Geologists, 27 (1), 11-28.

Skempton A.W. & Delory F.A. (1957) - Stability of natural slopes in London

Clay. Proc. 4th Int. Conf. Soil Mech., London, 2, 378-381.

Skempton A.W., Leadbeater A.D. & Chandler R.J. (1989) - The Mam Tor

landslide, North Derbyshire. Phil. Trans. Royal Society London, A 329,

503-547.

Siddle H.J., Jones D.B., Payne, H.R. (1991). Development of a methodology

for landslip potential mapping in the Rhondda Valley. In: Chandler R.L.

(Ed.) Slope Stability, Isle of Wight. Thomas Telford, p.137-148.

Soeters R., van Westen C.J. (1996). Slope instability, recognition, analysis

and zonation. In: Turner A.K. & Schuster R.L. (Eds.) Landslides:

Investigation and Mitigation. Transportation Research Board Special

Report 247. National Academy Press, WA, 129-177.

Soeters R., Rengers N., van Westen C.J. (1996). Remote sensing and

Geographical Information Systems as applied to mountain hazard

analysis and environmental monitoring. 8th Thematic Conference

Geology Remore Sensing (ERIM), Denver 2, 1389-1402.

Sorriso-Valvo M., Tansi C., Antronico L. (1996). Relazione tra frane, forme

del rilievo e strutture tettoniche nella media valle del Fiume Crati

(Calabria). Geogr. Fis. Dinam. Quat., 19, 107-117.

Sousa J., Voight B. (1991). Continuum simulation of flow failures.

Geotechnique, 41, 515-538.

Speight J.G. (1977). Landform pattern description from aerial photographs.

Photogrammetry, 32, 161-182.

Starkel L. (1966) - The palaeogeography of Mid and Eastern Europe during

the last cold stage and Western European comparisons.Phil. Trans.

Royal Society, London, B280, 351-372.

Starosolzky O. & Melder O.M. (1989). Hydrology of disasters. World

Meteorological Organisation Technical Conference, Geneva, November

1988. James and James, London, 319 pp.

Starr C. (1969). Social benefit versus technological risk; what is our society

willing to pay for safety? Science, 165, 1232-1238.

Stevenson P.C. (1977). An empirical method for the evaluation of the

relative landslip risk. IAEG Bull., 16, 69-72.

Stout M.L. (1977). Radiocarbon dating of landslides in Southern California.

California Geology, 99-105.

Sunamura T. (1992). Geomorphology of rocky coasts. John Wiley & Sons,

302 pp.

Takahashi T. (1981). Debris flow. Ann. Rev. Fluid Mech. 1981, 13, 57-77.


B.III-89

Talobre J. (1957). La Mécanique des Roches appliquée aux Travaux Publics.

Dunod, Paris, 444 pp.

Terlien M.T.J., van Westen C.J., van Asch Th.W.J. (1995). Deterministic

modelling in GIS-based landslide hazard assessment. In: Carrara A.,

Guzzetti F. (Eds.), Geographical Information Systems in Assessing

Natural Hazards. Kluwer Academic Publisher, Dordrecht, The

Netherlands, 57-77.

Terzaghi K. (1950). Mechanism of Landslides, Geol. Soc. America, Eng.

Geol. "Berkey" Volume, 83-123.

Terzaghi K. & Peck R.B. (1948). Soil Mechanics in Engineering Practice. 1st

ed; J. Wiley & Sons, New York.

Thorne C.R. (1982). Processes and mechanisms of river bank erosion. In:

R.D. Hey, J.C. Bathurst and C.R. Thorne (ed.) Gravel-bed Rivers,

Wiley, Chichester, 227-271.

Thorne C.R. & Tovey N.K. (1981). Stability of composite river banks. Earth

Surface Processes and Landforms, 6, 469-484.

Tobutt D.C. & Richards E.A. (1979). The reliability of earth slopes. Int. J. of

Numerical & Analytical Methods in Geomechanics, 3 (4), 323-354.

Thornthwaite C.W. (1948) - An approach towards a rational classification of

climate.Geogr. Rev. American Geogr. Society, 55, 94.

Trustrum N.A. & De Rose R.C. (1988). Soil depth-age relationship of

landslides on deforested hillslopes, Taranaki, New Zealand.


Turner A.K. & Schuster R.L. (Eds.) (1995). Landslides, investigation and

mitigation. Transportation Research Board Special Report 247. National

Academy Press, WA, 673 pp.

Uno T., Arai H. & Shibeyama M. (1977) - Models for predicting ground water

level. 11th ICSMFE, 3, 495-598.

USGS (1982). Goals and tasks of the landslide part of a ground failure

hazard reduction program. U.S. Geological Survey Circular 880, 48pp.

Valera J.E. & Donovan W.C. (1977). Soil Liquefaction Procedures. A Review.

J. Geol. Eng. Div. ASCE, 103.

Valentini G. (1967). Un modello statistico nello studio della franosità nel

quadro morfologico, geologico e geotecnico della media valle del

F.Fortore. Geologia Applicata e Idrogeologia, 2, 197-227.

van Gassen W. & Cruden D.M. (1989). Momentum transfer and friction in

the debris of rock avalanches. Canadian Geotechnical Journal, 26, 623-

628.

van Westen C.J. (1993). Application of Geographical Information System to

landslide hazard zonation. ITC publication no 15, ITC, Enschede, The

Netherlands, 245 pp.

van Westen C.J. (1994). GIS in landslide hazard zonation: a review with

examples from the Colombian Andes. In: Price M.F. & Heywood D.I.

(Eds.), Taylor and Francis, London, 135-165.

van Westen C.J., Rengers N., Terlien M.T.J., Soeters R. (1997). Prediction of

the occurrence of slope instability phenomena through GIS-based

hazard zonation. Geologische Rundschau, 86, 404-414.

Varnes D.J. (1978). Slope movements, type and processes. In: Schuster

R.L. & Krizek R.J. (Eds.), Landslides analysis and control. Washington

Transportation Research Board, Special Report 176. National Academy

of Sciences, WA, 11-33.


B.III-90

Varnes D.J. & IAEG Commission on Landslides (1984). Landslides Hazard

Zonation – a review of principles and practice. UNESCO, Paris, 63 pp.

Vecchia O. (1978) - A simple terrain indexfor the stability of hillsides or

scarps. In: J.D. Geddes (ed.) “Large Ground Movements and

Structures”. J.Wiley & Sons, New York, 446-461.

Verstappen H.T. (1983). Applied Geomorphology: Geomorphological Survey

for Environmental Development. Elsevier, Amsterdam.

Viberg L. (1984). Landslide risk mapping in soft clay in Scandinavia and

Canada. Proc. 4th Int. Symp. on Landslides, Toronto, 1, 325-348.

Voellmy A. (1955). Über die Zerstörungskraft von Lawinen. Sweiz

Bauzeitung, 73, 159-165, 212-217, 246-249, 280-285.

Voight B. (1988). Material science law applied to time forecast of slope

failure. Landslide News, 3, 8-11.

Wadge G. (1988). The potential of GIS modelling of gravity flows and slope

instabilities. Int. Journal of Geographical Information systems 2, 143-

152.

Ward T.S. (1976) - Factor of safety approach to landslide potential

delineation. PhD Dissertation, Department of Civil engineering,

Colorado State University, Fort Collins, Colorado (USA).

Wieczorek G.F (1984). Preparing a detailed landslide-inventory map for

hazard evaluation and reduction. Bull. IAEG, 21 (3), 337-342.

Wieczorek G.F. (1987). Effect of rainfall intensity and duration on debris

flows in central Santa Cruz Mountains, California. In: Costa J.E.,

Wieczorek G.F. (Eds.) Debris flows/Avalanches: process, Recognition

and Mitigation. Reviews in Engineering Geology, vol. VII. Geological

Society of America, Boulder, CO, 93-104.

Wieczorek G.F. & Sarmiento J. (1988) - Rainfall, piezometric levels and

debris flows near La Honda, California, in storms between 1975 and

1983. In: “Landslides, floods and marine effects of the storm of Jan 3-

5, 1982, in the S.Francisco Bay region, California”. USGS Prof. Papers.,

1434, 43-63.

Wieczorek G.F., Gori P.L., Jager S., Kappel W.M., Negussey D. (1996).

Assessment and management of landslide hazards near Tully Valley

landslide, Syracuse, New York, USA. Proc. 7th Int. Symp. On

Landslides, Trondheim, June 1996, 1, 411-416.

Whitman R.V. (1984). Evaluating calculated risk in geotechnical

engineering. ASCE Journal of Geotechnical Engineering, 110(2); 145-

188.

Wilson R.C., Wieczorek G.F. (1995). Rainfall threshold for the initiation of

debris flows at La Honda, California. Environmental and Engineering

Geoscience, 1 (1), 11-27.

Wong H.N., Ho K.K.S., Chan Y.C. (1997). Assessment of consequence of

landslides. In: Cruden D, Fell R. (Eds.), Landslide Risk Assessment.


WP/WLI-International Geotechnical Societies’ UNESCO Working Party on

World Landslide Inventory (1990). A suggested method for reporting a

landslide. IAEG Bull., 41, 5-12.


World Landslide Inventory (1991). A suggested method for a landslide

summary. IAEG Bull., 43, 101-110.


B.III-91


World Landslide Inventory (1993). A suggested method for describing

the activity of a landslide. IAEG Bull., 47, 53-57.


World Landslide Inventory (1994). Multilingual glossary for landslides.

Wright R.H. & Nilsen T.H. (1974). Isopleth map of landslide deposits,

Southern San Francisco Bay Region, California. US Geol. Surv. Misc.

Field Studies Map, MF-550.

Wright R.H., Campbell R.H., Nilsen T.H. (1974). Preparation and use of

isopleth maps of landslide deposits. Geological Society of America.

Geology, 2, 483-485.

Wu T.H., Tang W.H., Einstein H.H. (1996). Landslide hazard and risk

assessment. In: Turner A.K. & Schuster R.L. (Eds.) Landslides:

Investigation and Mitigation. Transportation Research Board Special

Report 247. National Academy Press, WA, 106-120.

Yin K.L. & Yan T.Z. (1988). Statistical prediction model for slope instability

of metamorphosed rocks. Proc. 5th Int. Symp. on Landslides, Lausanne,

2, 1269-1272.

Yong R.N., Alonso E., Tabba M.M., Fransham P.B. (1977). Application of risk

analysis to the prediction of slope instability. Canadian Geotechnical

Journal, 14 (4), 540-543.

Yoshimatsu H. (1991). Study of the mechanics of debris flow and its

simulation model. Journal of Japan Landslide Society, 28-2.

Zika et alii (1988) - Proc. 5th Int. Symp. on Landslides, Lausanne, 1, 3-36

Zimmerman M., Bichsel M., Kienholz H. (1986). Mountain hazards mapping

in the Khumbu Himal, Nepal, with prototype map, scale 1:50.000.

Mountain Research and Development, 6 (1), 29-40.


B.III-92

13 Appendix:Operational Standards for Risk Assessmentaimed at Spatial Planning

13.1 Minimum standard (simplified model) for hazardmapping aimed at a legal directive

The simplified model for landslide hazard mapping should follow, implicitly,

the definition of landslide hazard:

Probability that a landslide, with a given typology, intensity and return time,

may occur in a specified area.

An exhaustive landslide hazard assessment, as consequence of the above

postulates, considers the fulfilment of the following issues:

• Typological prediction: landslide type or types that may occur;

• Spatial prediction: where a landslide may occur;

• Intensity prediction: landslide dimension or magnitude (area, volume,

velocity, energy);

• Temporal prediction: when a landslide may occur;

• Evolution prediction: landslide run-out, retrogression limits, lateral

expansion.

13.1.1 Various methodologies related to the 3 assumed scalesof analysis in the light of a potential harmonisation ofhazard maps, based on a multi-hazard perspective

The methods that can be adopted to identify landslide hazard are strictly

depending on the scales of investigation and mapping, extension of the

study area, as well as on availability, typology and format of data.

Generally, three different approaches can be used according to scales of

analysis and representation of landslide hazard maps:

o Susceptibility approach: usually developed at regional/national scales (>

1:50.000), where areas prone to landslide occurrence are depicted in

discrete and qualitative categories, without any specification on landslide

probability of occurrence and potential causes of the events. This

approach is generally based on low but homogeneous data on landslide

preparatory factors such as a general inventory of landslides, geology,

geomorphology, land-use, climatic setting.

o Hazard approach: developed at local scale (1:2.000 – 1:10.000), where

landslide probability/return time is provided. Legends may describe

landslide types, landslide intensity, landslide activity, actual and/or

potential spatial extent of phenomena, potential triggering causes. This

approach need a large amount of data (i.e. geology, lithology, structural

setting, historical information, accurate landslide inventory maps) and

multi-discipline tasks.

o Site Engineering approach: developed at site scale (1:100 – 1:1.000).

Maps and legends describe carefully landslide or potentially unstable

areas, mostly through the calculation of the Safety Factor of slopes.


B.III-93

They need very detailed data, especially geotechnical parameters, for

implementing 2D or 3D slope stability modelling.

Figure 1: List of landslide hazard methodological approaches

Qualitativ

e

Hazard

Geomorpholo

gical

l

Index or

Parameter

Combination

or

overlay of

Logical

analytical

methods

Quantitati

ve

Bivariate

Multivariate

Deterministi

c

h

Probabilisticapproaches

Statistical

analysis

Geotechnical

engineering

approach

Neural

Network

l i


B.III-94

According to landslide hazard zoning scales and spatial planning scales, the following table has been developed (Table 1). MAP SCALE (SPATIAL PLANNING)

MAP SCALE (LANDSLIDE HAZARD)

CHARACTERISTICS / USE

DATA ACQUISITION

MAPPING PROCEDURES

HAZARD METHODOLOGY

LEGEND

Site-specific scale (< 1:1,000)

Absolute Hazard (classes, SF) related to specific triggering factors. Implementation and design landslide hazard and risk mitigation projects.

Slope stability modeling parameters (i.e. stratigraphy, geotechnical properties, hydrological data, seismic input).

Deterministic approaches (i.e. geotechnical modeling).

Hazard classes expressed as failure probability (affected area, return time, intensity) or SF range.

Local scale (< 1:5,000)

Local scale (1:1,000 - 1:10,000)

Absolute hazard and/or relative hazard according to landslide types. Large engineering structures, roads, urban areas, soil protection (detailed studies).

Data collection should support the production of detailed multi-temporal landslide distribution maps and provide information about the various parameters required in the adopted methodology.

Deterministic approaches (i.e. geotechnical modeling coupled with hydrological analysis). Statistical modeling. Geomorphological approach. Indexed maps. Hazard maps when geomorphic, geologic conditions and landslide types, are homogeneous (1).

Relative hazard as qualitative scales that depict spatial and/or temporal probability of occurrence (i.e. low, medium, high, very high). Rarely, (1) hazard as landslide probability (affected area, return time, intensity) or SF range.

Local scale (1:5,000 - 1:50,000)

Regional scale (1:10,000 - 1:50,000)

Relative hazard or susceptibility maps (medium-low detail). Large projects (feasibility studies) or regional developments.

Detailed data of individual factors (i.e. landslide inventory, lithology, structural setting), mostly derived by remote sensing techniques and literature (homogeneous terrain units).

Statistical modeling. Geomorphological approach based on a detailed landslide inventory. Indexed maps. Hazard maps (1).

Relative hazard as qualitative scales that depict spatial and/or temporal probability of occurrence (i.e. low, medium, high, very high).

Regional/ Strategic scale (> 1:50,000)

National scale (> 1:50,000)

General inventory of landslide areas or susceptibility maps with low level of detail. National policy makers and the general public.

National summary of regional landslide inventories and map products.

Susceptibility maps derived from geomorphological approach. Indexed maps. Descriptive statistical analysis.

Relative hazard as qualitative scales that depict spatial probability of occurrence according to expert judgment (i.e. low, medium, high, very high).

Table 1: Summary of landslide hazard mapping vs. scales


B.III-95

Landslide Hazard Mapping – Site Specific Scale (< 1:1.000)

The site specific scale provide absolute hazard classes and variable safety factor related to specific triggering factors, such as rainfall, seismicity, human-induced.

All data are related to slope stability modelling parameters (i.e. stratigraphical setting, shear strength values, hydrological data, seismic input). Generally, geotechnical engineering approaches (i.e. deterministic and or probabilistic modelling) are implemented. Hazard classes (legends) are expressed as failure probability, that may not be referred to return time of landslides, or safety factor (SF) range.

The maps are used for the implementation and design of landslide hazard and risk mitigation projects (Fig. 2).

Figure 2: Landslide site specific analysis: from safety factor calculation to landslide mitigation strategies (example of Civita di Bagnoregio reinforcement works)

Landslide Hazard Mapping – Local Scale (1:1.000 – 1:10.000)

Generally, a relative hazard is provided in qualitative scales that depict spatial and/or temporal probability of occurrence (i.e. low, medium, high, very high).

Rarely, when the study area is homogeneous as geological, morphological, climatic setting and landslide types are mostly superficial, a hazard analysis is possible, expressed as landslide probability (affected area, return time, intensity) or safety factor range (Fig. 3).

According to data availability, qualitative approaches (i.e. geomorphological) and quantitative methods (i.e. geotechnical, statistical) can be adopted for analysis.

This scale of analysis is usually addressed for large engineering structures, roads, urban areas, soil protection (detailed studies).


B.III-96

Figure 3: Local scale analysis: example of landslide hazard analysis through a geotechnical approach (SF range) (Map 1) and a multivariate statistical analysis (relative hazard) (Map 2)

Source: Delmonaco et al. (2001, 2003).

Landslide Hazard Mapping – Regional Scale ( 1:10.000 – 1:50.000)

At regional scale, landslide relative hazard or susceptibility analysis can be carried out.

The investigation may cover quite large areas with medium-low data resolution.

Usually, data on individual factors are collected (i.e. landslide inventory, lithology, land use) mostly derived by remote sensing techniques and literature. The approaches can be different, mostly statistical and geomorphological.

A relative hazard is provided in qualitative scales that depict a spatial probability of occurrence mostly based on a subjective judgement of experts.

These maps are generally used for large projects (feasibility studies) or regional developments.

1

2


B.III-97

Figure 4: Regional scale analysis: example of landslide hazard analysis through a geomorphological approach (relative hazard) starting from aerial photo interpretation. Source: ESA, project SLAM 2, 2002.

Landslide Hazard Mapping – National Scale ( > 1:50.000)

At national scale a relative hazard is provided in qualitative scales that express a spatial probability of occurrence according to expert judgement. Another approach is to depict a general inventory on landslide areas.

The investigation usually covers very large areas with low-very low data resolution.

Usually, data on individual factors are collected (i.e. landslide inventory, lithology, land use) mostly derived by bibliography, and analysed through statistical descriptive or heuristic approaches.

A relative hazard is provided in qualitative scales that depict a spatial probability of occurrence mostly based on a subjective judgement of experts.

The maps are generally used for national policy makers and the general public.

Figure 5: National scale analysis: example of landslide susceptibility analysis; Source: USGS


B.III-98

13.2 Minimum standard (simplified model) for risk mapping aimed at spatial planning

13.2.1 Multi-risk assessment perspective as element of the Strategic Environmental Assessment

The main purpose of a multi-risk mapping is to put together in one map the various hazard-related information on a study area to provide a general scenario of the natural hazards of varying magnitude, frequency, area.

Many natural hazards can be caused by the same natural event (i.e. heavy rainfall inducing floods and fast-moving landslides), so that to depict a multiple hazard map is mainly possible for hazards that can be related to similar triggering mechanisms.

Apart from the actual capability to produce reliable multi-hazard maps, that are very rare in the scientific literature or, when existing, very general, the adoption of a multiple hazard strategy is fundamental for assessing integrated vulnerability and risk, that maybe represent the right key to solve the problem of multiple hazard and spatial planning. A multiple risk perspective, rather than a multi-hazard perspective, could be the proper way to cope with different potential hazards affecting a specified area, towards the integrated development planning process. Failure to consider all of the natural hazards in the development planning process and to provide for their reduction will result eventually in the loss of lives, bodily injuries, property damage, critical facility failures and disruption of important economic activities. Depending upon the size of the event, its location and its effects, the actual impact of the hazard can be catastrophic and disastrous.

As a general rule, considering hazard mapping related to land use and spatial planning, the approaches at the local level consist of general plans, zoning regulations, and subdivision regulations. Mapping, even at small scale (1:50.000), can be useful to a community in helping shape its general plan for future development. Major areas of potential instability can be identified as needing special investigation or, in some instances, designated for open space use. In extreme conditions, general plans may propose cluster development in which construction is limited to stable areas and unstable areas serve as open space attend to the development.

The creative use of geological hazard information in preparing general plans, however, depends on a staff has had training in the application of geological information to plan making. Recognition that there are often negative implications from the identification of landslide prone areas, in the form of decreased valuations, emphasizes the important support role that nationally accepted standard of practice have for staff at local level. Local zoning regulations stipulate, usually in great detail, how land can be used. Some communities have developed landslide matrices that are including in the zoning ordinance or as an adjunct to the ordinance.

These matrices correlate categories of land stability with permitted or recommended land uses; they reflect a certain level of risk that the community has accepted. In some cases, not only are the land uses


B.III-99

identified, but they may be tied to general building types. It is at the subdivision stage that the future pattern of ownership and land use is firmly established. It is at this stage that the community must demand the most detailed information about geological hazards.

The preparation of subdivision regulations that address geological hazards is not complicated – a more difficult task is to ensure that the regulations are properly administrated. In addition, elected officials have to be convinced of the need for such regulations, and there must be both an administrative process and a staff capable of implementing the regulations. Guidance and assistance, in the form of publications and effective outreach, should be provided to local governments as part of the national strategy outreach, so that they are better able to incorporate landslide mitigation provisions into their general plan, zoning regulation, and subdivision regulations.

13.2.2 Methodologies, functions and outputs A landslide risk map should report the expected losses, direct and indirect, due a specific landslide with given intensity, affecting a given area and having a specific probability of occurrence. Risk is thus the product of hazard and the capability of resistance of the various elements at risk vs. a landslide event (vulnerability).

Likely for hazard mapping, also landslide risk mapping is a very complex task, due to the difficulty of assessing landslide hazard in a rigorous way as well as the complex and still poorly development of landslide vulnerability. Consequently, the available outputs (landslide risk maps) are generally incomplete and sometimes misleading, especially in defining key terms (i.e. hazard, vulnerability, risk).

Likely for hazard, considering landslide vulnerability, the following table has been resumed (Table 2).


B.III-100

MAP SCALE (SPATIAL

PLANNING)

MAP SCALE (LANDSLIDE

VULNERABILITY)


DATA ACQUISITION

MAPPING PROCEDURES

VULNERABILITY METHODOLOGY

LEGEND


Individual element at risk, exposed to landslide. Implementation and design of specific measures for vulnerability reduction.

Data are related to all the characteristics of the exposed elements (i.e. typology, worth, potential damage) at the highest possible resolution.

Site detailed inventory of exposed elements.

Quantitative vulnerability classes (i.e. potential damage vs. landslide intensity expressed as worth or number) for each typology of element at risk (i.e. population, structures, economic activities).


Local scale (1:1,000 - 1:10,000)

Overview of homogeneous sectors (i.e. districts, villages, land use, main infrastructures) exposed to potential landslides. Implementation and design of specific measures for vulnerability reduction.

Data are related to all the characteristics of the exposed elements (i.e. typology, worth, potential damage) with resolution related to single or group of elements.

Inventory of exposed elements (i.e. type and characteristics).

Quantitative vulnerability classes (i.e. potential damage vs. landslide intensity expressed as worth or number) for each typology of element at risk (i.e. population, structures, economic activities)

Local scale (1:5,000 - 1:50,000)

Regional scale (1:10,000 - 1:50,000)

Overview of homogeneous sectors (i.e. districts, villages, land use, main infrastructures) exposed to potential landslides. Implementation of specific policies for vulnerability reduction.

Data are related to all the characteristics of the exposed elements (i.e. typology, worth) with resolution related to group of elements.

Inventory of exposed elements (i.e. type and characteristics). Vulnerability indicators.

Qualitative vulnerability classes for each typology of element at risk (i.e. population, structures, economic activities) as worth and number of exposed elements.



Overview of homogeneous sectors (i.e. districts, villages, land use, main infrastructures) exposed to potential landslides. Implementation of specific policies for vulnerability reduction.

Data are related to categories of the exposed elements (i.e. typology, worth) with low resolution.

Inventory of typology of exposed elements. Vulnerability indicators.

Qualitative vulnerability classes for each typology of element at risk (i.e. population, structures, economic activities) as worth and number of exposed elements.

Table 2: Summary of landslide vulnerability mapping vs. scales


B.III-101

Landslide Vulnerability Mapping – Site Specific Scale (< 1:1.000)

Provide individual element at risk, exposed to landslide.

Data are related to all the characteristics of the exposed elements (i.e. typology, worth, potential damage) at the highest possible resolution.

Legends may be expressed as quantitative vulnerability classes (i.e. potential damage vs. landslide intensity) for each typology of element at risk (e.g. population, structures and infrastructures, economic activities).

The maps are used for implementation and design of specific measures for vulnerability reduction.

Figure 6: Landslide vulnerability mapping at site scale undertaken in the archaeological site of the ancient Stabiae (Italy).

Source: ENEA, 2004.

Landslide Vulnerability Mapping – Local Scale (1:1.000 - 1:10.000)

Provide an overview of homogeneous sectors (e.g. districts, census sections, land use, main infrastructures) prone to potential landslides.

Data are related to all the characteristics of the exposed elements (i.e. typology, worth, potential damage) with resolution related to single or groups of elements.

Legends may be expressed as quantitative vulnerability classes (i.e. potential damage vs. landslide intensity) for each typology of element at risk (e.g. population, structures and infrastructures, economic activities).

The maps are used for implementation and design of specific measures for vulnerability reduction.

13.2.2.1

Figure 7: Landslide exposure and potential damage maps at local scale performed in the village of Craco (Italy). Source: ENEA, 2004.


B.III-102

Landslide Vulnerability Mapping – Regional Scale ( 1:10.000 – 1:50.000)

This approach provides an overview of homogeneous sectors (e.g. districts, census sections, land use, main infrastructures) prone to potential landslides.

Data are related to all the characteristics of the exposed elements (i.e. typology, worth) with resolution related to groups of elements. The inventory of the exposed elements is related to type and characteristics or vulnerability indicators. Legends are usually qualitative, defining vulnerability classes for each typology of element at risk (e.g. population, structures and infrastructures, economic activities) as worth and/or number of exposed elements.

The maps are used for addressing specific policies of vulnerability reduction.

Figure 8: Landslide vulnerability index map at regional scale applied to Cultural Heritage.

Source: Istituto Centrale del Restauro, 2001. Landslide Vulnerability Mapping – National Scale ( > 1:50.000)

Provide an overview of homogeneous areas (e.g. urban areas, land use) exposed to potential landslides.

Data are related to categories of the exposed elements (i.e. typology, worth) with low resolution. The inventory of the exposed elements is related to type and characteristics or vulnerability indicators.

Legends are usually qualitative, defining vulnerability classes for each typology of element at risk (e.g. population, structures and infrastructures, economic activities) as worth and/or number of exposed elements.


B.III-103

The maps are used for addressing general policies of vulnerability reduction.

Figure 9: Land use map as data base for vulnerability analysis at national scale.

Source: CORINE Land Cover, application to Saulx watershed, 2000. Landslide risk mapping according to the various scales are reported in Table 3. MAP SCALE (SPATIAL PLANNING)

MAP SCALE (LANDSLIDE RISK)


DATA ACQUISITION MAPPING PROCEDURES

RISK METHODOLOGY

LEGEND


Provide rigorous risk classes related to probabilistic landslide occurrence and potential damage. The maps are used for implementing and design landslide risk mitigation projects.

Data are related to hazard and vulnerability classes or values and their combination.

Quantitative analysis: rigorous assessment.

Quantitative risk classes expressed as worth or number of potential losses.


Local scale (1:1,000 - 1:10,000)

Provide absolute or relative risk. The maps are used for implementing and design landslide risk mitigation projects


Quantitative analysis: potential damage, specific risk.

Quantitative risk classes expressed as worth or number of potential losses.

Local scale (1:5,000 - 1:50,000)

Regional scale (1:10,000 - 1:50,000)

Provide relative risk. The maps are used for depicting landslide risk scenarios at regional levels.


Qualitative analysis: damage propensity or risk susceptibility.

Qualitative risk classes according to social and economic consequences.



Provide relative risk. The maps are used for depicting landslide risk scenarios at regional/national levels.


Qualitative analysis: damage propensity or risk susceptibility.

Qualitative risk classes according to social and economic consequences.

Table 3: Summary of landslide risk mapping vs. scales


B.III-104

Landslide Risk Mapping – Site Specific Scale (< 1:1.000)

At the highest resolution, this approach may provide rigorous risk classes related to probabilistic landslide occurrence and potential damage expressed as worth and/or number of potential losses.

Generally, landslide risk maps at site scale are simply reporting the potential damage of few elements at risk, namely structures or infrastructures according to a single landslide. In literature these maps are not available for urban scale.

The maps are used for implementation and design of specific measures for landslide risk mitigation.

Landslide Risk Mapping – Local Scale (1:1.000 - 1:10.000)

Provide an absolute or relative risk according to the resolution of hazard (absolute or relative). At the highest resolution, legends report potential damage or specific risk as worth and/or number of potential losses.

Usually, risk is expressed as qualitative classes according to social and economic consequences, simply by superimposition of landslide hazard/susceptibility maps with location of elements at risk.

The maps are used for implementation and design of specific measures for landslide risk mitigation.

Figure 10: Landslide risk mapping at local scale.

Source: Autorità di Bacino, Regione Calabria – Piano Stralcio.

Landslide Risk Mapping – Regional Scale ( 1:10.000 – 1:50.000)

Provide a relative risk depicting a damage propensity or risk susceptibility through the superimposition of landslide susceptibility maps with elements at risk. Legends are typically qualitative (e.g. low, medium, high risk) according to potential socio-economic loss. The maps are used for defining general scenarios of landslide risk.


B.III-105

Figure 11: Landslide risk map at regional scale.

Source: Plan de Prévention aux Risques, Municipality of Veurey-Voroize, 1999.

Landslide Risk Mapping – National Scale ( >1:50.000)

Provide a relative risk depicting a damage propensity or risk susceptibility through the superimposition of landslide susceptibility maps with elements at risk. Legends are typically qualitative (e.g. low, medium, high risk) according to potential socio-economic loss. The maps are used for defining general scenarios of landslide risk.

Figure 12: Landslide risk map at national scale.

Source: Plan de Prévention aux Risques, France, 1999.


B.III-106

13.3 Minimum Standard for Landslide Risk Maps Considering the above mentioned examples derived from landslide hazard/risk mapping state of the art and the capability to produce an operational standard in the light of a multiple risk analysis applied to spatial planning, as the main objective of ARMONIA Project, the following scales of analysis are suggested:

• Local scale: ≤ 1:10.000 • Regional scale: > 1:50.000

13.3.1 Local Scale mapping (≤ 1: 10.000) Hazard

Due to the objective difficulty to define rigorously all the parameters required in a landslide hazard analysis due to the large amount of high-resolution data (landslide type, affected area, intensity, return time, triggering mechanism, evolution), a landslide hazard map should, at least, provide the following minimum requirements:

o Landslide typology according to Varnes (1984) or Cruden & Varnes (1996) classifications

o Physical extension of existing landslides and/or potential landslides

Further information, if available, should be referred to: o Landslide state of activity (active, quiescent, inactive) and evolution o Intensity (volume, velocity, energy) o Landslide probability of occurrence

Landslide hazard maps may be depicted as follows: o Landslide absolute/relative hazard maps – HIGH STANDARD o Landslide relative hazard/susceptibility maps – MEDIUM STANDARD o Landslide inventory maps – MINIMUM STANDARD

Vulnerability

The analysis of vulnerability should take into account the following:

o Typology of potential elements at risk with their absolute location (map of elements at risk)

o Analysis of potential damage of the various elements at risk vs. landslide intensity.

The vulnerability of all the exposed elements is calculated, from 0 to 1, according to the potential landslide intensity, considering the main typologies of the elements at risk (population, land use, structures and infrastructures) following the examples derived from the French experience (DRM, 1990) – HIGH STANDARD

The vulnerability is simply calculated from 0 to 1 by overlapping the landslide area with the elements at risk (0 = no exposure; 1 = presence of the exposed element) – MINIMUM STANDARD


B.III-107

Risk

The analysis of risk should take into account the following: o Analysis of potential damage of the various elements at risk vs.

landslide hazard. The risk of all the exposed elements is calculated according to

landslide hazard (absolute hazard) and vulnerability of elements at risk following the examples derived from the French experience (DRM, 1990), as number of value of potential losses – HIGH STANDARD

The risk of all the exposed elements is calculated according to landslide hazard qualitative classes (i.e. low, medium, high) and vulnerability of elements at risk (0/1) by overlapping landslide hazard areas with the location of all the exposed elements, providing a qualitative risk assessment (i.e. low, medium, high, very high) (see Italian experience of the Law 267/98) – MEDIUM STANDARD

The risk of all the exposed elements is calculated according by simply overlapping landslide inventories maps/susceptibility maps with the location of all the exposed elements, providing a qualitative risk assessment (i.e. low, medium, high, very high) – MINIMUM STANDARD

Regional Scale mapping (> 1:50.000) Hazard

This scale of analysis is mainly based on medium-low quality data. The requirements for producing a landslide hazard map are the following:

o Landslide inventory map reporting, if possible, landslide types according to Varnes (1984) or Cruden & Varnes (1996) classifications

o Physical extension of existing landslides and/or potential landslides

Further information, if available, should be referred to: o Landslide state of activity (active, quiescent, inactive) and evolution o Intensity (volume, velocity, energy) o Landslide probability of occurrence

Landslide hazard maps may be depicted as follows: o Landslide relative hazard/susceptibility maps – HIGH STANDARD o Landslide inventory maps – MINIMUM STANDARD

Vulnerability

The analysis of vulnerability should take into account the following: o Typology of potential elements at risk with their absolute location

(map of elements at risk) o Analysis of potential damage of the various elements at risk vs.

landslide occurrence. The vulnerability of all the exposed elements is calculated,

from 0 to 1, according to the potential landslide occurrence, considering the main typologies of the elements at risk or groups of elements at risk or vulnerability indicators – HIGH STANDARD


B.III-108

The vulnerability is simply calculated from 0 to 1 by overlapping the landslide area with the elements at risk (0 = no exposure; 1 = presence of the exposed element) – MINIMUM STANDARD

Risk

The analysis of risk should take into account the following: o Analysis of potential damage of the various elements at risk vs.

landslide hazard. The risk of all the exposed elements is calculated according to

landslide hazard qualitative classes (i.e. low, medium, high) and vulnerability of elements at risk (0/1) by overlapping landslide hazard areas with the location of all the exposed elements, providing a qualitative risk assessment (i.e. low, medium, high, very high) – HIGH STANDARD

The risk of all the exposed elements is calculated according by simply overlapping landslide inventories maps/susceptibility maps with the location of all the exposed elements, providing a qualitative risk assessment (i.e. low, medium, high, very high) – MINIMUM STANDARD


B.IV-1

B.IV Forest Fires

Author: Andrea Camia, EC-JRC

1 Physical definition of Forest Fires ............................2

1.1 Typologies .................................................................... 21.2 Intensities, Severity, Magnitude....................................... 2

2 Hazard assessment..................................................4

2.1 Definition...................................................................... 42.2 Current methodologies for analysing and representation ofhazard with respect to temporal scales .................................... 52.3 Dynamical hazard – climate change effects ....................... 72.4 Problem of scale ............................................................ 72.5 Data availability – typology, format – GIS structure ........... 92.6 Examples of hazard maps and legends referred to assumedscales10

3 Element at risk and exposure................................. 20

3.1 Typology of elements ................................................... 20

4 Analysis of vulnerability ........................................ 21

4.1 Definition of vulnerability and/or consequence................. 214.2 Methodologies for assessment related to structural and non-structural elements at risk.................................................... 21

5 Analysis of risk...................................................... 22

5.1 Definition of risk .......................................................... 225.2 Methodologies for risk assessment ................................. 22

6 Risk management.................................................. 22

7 Glossary of all keywords........................................ 24

8 References ............................................................ 25

Appendix: Operational Standards for Risk Assessmentaimed at Spatial Planning........................................... 30

1. Minimum standard (simplified model) for hazard mappingaimed at a legal directive ..................................................... 301.1. Various methodologies related to the 3 assumed scales ofanalysis in the light of a potential harmonisation of hazardmaps, based on a multi-hazard perspective............................ 302. Minimum standard (simplified model) for risk mappingaimed at spatial planning ..................................................... 32


B.IV-2

1 Physical definition of Forest Fires

Fire is a self-sustaining chemical reaction that can release energy in theform of light and heat. Three main ingredients must be present for fire toexist: heat, oxygen and fuel (fire fundamentals triangle). This is a generaldefinition of fire as a physical phenomenon. Forest fires are combustionprocesses that occur in the forest or, more generally, in the wildland whichincludes not only forests but also other natural vegetation such asshrublands or pastures, in other words all the vegetated lands which are notagriculture. In fact in the literature forest fires are often referred to aswildland fire, normally meaning the same as forest fires. The fuel that isburned in forest fires is mainly made up by vegetative material (either deador live).

It is important to consider also the legal definition of forest fire, since therisk analysis must be ultimately done within a legal framework. The legaldefinition is different according to the country. Within the EuropeanCommunity, the Regulation (EC) No 2152/2003 (Forest Focus) ‘forest fire’ isa fire which breaks out and spreads on forest and other wooded land orwhich breaks out on other land and spreads to forest and other woodedland. The definition of ‘forest fire’ excludes: prescribed or controlledburning, usually with the aim of reducing or eliminating the quantity ofaccumulated fuel on the ground.

1.1 Typologies

Different phases of the combustion process can be identified. In thesimplest approach they are pre-ignition, ignition, combustion andextinction. These phases are continuously occurring during a forest fire, forwhich the flame front is moving in space always finding new unburned fuel.Three main typology of fires can be identified: ground fires, surface fires,crown fire.Ground fire is a fire that consumes the organic material beneath the surfacelitter, such as a peat fire. It normally burns without flame (smolderingcombustion), being the combustion occurring in scarce oxygen, just underto thick organic layer on the ground.A surface fire is a fire that burns loose debris on the surface, which includesdead branches, leaves, and low vegetation. Therefore surface fires spreadby flaming combustion through fuels at or near the surface (grass, shrubs,dead and down limbs, forest needles and leaf litter, or debris fromharvesting or land clearing).A crown fire is a fire that advances from top to top of trees or shrubs, moreor less independent of a surface fire. Crown fires are sometimes classed asrunning or dependent to distinguish the degree of independence from thesurface fire.

1.2 Intensities, Severity, Magnitude

The intensity of a fire can be expressed by the combustion rate, alsoreferred to as the reaction intensity, which is the rate of heat release, per


B.IV-3

unit area of the flaming fire front. Although the reaction intensity can beconsidered an indicator of the effective intensity of the physicalphenomenon, the standard fire behavior parameter used to identify itsmagnitude is the fireline intensity.

The fireline intensity is the product of the available heat of combustion perunit of ground and the rate of spread of the fire, interpreted as the heatreleased per unit of time for each unit length of the fire front. The units arekW per meter of fire front or kcal per meter per second.The fireline intensity is the fire behavior parameter directly related to thefire suppression activities and the fire effects on the ecosystems. The lengthof the flames (flame length) is a function of the fireline intensity.

Fireline intensity and the flame length are related to the heat felt by aperson standing next to the flames. The following table gives firesuppression interpretations of flame length and fireline intensity.

FlameLength

(m)

FirelineIntensity(kW/m)

Interpretation

Under 1.2 Under 350 Fires can generally be attacked at the heador flanks by persons using hand tools. Handline should hold the fire.

1.2-2.4 350-1730 Fires are too intense for direct attack on thehead by persons using hand tools. Hand linecannot be relied on to hold the fire.Equipment such as dozers, pumpers, andretardant aircraft can be effective.

2.4-3.4 1730-3460 Fires may present serious control problems --torching out, crowning, and spotting. Controlefforts at the fire head will probably beineffective.

Over 3.4 Over 3460 Crowning, spotting, and major fire runs areprobable. Control efforts at head of fire areineffective.

Table 1: Flame length and fireline intensity suppression interpretation.Source: Rothermel (1983)

Numerically, fireline intensity is derived as the product of the fuel heatcontent, the quantity of fuel consumed in the fire front, and the rate of firespread (Byram, 1959).

The widely used expression for the Byram’s fireline intensity is thefollowing:

I = Hwr

Where:

I = Fireline intensity [kW/m]H = Net low heat of combustion [kj/kg]w = Quantity of fuel burned in the active flame front [kg/m2]r = Linear rate of fire spread [m/sec].


B.IV-4

Therefore fireline intensity is a function of rate of spread and heat per unitarea, and it is directly related to flame length through the expression(Byram, 1959):

Fl = 0.45 I 0.46

Where Fl (flame length) is in feet and I (fireline intensity) in BTU/ft/sec.

The rate of spread can be generically defined as the relative activity of a firein extending its horizontal dimensions. It can be expressed as rate ofincrease of the total perimeter of the fire, as rate of forward spread of thefire front, or as rate of increase in area, depending on the intended use ofthe information. In the fireline intensity calculation it is intended as the rateof forward spread of the fire front in a given direction.

Fire severity is generally referred to as the degree to which a site has beenaltered or disrupted by fire. Loosely, can be considered a product of fireintensity and residence time, where residence time is the time required forthe flaming front of a fire to pass a stationary point at the surface of thefuel; In other words is the total length of time that the flaming front of thefire occupies one point. There are not standard quantitative indicationsadopted about fire severity.

2 Hazard assessment

2.1 Definition

Forest fires are natural hazard, although it must also be considered that inthe European context most forest fires are caused directly or indirectly byhuman activities. Therefore the triggering factors, the ignition sources offorest fires in Europe are in the large majority of cases of anthropogenicnature. Only a small percentage of fires are caused by lightings in drystorms or other even rarer events.When the fire origin is human, the cause can be deliberate (arson) oraccidental (negligence) the latter meaning connection to a human activitybut without any intention of causing the fire (e.g. accidents caused bypower lines, railways, works, bonfires, etc.).

If the causative factor meets the environmental conditions for ignition, thefire starts. The major environmental factors that can interact with theignition source affecting forest fire behaviour are fuels, weather andtopography, which together constitute the so called fire environmenttriangle. The changing state of each of such environmental components andtheir interaction with each other and with the fire itself determine thecharacteristics and behaviour of a fire at any given moment. Changes in firebehaviour in space and time occur in relation to changes in theenvironmental components. From the viewpoint of fire environmentchanging conditions, topography does not vary with time but it can varygreatly in space, the fuel component varies in both space and time, weatheris the most variable component, changing rapidly in both space and time.


B.IV-5

Also because of the specificities illustrated, in the forest fire relatedterminologies, fire hazard is not explicitly associated to the probability offire occurrence.In many English speaking countries (except the USA) fire hazard is ameasure of that part of the fire danger contributed by the fuels available forburning (worked out by their relative amount, type and condition,particularly their moisture content). In the USA fire hazard is normallyreferred to as a fuel complex, defined by volume, type, condition,arrangement, and location, that determines the degree of ease of ignitionand fire suppression difficulty (FAO, 1986, McPherson et al. 1990).

On the other hand, from the same terminology sources, the concept of firerisk is referred to as the probability of fire initiation due to the presence andactivity of a causative agent. Fire risk is considered an element of thebroader fire danger, meant as the resultant, often expressed as an index, ofboth constant and variable danger factors affecting the inception, spread,and difficulty of control of fires and the damage they may cause (FAO,1986).

A similar terminology has been adopted also in Europe, through the DELFIConcerted Action "Definition and Creation of a Common Knowledge Base forForest Fires", whose aim was to organize and disseminate existingknowledge on forest fires, aiming to bridge the gap between researchersand practitioners and which produced a multi-language vocabulary of forestfire terms.It should be also pointed out that in the forest fire domain there is not ageneralized agreement about the use of the terms hazard, risk and danger,and in the literatures many different interpretations can be found.

A summary of the more common current definitions is given in the Glossarychapter. In the context of ARMONIA project the need of harmonizing the firerisk terminology with the other natural hazard is quite important. Withinthis framework we propose to adopt a terminology which is closer to theother natural hazard vocabulary and which is also in line with some recentapproaches of EU research projects, such as INFLAME and SPREAD.

The risk of a given natural hazard is most often referred to as thecombination of the probability of occurrence of an event and itsconsequences.In this respect fire risk can be well be meant as a combination of theprobability of occurrence of a fire with a given intensity and the extent ofthe consequences of the fire impact.The consequences of the fire impact are due to the vulnerability of theecosystem and the value given to the natural resources affected (perceptionof the potential impact).

2.2 Current methodologies for analysing andrepresentation of hazard with respect to temporalscales


B.IV-6

Based on the temporal scale considered, both the assessment procedures ormethods, and the fire management objectives or context supported by theestimates of fire risk distribution are ultimately quite different.

Two temporal scales are commonly identified in fire risk estimation: short-term and long-term.

Short-term fire risk estimations refer to the most dynamic factors of fireignition or fire behaviour, mainly those based on the estimation ofvegetation moisture content (either dead or live fuels) and the effect ofmeteorological variables on fire behaviour.Therefore short term risk estimation requires daily or also hourlyinformation on fuel moisture content, weather variables as temperature,relative humidity, wind, and precipitation.This kind of estimation allows to organise the activity of fire pre-suppression, detection and suppression and update decisions according tochanges in the fire risk level.Therefore this temporal scale has a main practical use in the update of thelevel of alert and in the organisation of the fire fighters actions directly onthe flaming front.

Based on meteorological input data and physical, semi-physical or empiricalmodel calculations, Wildland Fire Danger Rating Systems provide ‘indirectvalues’ — numerical indices — at different temporal scales (e.g., daily,weekly, monthly) denoting the physical conditions that may lead to fireignition and support fire propagation. The results can be expressed as firedanger levels, ranging from ‘low’ to ‘very high’, and are commonly used inoperational wildland fire management (e.g., the Canadian Fire WeatherIndex [FWI] System (Van Wagner, 1987), the Russian Nesterov Index(Nesterov, 1949), or the U.S. National Fire Danger Rating System [NFDRS](Deeming at al. 1974; Deeming at al. 1977; Bradshaw, 1983; Burgan,1988). Today, fire danger levels are often turned into broad scale mapswith the help of Geographical Information Systems (GIS) showing the areaswith the different fire danger levels, and are distributed via the World WideWeb.

Long-term fire risk includes the fire risk that does not change, or changesvery slowly over time, in practical term the risk level determined by factorsthat can be considered, for the purpose of risk assessment, static along atleast a fire season.Therefore in the long term trends of fire risk the variables involved aremostly related to the structural factors that affect fire ignition andpropagation in a given site (Chuvieco, 1999).Examples of such factors can be fuel types, topography or climatic patterns.In general the long term temporal scale estimation provides information forthe wildfire defence plan and so for the distribution of structural protectionresources and the prevention activities.

Within ARMONIA the focus will be on the long term fire risk analysis. Thelong term which focus on the static components of fire risk, is normallyaddressed in the fire management planning context. Therefore the main


B.IV-7

issues dealt with are related to fire prevention (i.e. fire suppression andpost fire analysis are not considered).

To define the reference time frame for the analysis it must be pointed putthat forest fire occurrence is strictly related to the socio-economic contextwhich affects to anthropogenic causes of fires and which is continuouslyevolving, therefore significantly modifying the hazard conditions. The timeframe normally referred to in order to correctly represent the actual firehazard conditions is less then 15 years, i.e. historical fire data analyzed forassessing current fire hazard conditions should cover around 10 to 15 years

On the other hand, the assessed current “static” fire hazard conditions, canbe taken as such for a period of around 5 years, meaning that after thistime the assessment should be revised (e.g. the fuel conditions can changesubstantially due to vegetation dynamics).

2.3 Dynamical hazard – climate change effects

Some studies on the climatic warming effect on forest fire risk suggest ageneralized increases in fire frequency (Overpeck et al., 1990; IPCC 2002).According to Flannigan et al. (200), the universality of these results isquestionable because an individual fire is a result of the complex set ofinteractions that include ignition agents, fuel conditions, topography andweather including temperature, relative humidity, wind velocity and theamount and frequency of precipitation. Increasing temperature alone doesnot necessarily guarantee greater fire disturbance.

Flannigan et al. (2000) argue that, in addition to climatic influences on thefire regime other factors such as ignition agents, length of the fire season,vegetation characteristics and human activities such as fire managementpolicies and landscape fragmentation may greatly influence the fire regimein the next century. Ignition probabilities may increase in a warmer worlddue to increased cloud-to-ground lightning discharges with warming. Thefire season will start earlier and extend longer. An increase in fire activitymay be expected especially in terms of fire severity due to climaticwarming, increased frequency and severity of drought years, increasedclimatic variability and incidence of extreme climatic events

The important aspect of the impact of climate change on forest fires withrespect to the influence on vegetation is that fire may be more importantthan the direct effects of climate change with respect to species distribution,migration, substitution and extinction (Weber and Flannigan, 1997).


Although the risk of wildland fires changes in a continuous way both in timeand space, for practical purposes in the assessment of fire risk it is commonto distinguish different spatial scales.

With reference to the spatial scale, the global approach involves territoriesof millions square kilometres (Chuvieco et al. 2003), and the resulting maps


B.IV-8

of the global (continental or world wide) distribution of fire risk have scalesof the range of 1:1,000,000 or less.Fire risk assessment at this scale is mainly undertaken for establishinggeneral guidelines or strategic purposes and for enhancing international co-operation.On the other hand local scale is referred to areas extended from hundredsup to few thousands square kilometres, with related thematic maps of1:10,000 to 1:250,000 scale, addressing various fire management issues atregional or lower level.

The scale often referred to as “local” in the forest fire literature, includes the3 scales addressed in ARMONIA Project, which are the following: regional(<1:50,000), local1 (1:5,000- 1:50,000) and local2 (>1:5,000).

At these scales the use of the fire hazard information is linked to thefollowing general fire planners requirements:

• To plan fire prevention measures– Spatialize protection priorities– Define and locate prevention measures (i.e. firebreak, water

reservoirs etc..)– Set up rules for fire management and settlements in the

Wildland Urban Interface• To manage natural resources for risk mitigation

– Fuel management, prescribed fire– Defensible space management (settlements)– Forest management

More specifically, according to the different ARMINIA scales, the followingmanagement needs have been identified:

• Scale: > 1:5,000– design and locate prevention measures (firebreaks, water

reservoirs, look out points etc..)– management rules for individual settlements and specific

ecosystems (fuel management, forest management etc..)

• Scale: 1:5,000 – 1:50,000– typical scale for local fire management plans– spatialization of protection priorities– identification of prevention measure– management guidelines at landscape level

• Scale: < 1:50,000– scale for regional fire management plans– spatialization of general protection priorities– definition of protection strategies and allocation of protection

resources– general management guidelines

The approaches to fire hazard assessment and mapping change accordingto the spatial scale not only because of the different user needs, but also


B.IV-9

due to the variables that can be considered and their changing role inmodelling and representing the spatial distribution of fire hazard,.From one part because of the different explanation the variables canprovide to the spatial distribution of the wildfire phenomenon, but alsobecause of the different purposes of the different hazard assessmentperspectives and because of data availability at the different scales.

Considering for example the risk variables related to human activities, atsmaller scale a more important focus must be given to socio-economicalcontext, and their spatial distribution is often analysed using administrativeboundaries to define geographical units. On the other hand at larger scale itis easier to go into more detailed analysis considering for example thelocation of anthropogenic infrastructures, such as roads or railway, that canbe correlated with the spatial distribution of fire ignition sources.

2.5 Data availability – typology, format – GIS structure

To map fire hazard spatial information are needed about historical firesoccurred in the area and data layers related to the mentioned fireenvironmental triangle (topography, fuels, meteorology) and to theanthropogenic factors.

Sound historical data on fire occurrence are not always available and firelocation in Europe is mainly given with reference to an administrativepolygon (e.g. Commune). Thus the geographical unit of analysis is often theadministrative unit.

In some countries (e.g. Spain) fires are also located with geographicalcoordinates but with poor resolution (i.e. using a grid 10 km spaced).For limited areas, i.e. for some National Park, or only for major fire events,the fire perimeter are digitized and geo-referenced.

In some cases fire data may be sensitive data, so local authorities are notalways willing to make them available to the public. Around 10 years ofindividual fire events data may be required.

The basic environmental data layers that may be useful for fire hazardassessment are a Digital Elevation Model (DEM) for topography (from whichslope and aspect maps can be derived), a fuel type map for vegetation anda long term weather pattern or climatic classification map for meteorology.All these maps are normally in raster formats, and their use and typologydepend on the scale.

Socio-economic data layers are normally represented using statistics whichare referred to administrative units, therefore they can be polygons thatcorrespond to the administrative boundaries used in the statistics.

At larger scales the role of anthropogenic factors can be accounted for ormodeled using features representing infrastructures that are directly orindirectly linked to the wildfire phenomenon. For example the road or


B.IV-10

railway networks, the camping or barbeque areas, location of settlements inthe wildland urban interface areas and so on.

Human fire-related activities, such as recreation or arson, are very difficultto model anyway, and research efforts are still required in this direction.

The data layers mentioned can be further detailed according to the scaleconsidered and the specific environmental conditions.Quite in general, the minimum data required for fire hazard assessment andmapping in the 3 scales of spatial planning adopted in ARMONIA are thefollowing:

• Scale: > 1:5,000– DEM, fuel map, settlements, roads, weather patterns (not

spatialized)

• Scale: 1:5,000 – 1:50,000– DEM, fuel map, settlements, roads, weather patterns, fire

data, administrative boundaries

• Scale: < 1:50,000– fire data, administrative boundaries, weather patterns,

bioclimatic regions (DEM, fuel map, WUI areas, roads)

2.6 Examples of hazard maps and legends referred toassumed scales

Fire hazard assessment is routinely performed in most develop countriesthat are affected by forest fires and quite different approaches are used. Areview of the most known currently run operational system can be found inSan Miguel-Ayanz et al. (2003). Such operational systems are producingand disseminating through internet updated evaluation of fire dangerconditions, and they are therefore significantly stressing the dynamiccomponent of the fire risk itself.

In Canada the Canadian Wildland Fire Information System (CWFIS)(http://cwfis.cfs.nrcan.gc.ca/en/index_e.php) produces daily fire dangermaps; these include maps of the various components of the meteorologicalForest Fire Weather Index System (Figure 1) as well as maps calculatedwith the Forest Fire Behavior Prediction System equations (Figure 2).


B.IV-11

Figure 1: Map from the Fire Weather Index SystemSource: http://cwfis.cfs.nrcan.gc.ca/en/index_e.php

Figure 2: Map from the Forest Fire Behaviour Prediction SystemSource: http://cwfis.cfs.nrcan.gc.ca/en/index_e.php


B.IV-12

The maps derived from the Forest Fire Behaviour Prediction System arebased on the general scheme depicted in Figure 3:

Figure 3: Scheme of the Canadian FBPSSource: Forestry Canada Fire Danger Group (1992)

In the USA the Forest Service operates the Wildland Fire AssessmentSystem (WFAS) (http://www.fs.fed.us/land/wfas/) which calculates dailymaps of various fire danger indices for the continental USA. These mapsinclude fire danger class based on the National Fire Danger Rating Systeminput from local meteorological stations (Figure 4), as well as dead and livefuel moisture, drought indices and Burgan’s (1998) recently developed FirePotential Index. In addition, weekly satellite composites of visual greenness,relative greenness, and departure from normal are available.


B.IV-13

Figure 4: Map from the Wildland Fire Assessment SystemSource: http://www.fs.fed.us/land/wfas/

In Europe The EC - DG JRC operates the European Forest Fires InformationSystem (EFFIS) (http://inforest.jrc.it/effis) which is currently part of the EU“Forest Focus” regulation (EC-2152/2003) and is meant to support forestfire protection through information at the European level. EFFIS, whichincludes several modules, has been developed and is implemented by JRCalso through collaboration with the relevant services of the Member States,and under the coordination of EC - DG ENV Civil Protection Unit. Thecurrently operational module on fire risk assessment is EFFIS- RiskForecast, while experimental work is on going and strongly supported inorder to improve and further develop new EFFIS modules. The Risk Forecastmodule computes daily EU maps of 6 different meteorological fire dangerindices processed from 1 and 3 days weather forecast data and mappedwith a spatial resolution of about 40 km (Figure 5). Fire risk deriving frommeteorological conditions is therefore forecasted and mapped into 5classes, which have been specifically calibrated for the area covered by theSouthern European member states. In addition a modified version ofBurgan’s (1998) Fire Potential Index is computed that integrates forecastmeteorological data (to estimate dead fuel moisture content), satellite data(to estimate the relative fraction of live fuels) and a fuel map. In this casemaps with a spatial resolution of 4.4 km are generated daily (Figure 6).


B.IV-14

Figure 5: Fire risk forecast Map from the European Forest FireInformation System (EFFIS)

Source: http://inforest.jrc.it/effis

Figure 6: Fire potential map from the European Forest FireInformation System (EFFIS)

Source: http://inforest.jrc.it/effis

Fire Potential Index


B.IV-15

The mentioned operational systems are dynamical, therefore their methodscannot be directly applied to the planning context of ARMONIA. Although insome cases they can be interpreted as static when a long historical series isused (Figure 7).

Figure 7: Average predicted fireline intensity along the fire seasonSource: http://cwfis.cfs.nrcan.gc.ca/en/index_e.php

After showing briefly examples of fire hazard assessment systems run atglobal level, we illustrate some of the approaches followed at local level forlong term fire hazard mapping.

Presently several approaches and methods of risk assessment and mappingcan be found in the literature and are applied at local level.It must be also noted the absence of standard or recommended methodsfor risk assessment, either by the scientific community or by the authorities.For almost every new case, researchers or practitioners elaborate a newway of handling the problem, in order to adapt to the local context, as wellas to make with the available data or the budget.

Therefore there is at present no unique method for risk assessment andmapping. In what follows we will try to summarize the most commonapproaches.


B.IV-16

A method for estimating and mapping forest fire hazard involves identifyingthe potentially contributing variables and integrating them into amathematical expression, i.e. an index. This index, therefore, quantifies andindicates the level of fire hazard.The main differences among the methods are mainly in the approaches forintegrating the fire hazard related variables, i.e. the type of model used forderiving the fire hazard index.

The different methods applied so far can be grouped into the followingmodelling approaches:

• Empirical combination of GIS layers (derived using more or lessconsolidated empirical or knowledge based models)

• Fire behavior (based on the equations of a fire behavior model)• Fire statistics (fire statistics used to derive empirical fire hazard maps

or local statistical models)

An extended analysis with examples of the different methodologies can befound in the analysis carried out by Chuvieco et al. (2002), from which whatfollows has been mainly extracted and integrated.

Since the goal is to obtain a single fire risk index, the component variables(vegetation, topography, climate, etc.) should first be classified in anumerical scale of risk and then combined into a single index. In somecases, the creation of risk levels from the original variables implies changingthe nominal-categorical scale to an ordinal scale. For instance, different fueltypes or slope ranges should be assigned a numeric value associated with aspecific risk level. On the other hand, the integration of these layers in asingle risk index requires that a weight be applied to each variableaccording to its importance on the fire occurrence. Both questions may beapproached in a more qualitative-subjective way or by using a quantitative-objective scheme.

The qualitative-subjective schemes often result from the experience ofexperts who assign risk levels and weights according to their ownperception of fire risk in the area. The simplest way to develop thisprocedure is to create risk tables, where the combinations of two variablesare assigned specific danger values (Brass et al., 1983; Gouma andChronopoulou-Sereli, 1998; Salas and Chuvieco, 1994; Yool et al., 1985).An example of such combinations is given in Table 1.

Behaviour RiskIgnitionRisk Very High High Moderate Low

Very High Very High Very High Moderate ModerateHigh Very High High Moderate ModerateModerate High High Moderate LowLow Moderate Moderate Low Low

Table 1: Fire risk index proposed by Salas and Chuvieco(1994) This index is a combination of risk associated tofire ignition and fire spreading

Another example of the qualitative-subjective approach followed in fire riskmapping consists in the application of an induction methodology aimed atformalizing the process of expert knowledge extraction and its subsequent


B.IV-17

organization in knowledge trees made up of parameters and functions(Camia and Bovio, 2002). An example of map is given in Figure 8, takenfrom the results of the EU project Prometheus. The model has been derivedfrom expert knowledge, and the combination of variables is mostly based onif…then rules.

Figure 8: Variables and derived fire start component maps of presuppressionplanning diagram of Prometheus system

Source: Camia and Bovio (2002)

The main problem of the empirical approaches described so far lies on theirsubjectivity and local validity. Experts make the decisions, but evenassuming their good knowledge of fire events in the study area, the methoddoes not offer a clear rationale for extending the defined criteria to otherareas. On the other hand, qualitative categories do not provide a clearimage about gradients of risk presented in the field. The quantitativeapproach to integrate fire-related variables can be achieved in differentways. First, it could be based on the selective weighting of danger variablesto create single danger indices (Abhineet et al., 1996; Benvenuti et al.,2000; Chuvieco and Congalton, 1989; Gouma and Chronopoulou-Sereli,


B.IV-18

1998; Lu et al., 1990; Salas and Chuvieco, 1994; Thompson, 2000;Vliegher, 1992). Commonly these weights are based on the knowledge ofthe authors, in a way similar to the qualitative criterion, but this proceduredoes offer a gradient of risk levels, which can eventually be classified indifferent risk categories or used as they are produced.

Some examples of such indices (Salas and Chuvieco, 1994) are:

Ignition Risk = 4 * H + 3 * V + 2 * I – E; where H represents human risk factor, V represents vegetation, Irepresents illumination factor, and E represents the elevation factor.

Propagation Risk = 5 * V + 4 * S + 3 * A - E – FB;where V represents fuel models factor, S slope factor, A aspect factor, Eelevation factor and FB, the presence of fire-breaks.

This kind of indices previously require establishing quantitative risk levelsfor each input variable. For instance, fuel types should be ranked accordingto their ignition or behavior risk, following some logic (for instance, rates ofpropagation from a fire behavior model). They are more objective than thequalitative criteria previously discussed, but they should be interpreted in arelative rather than an absolute way. In other words, they define higher andlower levels of fire risk, but they cannot be used to infer probabilities of fireignition or fire spread rates. Multicriteria evaluation techniques (MCE)(Barredo, 1996) may be a good alternative to reduce the subjectivity of thisassigning process, since the opinion of experts may be quantitativelyassessed. Moreover, each expert's opinion may be weighted according tohis/her degree of knowledge in the field or the study area. MCE techniqueshave been used for fire risk mapping, weighing each risk variable after theexpert's opinion in two different scenarios (Alcázar et al., 1998).

As a general comment it must be pointed out that the fire probability is verydifficult to quantify, especially at local level, also because the historicalseries should not go further than 15 years (see paragraph 2.2). In additiondata about the location of ignition points of past fire events, or about thefire perimeters delineation, are not known in most cases. Models based oninfrastructures or human related features of the landscape are sometimesused, e.g. buffering around roads and settlements.

The second mentioned approach for fire hazard assessment and mapping isthe use of fire behavior models (Caballero et al., 1994; Radke, 1995; vanWyngaarden and Dixon, 1989; Vasconcelos and Guertin, 1992; Wilson andBaker, 1998; Woods and Gossette, 1992; Camia et al. 2003).Using this approach, the fire hazard maps produced have an explicitphysical meaning and therefore can be more easily integrated into a firemanagement context. However the probability of ignition is less consideredin these cases, since the models concentrate on fire behavior once the fireevent has started.

An example of a fire hazard map derived from a fire simulation model isgiven in Figure 9.


B.IV-19

Figure 9: Expected fireline intensity map of Val Grande National Park (Italy)Source: Camia et al. (2003)

The simulations were in this case based on the Rothermel (1972) model,the most widely used fire behaviour model, and enhancements introducedusing the FARSITE system (Finney, 1998). The FARSITE system integratessome static raster layers to generate a landscape file (Figure 10), thensimulation can be run feeding the model with dynamic data such asmeteorological conditions and fuel moisture content. Such an approach forlong term fire hazard mapping implies the definition of static scenarios forthe dynamic factors. Also in this case the fire behavior was modeledassuming an homogeneous probability of being burned of all cells of theraster layer.

Figure 10: Raster landscape input layers required for FARSITE simulation.Source: Finney. (1998)

Expected fireline intensity


B.IV-20

The third mentioned approach to model the risk variables is using statisticalanalysis based on historical fire data. The most widely used methods arebased on local regression analysis techniques. Fire occurrence is thedependent variable, while fire risk variables are the independent ones.Coefficients of multiple regression become the weights of each risk variablefor the synthetic risk map. Models proposed in the literature for obtainingthese functions range from simple multiple linear regressions (Castro andChuvieco, 1998), to logistic regression models (Chou, 1992; Chuvieco etal., 1999; Vasconcelos et al., 2001; Vega-García et al., 1993) and neuralnetworks (Chuvieco et al., 1999; Chuvieco et al., 1998; Vasconcelos et al.,2001; Vega-García et al., 1993). Since these models are produced bystatistical fitting procedures, the accuracy can be assessed quantitatively(that is the percentage of original variance explained by the model), andtherefore a better understanding of the importance of each variable in fireoccurrence can be obtained. However, they should be applied carefullyoutside the period and study area in which they were produced.

3 Element at risk and exposure

The element at risk are basically the fire prone ecosystems. Therefore theconsequences of forest fires are mainly assessed in terms of environmentaldamage suffered first of all by the vegetation being burned by the fire.

3.1 Typology of elements

Fire is a natural factor in many ecosystems, and therefore, from theecosystem point of view, the impact of a given wildfire could be relativelycontained, being within the limits of a normal natural disturbance.In some cases, if the fire return interval is long enough, fire effects caneven be beneficial for the ecosystem, although in most cases thedisturbance induced by the fire has a negative impact. In ecosystems notadapted to fire, or in case of recurrent burnings in the same area, adegradation process can result.

The exposure of vegetation to the detrimental effects of a fire with a givenintensity depends of the resistance and the resilience of the ecosystem.While the resistance expresses the stability of an ecosystem against thedisturbance, e.g. low flammability of species or resistance to the hightemperatures, resilience is the ability of the system to recover from thechanges induced by the fire, leading back to the original conditions.Vegetation resistance to fire is often of little relevance in front of otherecosystem properties related to recovery capacity.

The exposed elements might be also human settlements in the wildlandurban interface (WUI). In this case they are normally private homes notconveniently protected through a correct management of the vegetationsurrounding the houses.


B.IV-21


4.1 Definition of vulnerability and/or consequence

As anticipated previously most fire risk studies are not focused on theconsequences of the events, therefore concentrating either on theprobability of having a fire or on the expected fire behavior, or on boththese aspects.

Vulnerability expresses the potential consequences of fire on the exposedelements. It depends from the potential fire effects and the value of theaffected natural resources. The potential fire effects depend on firecharacteristics and ecosystem response while the value of the naturalresources is quite difficult to assess even qualitatively.

With respect to the values of the affected resources, several aspects needto be considered, such as the recreational and socio-economic value of theburned area, or the intrinsic ecological richness of the landscapes affected.In any case the value is assigned by humans according to some criteria,often according to the expected outcome, or benefit, deriving from thethreatened natural resource.

In addition to the generally applicable concepts such as nature conservationor biodiversity, local potential benefits that can be threatened by wildfiresare for example related to soil protection, hydrological regimes, waterquality, wildlife, wood production, landscape, recreational and cultural valueand so on. They are quite diverse, hard to quantify and may be more or lessrepresented in every given site.

In some cases, there have been attempts to translate such benefits in acommon unit, i.e. economic value, but it is true that some elements of theterm vulnerability are subject to opinion or land management decisions (asfor instance assigning a prevailing recreational and nature protectionfunction to a natural resource through the establishment of a natural park)and in other elements we lack timely standard data (fire characteristics).This explains why there are hardly any global studies on vulnerability,although it is beginning to draw an interest in the scientific community.


Standard methods to assess and map forest fire vulnerability are still in aresearch phase. No operational examples can be given in this section.


B.IV-22

5 Analysis of risk

Since the vulnerability component is not yet developed, fire risk analysis islimited to the hazard part which has been described in the previouschapters.Attempts to refer to a more extended fire risk framework, that includes alsovulnerability can be found in the literature (Bachmann and Allgöwer, 1998;Bachmann and Allgöwer, 2001; Camia and Bovio, 2002; Chuvieco et al.2002; San-Miguel-Ayanz, 2002) but operational methodologies have not befully developed.


See hazard chapter (paragraph 2.1) for a discussion on fire terminology.

5.2 Methodologies for risk assessment

Methodologies are under development at JRC and have been proposed inthe SPREAD project, but have not been yet fully designed.

6 Risk management

Fire risk assessment is mostly performed in order to provide forest servicesand fire protection agencies with information to support their activities,enhance wildfire protection actions and optimise fire management plans.Therefore, in addition to the temporal and spatial scale issues illustratedpreviously, the specific fire protection activity that has to be supported mustalso be identified, since this one may strongly influence the approach to thefire risk assessment procedure.In fact the context and the related fire protection tasks for which theinformation on fire risk is needed can be quite different.All fire risk studies address a specific requirement, the reason why theinformation on fire risk is needed, and consequently who and for whatpurpose will have to use the information on fire risk estimation provided,are all relevant issues.The rationale behind is that the different domains of fire management havespecific problems to address from which the components of fire risk mayresult with different emphasis, and also the proper temporal and spatialscales have to be selected accordingly.The following fire management contexts can be considered:Fire preventionFire pre-suppressionFire detectionFire fightingPost-fire

In the context of fire prevention, information about the most fire proneareas and their location are required.


B.IV-23

Long term fire risk estimation is typically needed in order to set up properfire management plans at the beginning at the fire season.Typical management actions that count on the spatial distribution of fire riskestimates are for example silvicultural interventions, fuel managementpractices, prescribed fire, location of defence infrastructures such asfirebreaks, water reservoirs, look-out towers, optimization of the roadnetwork.At global scale, long-term fire risk estimation done as a fire prevention task,can be used to support strategic and political decisions.

Both long-term and short-term fire risk estimation are applied to supportdecisions in the fire pre-suppression context.In fact the allocation of fire fighting personnel, funds and equipment has tobe defined also on the base of a long-term fire risk analysis, but thesedecisions can be changed in the light of short-term risk information(Chuvieco, 2003).The fire pre-suppression activities, concerned with real time allocation ofprotection resources to optimise the preparedness level of the fireprotection organisation following the changing fire danger conditions withtime, are typically local ones.At global level the monitoring of fire danger conditions is mostly relevant forthe displacement of heavy fire fighting means and pre-alert of protectionagencies.

While in prevention and pre-suppression both fire occurrence and behaviourestimates are concerned, in fire detection the focus is mostly on theprobability of fire occurrence.The applications are basically at local scale. In this case the short-term firerisk evaluation combined with information derived from long-term fire riskassessment, permit to define the areas in which remote cameras are moreuseful (Arrue et al., 2000).In addition short-term fire risk maps can be used as a criterion to evaluatethe alarms given by automatic fire detection systems in order to reducefalse alarm.In any case, the focus is basically on fire occurrence, while fire spreading isrelatively less important.

Fire fighting (suppression) activities require information derived from short-term fire risk assessment to evaluate the behaviour of the wildfires anddefine the most appropriated attack strategies and means in real time.Weather conditions and their changing over time are, for example,important data on which suppression decisions must be based on.

Within the post-fire context, restoration is the task that is relevant and themain data required are related with long-term fire risk assessment.In particular, it is necessary to consider the structural properties of fuel,topography and climatic conditions of the site in which is applied in order tosupport the restoration work with guidelines and priorities also based on firerisk criteria.

Very little information are available about fire risk perception. Based onrecent studies done in Southern France, Spain and Finland through surveys


B.IV-24

on fire risk awareness, it appears that the population tends to considerwildfires firstly as a source of damage to flora and fauna, and not toeconomic values as one could expect. At least in Spain there seems to be aconsiderable difference between urban and rural perception of fire risk.While urban people think that most fires are caused intentionally, ruralpeople consider most fires being caused by negligence.In exposed areas a large percentage of people consider that the privateforest owners are responsible for applying fire prevention measures.


CROWN FIRE: A fire that advances from top to top of trees or shrubs moreor less independent of a surface fire. Crown fires are sometimes classed asrunning or dependent to distinguish the degree of independence from thesurface fire.

FIRE DANGER (FAO, 1986; DELFI, 1999): The resultant, often expressed asan index, of both constant and variable danger factors affecting theinception, spread, and difficulty of control of fires and the damage theycause.

FIRE FRONT: The part of a fire within which continuous flaming combustionis taking place. Unless otherwise specified, the fire front is assumed to bethe leading edge of the fire perimeter. In ground fires, the fire front may bemainly smoldering combustion.

FIRE HAZARD (FAO, 1986; DELFI, 1999): A measure of that part of the firedanger contributed by the fuels available for burning (worked out by theirrelative amount, type and condition, particularly their moisture content. Inthe USA fire hazard is referred to as a fuel complex, defined by volume,type, condition, arrangement, and location, that determines the degree ofease of ignition and fire suppression difficulty.

FIRE RISKFAO (1986): (1) The chance of fire starting, as affected by the nature andincidence of causative agents. An element of fire danger in an area (2) Anycausative agent.DELFI (1999): The probability of fire initiation due to the presence andactivity of a causative agent.

FIRE SEVERITY: Degree to which a site has been altered or disrupted byfire; loosely, a product of fire intensity and residence time.

FIRELINE INTENSITY: The product of the available heat of combustion perunit of ground and the rate of spread of the fire, interpreted as the heatreleased per unit of time for each unit length of the fire front. The units arekW per meter of fire front or kcal per meter per second.


B.IV-25

FLAME LENGTH: The distance between the flame tip and the midpoint of theflame depth at the base of the flame (generally the ground surface), anindicator of fire intensity.

GOUND FIRE: Ground fire is a fire that consumes the organic materialbeneath the surface litter ground, such as a peat fire.

RATE OF SPREAD: The relative activity of a fire in extending its horizontaldimensions. It is expressed as rate of increase of the total perimeter of thefire, as rate of forward spread of the fire front, or as rate of increase inarea, depending on the intended use of the information. Usually it isexpressed in meter per minute or hectares per hour for a specific period inthe fire's history.

REACTION INTENSITY: It expresses the combustion rate, the rate of heatrelease, per unit area of the flaming fire front, expressed as heatenergy/area/time (such as kcal/m2/sec or kW/m2).

RESIDENCE TIME: The time, in seconds, required for the flaming front of afire to pass a stationary point at the surface of the fuel. The total length oftime that the flaming front of the fire occupies one point.

SURFACE FIRE: A surface fire is a fire that burns loose debris on thesurface, which includes dead branches, leaves, and low vegetation.

VULNERABILITY: potential consequences of fire on the exposed elements. Itdepends from the potential fire effects and the value of the affected naturalresources.

8 References

Abhineet, J., Ravan, S.A., Singh, R.K., Das, K.K. and Roy, P.S. (1996),Forest fire risk modelling using remote sensing and geographicinformation system, Current Science. 70(10): 928-933.

Alcázar, J., Vega-García, C., Grauet, M., Pemán, J. and Fernández, A.,(1998). Human risk and fire danger estimation through multicriteriaevaluation methods for forest fire prevention in Barcelona, Spain. In:D.X. Viegas (Editor), III International Conference on Forest FireResearch - 14th Conference on Fire and Forest Meteorology. ADAI,Coimbra, pp. 2379-2387.

Arrue B. C., Ollero A., and Martinez de Dios J. R., 2000. An IntelligentSystem for False Alarm Reduction in Infrared Forest-Fire Detection.IEEE Intelligent Systems. 15(3): 64-73.

Bachmann, A. and Allgöwer, B., (1998). Framework for wildfire riskanalysis. In: D.X. Viegas (Editor), III International Conference onForest Fire Research - 14th Conference on Fire and ForestMeteorology. ADAI, Coimbra, pp. 2177-2190.


B.IV-26

Bachmann, A. and Allgöwer, B. (2001), A consistent wildland fire riskterminology is needed!, Fire Management Today. 61(4): 28-33.

Barredo, J.I. (1996). Sistemas de Información Geográfica y EvaluaciónMulticriterio en la ordenación del territorio, RA-MA, Madrid.

Benvenuti, M., Conese, C. and Dainelli, N., (2000). ISOLE: An integratedsystem for the analysis of tourist impact on the insular environment,IX Simposio Latinoamericano de Percepción Remota, Iguazú, pp. CD-ROM.

Bradshaw L, Deeming J, Burgan RE, Cohen J (1983) The 1978 National Fire-Danger Rating System: Technical Documentation. USDA, ForestService, Intermountain Forest and Range Experiment Station, GTR INT-169, pp 44.

Brass, J., Likens, W.C. and Thornhill, R.R. (1983). Wildland Inventory andResource Modeling for Douglas and Carson City Counties, Nevada,Using Landsat and Digital Terrain Data. NASA Technical Paper 2137,NASA , Scientific and Technical Information Branch, Washington, D.C.

Burgan RE (1988) 1988 Revisions to the 1978 National Fire-Danger RatingSystem. USDA, Forest Service, Research Paper SE-273, pp 39.

Burgan, R.E., Klaver, R.W. and Klaver, J.M. (1998), Fuel models and firepotential from satellite and surface observations, International Journalof Wildland Fire. 8(3): 159-170.

Caballero, D., Martinez-Millan, J., Martos, J. and Vignote, S., (1994).CARDIN 3.0 A Model Forest Fire Spread and Fire Fighting Simulation,2nd International Conference on Forest Fire Research, Coimbra, pp.501-502.

Camia A., Bovio G., 2002 - Wildfire Risk Potential and Expected ImpactAnalysis for Sustainable Forest Management. In: Proceedings IUFROConference Collecting and Analyzing Information for Sustainable ForestManagement. Palermo, Italy, 4.7 Dec. 2001.

Camia A., Busti M., Daviá M. 2003 - Piano antincendio boschivo del ParcoNazionale della Val Grande.

Castro, R. and Chuvieco, E. (1998), Modeling Forest Fire Danger FromGeographic Information Systems, Geocarto International. 13: 15-23.

Chou, Y.H. (1992a), Management of Wildfires with a GeographicalInformation System, International Journal of Geographical InformationSystems. 6(2): 123-140.

Chuvieco E. (ed.) 1999. Remote Sensing of Large Wildfires in the EuropeanMediterranean Basin. Berlin, Springer-Verlag. 212 p.

Chuvieco E., Blanchi R., Allgöwer B., Koutsias N., Salas J., Camia A. 2002.Fire risk mapping (I): Methodology, selected examples and evaluationof user requirements. Spread Project Deliverable D161. p. 45.

Chuvieco E., Allgower B., and Salas J., 2003. Integration of Physical andHuman Factors in Fire Danger Assessment. In: Chuvieco E. Ed., 2003 -Wildland Fire Danger Estimation and Mapping. The role of remote


B.IV-27

sensing data. Series in Remote Sensing. Vol. 4, Singapore, WorldScientific Publishimg Co., 264 p.

Chuvieco, E. (ed.), 2003: Wildland Fire Danger Estimation and Mapping:The Role of Remote Sensing Data. Series in Remote Sensing. Vol. 4,Singapore, World Scientific Publishimg Co., 264 p.

Chuvieco, E. and Congalton, R.G. (1989), Application of remote sensing andGeographic Information Systems to Forest fire hazard mapping,Remote Sensing of Environment. 29: 147-159.

Chuvieco, E., Salas, F.J., Carvacho, L. and Rodríguez-Silva, F. (1999),Integrated fire risk mapping. In: Remote Sensing of Large Wildfires inthe European Mediterranean Basin (E. Chuvieco, Ed.) Springer-Verlag,Berlin, pp. 61-84.

Chuvieco, E., Salas, J., Barredo, J.I., Carvacho, L., Karteris, M. andKoutsias, N., (1998). Global patterns of large fire occurrence in theEuropean Mediterranean Basin. A G.I.S. analysis. In: D.X. Viegas(Editor), III International Conference on Forest Fire Research - 14thConference on Fire and Forest Meteorology. ADAI, Coimbra, pp. 2447-2462.

Deeming JE, Burgan RE, Cohen JD (1977) The National Fire-Danger RatingSystem - 1978. USDA Forest Service, GTR INT-39, pp 63.

Deeming JE, Lancaster JW, Fosberg MA, Furman RW, Schroeder MJ (1974)The National Fire-Danger Rating System. USDA, Rocky MountainForest and Range Experiment Station, RM-84, pp 53.

DELFI (1999) The DELFI vocabulary. CONCERTED ACTION Definition andCreation of a Common Knowledge Base for Forest Fires ENV4-CT98-0735.

FAO (Food and Agriculture Organization) (1986). Wildland fire managementterminology. Terminologie de la lutte contre les incendies de forêt.Terminología del control de incendios en tierras incultas. Report nº 70,FAO Forestry Paper, Roma.

Finney, Mark A. 1998. FARSITE: Fire Area Simulator—model developmentand evaluation. Res. Pap. RMRS-RP-4, Ogden,UT: U.S. Department ofAgriculture, Forest Service, Rocky Mountain Research Station. 47 p.

Flannigan M.D., Stocks B.J., Wotton B.M., 2000 - The Science of the TotalEnvironment 262 (2000) 221-229

Forestry Canada Fire Danger Group. 1992. Development and structure ofthe Canadian Forest Fire Behavior Prediction System. Forestry Canada,Ottawa, ON. Information Report ST-X-3.

Gouma, V. and Chronopoulou-Sereli, A. (1998), Wildland fire danger zoning- A methodology, International Journal of Wildland Fire. 8(1): 37-43.

Intergovernmental Panel on Climate Change 2002 – Climate change andbiodiversity. IPCC Technical paper V.

Lu, J., Bomba, P. and Kind, T., (1990). A microcomputer-based geographicinformation system for forest fire management, ACSM-ASPRS AnnualConvention, Denver, pp. 180-192.


B.IV-28

McPherson G.R., Wade D. D. and B., P.C. (1990). Glossary of Wildland FireManagement Terms Used in the United States., SAF (Society ofAmerican Foresters) 90-05., Washington D.C.

Nesterov VG (1949) Combustibility of the forest and methods for itsdetermination. State Industry Press, USSR.

Overpeck JT, Rind D, Goldberg R. Climate-induced changes in forestdisturbance and vegetation. Nature 1990;343: 51-53.

Radke, J. (1995), Modeling Urban/Wildland Interface Fire Hazards within aGeographic Information System, Geographic Information Sciences.1(1): 9-21.

Rothermel, R.C. 1972. A mathematical model for predicting fire spread inwildland fuels. USDA For. Serv. Res. Pap. INT-115.

Rothermel, R.C. 1983. How to predict the spread and intensity of forest andrange fires. USDA For. Serv. Gen. Tech. Rep. INT-143.

Salas, F.J. and Chuvieco, E. (1994), G.I.S. applications to forest fire riskmapping, Wildfire. 3: 7-13.

San Miguel-Ayanz, J., Carlson, J.D., Alexander, M., Tolhurst, K., Morgan, G.,Sneeuwjagt, R. and Dudley, M. (2003), Current Methods to Assess FireDanger Potential. In: Wildland Fire Danger Estimation and Mapping.The Role of Remote Sensing Data (E. Chuvieco, Ed.) World ScientificPublishing, Singapore, pp. 21-61

San-Miguel-Ayanz, J., 2002, Methodologies for the evaluation of forest firerisk: from long-term (static) to dynamic indices, in Forest Fires:Ecology and Control, Anfodillo T. and Carraro, V. (Eds), Forest Fires:Ecology and Control, Univesity degli Studi di Padova, pp. 117-132.

Thompson, W.A. (2000), Using forest fire hazard modelling in multiple useforest management planning, Forest Ecology and Management. 134:163-176.

Van Wagner CE (1987) Development and structure of the Canadian ForestFire Weather Index System. Canadian Forestry Service, TechnicalReport 35, pp 37.

van Wyngaarden, R. and Dixon, R., (1989). Application of GIS to modelforest fire rate of spread, Challege for the 1990's GIS, Ottawa, pp.967-977.

Vasconcelos, M.J. and Guertin, D.P. (1992), FIREMAP. Simulation of firegrowth with a Geographic Information System, International Journal ofWildland Fire. 2(2): 87-96.

Vasconcelos, M.J.P., Silva, S., Tomé, M., Alvim, M. and Pereira, J.M.C.(2001), Spatial prediction of fire ignition probabilities: comparinglogistic regression and neural networks, Photogrammetric Engineeringand Remote Sensing. 67(1): 73-83.

Vega-García, C., Woodard, P.M. and Lee, B.S., (1993). Mapping Risk ofWildfires from Human Sources of Ignition with a GIS, 13th AnnualESRI User Conference, pp. 419-426.


B.IV-29

Vliegher, B.M. (1992), Risk assessment for environmental degradationcaused by fires using remote sensing and GIS in a MediterraneanRegion (South-Euboia, Central Greece). In: IGARSS'92. INt.Geoscience and Remote Sensing Symposium, Houston, TX., pp. 44-47.

Weber MG, Flannigan MD. 1997 - Canadian boreal forest ecosystemstructure and function in a changing climate: impact on fire regimes.Environmental Reviews. 5 (3-4):145-166.

Wilson, J.S. and Baker, P.J. (1998), Mitigating fire risk to late-successionalforest reserves on the east slope of the Washington Cascade Range,USA, Forest Ecology and Management. 110(1998): 59-75.

Woods, J.A. and Gossette, F., (1992). A Geographic Information System forbrush fire hazard management, ACSM/ASPRS Symposium,Washington, pp. 56-65.

Yool, S.R., Eckhardt, D.W., Estes, J.E. and Cosentino, M.J. (1985),Describing the brushfire hazard in southern California, Annals of theAssociation of American Geographers. 75(3): 417-430.


B.IV-30

Appendix:Operational Standards for Risk Assessmentaimed at Spatial Planning

1. Minimum standard (simplified model) for hazardmapping aimed at a legal directive

Several methods of risk assessment and mapping among the most commonhave been described in the state of the art, providing examples and maps.Many other methods exists, although in the state of the art an attempt hasbeen made to group them identifying common approaches.

The main conclusion is that at present no standard or recommendedmethods for fire risk assessment and mapping can be recognized, eitherfrom the scientific community or from the local authorities perspectives.

As it has been stated, for almost every new case, researchers orpractitioners have elaborated a new way of handling the problem, in orderto adapt to the local context, as well as to make with the available data orbudget.

The most common approaches have been summarized in the report andsome guidelines can be drawn, that will be schematically recalled in whatfollows. Reference has to be made to the state of the art document mainbody for fully understanding the schemes.

Numerous uncertainties still remain and it is felt that a definitivemethodology will have to be fully defined only within the harmonization andimplementation phases of ARMONIA (WP3 and WP6), when integration withother natural hazards will be attempted.

Nevertheless it also appears that a generalized method might be difficult toachieve, since the role and relative weight of the different environmentaland human factors affecting forest fire hazard can change locally.

1.1. Various methodologies related to the 3 assumed scales ofanalysis in the light of a potential harmonisation of hazardmaps, based on a multi-hazard perspective

Local Scales (> 1:5,000 and 1:5,000 – 1:50,000)

Modeling approachFire occurrence: little application at the higher scales. A qualitative estimate(no probability) can be attempted, based on roads and settlements typesand location.Fire behavior potential: quantitative estimates using fire simulation models.


B.IV-31

MethodsFire occurrence: buffers of given distances from roads and settlementsFire behavior potential: fire simulation models such as the BEHAVE system(http://www.fire.org/).

Basic input data requiredDEM, fuel model map, settlements, road network, weather patterns,administrative boundaries. If available: fire perimeters of past 5-10 years orfire frequency in the municipalities of past 10-15 years.

Data formatsRaster (pixel size < 100 m)

Map legendIf only fire behavior potential is considered (suggested for >1:5.000scales), a quantitative legend can be foreseen, that shows the estimatedpotential fire line intensities under given meteorological scenarios.The classes of expected fire line intensity might be the following:

1. 0-50 kW/m2. 50-350 kW/m3. 350-1750 kW/m4. 1750-3500 kW/m5. 3500 kW/m

At the scale 1:5,000 – 1:50,000, fire behavior classes might be combinedwith 2-3 expected fire occurrence pattern.

Regional Scale (< 1:50,000)

Modeling approachFire occurrence: depending on data availability. Basic is statistical analysisof historical fires (10-15 years) at municipality (commune) level. If firelocations and/or perimeters are available, more sophisticated approachescan be pursued (e.g. with regression over environmental features).Fire behavior potential: fire simulation models or estimates from either pastevents or from environmental features (fuels, topography, climate).

MethodsFire occurrence: kernel density probability based estimates or fire frequencydistribution analysis at municipality level.Fire behavior potential: based on fire simulation model (such as theBEHAVE system) or ad hoc empirical methods derived from statisticalanalysis of local environmental and anthropogenic factors.

Basic input data requiredDEM, land use, fuel types, fire data (last 10-15 years), administrativeboundaries, climatic data, bioclimatic regions, WUI (Wildland UrbanInterface) areas, (settlements, road network, socio-economic variables)

Data formatsRaster (pixel size > 100 m) and vector (if administrative boundaries aretaken as geographical units.


B.IV-32

Map legendIf only fire simulation is considered, a quantitative legend can be foreseen,that shows the average potential fire line intensities under givenmeteorological scenarios.The classes might be the following:

1. 0-50 kW/m2. 50-350 kW/m3. 350-1750 kW/m4. 1750-3500 kW/m5. 3500 kW/m

If fire simulation is mixed or replaced with other analysis (suggested), i.e.empirical combination of data layer, or statistical analysis of fire data,qualitative classes of fire hazard are more conveniently applied. Thesuggested number of classes is again 5, e.g. level of fire hazard very low,low, average, high, very high.

2. Minimum standard (simplified model) for riskmapping aimed at spatial planning

Fire risk mapping (sensu probability x consequences) applications still notdeveloped enough for standard operational definitions. As illustrated in thestate of the art, only fire hazard could be considered at this stage.


B.V-1

B.V Volcanic risk

Authors: Andrea Ceudech, Massimiliano Pistucci, UNINA;Giovanni Orsi, Sandro de Vita, Osservatorio Vesuviano

1 Physical definition of volcanic phenomena ......................3

1.1 Typologies ............................................................................... 3

1.2 Intensities, Severity, Magnitude................................................. 6

2 Hazard assessment..........................................................7

2.1 Definition................................................................................. 7

2.2 Current methodologies for analysing and representation of hazardwith respect to temporal scales .......................................................... 7

2.3 Dynamical hazard – climate change effects ............................... 11

2.4 Problem of scale..................................................................... 11

2.5 Data availability – typology, format – GIS structure ................... 12

2.6 Examples of hazard maps and legends referred to assumedscales............................................................................................ 13

3 Elements at risk and exposure....................................... 13

3.1 Typology of elements.............................................................. 15

4 Analysis of vulnerability ................................................ 19

4.1 Definition of vulnerability and/or consequence........................... 19

4.2 Methodologies for assessment related to structural and non-structural elements at risk............................................................... 20

4.2.1 Functions for vulnerability/consequence analysis.................... 23

4.2.2 Examples of vulnerability maps and legends .......................... 24

4.3 Most common damage potentials ............................................. 24

5 Analysis of risk .............................................................. 25

5.1 Definition of risk..................................................................... 25

5.2 Methodologies for risk assessment ........................................... 255.2.1 Qualitative and quantitative methods, direct and indirect risk .. 26

5.2.2 Functions of risk analysis..................................................... 28

5.2.3 Examples of risk maps and legends ...................................... 28

6 Risk management.......................................................... 31

7 Glossary of all keywords................................................ 37

8 References..................................................................... 38


B.V-2

Appendix: Operational Standards for Risk Assessment aimedat Spatial Planning.............................................................. 40

1. Minimum standard (simplified model) for hazard mapping aimed ata legal directive.............................................................................. 40

1.1. Various methodologies related to the 3 assumed scales of analysis inthe light of a potential harmonisation of hazard maps, based on a multi-hazard perspective ......................................................................... 40

2. Minimum standard (simplified model) for risk mapping aimed atspatial planning.............................................................................. 40

2.1. Multi-risk assessment perspective as element of the StrategicEnvironmental Assessment .............................................................. 41

2.2. Methodologies, functions and outputs ....................................... 41


B.V-3

1 Physical definition of volcanic phenomenaThe words hazard and risk are often used as synonyms although they havevery different meanings. Volcanic hazard is the probability of a given areabeing affected by potentially destructive volcanic processes or productswithin a given period of time (Fournier d’Albe 1979). Technically, therefore,the actual destructive volcanic processes themselves should be referred toas ‘hazardous volcanic phenomena’ rather than as ‘volcanic hazards’.However, the popular understanding of the word ‘hazard’ as a ‘source ofdanger’, however, means that potentially dangerous eruptive and post-eruptive phenomena such as pyroclastic flows, wind-borne ash, lava flows,volcanic gases and lahars can also be referred to as ‘volcanic hazards’ whennot used in the context of probabilistic assessments.

Risk is the possibility of a loss (e.g. of life, property, infrastructure) withinthe area subject to the hazard(s) (Fournier d’Albe 1979). Risk is evaluatedby the relation: risk = value x vulnerability x hazard. Value includeseverything threatened by the hazard, whereas vulnerability is thepercentage of the value likely to be lost in a given hazardous event.

It is important to understand the differences between hazard and risk.Volcanic hazards result from natural phenomena beyond human control andcannot be avoided. However, appropriate land management and riskmitigation actions based on detailed hazards assessments can reduce bothexposed value and vulnerability, and thus risk.

1.1 TypologiesVolcanoes can produce a variety of hazardous phenomena with variablefrequency. Such phenomena may occur during an eruption (direct hazards)or before or after an eruption (indirect hazards). The latter include the ever-present hazardous phenomena related to the presence of a live volcano,such as volcanic earthquakes and volcanic gases. Crandell et al. (1984)have distinguished two broad categories of hazards: 1) short-term (orintermediate) hazards are those that occur at such high frequency (morethan once per century) that inhabitants of the area will likely experiencethem; and 2) long-term (or potential) hazards are those that occur at suchlow frequency (less than once per century) that they will not likely beexperienced by people alive today.

Lava flows - Lava flows are hot streams of molten rock that travel downvalleys on the slopes of volcanoes at velocities ranging from a few m/hourto 60 km/hour. Lava flows generally move relatively slowly along relativelypredictable paths, and therefore usually do not threaten human life,although they destroy everything in their path and can cause forest fires.Although there are other controlling factors, the speed and distance lavaflows travel depends primarily on their viscosity; low-viscosity lava flowscan be tens of kilometers long.

Lava domes - Because viscous lava cannot flow easily, it tends to form shortthick lava flows or pile up around the vent to form a hill, or lava dome.Viscous lava flows and domes can be hazardous as their steep sides oftenbecome unstable and can collapse, causing a type of small pyroclastic flowknown as a block and ash flow, and associated ash fall.


B.V-4

Pyroclastic fall - Pyroclastic fall refers to the fragments (ash, lapilli, blocksor bombs) produced during an explosive eruption that fall to Earth, usuallyfrom an eruption column. Such pyroclasts can land after following a ballistictrajectory, or can rise through the atmosphere within a Plinian eruptioncolumn, be entrained into the umbrella cloud, and then fall by gravity. Falldeposits tend to blanket the ground as widespread sheets characterized bythickness and grain size that decrease with distance from the eruption vent.

Pyroclastic fall hazard is often subdivided on hazard maps. The hazard fromash fall is usually shown as ash isopachs, derived by measuring ash fallthicknesses from past eruptions either at the volcano in question or asimilar volcano. Ash is strongly affected by the direction of the prevailingwind, and isopachs are generally elongated downwind. The areas affectedby ballistic blocks and bombs are often depicted as concentric circlessurrounding the vent as these are less likely to be affected by wind. Mostballistic ejecta fall within 5 km of the vent, although in extremely explosiveeruptions ballistic ejecta may travel > 10 km.

Lateral blasts - A lateral blast is a laterally directed volcanic explosion ofrock fragments and gas that explodes outwards at high velocity from theside of a volcano. It can affect a 180° sector and extend up to 30 kmoutward from the volcano. Lateral blasts are not affected by topography andcan develop without warning. These types of eruptions are rare but can betriggered by failure of newly erupted lava domes or by the collapse of alarge portion of the volcanic edifice.

Pyroclastic density currents - A pyroclastic density current is a heavier-than-air, hurricane-like, ground-hugging mixture of volcanic particles, rockfragments and gas. Depending on magma fragmentation dynamics, thesecurrents can be generated by variable mechanisms and their physicalproperties can vary accordingly. A large spectrum of currents can begenerated, mostly characterised by their density. Generally the most densecurrents are called pyroclastic flows, while the most dilute are calledpyroclastic surges.

Pyroclastic flows are hot (100-900°C), fast-moving (>100 km/hr) currents,which form ground-hugging mixture of ash, rock fragments and gas. Suchflows form when an eruption column or a lava dome collapses. They usuallytravel down valleys and cause total devastation of the area over which theyflow. Small flows travel 5-10 km down topographic lows; large flows canovertop topographic barriers and travel for 50-100 km.

Pyroclastic surges are dilute, turbulent clouds of gases and rock that moveat great speeds above the immediate ground surface. The pyroclasticsurges form in a similar way to pyroclastic flows or in relation tophreatomagmatic eruptions, but their effects are more widespread as theyare less confined by topography and may therefore sweep across ridges andhills as well as down valleys. Pyroclastic surges can be either hot (severalhundred °C) or cold (< 100 °C). Cold pyroclastic surges are generally knownas “base surges,” and are commonly generated by phreatic andphreatomagmatic explosions. The hazardous aspects of both types ofsurges include the destruction of vegetation and structures, impact damageby rock fragments, and burial by ash and rock debris.


B.V-5

Lahars - Lahars are mudflows formed when volcanic particles and debrismixes with water. The source of the water may be a crater lake, heavy rain,or melted ice or snow. The loose ash and volcanic fragments aretransformed into a dense fluid-rock mixture that rushes down the slopes ofa volcano and into surrounding valleys. Lahars are destructive to everythingin their path, and the threat from rainfall-induced lahars may last for yearsafter an eruption has ended.

Debris avalanches - A debris avalanche is a sudden and rapid movement oflarge volumes (>10-20 million m3) of rock and other debris (e.g.,vegetation) driven by gravity. It may result from the collapse of the side ofan oversteepened volcano or gravitational collapse of unconsolidatedsediments. Depending on their scale, debris avalanches may destroyeverything in their path. They may travel over 30 km, and cover an area>1,000 km2. They may produce tsunamis in coastal areas. They can occurduring volcanic eruptions or when a volcano is not actively erupting. Theyare one of the most hazardous but least common volcanic events.

Tsunamis - Tsunamis are large seismic sea waves generated by the suddendisplacement of water resulting from underwater disturbances such as alarge earthquake or submarine volcanic eruption, or material impacting onthe sea. Tsunamis travel extremely fast, reaching ~800 km/hr in the deepoceans. When tsunamis reach land they inundate low-lying coastal areas.

Tsunami hazard is evaluated through from the effects of past tsunami orfrom computer modelling for areas to date not yet affected; it is , anddepicted as inundation zones on low-lying areas which may be manykilometres away from the source of the tsunami (e.g., an underwatervolcano).

Volcanic gases - Magma contains dissolved gases that are released into theatmosphere during eruptions. In addition, fumaroles at geothermal systemsassociated with volcanoes also emit large amounts of gases, even when thevolcano itself is quiescent. The most common gases in volcanic areas arewater vapour (H2O), carbon dioxide (CO2) and sulphur dioxide (SO2) withsmaller amounts of hydrogen sulphide (H2S), carbon monoxide (CO),hydrogen chloride (HCl) and hydrogen fluoride (HF). SO2, CO, CO2 and H2Sare present in toxic amounts close to the vent of an erupting volcano andmay be emitted from fumaroles. Further away from the vent these gasescan become dissolved in atmospheric clouds to produce acid rain and mist,which affect human and animal eyes and respiratory systems and corrodemetal building materials. Usually In general, gases are emitted in acontinuously fashion; occasionally, though, large quantities of gas aresuddenly vented, either during an eruption (e.g., Dieng volcano, Java 1979)or during the sudden overturn of a crater lake (e.g., Lakes Monoun andNyos, Cameroon 1984 and 1988).

One of the most common volcanic gases, carbon dioxide (CO2) is extremelydangerous as breathing air with greater than about 20% CO2 can causealmost instantaneous death. As it is heavier than air, CO2 tends toaccumulate in hollows in the topographic lows, displacing the breathable air.People have died in this way at the Boiling Lake in the Valley of Desolationin Dominica, and livestock have been found dead in low-lying areas nearHekla in Iceland).


B.V-6

Volcanic gas hazard is not usually depicted on volcanic hazard maps,although in some cases, such as if a crater lake is present, this may bewarranted.

Volcanic earthquakes - A volcanic earthquake is characterised by high-frequency seismic signals thought to be generated by the fracturing of rockin response to the intrusion and migration of magma. Volcanic earthquakesalmost always precede the onset of volcanic activity, although they do notalways culminate in a volcanic eruption. They often occur in swarms alsoduring or after an eruption. In some cases, they may in themselves besevere energetic enough to cause significant damage, destroying buildingsand triggering gravitational mass movements.

Lightning strikes - Powerful displays of lightning produced by staticelectricity can occur during volcanic eruptions. Such lightning results fromfriction between ash, rock fragments, steam and gases in the eruption cloudand occur to about the radius of the ballistic trajectories. Lightning strikescan pose a threat to life and property and disrupt communication systems.

Although not normally depicted on hazard maps, atmospheric effects in theeruption column would generate frequent lightning strikes to about theradius of the ballistic trajectories.

1.2 Intensities, Severity, MagnitudeThe intensity of an eruption is a measure of the rate at which magma isdischarged during an eruption. It is defined as the mass eruption rate and isexpressed in kg/s. An intensity scale, based on a logarithmic index ofintensity is defined by:

Intensity = log10(mass eruption rate, kg/s) + 3

On this scale, an extremely vigorous eruption will have an intensity of 10-12, whereas a very gentle eruption might have an intensity of 4 or 5 (Pyle,2000).

The magnitude is the total mass of material ejected during an eruption,expressed in kg. A magnitude scale, based on a logarithmic index ofmagnitude is defined as follows:

Magnitude = log10(erupted mass, kg) – 7

According to this scale, a large eruption of a Plinian type is of magnitude 6or more (Pyle, 2000).

Severity has not been defined for volcanic eruptions.


B.V-7

2 Hazard assessment

2.1 DefinitionFor the purposes of hazard assessment it is necessary to determine, as bestas possible, the time, place and nature of future activity. This is known asthe forecasting or predicting of eruptions, depending on the precisionpossible: A forecast is a comparatively imprecise statement of the time,place, and nature of expected activity; whereas a prediction is acomparatively precise statement of the time, place and, ideally, the natureand size of impending activity. A prediction usually covers a shorter timeperiod than a forecast and is generally based dominantly on interpretationsand measurements of ongoing processes and secondarily on a projection ofpast history (Banks et al. 1989). Forecasts can be further subdivided intolong- and short-term forecasts. Long-term forecasts are those that pertainto the coming years, decades or longer. Most hazard assessments areessentially long-term hazard forecasts. Short-term forecasts are those thatpertain to the coming hours, days and weeks, and are usually issued whenunrest is escalating sharply, or a hazardous eruption has just begun.

Long-term forecasting is based on the assumption premise that a givenvolcano will generate the same eruption phenomena as in the past, if thestructure of the volcanic system has not changed. The reliability of a long-term forecast is therefore directly related to the amount and quality of theavailable data on past eruptive history of a given volcanic system, and thelength of time that the data cover. The reconstruction of the past history ofa volcanic system through geological investigations and evaluation ofhistorical documents is essential in long-term forecasting. The evolution of avolcanic system from quiescence to an eruption involves magma rising froma certain depth up to the surface, which generates variations in the physicaland chemical parameters of both the magma and the surrounding rocks.The evolution of these eruption precursors, which can be detected at thesurface via a monitoring system, forms the basis of short-term forecasting.

Ideally, all ‘live’ volcanoes of the world should have a hazards map whichreflects the long-term hazard forecast at that volcano, and which should beused by authorities, during times of quiescence, for risk mitigation andland-use planning. Once activity at a volcano escalates towards eruptionconditions or a volcano begins erupting, the existing hazards map can beupdated and adapted to reflect short-term forecasts of anticipatedbehaviour during the course of the eruption at the volcano.

2.2 Current methodologies for analysing andrepresentation of hazard with respect to temporalscales

The ideal volcanic hazards assessment at a given volcano includes datafrom three main sources: geological investigations, volcano monitoring, andcomparison with similar volcanoes.

Geological investigations of past activity, including evaluation of allprehistoric and historical activity at the volcano. This provides an indication


B.V-8

of size, style and frequency of past activity.; A monitoring network reflectsthe current state of the volcano, including observations of actualtopography, presence of a crater lake or glaciers and meteorologicalconditions, such as wind direction profiles above the volcano and annualprecipitation variations. The monitoring network provides an indication ofwhen and where future activity may occur, and insights into the likely styleof activity and possible areas affected. An evaluation of past and presentactivity at other similar volcanoes, provides an indication of possible activitythat may be either unprecedented or not preserved in the geologic record atthe volcano in question.

Geological investigations - geological investigations carried out for volcanichazards assessment, have to be focused at defining the past behaviour of agiven volcano. They involves detailed fieldwork accompanied bysedimentological, palaeontological, geochronological, mineralogical andchemical analyses of representative rock samples. Collection of all availabledata from logs and cores of bore-holes drilled in the area, is of extremeinterest. Vast amounts of information may be gleaned through suchinvestigations, giving information on style, size, vent location and timing ofpast eruptions, as well as on the areas affected by the volcanic and relatedphenomena. This information is fundamental to perform a long-termforecast of the volcano’s activity.

Recognition of rock bodies, reconstruction of their geometrical relationshipsand elaboration of a general stratigraphic sequence, is the first step in thegeological mapping. The characterization of the type of deposits is the baseon which to hypothesise the possible style of future activity. present arounda volcano provides an indication of the possible style of future activity.Radiometric dating of these deposits, together with the identification oferosional surfaces, paleosols and non-volcanic sediments, which oftenindicate periods of quiescence at the volcano, provides insights into pastfrequency of activity at the volcano as well as the duration of the currentstate of the volcano, permitting estimates of when certain activity mayoccur in the future. Deposits thickness and its areal distribution can be usedto evaluate the volume of magma erupted during past eruptions which,together with petrological and geophysical data, give an indication ofexpected eruption size.

Radiometric age dating of these deposits together with the identification oferosional surfaces, paleosols and non-volcanic sediments, which oftenindicate periods of quiescence at the volcano, provides insights into pastfrequency of activity at the volcano as well as the duration of the current(quiescent) state of the volcano, permitting estimates of when certainactivity may occur in the future.

Structural analysis aimed at the identification of the nature and mechanismsof past deformation events, such as caldera collapse and calderaresurgence, provides insight into variations in the stress regime throughtime which is essential for understanding the behaviour of the volcanicsystem. The areal distribution of eruption vents through time can also be agood indicator of the structural evolution of the volcano and thus thepossible location of future vents.


B.V-9

Mapping of the areal distribution of pyroclastic flow and surge currents andlavas, and lahar deposits associated with the volcano, combined with anevaluation of paleomorphology and current topography and a anunderstanding of transport and deposition mechanisms, is necessary todetermine the areas likely to be affected by similar future activity. The arealdistribution, thickness variations and clast-size characteristics of pyroclasticfall deposits can be used to develop isopach and isopleth maps as well asdispersal indices, which, when combined with knowledge of present-daydominant wind directions, provide an indication of the areas likely to beaffected by future pyroclastic fall. On hazard maps pyroclastic fall should bedepicted as isopachs or, to simplify risk assessment, as load on the ground.

The reconstruction of historical the activity at the a given volcano based onthe analysis of historical documentation is absolutely necessary todetermine the volcano’s most recent past, as this may provide the bestindication of style and size of future eruptions at the volcano. The quality,quantity, and reliability of such documentation differ vastly from volcano tovolcano, which is a reflection of the time period for which the area has beeninhabited by humans, and the cultural level of the inhabitants.

The present configuration and state of the magmatic volcanic plumbingsystem can be deduced by geophysical investigations incorporating forexample seismic tomography, and magnetic and magnetotelluric methods.Fluid geochemistry data, collected on fumaroles and well and spring waters,allow to put constraints on the present state of both magmatic andhydrothermal systems. These can be combined with petrological data, whichinvestigations provide information on depth, temperature and compositionof the magma chamber feeding system up to the last eruption, needed toreconstruct the behaviour of the magmatic system through time. They alsopermit estimates of the amount and composition of the magma available forthe next eruption. Combination of petrological, fluid geochemistry andgeophysical data may be used to place important constraints on the type offuture eruptions.

A volcanic hazards assessment should needs not necessarily be based onthe entire past history of a volcano, rather on its most recent history. Thereasons for this are two-fold: firstly, the farther back in time a record theeruptive history is extended, the less complete and reliable it is likely to be;and secondly, the style and type of activity at a volcano usually commonlyevolves with time, and the most recent activity, in particular that partfollowing a significant structural change, if any, usually provides the bestindication of likely future activity. Thus, if a volcano erupted effusivelygenerating basaltic lava flows between 2 Ma and 1 Ma but became moresilicic and explosive over time such that the last 50,000 years have beendominated by andesitic dome-growth and collapse interspersed with periodof explosive plinian activity, then it would be appropriate to only include thelast 50,000 years of past activity as a reference for likely future activity.The period of time to be taken into consideration will vary from volcano tovolcano, and will be largely determined by its reconstructed past behaviour.

Evaluation of past-activity at a volcano’s past behaviour is extremelyimportant in producing a volcanic hazards assessment, but, for the followingseveral reasons, should be combined with any available information from


B.V-10

both the monitoring network as well as past and present activity (both pastand present) at similar volcanoes elsewhere.

Eruptive behaviour at a given volcano may change over time, and thepossibility exists for sudden, large-magnitude events that areunprecedented in its eruptive history, such as the debris avalanche anddirected blast of 18 May 1980 eruption at Mt. St. Helens.

Not all erupted products are preserved in the geologic record, particularlypyroclastic deposits, which are unconsolidated and easily eroded. Acomparison with historically active similar volcanoes would highlight thisincompleteness. For example, the deposits of the 1902 eruption of theSoufrière of St. Vincent, which killed about 1,600 people, have been almostcompletely eroded away and presently there is very little geologic record ofthis major eruption (R. Robertson, pers. comm.).

The areas affected by volcanic activity in the past may be different to theareas likely to be affected in the future due to changes in topography overtime. The growth of a volcano may fill valleys thus directing future lava andpyroclastic flows, and lahars down previously unaffected valleys. Growth orcollapse phases of a volcano may either generate new topographic barriers,thus sheltering areas that were previously affected by activity from thevolcano, or expose new areas to the effects of the volcanic activity.Furthermore, climatic conditions (such as wind direction) may also changewith time (e.g., before/after the Pleistocene/Holocene boundary), meaningthat tephra fall isopachs based on past eruptions may not accurately reflectthe expected pattern of a future eruption. This implies that determinederuption frequencies have to be considered as minima.

Not all erupted products are preserved in the geologic record, particularly aspyroclastic deposits are unconsolidated and easily eroded. A comparisonwith historically active similar volcanoes highlights this incompleteness: Forexample, the 1902 eruption of the Soufrière of St. Vincent killed ~1600people but the deposits from this major eruption have been almostcompletely eroded away and there is very little geologic record of theeruption.

The areas affected by volcanic activity in the past are usually different tothe areas likely to be affected in the future due to changes in topographyover time. The growth of a volcano may fill valleys thus directing futurepyroclastic flows and lahars down previously unaffected valleys. Growth orcollapse of nearby volcanoes may generate new topographic barriers thussheltering areas that were previously affected by activity from the volcano.Furthermore, climatic conditions (such as wind direction) may also changewith time (e.g., before/after the Pleistocene/Holocene boundary), meaningthat ashfall isopachs based on past eruptions may not accurately reflect theexpected pattern of a future eruption.

The monitoring network - Many Some live volcanoes of the world have amonitoring network which provides critical information on the current stateof the volcanic system. Ideally each live volcano should have a monitoringsystem. Scientists should summit projects to reach this goal and urge civilauthorities to support them. Various techniques are used to monitor activityat live volcanoes, including seismic, ground deformation, geochemical,remote sensing, and geothermal thermal methods. The locations of


B.V-11

historical seismic swarms, ground deformation and hydrothermal activitymay help constrain the location of a future vent as well as the probability ofa future eruption. An additional, extremely important aspect of monitoringis actual visual appraisal of the volcano and its surrounds surroundings. Thisincludes evaluating present-day topography (to determine likely flow pathsof lavas, pyroclastic density currents and lahars), climate conditions (todetermine likely airfall patterns) and hydrology (to determine the likelihoodof magma-water interaction and lahar occurrence). If crater lakes orglaciers are present their behaviour and physical conditions also requireclose observation as they might contribute to the generation of lahars andother lethal phenomena.

Comparison with past and present activity at similar volcanoes elsewhere -As mentioned above, this can be very useful in countering some of theshortcomings associated with hazards assessment based solely on pastactivity at the volcano in question. It is of particular value in cases wherevery little data is available or there have been no historical eruptions at thevolcano.

Time scale - Active volcanoes can be either quiescent or in persistentactivity. Volcanic hazards assessment depends not only upon past history ofa given volcano, but also on its present state. As such a state can change,the time scale of the assessment has to be of the order of months/years incase of persistently active volcanoes and of tens of years in case ofquiescent volcanoes.

2.3 Dynamical hazard – climate change effectsNone for volcanic hazards

2.4 Problem of scaleVolcanoes can produce a variety of hazardous phenomena with variablefrequency and variable impact on the territory. Such phenomena may occurduring an eruption (direct hazards) or before or after an eruption (indirecthazards). Therefore each kind of hazard has to be evaluated independentlyand mapped at the most suitable scale.

Lava flows - Lava flows generally move relatively slowly along relativelypredictable paths, and therefore usually do not threaten human life,although they destroy everything in their path and can cause forest fires.Suggested scale: 1:500 – 1:5000.

Lava domes - Because viscous lava cannot flow easily, it tends to form shortthick flows or pile up around the vent to form a hill, or lava dome.Suggested scale: 1:500 – 1:5000.

Pyroclastic fall - Fall deposits tend to blanket the ground as widespreadsheets characterised by thickness and grain size decrease with distancefrom the eruption vent, affecting areas as large as 500 km2. The areasaffected by ballistic blocks and bombs usually do not exceed 100 km2,although in extremely explosive eruptions, they can reach 300 km2.Suggested scale: 1:5000 – 1:50000.


B.V-12

Lateral blasts - Lateral blasts can affect a 180° sector and extend up to 30km outward from the volcano. Suggested scale: 1:500 – 1:5000.

Pyroclastic density currents - Dense pyroclastic currents, called pyroclasticflows, usually travel down valleys and cause total devastation of the areaover which they flow. Small flows travel 5-10 km down topographic lows;large flows can overtop topographic barriers and travel for several tens ofkilometres.

Dilute pyroclastic currents, called pyroclastic surges, are more widespreadas they are less confined by topography and may therefore sweep acrossridges and hills as well as down valleys. Suggested scale: 1:500 – 1:5000and 1:5000-1:50000.

Lahars - Lahars are mudflows that rushes down the slopes of a volcano andinto surrounding valleys. Lahars are destructive to everything in their path,and the threat from rainfall-induced lahars may last for years after aneruption has ended. Suggested scale: 1:500 – 1:5000.

Debris avalanches - Debris avalanches are drive by gravity and usuallymove down valleys, although in some cases they are able to surmounttopographic barriers. They may travel over 30 km, and cover an area>1,000 km2. They may produce tsunamis in coastal areas. They can occurduring volcanic eruptions or when a volcano is not actively erupting.Depending on their scale, debris avalanches may destroy everything in theirpath. They are one of the most hazardous but least common volcanicevents. Suggested scale: 1:500 – 1:5000.

Tsunamis - Tsunamis may affect large areas which may be many kilometres(thousands) away from their source. Suggested scale: 1:5000 – 1:50000.

Volcanic gases - The hazard related to volcanic gas emission is usuallyconfined in a limited area around the volcano but further away from thevent these gases can become dissolved in atmospheric clouds to produceacid rain and mist, which affect vegetation and eyes and respiratorysystems, and corrode metal building materials. Suggested scale: 1:500 –1:5000 and: 1:5000 – 1:50000.

Volcanic earthquakes - Usually volcanic earthquakes are characterised byhigh-frequency seismic signals generated at shallow depth below a volcano.Although they could be highly energetic, volcanic earthquakes can be feltonly at a limited distance from the epicentre. Suggested scale: 1:500 –1:5000.

Lightning strikes - Although not normally depicted on hazard maps,atmospheric effects in the eruption column would generate frequentlightning strikes to about the radius of the ballistic trajectories. Suggestedscale: 1:500 – 1:5000.

2.5 Data availability – typology, format – GIS structureGenerally, GIS are planned to set up a decision support system for volcanicrisk mitigation (hazard, value, vulnerability and risk map assessing), toprovide suitable tools during an impending crisis and to provide a basis foremergency plans.


B.V-13

The structure of GIS carried out by Pareschi et al. (2000), aimed atmitigating and managing the volcanic hazard and risk of the Vesuvius andEtna, is articulated in five main thematic layers: digital elevation models,digital images from satellite or aircraft, vector data on natural and artificialfeatures, population density, hazard maps. Concerning these latter, theavailable hazard maps, either simple sketches or based on a quite detailedbasis, represent a sub-division of the land affected in the past with variousfrequencies by destructive volcanic phenomena.


In Europe, the hazard maps for Campi Flegrei caldera (Orsi et al., 2004) arethe most recent and advanced products carried out. The volcanicphenomena considered are the tephra fallout (figure 1), articulated in fourhazard levels and the pyroclastic currents (figure 2), articulated in twohazard levels. The volcanic hazard map (figure 3) results from theoverlapping of these maps at the local scale (1: 5,000 – 1: 50,000).

3 Elements at risk and exposureWe can define elements at risk those threatened by hazardous volcanicphenomena in a definite area and exposure the measurement of structuraland non structural (population, properties, economic facilities, publicstructures, duties) elements at risk.

Figure 1: Tephra fallout hazard map of the CampiFlegrei caldera; Source: Orsi G. et al. (2004)


B.V-14

Figure 2: Pyroclastic currents hazard map of the CampiFlegrei caldera; Source: Orsi G. et al. (2004)

Figure 3: Volcanic hazard map of the Campi Flegrei;Source: Orsi G. et al. (2004)

Referring to the EU and non-EU examined studies about volcanic riskassessment, two main scales are used: regional scale and local scale.


B.V-15

3.1 Typology of elementsAt regional scale (1:50.000 – 1:500.000), most of the studies considerresident population as the main element at risk.

In the quantitative approach to assess the risk in Montserrat (MVO, 1998)people is considered as the only “element” at risk to evaluate individual andsocietal risk level through a quantitative risk assessment approach.

Other studies also include infrastructures (transport lines and terminals andservice distribution networks), major economic sectors and economiccentres, strategic facilities (hospitals, public rescue teams building, schools,etc…), environmental resources and territory.

Environmental resources could be considered elements at risk not only forthe presence of the main hazard, volcanic hazard, but even for the threatrepresented by secondary hazards, for example toxic releases or hazardousspills that could occur as result of a volcanic phenomenon (Trople, 2002).

Historical and architectural heritage is not generally included amongelements at risk. Even if it is not possible to implement mitigation actionsfor these goods against the majority of the volcanic hazardous phenomena,it could be done against some others (e.g. ash falls) or against secondaryminor hazardous events (e.g. toxic releases or hazardous spills).

Figure 4: Facilities vulnerable to volcanic hazards;Source: Trople T.L. (2002)

Even if mitigation actions are mainly oriented at minimizing theconsequences of volcanic hazardous phenomena for people’s health, actionsaimed at safeguarding historical and architectural heritage could represent avalid cultural and social starting point for the rehabilitation of urbansettlements in case of a volcanic disaster.


B.V-16

Exposure has been differently assessed at regional scale in order todifferent mapping outputs.

Some studies simply aim at overlaying hazard maps with elements at riskwithout measuring exposure. Applying an overlaying method, Trople (2002)produced a map of the Enumclaw and Buckley area, sited near the MountRainer volcano, to identify intersections of critical facilities with risk areas(figure 4).

Cronin and Neal (2002) made a risk assessment and mapping for theTaveuni volcano on the homonymous island of the Fiji.

A map concerning elements at risk considered for risk assessment has beenproduced (figure 5). In this map hazard levels are not indicated, but justmajor infrastructures and the prevalently farmed areas are localized. Aboutthe former, main villages, hospitals, schools and tourist accommodationsare indicated. About linear infrastructures, roads and water pipelines(existent and in project) are reported. Some other peculiar elements, to beconsidered in case of emergency, have been directly described on the maplike the airport, some water bores, the main fuel storage site and thecommunication centre.

Other studies aim at defining single risk map resulting from joining value ofhazard, exposure and vulnerability. In this case it is necessary to relateelements at risk to only one parameter.

Figure 5: Main infrastructural elements on Taveuni ;Source: Cronin S.J. et al. (2002)


B.V-17

For example, structural and non structural elements could be related totheir economic value. In order to work out a volcanic risk map and toforecast the cost of volcanic activity in Guatemala (Green et al., 1995), thenumber of resident people has been converted in economic value throughthe Gross Domestic Product (GDP) per capita; the value of the territory hasbeen measured through land use value per hectare. They consider eveninfrastructures but they do not specify how to measure their value. In figure6 there are some examples of the maps produced for this study.

Figure 6: Exposure of the Volcano Santa Maria; Source:http://www.geo.mtu.edu/volcanoes/santamaria

About measurement of population at risk, some studies simply consider thenumber of residents in the threatened area (Trople, 2002) (Baxter et al.,1998).

An European study on the Campi Flegrei caldera (Alberico et al., 2001)measure the exposure combining census data about population density andan urbanization index that indicates the ratio between built area and totalarea of a community (figure 7).

Referring to local scale detailed (1:500 – 1:5.000), volcanic hazardousareas are mostly studied through an emergency approach and just in a fewcases through a risk assessment approach.

Among those, Lavigne (1999) developed a lahar hazard micro-zonation andrisk assessment in Yogyakarta city, Indonesia. Located 25 km south ofMount Merapi, one of the most active volcanoes of the world, Yogyakartacity (> 500,000 people) is a centre exposed at an increasing volcanic risk:the summit dome of Merapi has continuously grown since 1984; theinstability of the volcano flanks is potentially growing and they could resultin debris avalanche; pyroclastic flow deposits, emplaced during and afterthe 1994 dome-collapse, could flow away as lahars, through the urban area,even because of hard rainfalls. In spite of all that, the urban areapopulation is growing 2% a year.


B.V-18

Combined geomorphological investigation, lahar flow simulation were usedto delineate areas exposed at volcanic lahar risk in Yogyakarta. The hazardmap on which risk assessment has been developed is at 1/2000 scale.

Figure 7: Urbanization index of Campi Flegrei.; Source:Alberico I. et al. (2002)

Elements at risk considered are houses, public buildings (schools, mosquesand prayer houses), infrastructure equipment (stores, market, warehouse,asphalt roads and bridges) and hectares of tilled land. The average value (inUS dollars) of each element at risk has been used to estimate anapproximate value of likely loss. Furthermore, population living in lahar riskprone areas has been simply counted.

Produced hazard and risk maps at 1/2000 scale for highly populated areasare available at the Merapi Volcano Observator.

The choice of working with 1/2000 scale allow to produce maps clearlyunderstandable by the public, that is able to recognise their own houses.Those kind of maps are very useful even for decision makers (local andregional authorities).

In Europe, studies have been developed to assess the vulnerability ofstructural elements to some volcanic hazardous phenomena (especiallyabout the interaction with pyroclastic flows) (Zuccaro, 2004). Single


B.V-19

buildings are then considered as elements at risk without considering atleast the identification of their value (economical, architectural, etc.).


4.1 Definition of vulnerability and/or consequenceMost of the experiences carried out on volcanic risk assessment are basedon the definition of “risk” formulated by Fournier d’Albe (1979). Thisdefinition was developed by UNDRO (1991) and extended to all naturalhazards as follows: Risk = (Element at risk) *(Natural hazard *Vulnerability). Referring to this definition, Vulnerability is interpreted asdegree of loss between 0 and 1 of an element at risk, or of a number ofsuch elements, resulting from the occurrence of a natural phenomenon of agiven magnitude. Generally, elements at risk are population, buildings andinfrastructures, economic activities, public services in a specific area. Thisdefinition does not automatically represent a mathematical formula, but itexpresses the integration of different dimensions in the risk assessment.

Although this definition is the most common interpretation of thevulnerability concept, in some experiences we find some attempts to definevulnerability as the propension of all exposed elements to be damaged byvolcanic activity. In such experiences this interpretation is referred tobuildings or infrastructures and to territorial or urban systems.

Vulnerability will change as the type of volcanic activity changes (i.e. fromeffusive to explosive). For example, referring to buildings andinfrastructures, these experiences define volcanic vulnerability as thepropension to the damage due to pyroclastic and lava flows andaccumulation of volcanic ashes. Only in few cases vulnerability is linked toterritorial and urban systems. In detail, vulnerability is related to the sum ofbuilding and infrastructure vulnerability and to the characteristics of themorphology of settlements which can determine functional crisis anddifficulty of exodus or help for the population.

It is useful to underline that in some cases the vulnerability of buildings andinfrastructures is referred to seismic risk, intending the earthquake as themain display of volcanic activity. In this report we will exclude seismicvulnerability because it is treated elsewhere in the ARMONIA Project.

Finally, we have to remark that in some cases territorial or urban systemvulnerability is analysed referring to the damages due to the unsatisfactorypreparation to manage the emergency induced by volcanic activity.

In synthesis, we can define volcanic vulnerability of a territorial or urbansystem as the predisposition of the system to damage due to volcanicphenomena. Referring to the different kind of damages caused by a volcaniceruption, we have different types of vulnerability:

− vulnerability of building stock, roads, emergency facilities;

− urban or territorial vulnerability, which expresses the tendency of a cityto functional crisis due to an inadequacy of spatial organization ofdifferent urban areas (urban textures);


B.V-20

− organizational vulnerability referred to the tendency of urban systemstowards a functional crisis due to the lack of coordination among differentinstitutional organizations involved in the emergency management.


Vulnerability is effectively a multidimensional characteristic and it dependson many factors (such as environmental, physical, technical, economic,social, political, institutional and cultural). These factors are notindependent and interact resulting in a global vulnerability. We will stressour attention only on physical and functional characteristics of the exposedterritorial systems and on the damages to population.

The few European and international experiences which are focused onvolcanic vulnerability assessment are developed at two main scales:territorial and site scale. Besides, volcanic vulnerability is mainly related tothe phenomena of lava and pyrochlastic flows, and accumulation of ashes.

At regional scale (1:50,000 – 1:500,000) exposure and vulnerability are notclearly distinguished because all the elements at risk are considered astotally vulnerable. Sometimes vulnerability is calculated upon the populationdensity and the GDP of the regions.

At local scale (1:5,000 – 1:50,000), vulnerability is often expressed as thedegree of loss between 0 and 1 of elements at risk. The most importantelements exposed to the volcanic risk are: population, buildings andinfrastructures, economic activities, public services.

At local detailed scale (1:500 – 1:5,000) we have studies focused on thevulnerability of buildings referring to the impact of pyroclastic flows and tothe accumulation of ashes.

Referring to the local scale (1:5,000 – 1:50,000), in the studies carried outfor Montserrat Volcano (MVO et al.,1998) after that volcano activityescalated in June 1997, vulnerability is interpreted as the expected damage.The assessment of volcanic vulnerability of the population takes intoaccount that vulnerability may arise from varying circumstances: e.g.daytime or night-time occurrence of the event; any alert or warning lead-time which might be possible (rapidity of event onset, or scientists warning,for instance); proximity or occupation of houses (especially for tephra fall),etc. These vulnerability factors have been set to range from 1.0 to 0.5,depending on the considered scenario, where the higher figure indicatesthat no effective reduction in vulnerability is allowed. In this study differenthazard scenarios and risk assessment were defined using the Monte Carloevent probability trees. For each event scenario carried out in this study, afurther estimate includes population vulnerability factor referred to thelimited protection which might be gained from buildings etc. Thevulnerability factor could be reduced by mitigation measures.

For tephra fall hazards, a numerical approach has been adopted forassessing percentage impact on each settlement. Estimates of clast sizesand accumulation rates of tephra from numerical models have been used inconjunction with studies of roof resistance to both loading of material andclast impacts. The number of roof collapses can then be calculated basing


B.V-21

on the knowledge of building stock distribution for each area, and casualtyrates can be estimated. A constant vulnerability factor and fatalities factorhave been used for all airfall hazard scenarios.

Referring to pyroclastic flows, an european research project, Human andStructural Vulnerability Assessment for Emergency Planning in a FutureEruption of Vesuvius using Volcanic Simulation and Casualty Modelling(1998 - 2000), worked out a model to estimate potential impacts onbuildings, the likely numbers of deaths and injuries in the hazard zones,using

data on a well-defined pyroclastic flow events and data on the resistance ofthe openings of the buildings (position, size, design and performances).

Referring to the accumulation of volcanic ashes, building vulnerability hasbeen defined using the relationship between the different attended ashloads, determined with the historical deposits, and the resistance of buildingcoverages.

In some recent experiences, methods for the assessment of buildingvulnerability to volcanic hazard have been extended to territorial and urbanscale and only few of them defined some urban vulnerability parameters.

In the study carried out by Spence, Baxter and Zuccaro (2004) referring tothe pyroclastic flows, the volcanic vulnerability of the building stock in theVesuvius’ area is defined starting from a survey of buildings and urbanenvironment. Pyroclastic flows are a serious threat to life for the inhabitantsof settlements near volcanoes with an explosive eruption history. However,buildings can provide protection to people trapped by these flows.

This analysis identifies the incidence of characteristics and elements likelyto improve building vulnerability, and classifies the building stock, basing onthe period of construction, load-bearing vertical structure, floor structure,roof structures, condition of maintenance of structures, factors affectingvulnerability (poor connection between vertical and horizontal structure,openings that are in poor condition, etc.). The survey emphasisedparticularly the number, location, size and type of openings of the majorclasses of the local building stock. Subsequently, this survey formed thebasis for estimates of the probable impact of the pyroclastic flow on theenvelope and internal air conditions of typical buildings. A number ofdistinct ways in which human casualties would occur were identified, andestimates of the relationship between casualty rates and environmentalconditions for each casualty type (due to failure of openings, infiltration ofhot gases and ash, being out of doors) were carried out. Casualty rateswere used to estimate the proportions of occupants who would be killed orseriously injured for the assumed pyroclastic flow scenario in the Vesuvianvillages studied, and their distribution by distance from the vent. Finally,some risk factors for casualties were identified and ranked in order tomitigate their impact in the eruption scenario.

Referring to the scale 1:500 – 1:5,000, a study on the interaction ofpyroclastic flows with building structures (Zuccaro and Ianniello, 2004) hasbeen carried out. In this study a fluid-dynamic model has been applyed tosimulate pyroclastic flow-urban settlement interactions. The model is basedon partial differential equations of mass, momentum and turbulent energyintegrated using a finite element method on a 3-D domain. The model was


B.V-22

tested on an urban sector of Torre del Greco, municipality very close toVesuvius. The results show a partial shielding effect of structures closer tothe volcano, on structures behind them as well as a total pressure waningpattern along the mean direction of the pyroclastic flow. The aim of thestudy is to supply a first investigation of the sheltering effect and of thepyroclastic flows action on tall buildings facing Vesuvius, and also to find anevaluation of possible pressure decay factors. The influence of these factorson the volcanic vulnerability of buildings is crucial to evaluating reliabledamage scenarios.

Studies and researches performed in the draft of the Vesuvius’ NationalEmergency Plan, an advanced experience in the topic of vulnerabilityassessment, are very interesting because they synthesize many of thementioned approaches.

In a first phase, the study of vulnerability carried out in 1994-1995 for thedraft of the Vesuvius’ Preliminary Emergency Plan defined, within the 18municipalities of the Vesuvius’ belt, 120 microzones to which a vulnerabilitylevel referred to the concentration of vulnerable buildings was assigned.Besides the parameters connected to the structural characteristics of thebuildings, other two parameters were considered: the housing qualitativelevel and the characteristics of coverages of buildings.

The first one was aimed at putting in evidence critical zones from a socio-economic point of view, the second one was aimed at assessing theresistance of the coverages to the accumulation of volcanic ashes. Besidessome factors of urban vulnerability were assessed referring to such areas,such as:− population density;− relationship between height and width of the buildings;− width of the roads;− presence of barriers;− distance from the life-lines.

This survey was enough detailed for the activities of planning connectedwith the draft of the preliminary of the Vesuvius’ Emergency Plan, but it wasnot sufficiently detailed for the draft of the Communal Plans of CivilProtection.

At the end of 1998, after a national survey (LSU - DPC Project), thepreviously analyses have been integrated with analyses of greater detail. Allthe data and the information have been integrated into a GIS, which in thefuture will be integrated and modified with further detailed analyses locallyproduced. In detail, four cartographies have been drawn for eachmunicipality:− seismic vulnerability;− typological-structural distribution (MSK);− height of the buildings;− characteristics of the coverages or horizontal building structures.

Within Vesuvius’ National Emergency Plan of the 1995, an investigation wasperformed on the seismic vulnerability of the urban settlements of theVesuvius’ area.

The eruptive scenery foresees a seismic activity of middle intensity(maximum magnitudo 4-5 and a degree of damage inferior to the VIII


B.V-23

Mercalli degree). In this hypothesis the damages should interest onlymasonry buildings. Investigation has almost exclusively been turned to suchbuilding typology. In the meanwhile the ability of an urban settlement toface the emergency, called "urban environment vulnerability", has beenassessed in a quantitative way.

The total number of buildings in the Vesuvius’ area is very high. Insofar, theNational Group for the Defense from the Earthquakes (GNDT), has set amethodology for a quick survey for the assessment of seismic vulnerabilityof all the building structures of the inhabited centers and the evaluation ofthe "urban environment vulnerability".


Generally, functions used for the vulnerability analysis are simple. In factvulnerability is interpreted as the degree of loss between 0 and 1 of theelements at risk. At regional scale all the exposed elements are supposed tobe totally vulnerable. At local scale (1:5,000 – 1:5,000) we have somedifferences referring to the kind of volcanic phenomenon considered.

For example, vulnerability of the population exposed to the lava flows(Blong, 1984) is nearly equal to 0, considering the low speed of lava flowsand the ability to act with evacuation plans. On the contrary, because of thedestructive aftermath of lava flows, it can be assumed a vulnerability valueequal to 1 for all land use classes and any man-made structures.

Also in the Volcanic Risk Map worked out for Santa María, Guatemala,vulnerability measures a percentage (0-100%) of the value likely to be lostin a given event. In this study the percentage of attended loss is related todifferent kinds of natural phenomena connected to the volcanic activitywhich can occur in different areas.

At local scale (1:5,000 – 1:5,000) the elements considered in thevulnerability assessment are non structural elements like population,activities (types of land use) and structural, like building stock andinfrastructures. Data sources are referred to the cartographical,demographic, economic and land use data provided by national agenciesand regional administrations.

At local detailed scale (1:500 – 1:5,000), we find risk assessments whichhave both demographic and economic data obtained from national, localagencies, both more detailed data on physical and structural characteristicsof buildings, mainly derived from direct surveys.

At this scale, vulnerability functions are mainly referred to buildings.Vulnerability of buildings (and infrastructure) is mainly expressed throughthe building age, load-bearing vertical structure, floor structures, roofstructures, condition of maintenance of structures, type of connectionbetween vertical and horizontal structure. In particular, for the volcanicvulnerability of buildings to pyroclastic flows the assessment is referred tothe number, location, size and type of openings of the major classes of localbuilding stock. In same cases we find a statistical relationship betweennumber of roof collapsed and levels of ash loads for a well-defined typologyof building stock. All these functions are carried out in very detailed studies


B.V-24

and at the present a simplified function useful for the harmonization processis not available.

4.2.2 Examples of vulnerability maps and legends

As mentioned previously, vulnerability is interpreted as the degree of lossbetween 0 and 1 of an element at risk, resulting from the occurrence of anatural phenomenon linked to volcanic activity. For this reason it is not easyto find vulnerability maps because they coincide partially with the exposuremaps. At regional scale (1:50,000 – 1:500,000) we have maps related tothe population density and to the GDP product because all the exposedelements are considered as totally vulnerable.

At local scale (1:5,000 – 1:50,000), we find the exposure maps related tothe population density, GDP, land use, infrastructures. However, in somecases maps related to the vulnerability of building stock to volcanic riskhave been carried out. For example, results collected for the draft of theVesuvius’ National Emergency Plan have been provided both undernumerical form and both trough maps. Five levels of seismic vulnerabilityhave been defined (nothing - low - average - high - very high). Theinvestigation has included all the public and strategic buildings. Besidessome maps related to the "urban environment vulnerability" have beenworked out. These maps define three levels of vulnerability of the urbanenvironment (low, average and elevated).

At local detailed scale (1:500 – 1:5,000) in depth analyses on thevulnerability of urban sectors to the pyroclastic flows or to the accumulationof ashes have been set up but, at the present, well-defined maps are notavailable.

4.3 Most common damage potentialsThe damages to the elements of a territorial system due to the volcanicactivity are dependent from the type of natural phenomena considered. Forexample, lava flow is a relevant threat for buildings and infrastructures andactivities but not for people. Other phenomena connected with an explosivevolcanic eruption, in particular pyroclastic flows, are a serious threat topeople. Pyroclastic flows are the most dangerous of the volcanic hazardsbecause of their rapid onset and potential destructiveness. They can engulfhuman settlements with little warning, and can cause large numbers ofhuman casualties as well as destruction of buildings and infrastructure. Forany particular type of building, the degree of correlation between the near-ground characteristics of the flow and the type and degree of damage isdefined.

Referring to the accumulation of volcanic ashes the damages generallyconsidered are building coverage collapses and road interruptions.

However, at the local scale (1:5,000 – 1:50,000), the main damages are:potential deaths or damage to buildings or infrastructure, rather than toeconomic activities. At the local detailed scale, the considered damage ismainly referred to deaths, injuries and building and infrastructures damage.


B.V-25

5 Analysis of risk

5.1 Definition of riskReferring to the definition formulated by Fournier d’Albe (1979) anddeveloped and extended to all natural hazards by UNDRO (1991), “risk” isthe result of the integration of different components: hazard, elements atrisk and their vulnerability.

Thus, volcanic risk is the possibility of harmful consequences, or expectedloss (of lives, people injured, property, infrastructure, livelihoods, economicactivities, etc.) resulting from interactions between volcanic eruption andanthropic environment. Risk is the quantitative (or qualitative) expressionor measure of expected damages and it is evaluated as a result of volcanichazard which affects a territory exposed to it and its vulnerability.Furthermore, the concept of damage gets wider and wider including, atshort and long term, physical damage, social and economical losses and theloss of natural and anthropic resources too which represent the identity of aterritory.

5.2 Methodologies for risk assessmentReferring to the state of the art of the volcanic risk assessment, till nowfocus is mainly on hazard assessment and the other components of volcanicrisk assessment, exposure and vulnerability, related to the anthropicsystems are not investigated in depth.

There are only few experiences related to the volcanic risk assessment.These research projects and practices are developed at two main scales:the territorial and the building scale.

Volcanic risk assessment can be of course related to different kind ofnatural phenomena connected with the volcanic activity. For example, riskconnected to tephra fallout can be computed as the product of hazard,vulnerability to different ash loads and value. This latter has beensometimes considered as 1 where buildings are present, 0 otherwise. In thiscase, risk is expressed in terms of number of probable building collapsesand people injured or died.

At local scale (1:5,000 – 1:50,000), risk is expressed in terms of loss oflives or people injured, damage to buildings or to economic activity.Sometimes the attended damage is expressed through its economic value.Risk assessments are based on both demographic and economic dataobtained from national, local agencies, both on data referred to physical andstructural characteristics of buildings.

At local detailed scale (1:500 – 1:5,000), risk assessments consider bothdemographic and economic data obtained from national, local agencies,both more detailed data on physical and structural characteristics ofbuildings, mainly derived from direct surveys. At this scale, risk is mainlyexpressed in terms of deaths, injuries and building damaged or collapsed.


B.V-26

5.2.1 Qualitative and quantitative methods, direct and indirectrisk

Risk assessment is mainly based on quantitative methods and is focused onthe direct risk that comes from the volcanic activity to the exposedelements. The most common scale of analysis is the local scale between1:5,000 and 1:50,000.

At regional scale, the study carried out by Cronin and Neal (2001) onTaveuni, Fiji, provides a qualitative assessment of volcanic risk combininghazard information (both from maps and volcanic processes knowledge)with the location and nature of the vulnerable elements.

The risk map singles out the areas characterized by the highest combinationof vulnerable elements and degree of hazard. The elements considered arepopulation, infrastructures, land use.

Risk to population is considered low, due to the period of warning probablyafforded by pre-event seismicity and to the low explosivity of most events.By contrast, the risk to infrastructures, buildings and agriculture is high insome parts of the island. Combining hazard information with population anddevelopment data highlights these areas.

The most relevant impact for Taveuni is the long-term economic impactcaused by the combination of: tourism losses, crop destruction, long periodsof limited access to arable land, isolation of some areas from transport tomarkets, and effectively permanent destruction of the agricultural potentialof some land.

At local scale (1:5,000 – 1:50,000), the study on volcanic risk assessmentin Vesuvius’ area (Lirer and Vitelli, 1998) considers risk as monetary lossdue to lava flow, by extracting the built-up areas (urban and rural areas),classified according to the different house densities and multiplied by amean economic value, evaluated for each single municipality. Initially, bothlava flow hazard and land use maps were combined to single out all areassubjected to risk. The resultant map shows the spatial variation of theeconomic value, assigning a mean market value for each single municipalityin Italian lira per unit area (lira/km2) of the builtup areas exposed to lavaflow hazard. The characteristics considered are the housing density and thelack of agricultural and rural zones.

The evaluation of long-term volcanic risk from pyroclastic flows in CampiFlegrei (Alberico et al., 2001) considers a relative volcanic risk obtained bythe analysis of the value of the population distribution. An urbanizationindex, articulated into five classes, indicates the ratio between the built areaand the total area of the community. Naples’ area has the highest valuesand the municipalities of the internal area have a low index. The risk mapshave been obtained by the product of fatal impact maps and urbanizationmap.

Researches carried out on the Furnas Volcano in the Azores were focused onbuilt environment. In particular, the studies analysed the relationshipsbetween building type, construction quality and tephra fall/seismic hazards,basing on GIS overlay techniques (Chester et al., 2002). Furthermore, theyanalysed the communications, mainly between scientists, decision makersand civil defence officials (Pomonis et al., 1999).


B.V-27

In the studies carried out for the Montserrat after June 1997 (MVO etal.,1998), the main objective of the risk assessment was the calculation ofthe probability of fatality figures resulting from the different types oferuptions that could occur within a period of six months after the event. Theanalysis does not include estimates of injuries (which, for emergencyplanning purposes, might be inferred from fatality numbers). The number ofpeople impacted depends on the spatial extent of pyroclastic flows andsurges, tephra and ash falls etc., which in turn depends on the scale of theeruptive events. In the assessment, experts defined ranges of populationimpact factors for each identified population by each event scenario,expressed as impact percentages (which are again turned into equivalentBeta probability distribution function). Further additional vulnerabilityfactors have been introduced for taking into account the vulnerability whichmay arise from varying circumstances (day-time or night-time occurrence;alert or warning lead-time; proximity to or occupation of houses, etc.). Forsome of these factors the study has carried out semi-deterministicnumerical modelling and a detailed probabilistic assessment ofconsequences. For example, the transport of clasts and the dangers topeople of bombardment by clasts have been so modelled. Referring to thenon-European experiences, Volcanic Risk Map for Santa María, Guatemalacombines volcanic hazard zonations with four layers of economic andpopulation data, represented through four thematic maps:

− Standard of Living (adjusted GDP per capita, based on crowding, housingconditions, basic sanitation, availability of potable water, access to basiceducation and basic needs);

− Population Density (number of people/hectare);− Infrastructure (kilometres of highways, electrical distribution and

transmission lines);− Land use (dollar value/hectare of all economic activities contributing to

Guatemalan GDP).

The risk map is expressed in terms of total cost of the volcanic activity forGuatemalan government: Volcanic Risk = Value * Vulnerability * Hazard.

Value is the Standard of Living * Population Density + Infrastructure +Landuse (dollars/hectare); Vulnerability measures a proportion of the valuelikely to be lost in a given event; Hazard is the probability of a given areabeing affected by a potentially destructive process within a given period oftime. The volcanic risk map for Santa Maria calculated the economic impactof an active volcano in dollar terms.


B.V-28

5.2.2 Functions of risk analysis

Generally, the basic function used to calculate the risk is Volcanic Risk =Value * Vulnerability * Hazard. Well defined functions for risk analysis arenot available.


Montserrat Volcano Observatory carried out several volcanic risk maps forSoufriere Hills Volcano (figure 8). In the risk map carried out in September1997 three Zones have been defined: Exclusion Zone (in green), CentralZone (orange) and Northern Zone (yellow). In the Exclusion Zone entranceis not allowed except for scientific monitoring and National Security Matters.The Central Zone is a residential area only: all residents are on heightenedstate of alert and are required to have rapid means of exit 24 hours perday. The Northern Zone is an area with lower risk, suitable for residentialand commercial activities.

The volcanic risk map for Santa Maria (figure 9) defines nine risk classesexpressed in economic terms, as mentioned previously. However this mapis not very simple to understand.

Figure 8: Volcanic risk map for Soufriere Hills;Source:http://www.geo.mtu.edu/volcanoes/west.indies/soufriere/govt/miscdocs/rskzone.html


B.V-29

Referring to the study on the Vesuvius’ area carried out by Lirer and andVitelli (1998), a risk map articulated into five levels of risk has been carriedout (figure 10): Very High, High, Medium, Low and Very Low. The riskclasses are expressed in gray tone. This risk map was produced at thesame scale of 1:50.000.

The study carried out by Alberico et al. (2001) on the Campi Flegrei’s areadefines a risk map (figure 11) articulated into five risk classes: Very High(red), High (yellow), Medium (orange), Low (Green), Very Low (Gray).

The volcanic risk map for Tavenui (figure 12) (Cronin and Neal, 2001) isbased on the volcanic hazard and the population distribution andinfrastructure on the island. This map is suitable for general disastermanagement work and public awareness purposes. For detailed land-useplanning, building site investigations, and engineering projects, furthermore-detailed site investigations are required. The map is developed atregional scale and defines four levels of risk: High, Moderate/High,Moderate/Low, Low.

Figure 9: Volcanic risk map for Santa Marìa; Source:http://www.geo.mtu.edu/volcanoes/santamaria


B.V-30

Figure 10: Volcanic risk map for Vesuvius’ area; Source:Lirer and and Vitelli, 1998.

Figure 11: Volcanic risk map for Campi Flegrei; Source:Alberico et al., 2001.


B.V-31

Figure 12: Volcanic risk map for Tavenui, Fiji; Source:Cronin and Neal, 2001.

6 Risk managementTaking into account: perception, tolerance, acceptability, mitigationmeasures, preparedness, response, recovery

Risk management includes all the measures aimed at facing a catastrophicevent, from preventive mitigation measures to rescue and safety actions.

Among the former, we could find regulatory and physical measures toreduce expected losses, people information actions, analysis of riskperception, etc; among the latter, we can find mostly emergency plans.

Not for all the volcanoes a complete system of actions for risk managementhas been developed: in some contests only rescue and safety actions havebeen carried out, while in others both the aspects have been faced.

In the following lines, some peculiar experiences concerning volcanic riskmanagement have been illustrated.


B.V-32

Vesuvian area, Italy.

Because of its peculiar volcanic hazard conditions, an in-depth riskmanagement system has been developed in the Italian Campania Region,for the Vesuvian area, one of the higher volcanic risk area in the world: anintegrated system of actions concerning urban planning, social behavioursand emergency phase programming exists.

Concerning the management of rescue and safety phases, the first releaseof the “National emergency Plan for Vesuvio volcanic area” has beendeveloped in 1995 and it has been updated in 2001. A further updating is inprogress.

It is a “national” emergency plan because the Vesuvian emergency has tobe treated with extraordinary means. In fact, the number of peoplecertainly to be evacuated (about 600.000) and the wideness of the areainterested (200 km2) requires “national” resources.

The plan defines the expected volcanic eruption. The Vesuvian area is thendivided in three different zones (red, yellow and blue) according to thedifferent volcanic hazardous phenomena they are exposed to.

The most dangerous zone is the red one (composed by 18 municipalities ofthe Province of Naples) which spreads immediately around the volcanocrater. It is the most dangerous zone, because it potentially could be floodby white-hot pyroclastic flows, running at high speed, destroying everythingon their path. The yellow zone is less dangerous than the red one.Potentially ashes and lapillus falls characterize this zone. Because of thisphenomena an excessive overload on the roofs up to collapse is expected.The blue zone is a part of the yellow zone, but it has a higher hazard level.It includes the area that could be subject to floods and inundations, as wellas ashes and lapillus falls, because of its peculiar hydrogeologicalcharacteristics.

For the residents of the red zone, the plan describes rules and actions toevacuate. In particular, each Italian Region has been coupled to amunicipality of the red zone. This coordination allows a better logistic andadministrative management of the crisis. Where necessary, people to beevacuated from the yellow and blue zone, will be allocated in safe areas ofthe Campania Region itself.

The effectiveness of the “National emergency Plan for Vesuvio volcanicarea” would be higher if appropriate administrative actions aimed atmodifying urban shape, damping settlements and implementing suitableexodus ways are carried out.

To this aim, Campania Region administration issued many acts concerningthose topics.

The regional “Vesuvia” project, “Vesuvio Risk Mitigation Program”, is awhole of initiatives started in 2003 (see also Regional Ordinance n°2139,B.U.R.C. n°31 14/04/03) involving all the administrative levels in anintegrated land use management. Several targets must be pursued in thered zone. Decreasing residential density is one of these targets, especiallyconcerning people who is not living there for many years. To chase thisobjective, a voluntary movement of the population is required and moneyincentives are fixed for those who want to buy a house in out from the red


B.V-33

zone (see also Regional Ordinance n°2145, B.U.R.C. n°31 14/04/03).Another target to pursue is the total blockage of new residence building andthe implementation of exodus ways and infrastructures to facilitate peoplemoved in secure areas to come back and work in the red zone. Theseactions are described in Campania Region Act n°21 of the 21/12/2003,“Town-planning rules for municipalities of the Vesuvian area prone tovolcanic risk” (Legge Regionale Campania n°21 del 21/12/03, “Normeurbanistiche per i comuni rientranti nelle zone a rischio vulcanico dell’areavesuviana”). Moreover, a massive repression program has been developedagainst illegal buildings (see also Regional Ordinance n°2149, B.U.R.C. n°3114/04/03). Conversion of existing residential volumes into industrial,touristic, tertiary facilities and public interest facilities is favoured throughmoney incentives from P.O.R. Campania 2000-2006.

Success of the “Vesuvia” project hardly depends from populationinformation. Actions have being carried out to acquaint red zone people andto let them accept the mitigation program.

Popocatepetl Volcano, Mexico.

In Mexico, the General Direction of the Civil Defence developed the CivilDefence Operative Plan of Popocatepetl Volcano (CENAPRED, 1996), aplanning tool aimed at helping population exposed to volcanic risk.

Popocatepetl Volcano raises in Central Mexico, 55 kilometres east of MexicoCity and 45 kilometres west of the Puebla metropolitan area. More than 30million people live within view of the volcano and hundreds of thousands ofpeople would be endangered by hazards associated with a large explosiveeruption of the volcano.

This Plan, like the Vesuvian one, is still based on an emergencymanagement approach.

It aims at the management of the exodus of people living in the areas atrisk indicated by the existing “Volcanic risk map”, previously elaborated bythe CENAPRED.

The “Emergency planning map” (figure 13) is the main document of theplan. It divides each of the three risky zones of the “Volcanic risk map” ineight sectors considering different eruptive scenarios. The consequentzoning of the risk area in 48 zones allows to communicate opportunely thealert state of the volcano and if evacuation or protection mechanisms haveto be implemented.

Referring to this, tasks for each of the bodies involved in the emergencyphase are clearly defined. Furthermore, the temporal coordination is ruledby a “Volcanic alert traffic light” managed, at the federal level, by theGeneral Direction of the Civil Defence, supported by CENAPRED, that alsomonitors the Volcano.

The Green colour of the alert system corresponds to the normality time.People can have normal life. This is a preparation time to define theemergency routes and the safe open spaces to recover the population. TheYellow colour means the necessity of strict communications among people,authorities and media to know the right actions to do in case of emergency.Shifting to red colour is followed by acoustic signals that indicate the


B.V-34

population to run immediately to the nearer gathering centre to haveinstructions from authorities to evacuate.

After that, another task of the General Direction is to evaluate operativeplans developed by the Federal States belonging to the risk area, trying toharmonizing and to finance them through the National Disaster Found.

Concerning the post-disaster phases, a relevant body operating in this planis the Reconstruction Committee; it is aimed at developing preventivestudies to assess damages and elaborating programs to allow a completerehabilitation of the affected areas.

The Plan is structured on the three Mexican government levels (Federal,State and Municipal). The four states involved in the plan at Federal levelare Mexico, Morelos, Puebla y Tlaxcala State, and, at State level, a moredetailed Operative Plan has been developed for the Mexico State.

About maps, at regional scale, the Emergency Planning Map (figure 13) isavailable on the Operative Plan internet site in which the 48 zones of theentire volcanic risk area are shown. The urban areas and the main roadnetworks are indicated. The number of people at risk in Mexico State isshown in a table coupled with the map.

Figure 13: Emergency Planning Map of Popocatepetl;Source:http://www.edomexico.gob.mx/sgg/planoperativo


B.V-35

Figure 14: Exodus and rescue roads of Popocatepetl;Source:http://www.edomexico.gob.mx/sgg/planoperativo

Another regional scale map produced for the Mexico State, concerns exodusand rescue roads (figure 14) with the location of hotels to accommodatepeople evacuated.

Related to this map, Popocatepetl Operative Plan also includes tablesconcerning, for each municipality of the Mexico State, availableinfrastructures, exodus and rescue roads, temporary accommodations forrefugees, hospitals and gathering areas.

For 16 municipalities belonging to the Mexico State risk area, easy-to-readmaps are available (an example is shown in figure 15). Contents of thismaps concern the urban area of a single municipality, the gathering point,the main exodus route and some peculiar existing activities (hospitals,churches and schools). The scale is not specified, but it could be addressedto a local scale, depending from the extension of the urban area.

Risk perception.

Mitigation actions and emergency and rescue operations would be moreeffective if people perceive the real risk they are prone to and they areaware of the existing means and ways to deal with the problem.

From this point of view, risk perception is one of the most important factorsin natural risk management. Understanding how risk perception varies allowus to motivate people into react to hazards in a correct way.

Not many studies on this topic have been carried out for Europeanvolcanoes. One of the most recent research work in Europe (Ricci, 2004)aims at analysing, for the first time in Italy, risk perception among peopleliving nearby the two most important Italian volcanoes, Vesuvio and Etna.


B.V-36

Figure 15: The first exodus step for San JuanTlacotompa Ecatzingo village. Source:http://www.edomexico.gob.mx/sgg/planoperativo

The objective of the research work was to point out links between riskperception and some factors as volcanic phenomena knowledge, communitysense, auto-efficacy, trust in scientific community and authorities and othersocio-demographic aspects.

On the 2000 questionnaires delivered, just 516 were filled. In particular,referring to the Vesuvian area, they were distributed to population living inthe red zone (the most dangerous as defined in the National emergencyPlan for Vesuvio) and population living in four municipalities included intothe yellow one, the most damaged during the last eruption; in the Etneanarea, questionnaires has been filled by people from the four municipalitiesexposed to lava flows, ash falls and earthquakes in the recent volcanicevents.

Living nearby a volcano in constant eruptive activity influences directly riskperception. Research results confirm it.

In fact, Vesuvio, quiescent volcano, represents one of the three mainproblems for the Vesuvian community just for the 7% of people living in thered zone and for no one from the yellow one. On the contrary, Etna, afrequent active volcano, represents the third major problem for the 16% ofEtnean people.

Moreover, while people from Etna is well informed on the hazardousvolcanic phenomena, population from the Vesuvian red zone are concernedfor the beginning of a new volcanic activity and they are not aware of themeans and ways to deal with problem.

Concerning non European countries, many studies have been developedabout volcanic risk perception in New Zealand.


B.V-37

Paton et al. (2001) developed a study aimed at assessing communityresilience to volcanic hazard consequences resulting from the 1995 and1996 eruptions at Ruapehu volcano, New Zealand. The eruptions throughCrater Lake generated lahars down valleys occupied by ski lifts and downseveral rivers. Therefore, an interesting objective of the study was to assessthe relative contributions of volcanic and economic threat to community riskperception.

550 questionnaires were distributed in June, at the beginning of the 1997ski season, and again, in September, at the end of the season. Only 92people filled the June questionnaire and just 52 of them completed thesecond one.

After the success of the sky season, the economic threat decreased whilethe volcanic threat remained the same. The conclusion of the authors is thatrespondents perceived economic and volcanic hazard threats differently,and attributed a greater importance to the former. In order to that, we canargue that risk perception is influenced by the relationship between hazardeffects and personal businesses rather than by volcanic activity itself. Thelesson learnt is that risk communication, to be more effective, has topresent mitigation measures not only in relation to risk reduction and tovolcanic activity in itself, but even to the safety of the economical activitiespotentially hit.

One of the most recent report about volcanic hazard risk perception studiesin New Zealand has been done by Finnis and Johnston (2004). They reportanalysis carried out about Auckland volcanic field, Mount Taranaki andMount Ruapehu. Concerning the latter, a useful study confronting riskperception variation before and after the Mount Ruapehu eruption of theOctober 1995 was possible. Two communities living near the volcano havebeen investigated, Whakatane and Hastings; only the latter has beeninvolved in the eruption and covered by ashfalls. Questionnaires concernedvolcanic phenomena impacts on personal safety and on daily life, theperception of threats and the way to face them.

After the eruption, Hastings people enhanced their risk perception whileWhakatane people still perceived the same high risk than before. Althoughthat, before and after the eruption, 66% of Whakatane interviewed peopletake some protective measures, while the number of Hastings people doingthat decreased from 63% to 53%. This implies that increased riskperception does not necessarily lead to better preparedness. This means a“normalization bias” phenomenon in people that, faced a minor volcanichazard, think to be able to face a more hazardous one.


HazardA property or situation that in particular circumstances could lead to harm.More specific, a hazard is a potentially damaging physical event,phenomenon or human activity, which may cause the loss of life or injury,property damage, social and economic disruption or environmentaldegradation. Hazards can be single, sequential or combined in their origin


B.V-38

and effects. Each hazard is characterised by its location, intensity andprobability.

ExposureThe economic value or the set of units potentially hit by each hazard withina given area. The exposed value is a function of the type of hazard.

VulnerabilityVulnerability is the propension of a person, a group, a community or anarea to be damaged by hazardous events. In a broader sense, vulnerabilityis defined as a set of conditions and processes resulting from physical,social, economical and environmental factors, which increase thesusceptibility of a community to the impact of hazards. Vulnerability isdetermined by the potential of a community to react and withstand adisaster, e.g. its emergency facilities and disaster organisation structure(coping capacity).

RiskRisk is the possibility of harmful consequences, or expected loss (of lives,people injured, property, infrastructure, livelihoods, economic activities,etc.) resulting from interactions between volcanic eruption and anthropicenvironment.

Risk perceptionRisk perception is the overall view of risk held by a person or group andincludes feeling, judgement and group culture.

8 References

Alberico I., Lirer L., Petrosino P., Scandone R. (2002), “A methodology forthe evaluation of long-term volcanic risk from pyroclastic flows in CampiFlegrei (Italy)”, in Journal of Geolgical Society, London, 116, 63–78.

Blong R.J. (1984), Volcanic hazards: a source book on the effects oferuptions, Academic Press, Orlando.

CENAPRED, Centro National De Prevencion de Disastres (1996), PlanOperativo del Volcan Popocatepetl, Mexico, January 1996, [internet]Available from<http://www.edomexico.gob.mx/sgg/planoperativo/principal.html>[accessed, 09/03/2005];

Chester D.K., Dibben C. J.L., Duncan A. M. (2002), “Volcanic hazardassessment in western Europe”, in Journal of Volcanology andGeothermal Research, 115, 411-435;

Finnis K., Johnston D., Paton D. (2004), “Volcanic hazard risk perceptions inNew Zeland”, in Tephra, June 2004. [internet] Available from<http://www.mcdem.govt.nz> [accessed, 31/01/2005];

Fournier d’Albe E.M. (1979), “Objectives of volcanic monitoring andprediction”, in Journal of Geolgical Society, London, vol. 136, 321–326;

Green B. D., Rose W.I. (1995), “Volcanic risk map for Santa Maria,Guatemala: What can risk maps contribute to volcanic hazardcommunications?”, in International Union Geodesy and Geophysics XXIGeneral Assembly, 2-4 July 1995, Boulder, Colorado, USA. [internet].


B.V-39

Available from<http://www.geo.mtu.edu/volcanoes/santamaria/volcrisk/mosaic.html>[accessed 31 January 2005];

Lavigne F. (1999), “Lahar hazard micro-zonation and risk assessment inYogyakarta city, Indonesia”, in GeoJurnal n°49, pp. 173-183, KluwerAcademic Publishers, 2000;

Lirer L., Vitelli L. (1998) “Volcanic Risk Assessment and Mapping in theVesuvian Area Using GIS”, in Natural Hazards, 17, 1–15, KluwerAcademic Publishers;

Montserrat Volcano Observatory (MVO), Baxter P.J., Woo G., Pomonis A.(1998) Preliminary Assessment of Volcanic Risk on Montserrat [internet].Available from <http://www.geo.mtu.edu> [accessed 20 December2004];

MVO, Montserrat Volcano Observatory (1998), Preliminary assessment ofvolcanic Risk on Montserrat, January 1998, [internet] Available from<http://www.geo.mtu.edu/volcanoes/west.indies/soufriere/govt/>[accessed, 09/03/2005];

Orsi G., Di Vito M.A., Isaia R. (2004), Volcanic hazard assessment at therestless Campi Flegrei caldera, Bull Volcanol (2004) 66:514–530,Springer-Verlag;

Pareschi M.T., Cavarra L., Favalli M., Giannini F., Meriggi A. (2000), “GISand Volcanic Risk Management”, in Natural Hazards n°21, pp. 361–379,Kluwer Academic Publishers, Netherlands;

Paton D., Millar M., Johnston D. (2001), “Community Resilience to VolcanicHazard Consequences”, in Natural Hazards n°24, pp. 157–169, KluwerAcademic Publishers, Netherlands;

Pyle D.M. (2000), “Size of volcanic eruptions”, in Sigurdsson H. (ed.)Encyclopaedia of Volcanoes, Academic Press;

Pomonis A., Spence R., Baxter P. (1999), “Risk assessment of residentialbuildings for an eruption of Furnas Volcano, Sao Miguel, the Azores”, inJournal of Volcanology and Geothermal Research, 92, 107-131;

Ricci T., Davis M.S., Pacilli M.G. (2004), “Percezione del rischio vulcanico alVesuvio e all’Etna”, in GNV INGV – Civil Defence 200-2003 finalassembly, Naples 20th – 22nd December 2004, Napoli, Italy, postersession;

Spence R. J.S., Baxter P. J., Zuccaro G. (2004), “Building vulnerability andhuman casualty estimation for a pyroclastic flow: a model and itsapplication to Vesuvius”, in Journal of Volcanology and GeothermalResearch, 133, 321-343;

Trople T.L. (2002), “Volcanic hazard vulnerability assessment of theEnumclaw – Buckley, Washinghton Community” in Minnesota GIS/LISConsortium 12th Annual Conference & Workshops, 2-4 October 2002,Duluth, Minnesota, USA. [internet]. Available from<http://www.gis.smumn.edu/> [accessed 31 January, 2005];

Zuccaro G., Ianniello D. (2004) “Interaction of pyroclastic flows withbuilding structures in an urban settlement: a fluid-dynamic simulationimpact model”, in Journal of Volcanology and Geothermal Research, 133,345-352.


B.V-40

Appendix:Operational Standards for Risk Assessmentaimed at Spatial Planning

1. Minimum standard (simplified model) for hazardmapping aimed at a legal directive

Hazard assessment of a volcano, aimed at mitigating the related risk, ispossible only if its past behaviour and present state is known. Furthermore,to forecast the type of eruption in short-mid terms, considering thestructural setting of the volcano, all the types of eruptions generated by thevolcano have to be known, and the structural conditions in which theactivity has occurred, have to be reconstructed. It is also very important todefine the compositional evolution of the erupted magmas and theirrheology.

To assess the volcanic hazards to which an area is exposed, it is essential atleast a) to reconstruct the past history of a volcano, b) to define the time ofits entire life which can be taken as reference to hypothesise its futurebehaviour, c) to define the variable type of eruptions, d) to reconstruct thevariable phenomenologies of each eruption, e) to determine the physicaland chemical characteristics and of the erupted magma of eachphenomenology, f) to reconstruct the areal distribution of the eruptedproducts of each phenomenology, g) to identify the transport and depositionmechanisms of the erupted material, h) to evaluate the impact on theterritory of each phenomenology; i) to reconstruct stratigraphy and arealdistribution of surface gravitational movement deposits and their impact onthe territory. These objectives can be pursued by carrying outstratigraphical, sedimentological, structural, geomorphological,volcanological, petrological and geochronological studies, integrated witharchaeological investigations and analysis of historical documents.

1.1. Various methodologies related to the 3 assumed scales ofanalysis in the light of a potential harmonisation of hazardmaps, based on a multi-hazard perspective

(See paragraph 2.2 of the main document).

2. Minimum standard (simplified model) for riskmapping aimed at spatial planning

Referring to volcanic risk, we have to underline the needs of spatialplanners dealing with volcanic risk. At regional scale, the aims of spatialplanning are the definition of priority risk areas for the implementation ofthe mitigation measures and the definition of Guide-lines for the re-allocation of activities and population and for the diction of an EmergencyNetwork. It is also necessary to define the sites useful to allocate newsettlements, infrastructures and industrial sites.

At local scale (urban level), it is necessary to set up measures for buildingvulnerability mitigation, urban vulnerability mitigation and local emergency


B.V-41

network organization. It is also necessary to define the best location fornew settlements, infrastructures and industrial sites.

At local detailed scale (1:500 – 1:5,000) the most relevant objective is toimprove the resistant of residential building, infrastructures and publicfacilities.

2.1. Multi-risk assessment perspective as element of theStrategic Environmental Assessment

Referring to the EU Directive 2001/42/EC and from a multi-risk analysispoint of view, the following aspects have to be considered (Greiving, 2004):probability, duration, frequency and reversibility of the effects; cumulativenature of the effects; risks to human health or environment (e.g., due toaccidents); magnitude and spatial extent of the effects; value andvulnerability of the area. The first and the second point of this list arereferred to the characterization of the volcanic hazard made in the first partof this report. The third point is referred to the list of potential damagesmade in the paragraph 4.3.

The fourth point concerns the extent of the effects of the plans/programs,object of the SEA; we must consider two aspects: first, potential damagechains due to natural hazard impacts that could improve losses and reduceenvironmental and human resilience and, second, how the plan/programcould interfere with risk management actions (emergency management andmitigation actions).

The last point, value and vulnerability of the area affected by volcanicactivity is developed in the next paragraph. In fact, according to this pointwe have set up minimum standards for volcanic risk articulated on exposedvalue and its vulnerability referring to the different scale of analysis definedin the ARMONIA project.

Volcanic risk analysis proposed as minimum standard is interpreted as thedefinition of expected losses and the vulnerability as the possibility of theexposed elements to face the volcanic impact, according with proceduralobligations of SEA.

2.2. Methodologies, functions and outputs

Referring to the general objectives of spatial planning dealing with volcanicrisk and to the current methodologies for volcanic risk assessment andmapping we can suggest 3 simplified methodologies and outputs related tothe assumed scales of analysis and representation of risk.

However, we have to underline that the scale of the analysis is stronglydependent from the extension of areas exposed to volcanic hazard. Thisarea is quite variable: in Italy, for example, the exposed area of Strombolihas an extension of 12 km2, the Vesuvius’ area of 1400 km2 and the Etna’sarea of 3850 km2.


B.V-42

Regional scale (1:500,000 – 1:50,000)

At this scale, for a quantitative risk analysis we can consider only populationdensity on administrative base and GDP per capita of the regions (50/50percent relationship), according with the ESPON 2006 Project 1.3.1“Hazards”. All the elements in a hazard zone are supposed to be vulnerable.Risk is calculated in a relationship of 50% of hazard level and exposurelevel.

However, sometimes it can be useful to set up a qualitative analysisdefining the volcanic risk overlapping the hazard levels with four levels ofpopulation density and layers referred to the presence/absence ofinfrastructures (roads and railways), strategic facilities (hospitals,infrastructure terminals, regional and local administration offices, safety andrescue centres) and main infrastructures (main roads, railways, power andwater distribution main lines) and simplified land use (agricultural andurban ranked for number of inhabitants). This kind of hazard map is moreuseful for emergency planning purposes.

We suggest to define four levels of risk (Very High, High, Medium, Low) anda legend of coloured areas corresponding to a black hatch legend, for asimple printing and dissemination of the maps.

Local scale (1:5,000 – 1:50,000)

At this scale, a useful risk analysis has to consider two levels of assessmentand mapping.

A first simplified level above all the territory prone to volcanic hazard. It isuseful to set up guide-lines and to define priority areas for risk mitigation. Asecond analysis level for the urban areas. This latter is useful to defineactions for reducing urban and building vulnerability and to define a localemergency network.

For the first level of analysis we can take into account as exposed elementspopulation and land use activities.

For the population, we can consider four levels of people density onmunicipal base. For land use, we can consider urban, rural, agricultural,forest, and other natural areas.

Vulnerability depends on the type of volcanic phenomenon considered.

The most common volcanic phenomena considered in the volcanic hazardassessment are lava flow, pyroclastic flows and volcanic ashes and tephrafall. Vulnerability of the population exposed to the lava flows and ashes canbe considered equal to 0, but vulnerability of people exposed to pyroclasticflows depends on many experimental factors. In this case we can considerthis vulnerability equal to 1.

The vulnerability to all volcanic phenomena of all land use classes and anyman-made structures can be considered equal to 1.

All vulnerable exposed land use classes can be express with thecorresponding economic value and classified into four level. For the built-upareas we can classify the urban and rural areas according to the differenthouse densities and multiplied by a mean economic value evaluated foreach single municipality. The risk can be defined overlapping the levels of


B.V-43

vulnerable people exposed and the economic value for each kind of volcanicphenomenon considered.

Referring to the second level of analysis suggested, we underline thenecessity of this level of analysis for the high risk urban areas. Although thislevel is not until today strongly investigated, we suggest a more detailedrisk assessment.

First of all, the statistical analysis referred to population and to urbanactivities can be carried out on census unit administrative base instead ofthe municipal base.

Beyond the population density, other elements considered in the exposureare: economic activities, industrial activities, infrastructures and buildingstock. For each element we can define a vulnerability level from 0 to 1referred to a specific volcanic phenomenon.

In particular, referring to the pyroclastic flow and to the accumulation ofvolcanic ashes, we have to consider the different structural typologies forthe building stock. According with Spence, Baxter and Zuccaro (2004), wecan classify three types of buildings: Rubble stone load-bearing masonry,squared rubble masonry and poor quality reinforced concrete, squaredmasonry with concrete floors and good-quality reinforced concrete framestructures. For the vulnerability to the pyroclastic flow we have to considerthe typologies of openings and the resistances of the structural verticalelements. The study of Spence, Baxter and Zuccaro (2004) defines somerelationships between the typology of buildings and their probableresistance to the pyroclastic flow. Also for volcanic ash load it is necessaryto link the building typology to the roof resistance. From this point of view,it is useful to set up different vulnerability map referring to the differentvolcanic phenomena considered.

Also at this scale, we suggest to define four levels of risk (Very High, High,Medium, Low) and a legend of coloured areas corresponding to a blackhatch legend, for a simple printing and dissemination of the maps.

Local detailed scale (1:500 – 5,000)

At this scale, until today we have only very deepened studies on singlebuildings and it is not possible and useful for planning aims to suggestsimplified methodologies for the vulnerability of buildings andinfrastructures.


B.VI-1

B.VI Meteorological extreme events and climatechange

Author: Juergen Kropp, PIK

1 Introduction.............................................................. 3

2 Physical definition of climate change ......................... 4

2.1 Typology...................................................................................4

2.2 Intensity and Magnitude of Anthropogenic Climate Change.............5

2.2.1 Assessment of Extreme Events: Typology, Intensity, Severity

and Magnitude .................................................................................7

3 Hazard assessment.................................................. 13

3.1 Definition ................................................................................ 13

3.2 Current methodologies for analysing and representation of risks

(hazard) with respect to temporal scales.............................................. 14

3.3 Dynamical hazard – climate change effects................................. 14

3.4 Problem of scale ...................................................................... 14

3.5 Data availability – typology, format – GIS structure..................... 14

3.6 Examples of hazard maps and legends referred to assumed scales 15

4 Elements at risk and exposure ................................. 15

4.1 Typology of elements ............................................................... 15

5 Analysis of vulnerability .......................................... 15

5.1 Definition of vulnerability .......................................................... 15

5.2 Methodologies for assessment related to structural and non-

structural elements at risk.................................................................. 16

5.2.1 Functions for vulnerability/consequence analysis ..................... 16

5.2.2 Examples of vulnerability maps and legends ........................... 16

5.3 Most common damage potentials............................................... 25

6 Analysis of risk........................................................ 25

6.1 Definition of risk ...................................................................... 25

6.2 Methodologies for risk assessment............................................. 25

6.2.1 Qualitative and quantitative methods, direct and indirect risk ... 26

6.2.2 Functions of risk analysis ...................................................... 26

6.2.3 Examples of risk maps and legends ....................................... 26

7 Risk management.................................................... 26

8 Analysis of natural risks in relation to climate change27


B.VI-2

9 Conclusion............................................................... 28

10 Glossary of all keywords.......................................... 28

11 Appendix: Operational Standards for Risk Assessmentaimed at Spatial Planning............................................. 31

11.1 Minimum standard (simplified model) for hazard mapping aimed at

a legal directive................................................................................. 31

11.2 Various methodologies related to the 3 assumed scales of analysis

in the light of a potential harmonisation of hazard maps, based on a

multi-hazard perspective .................................................................... 32

11.3 Minimum standard (simplified model) for risk mapping aimed at

spatial planning................................................................................. 33

11.4 Multi-risk assessment perspective as element of the Strategic

Environmental Assessment ................................................................. 33

11.5 Methodologies, functions and outputs......................................... 33

12 References .............................................................. 33


B.VI-3

1 IntroductionClimate Change impacts and meteorological extremes are closely

interconnected. Therefore, the state of art regarding these two tasks are

combined in one single report. With respect to ARMONIA’s aims it is planned

to provide a harmonized multi-risk mapping for policy advice. This aim is

consequent, since for historical times weather and climate play an

important role in the daily life of humankind. However, comparing climate

related disasters and meteorological extremes with other disasters one have

to consider that the scales of planning authorities and climate researchers

widely differ in both space and time. This, however, is not the only difficulty

for a harmonization. While climate change can be considered as a smooth

(long-term) trend (cf. Sects. 2, 2.2) extreme events are (singular) “peaks”

on this trend. One major question of ARMONIA is how influences a possible

climate change the local probability and occurrence of (distinct)

meteorological extremes. Although major progress in the understanding of

climate has been made, it is mainly uncertain how climate change affects

local weather variability and the occurrence of extremes. This is the reason

why the IPCC provides only more general assertions regarding this issue

(cf. Tab. 1, cf. discussion in Sect. 2.2ff, in particular, Sect. 2.2.1.2ff) and

has decided that the forthcoming Fourth Assessment Report will have an

explicit focus on extreme events.

Currently three areas of deficit knowledge are identified: (i) lack of high-

quality long-term data (cf. Sect. 2.1.1), (ii) climate models are not designed

to forecast extremes and their inherent scales are commonly too coarse,

and (iii) statistical methods used for extreme value assessment are

commonly unsuitable (new approaches, mainly in Europe, are under

investigation, cf. Sect. 2.2.1.1). Having this in mind it is clear why, regional

extreme value assessment becomes quite difficult, in particular, with

respect to a local mapping. Due to these circumstances in climate change

research the vulnerability concept is the most prominent concept for

assessing climate related risks (cf. Sect. 5). It extends the one-dimensional

focus on extreme events, e.g. whether we will have more heavy rains and

subsequently floods expected in region X due to climate change or whether

heat waves becoming more frequent in e.g. Europe by an additional

question: are modern societies sensitive against these changes and if yes,

are they prepared to cope with this changes? This extension is consequent,

because any weather related adverse/beneficial effect might have impact on

societies.

However, any strategy to analyse these questions depend on the regional

settings, since in certain regions we have a distinct inventory and possibly

decision makers may have different scopes (cf. Sect. 5.1, and example in

Sects. 5.2.2ff). Regarding ARMONIA this implies that we have to come to a

decision which kind of questions should be answered for a case study

region. Nonetheless, also in this case the achieved integrated mapping will

be exemplary. Before we can start with such a task a systematic

stocktaking of the natural and socio-economic inventory must be

undertaken for this region, i.e. determine which data are available, which

data are useful indicators, how to value assets, what should be the

prognostic time horizon? Subsequently, integrated measures can be

defined, which might be useful for a multi-hazard risk mapping (regarding


B.VI-4

possible uncertainties and methodological problems, cf. Sect. 2.2.1,

2.2.1.1). This is one the reason, why in climate change research scenarios

are used. They allow to derive storylines for distinct regions in the case of a

business of usual, worst or best case scenario.

Directly related to these problems are the impact of climate change on

other natural risks (cf. Sect. 7). It is clear that any natural risk can be

enforced and sometimes also mitigated by climate change. An analysis of

these impacts must at least fit the preconditions as mentioned above, i.e.

for any kind of risk, e.g. landslides, the (local!) natural settings and

potential changes have to be examined.

2 Physical definition of climate change

2.1 Typology

By definition weather and climate prediction are mutually exclusive. The

atmosphere is a chaotic system which is unstable with respect to small

perturbations of “initial conditions”. This sets a prediction limit of 20 day for

weather forecasts. Climate in contrast is defined in terms of statistics of

weather, i.e. it is defined as the 30yr average of weather. Therefore,

climate prediction – and thus climate change – concerned with slow

changes in the statistical properties of weather beyond the time scale of 20

days. In other words climate change is a process not a singular event (or

hazard). Focussing with more details on this process one have to distinguish

between “natural” and anthropogenic climate change. The first is an

everlasting process in earth’s history (paleoclimatic changes, cf. Fig. 1).

Figure 1: Temperature reconstruction from the 18O content

obtained from GRIP, NGRIP ice cores (Greenland) for the last

125,000 years. For an assessment of human induced climate

change one have to consider time dimension. Source: after

NGRIP members (2004).

Short-term cyclic changes can be related to, e.g., cycles within the solar

radiation (11 yrs, e.g. CURRIE & O’BRIEN 1990; Hale cyle: 22yrs; HALE 1924;

Gleissberg cycle 78-80yrs, GLEISSBERG 1955, 200yrs, THOMPSON 1990),

which have been detected in many meteorological variables including

temperature and rainfall. These short-term cycles are superimposed by

several mechanisms of short- to mid-term gravitional forcing (e.g. lunar

tidal cycles) which are chronologically interlocked in a commensurable way.

Long-term cycles are mainly due to changes of the earth’s orbit caused by

celestial-mechanical disturbances (CROLL 1875, MILANKOVITCH 1930: e.g.


B.VI-5

100,000 and 400,000 yrs eccentricity cycle; 41,000 yrs tilt cycle; and the

precessional cycle with a periodic component of 19,000 – 23,000 yrs). All

these forcings had and have – as shown by paleo-climatic research – a

strong influence on earth’s climate (MENDE & STELLMACHER 2001). Discussing

climate change in the modern context the maximal time span examined is

the Holocene (cf. Fig. 1). During this phase only slight changes in

temperature distinguish between favourable and unfavourable climate

phases (Fig. 1). Due to increasing temperature at the end of the

Weichselian ice age evolution of humankind increases. In a first warm

period of the Holocene, for example, agriculture was developed (8000 yrs

BP) and the ancient Sumerian culture evolves (5000 yrs BP). During a

period which had similar temperatures as at present the Vikings settles on

Iceland and Greenland (800-1000 AD). In the “Little Ice Age” (1350-1850

AD, Maunder Minimum: 1675-1715 AD), where the temperature was

approx. 1 °C lower than the most episodes during Holocene, migrations

from north to south and North-America, crop failures, famines, and

epidemics in Europe are documented (cf. LOZAN 2001). If we are discussing

human induced climate change we are focussing only the last 150 yrs in

which anthropogenic activities have evolved increasing influence on earth’s

atmosphere. During this time the global mean temperature is increasing,

with a first maximum about 1940, and with respect to our knowledge from

the past this could threaten earth’s integrity as well as humankind itself to a

broad extent.

2.2 Intensity and Magnitude of Anthropogenic ClimateChange

The definition of climate change used by the IPCC includes both, natural

variability and human induced change (cf. Sect. 5), whilst the UN

Framework Convention on Climate Change (Fccc) defines that climate

change is only that part of the change which is due to human interference.

This discrepancy sounds a bit artificial, since it is neither simple to separate

both parts, nor both are a one-to-one superposition. In the first assessment

report of the IPCC (1990) was asserted that the anthropogenic climate signal

could not clearly detected. The second report (IPCC 1995) concludes that a

balance of evidence suggests discernible human influence on climate, whilst

in the TAR (IPCC 2001) was stated that “there is new and stronger evidence

that most of the warming observed over the last 50 years is attributable to

human activities”. Recent progress in the analysis of empirical time series

data allows reliable assessments of global climate behaviour since the end

of the 19th century. An increase of the global mean temperature of about

0.6 °C is likely evident. For the future model outputs imply that the largest

warming will concentrated between 40° - 70° N (winter and spring) over

the continents (cf. Fig. 2).


B.VI-6

Figure 2: Near surface temperature distributions computed by

nine different coupled atmospheric-ocean general circulation

modes at time of a doubling of CO2 concentration. Source:

Hasselmann (2002), for details regarding the model runs cf.

IPCC (2001).

Nevertheless, a question of major interest in climate research is: How large

is the influence of humanity on climate? This is difficult to answer, since the

detection of anthropogenic interference in observation data is hampered by

superimposed natural variability of climate ( detection and attribution

problem). In common approaches the verification of human induced climate

change is a two-step strategy: (i) first, one have to identify climate change

as an anthropogenic signal and (ii) second, one have to examine whether

this signal exceeds natural variability to a sufficiently high level of statistical

significance or not. For this task several modelling runs are performed by

usage of different models including either natural or anthropogenic forcing

and both. HASSELMANN (2002) states that the observed climate signal is,

indeed, strong enough that a detection and attribution becomes feasible

(for methodological details cf. HASSELMANN 1997, BARNETT et al. 1999). The

results of these examinations1 show that only the combination of natural

1 An example is the current discussion on the so-called “hockey stick curve” which was

introduced by MANN et al (1998). This most quoted temperature reconstruction implies that thenorthern hemisphere temperature was not higher during the last 1,000 yrs than today. Someclimate sceptics have blamed the Mann group for unsuitable methods and analytical errors andhad presented a curve indicating that the highest temperature already occurred in the 15

th

century (MCINTYRE & MCKITRICK 2003). MANN et al (2004), however, have applied somecorrections which supports his original assertion. In addition, recently presented results basedon improved methods show that, indeed, exists some uncertainty, but that northern hemispheretemperature is characterized also by a steeper increase during the last 150 yrs as indicated bythe Mann et al. 1998 results (VON STORCH et al. 2004).


B.VI-7

and anthropogenic forcing can explain the observed temperature increase in

the 20th century (CUBASCH 2004).

In general, the detection of the anthropogenic climate signal is of specific

interest, since further concepts, i.e. extreme value definition rely on the

idea that extremes are events beyond the normal/natural range of systems

variability. However, despite of enormous improvements in our

understanding of earth’s climate, a long history of empirical climate and

weather monitoring the exact extent and nature of changes in our climate

remains uncertain and is part of the scientific debate, in particular, with

respect to their regional expression (cf. Sect. 2.2.1).

2.2.1 Assessment of Extreme Events: Typology, Intensity,Severity and Magnitude

Discussing climate change from the point of view of hazard assessment and

under the aims and scope of the ARMONIA project it is quite difficult to

provide a useful assessment strategy. Climate change per se is not a

hazard (cf. Sect. 3.1). Nevertheless evidence exists that climate change

have an influence on the occurrence and magnitude of weather extremes

(cf. IPCC 2001, IPCC 2002, STOTT et al. 2003, MEEHL & TEBALDI 2004). The

biggest problem in the analysis of extremes is the lack of high-quality long-

term data (regarding the methodological problems cf. Sect. 2.2.1.1) which

allows to assess the last 100-150yrs. Regarding the prognosis of weather

extremes one have to rely on model simulations. This, however, is

interconnected with a variety of difficulties. First, climate models are not

designed to forecast extreme events, since they calculates climate variables

for more or less large grid cells (model resolution) (cf. MCGUFFIE &

HENDERSON-SELLERS 1996). Second, extreme weather events occur mainly

on smaller scales. Thus simulation scenarios must be downscaled, which

may be combined with various uncertainties related to both (i) model

scenarios and (ii) downscaling algorithms. Thus, although climate models

(e.g. development of regional models) have been improved over the time,

they have still limitations regarding the simulation of extreme events

(NOGUER et al. 1998, MEEHL et al. 2000).

Changes in severe weather due to climate change will have particular

impacts on society and the natural environment. This, however, is exactly

one of the foci of the ARMONIA project. The most robust conclusions of the

IPCC are listed in Tab. 1, but the IPCC concluded that the analysis of

extreme events faces two major challenges: (i) lack of adequate data and

(ii) scale, i.e. the small temporal and spatial scales of extremes mismatch

the scales resolved by models and that of validating data (IPCC 2002).


B.VI-8

Change in phenomenon Confidence in observedchanges (latter half 20th

century)

Confidence in projectedchanges (during 21st

century)

Higher maximum

temperatures and more hot

daysa over nearly all land

areas

likely Very likely

Higher minimum

temperatures, fewer cold

days and frost days over

nearly all land areas

Very likely Very likely

Reduced diurnal temperature

range over most land areas

Very likely Very likely

Increase of heat indexb over

land areas

Likely, over many areas Very likely, over many areas

More intense precipitation

eventscLikely, over many northern

hemisphere mid- to high

latitude land areas

Very likely, over many areas

Increased summer

continental drying and

associated risk of drought

Likely in a few areas Likely, over most mid-latitude

continental interiors (lack of

consistent projections in

other areas)

Increase in tropical cyclone

peak wind intensitiesdNot observed in the few

analyses available

Likely over some areas

Increase in tropical cyclone

mean and preak

precipitation intensitiesd

Insufficient data for

assessment

Likely, over some areas

ahot days refers to a day whose maximum reaches or exceeds some temperature that is

considered as critical for nature and humanity. Actual typical values are 32 °C, 35 °C, 40 °C;bheat index refers to a combination of temperature and humidity that measures human

comfort;cfor other areas there are either insufficient data or conflicting analyses;dpast and future changes in tropical cyclone location and frequency are uncertain.

Table 1: Estimates of confidence in observed and projected

changes in extreme weather and climate events. Source:

IPCC (2001) Third Assessment Report, Chapter 9.

Thus, on a workshop on changes in extreme weather and climate events

organized in Bejing 2002 had formulated future issues in this context (IPCC

2002). The most relevant for the ARMONIA project are:

1. Definition of extremes2 and useful indicators? The definition of

extremes is not only a statistical task, perception partly determines

what is an extreme event or a dangerous trend and what is not.

2. Improvement of data availability: up to now globally only 1,200-

1,400 weather stations report monthly means of minimum and

maximum temperature. It is planned to extend these number to

approximately 5,000 stations for the Fourth Assessment Report

(FAR).

2 Statistical methods are normally used to assess extreme events (cf. Sect. 2.2.1.1). In climate

research an extreme is not only describable by single meteorological variables, e.g.temperature, since a drought, for instance, is characterized by high temperatures and sparseprecipitation during a distinct time span. Thus, meteorological extremes are often complex andneed an integrated measure as, e.g. established by the U.S. who has developed a so-called“Climate Extreme Index” combining temperature, drought and precipitation measurements withthe size of an affected region (KARL et al. 1996).


B.VI-9

3. How well do models simulate extremes, how confident these

projections of severe weather, and can the uncertainties quantified?

4. How can projected changes in extremes most usefully characterized

for infrastructure planning?

Further, the FAR will have an explicit focus on climate/weather extremes.

Current analytical efforts imply an increasing likelihood on both sides the

warm and the cold tails of the temperature distribution function (cf. Tab.

1). Of particular interest, however, are also so-called complex extremes (cf.

footnote 2). Complex extremes might have a variety of impacts on socio-

economic systems, in particular, in areas which are not able to cope with

such events due to an reduced adaptive capacity. Very recently research

efforts that try to relate extreme weather situations to changes in large

scale circulation pattern adepted growing appreciation.

2.2.1.1 Methodological considerations

In global change research the application of extreme value theory underlies

several misconceptions. A statement from the famous statistician Emil

GUMBEL (1941) this makes clear in an impressive way: “In order to apply

any theory we have to suppose that the data are homogeneous; i.e. that no

systematical change of climate and no important change in the basin have

occurred within the observation period and that no such changes will take

place in the period for which extrapolations are made.”

This statement implies that stationarity and the IID (identically and

independently distributed) assumption are essential for any type of extreme

value assessment. Two strategies are commonly used. First, the generalized

extreme value distribution (GEV) as a limiting distribution for Gumbel,

Frechet, and Weibull distributions (three types- or Fisher-Tippett-theorem).

Second, the peak over threshold (POT) approach, which is a point process

representation and considers a Poisson process for the occurrence of

threshold exceedances and uses the generalized Pareto distribution (GPD)

for the excesses.

In the analysis of empirical data several of the above mentioned

assumptions are not given, since the view of climate change includes a

trend and, for instance, daily measures of temperature and river run-off are

not statistically independent. Therefore, standard theory does not apply

under a changing climate and also not to statistical downscaling (IPCC

2002). Thus, it exists the urgent need to develop new techniques, e.g. for

fitting of extremal distributions with time varying parameters (KATZ et al.

2002) or the usage of “declustering strategies” guaranteeing statistical

independence. However, this new approaches are rarely applied up to now

and although progress has been made in the recent years the statistics of

extremes is still a field of active research (cf. COLES 2001). However, the

awareness that trends are likely and that trends influence extreme value

statistics is not new. Several approaches were made to separate trends

from variability with a sufficiently high level of statistical significance (e.g.

KALLACHE et al. 2005). The discovery that river run-off and temperature are

long range-correlated has introduced further difficulties in the current

methodologies (Fig. 3, 4) (KALLACHE et al. 2004). But it has also initiated

new and unconventional analytical strategies (BUNDE et al 2004, BUNDE et

al. 2005). Summing up, research on extreme value assessment is an


B.VI-10

ongoing process. Recent progress sounds promising, but new concepts

sometimes are not applicable in practice due lack of data.

Fig. 3: Upper panel: autocorrelation function for the river run-off at

Achleiten/Danube, Germany (daily anomalies, 100 yrs) showing

that significant correlations can be detected for a time span larger

than 1,000 days, the dashed red lines indicate the confidence

interval. Lower panel: Monte Carlo simulation studies showing the

dependency of estimates for the 0.99 quantile (e.g. 100 yr flood)

from the length of time series, type of correlation, and choice of

method; left block approach, GEV, right POT/GPD approach .

Source: Kropp et al. 2005 (unpublished).

2.2.1.2 Impact of Climate Change: Precipitation, River Run-Off,and Floodings

There is no clear evidence yet of changes in the hydrological cycle that are

caused by climate change. Nevertheless, with respect to theoretical

considerations there is an evidence that an increase in precipitation can be

expected with an ongoing global warming, since the water vapor saturation

value of air increases by about 8% for 1 °C temperature increase.

Increasing temperature also leads to enhanced evapotranspiration and

hence intensification of the hydrological cycle. The IPCC (1996) estimates

that a global temperature increase of approx. 2 °C may increase potential

evapotranspiration up to 40%. Recent model runs confirm a general


B.VI-11

increase in precipitation, in particular, in the mid- to high latitudes (MEEHL

et al. 2000). Calculations show that a CO2 doubling will increase global

mean precipitation of about 4%. At present, however, the data do not allow

to answer the question whether the precipitation did increase substantially

due to the 0.6 °C temperature global mean temperature increase or not.

Anyhow, in several regional studies an increase in precipitation during the

last 100 yrs were observed (USA, Canada, Northern & Western Europe)

(WATSON et al. 1998). Also in the most of west, central and eastern Europe

regions the precipitation increased, whilst this is contrasted by a decrease in

the Mediterranean region during the second half of the 20th century

(FRAEDRICH & SCHÖNWIESE 2002).

Fig. 4: Trend assessment for the Danube catchment (120

river gauges) by using a new developed trend test (Kallache

et al. 2005). It is shown that the trend behaviour shows large

differences, but also some clusters can be observed. Source:

Kallache et al. 2005b (unpublished).

Recent examinations show a likely increasing trend in river run-offs, but

already in a same catchment large difficulties exists (cf. Fig. 4). These

differences might be related to local changes in weather regimes or to slow

and long-term changes of physical properties in an observed catchment. In

addition, in case of persistence common statistical methods could provide

misleading results if unsuitable methods are used (see above). The IPCC

(2002) mentioned that regarding flood assessment the best statistical

methods are not used and that statistics were applied without fundamental

understanding of the distributions. Thus, it can be stated that it is – at

present - difficult to detect the global warning signal in empirical river run-

off data. The IPCC (2002) reminds to extend the research efforts for an

achievement of consistent analyses, in particular, for gridded analyses and

data surveys.

2.2.1.3 Impact of Climate Change: Temperature and Droughts

Regarding the global mean temperature the most relevant statement are

already discussed in Sect. 2.2. The global temperature increase is mainly

due to an increase in night time and winter temperatures, rather than to an

increase in day time and summer temperatures. Regional studies show an


B.VI-12

expansion of areas with warm extremes. Regarding the local expression of

temperature trends it will be likely that with an increase of the global mean

also the frequency of heat waves will increase (cf. Fig. 2, Fig. 4 upper

panel). Several heat waves are well documented, e.g. 1987 (Greece), 1995,

1999 (USA), and 2003 (Western Europe). They were associated with a

considerable number of deaths and other consequences in several sectors

(yield loss, water scarcity, etc.). Regarding the 2003 heat wave over Europe

several research groups have undertaken statistical examinations in order

to characterize its properties. SCHÄR et al. (2004) mentioned that it was the

hottest summer since AD 1500 (Fig. 4, lower left panel). STOTT et al. (2004)

estimates the human contribution to the summer heat wave 2003. By

defining a threshold value for the summer mean temperature, which was

exceeded in 2003, but in no other year since 1851, they calculate that

human influence has at least doubled the risk of a heat wave exceeding this

threshold (confidence > 90%).

Fig. 4. Upper panel: shift in the distribution function for e.g.

temperature (estimated from simple statistical considerations.

Slight increases increment the probability of hot summers

considerably. Lower right panel: distribution of Swiss monthly

and seasonal summer temperatures for the time period

1864–2003 (summer month June, July, August, and

aggregated). The fitted Gaussian is indicated in green. Values

in the lower left corner of each panel indicate the standard

deviation ( ) and the 2003 anomaly normalized by the

1864–2000 standard deviation (T‘/ ). Source: Schär et

al.2004.


B.VI-13

Regarding droughts the global pattern is unequivocal. A drought is not a

singular event, but a more or less long lasting event with tremendous

effects, in particular, on marginal land. Thus, one can understand them as a

disaster. For the Sahel region, for instance, DAI et al. (1998) have

estimated that in the first half of the 20th century only a quarter of the

region was affected by severe droughts, whilst this doubles to 50% since

the 1970ties. Nevertheless, currently one cannot provide any evidence that

extension and severeness of droughts have been changed. The IPCC (2002)

suggests to increase research efforts in this field.

2.2.1.4 Impact of Climate Change: Storminess and Storm Tracks

Regarding storminess a variety of different methods have been used to

describe extremes and track cyclones, so that an intercomparison is quite

difficult (IPCC 2002, for examples, cf. ALEXANDERSON et al. 2000, LUNKEIT et

al. 1998). The storm climate for Europe is closely correlated with the North

Atlantic circulation (NAO), i.e. by pressure variations between the Iceland

low and the Azores high pressure system, which is often used as an

indicator for macro-climatic weather situations (FRAEDRICH & SCHÖNWIESE

2002). An analysis of air pressure measurements at many stations in

Northern Europe has not shown significant changes in the storm climate in

the Northeast Atlantic over the last 100 yrs (LANGENBERG & VON STORCH

1996). Also the German Weather Service has not found any increasing

trends in mean wind speeds for the time interval 1969-1999, even though a

significant increase in the number of days with gusts above 8 Beaufort was

found (OTTE 2000). ALEXANDERSON et al. (2000) have determined very

unequivocal situations for Europe, i.e. in Scandinavia, Finland and Baltic

Sea area the most recent years, especially the cold and calm year 1996,

seem to have brought an end to the stormy period centred on 1990. In the

more westerly British Isles, North Sea and Norwegian Sea area, storminess

is still at high levels compared with the less intense period between 1930

and 1980. The long-term increasing trend in NW Europe storminess that

started in the 1960s seems to have been broken. However, the IPCC (2002)

states that observational records of storm events are of insufficient length

to reliably determine the statistics of very rare events. The consequence is

that trend estimates should be interpreted cautiously for predictive

purposes.

These examinations show that an extreme value assessment is combined

with a variety of problems, in particular, with respect to mappings, which

are up to now non-existent.

3 Hazard assessment

3.1 Definition

In the context of the climate change debate hazard is a term which is

difficult to use. In particular, if one considers that a hazard is a natural

occurrence causing a damage. In other words hazards are defined as

threats to a system, comprised of perturbations and stress (and stressors)

and the consequences they produce. A perturbation is considered as a

major spike in pressure (e.g., a tidal wave or hurricane) beyond the normal

range of variability in which the system operates. Stress is a continuous or


B.VI-14

slowly increasing pressure commonly within the range of normal variability.

In climate change therefore, hazard assessment focuses mainly on the

perturbations inducing extreme events (cf. glossary, Sect. 2.2ff). Thus,

hazard assessment can be subsumed under extreme event assessment in

climate change research.

Questions, whether an extreme (or a hazard) was caused by anthropogenic

greenhouse gas emissions or not are ill-posed. Relevant questions in

climate change research and in the hazard context are twofold: (i) are

heavy rain, heat waves, etc. more frequent due to climate change (see,

Sect. 2.2ff), and (ii) are modern societies sensitive against these climate

extremes? Both together have lead to the definition of the vulnerability

concept during the last two decades (cf. Sect. 5ff). Having this in mind

hazards in the climate change context are only those events, which are

influenced by the long-term process of anthropogenic forcing, i.e. the

intensity and magnitude of weather extremes: storms, floods, heat waves

etc.

3.2 Current methodologies for analysing andrepresentation of risks (hazard) with respect totemporal scales

A prerequisite for a risk (hazard) assessment is a sound (regional) data

base and adequate methodological concept which allow a scientific

assessment of climate related hazards. This issue is discussed at length in

section 2.2ff.

3.3 Dynamical hazard – climate change effects

As already mentioned climate change is a process, which may influence

future extreme value distribution (cf. Sect. 2.2).


See, Sect. 2.2 for this issue.

3.5 Data availability – typology, format – GIS structure

PIK supports are meta-database comprising a lot of empirical time series

data of common climate variables obtained from the worldwide weather

stations. Similar holds for river run-off data. The length of these time series

varies. The longest comprise approximately 200 yrs of daily measures.

These data are point measures. Empirical socio-economic data are available

on coarser scales, e.g. district or country level. Further, PIK hosts the

results of a variety of several model runs (e.g. from global/regional climate,

socio-economic, and vegetation models). These data are commonly gridded

in varying resolutions. PIK has access to several data distribution centres,

mainly for comparison of the own model runs with other model approaches.

PIK data are not associated with specific GIS structures, since they

commonly used in plain ASCII format. Regarding mapping several mapping

tools are used, whose choice depends on the certain questions to be

examined.


B.VI-15


Not available in the narrower sense (cf. examples in this report). May be

that the ESPON project can provide some progress.

4 Elements at risk and exposureSee below, Sect. 5.1: the exposure element depends on the decision

maker’s problem! I hope that we will obtain some insights regarding this

issue from the WP1 report.


Depends of the question, see examples below.


5.1 Definition of vulnerability

The assessment of climate “risks” is a complex undertaking that must

support judgements and decisions concerning future courses of action. It

requires a combination of scientific – not just from climate sciences – but

from those who understand the consequences of decisions for business,

society, economy, institutions, and environment. Therefore, risk assessment

in climate research is at best characterised by the term vulnerability

assessment. Within the climate research community vulnerability defines

the extent to which a system is susceptible to, or unable to cope with,

adverse effects of climate change, including variability and extremes.

Vulnerability is a function of system's sensitivity, exposure, and its

adaptive capacity (IPCC 2001). The sensitivity defines the degree to which

an exposure unit would be affected, either adversely or beneficially, by a

change of a particular climate variable (e.g. crop yield with respect to

precipitation/temperature mean or variability). Different systems may

differ in their sensitivity to climate change, resulting in different levels of

impact. The adaptive capacity defines the ability of a system to adjust to

climate change, e.g. to moderate potential damages. The exposure unit will,

in general, defined by the nature of decision-maker’s problem. It is the

responsibility of the decision-maker to specify the location and geographical

extent of an exposure unit. In climate research the major aim is to analyse

and assess how sensitive modern societies are with respect to climate

change. This implicitly takes into account a regional view, but also a trans-

sectoral focus. Nevertheless, currently there has been no systematic

methodology to operationalize vulnerability in the context to multiple

stressors (cf. Tab. 2). Different stages of vulnerability assessments are

more or less ideal prototypes rather than disjunct categories. This is the

reason why the approaches to measure vulnerability differ (cf. Sect. 5.2.2)

(cf. DOWNING et al. 2001, TURNER et al 2003, FÜSSEL & KLEIN 2005). Thus,

earlier vulnerability assessment strategies are not obsolete.


B.VI-16

Analyticalpurpose

Main drivers Main outputs Considera-tion of

adaptation

Integrationof natural

and socialsciences

Impact

assessment

Positive GHG emissions Climate impacts Little Little

1st-

generation

vulnerability

assessment

Positive GHG emissions,

& non-climatic

factors

Pre-adaptation

vulnerability

Partial Low – medium

2nd-

generation

vulnerability

assessment

Positive Climate change,

& non-climatic

drivers

Post-adaptation

vulnerability

Full Medium – high

Adaptation

policy

assessment

Normative Climate change,

& non-climatic

drivers

Recommended

adaptation

measures

Full High

Table 2: Characteristic properties of four different stages of

climate change vulnerability assessment Source: after Füssel &

Klein (2005).

In its widest context vulnerability concepts do not only consider climate

change but try to integrate various aspects of global environmental change

including socio-economic aspects of mitigation and adaptation (cf. Tab. 2).


See, the following examples.


Depends on the questions which should be answered, cf. Sect. 5.1, 5.2.2

5.2.2 Examples of vulnerability maps and legends

In the following several examples of vulnerability mappings are briefly

discussed. Regarding to the above discussion it is consequent that risk

assessment in climate change research does not rely on singular events,

since it is currently rather impossible to provide likelihoods of occurrence

and damage estimates for, e.g., weather extremes. This is the major reason

why risk (hazard) mapping strategies play only a minor role in climate

impact assessment and almost all presented examples have a more or less

broad focus (earth system analysis).

5.2.2.1 Vulnerability against Extreme Events in North-RhineWestphalia/Germany

The North-Rhine Westphalia (NRW) study differs from the majority of

vulnerability studies by focusing explicitly on extreme weather events rather

than on smooth modifications of mean values of crucial climate parameters

(cf. KROPP et al. 2005). The pace of climate change which may influence the

future intensity of extreme weather (see, Sect. 2.2ff) events could push us

to the limits of adaptive capacity. In general, it is rather difficult to

determine local vulnerability, but there exists sufficient evidence that a

variety of assets located in densely populated areas could be affected most


B.VI-17

seriously (MUNICHRE 2003). It is, of course, a formidable scientific task to

estimate the possible damages that might arise for ecological and socio-

economic systems by irregular events accompanying climate change in

these areas. The associated impacts are generally unevenly distributed

among social structures and economic sectors. In the NRW study

considered values at stake do not only comprise markets assets, but also to

ecosystem functions, human well-being, and socio-political stability. As a

basis of the of the vulnerability assessment shown in this subsection a

systematic stocktaking of al conceivable types of damage caused by

weather extremes was carried out and a set of vulnerability indicators for

each category of damage was identified. These 24 indicators (from socio-

economics, society, nature, industry, and infrastructure) are used as

measures for the degree of susceptibility of a given sector in the face of

climate stimuli, and they are therefore suitable for a comparative risk

assessment (Fig. 5).


B.VI-18

Fig. 5: Examples of vulnerability maps for 396 communities of North-

Rhine Westphalia indicating susceptibility against weather extremes:

(a) susceptibility to heat waves estimated by population density and

number of elderly people, (b) vulnerability of forest sector assessed

by combining the landscape orography and certain types of trees, (c)

susceptibility of local labour market calculated on the basis of the

seasonal rate of non-employment, and (d) production loss by traffic

collapse through extreme weather conditions on the basis of number

of commuting employees for each community. Lower left panel:

geographically explicit distribution of integrated vulnerabilities against

extreme weather events on a community level. Source Kropp et al.

(2005).

Nevertheless, it is difficult to develop a universal acceptable ‘metric’

defining vulnerability. This incommensurability is due to the inherently

normative nature of any vulnerability concept, e.g. valuing impacts under

largely unknown probabilities of occurrence (see above). Thus, the

vulnerability measure should be only considered in comparison to similar

settings and not, for example, with those measured for Angola or Brazil. In

order to determine the overall vulnerability measure a neural network

algorithm was used for pattern recognition and classification (cf. Fig. 5,

bottom left)

5.2.2.2 Agricultural Vulnerability against Climate Change in India

The approach presented in this section tries to assess India’s agricultural

vulnerability with respect to two stressors: climate change and economic

globalisation. The authors argue that agriculture is already susceptible, in

particular, to changes in the monsoon pattern. In there approach the

authors apply the IPCC typology to develop measures for adaptive capacity,

sensitivity and exposure (O’BRIEN et al. 2004). Due to sparse data the

defined adaptive capacity profile is based on the conditions in 1991 (Fig. 6,

lower left panel). Therefore, the presented analysis is partly static and has a

strong diagnostic component. The used data for the measurement of

adaptive capacity comprises soil conditions, groundwater availability,

human capital (adult literacy rate), social capital (gender equity),

presence/lack of alternative economic activities (measures the possibility to

shift to other economic activities), irrigation capacity, and quality of

infrastructure on the district level. The variety of data they are using to


B.VI-19

construct the integrated indices are amalgamated equal weighted (O’BRIEN

2005, personal communication) To measure the sensitivity under exposure

to climate change a sensitivity index (CSI) was constructed comprising

dryness and monsoon dependence. The dryness was considered as a

smoothed representation of drought sensitivity. The authors argue that

approx. 80% of the total annual rainfall is provided by the monsoon. If this

fails this will have tremendous effects on Indian agriculture. For the period

1961-1990 the CSI is shown in Fig. 6a. The future sensitivity was estimated

by using a regionally downscaled climate scenario (used model HadRM2,

CO2 doubling) (Fig. 6b).

Fig 6: Vulnerability to climate change in India (in quantiles):

to measure sensitivity (upper panel) under exposure to

climate change a sensitivity index (CSI) is defined based on a

gridded data set. The lower left panel represents the adaptive

capacity on a district level for 1991. In lower right panel the

integrated vulnerability is shown as a composite of adaptive

capacity and climate sensitivity under exposure of climate

change. Source O’Brien et al (2004).


B.VI-20

The results shown in Fig. 6 comprise only parts of the whole analysis, since

O’BRIEN et al. (2004) have also examined the vulnerability against

globalisation.

5.2.2.3 Vulnerability of Global Water Resources

Regarding the scale assessments of water vulnerability traditionally have

been cast at the country or regional scale. VÖRÖSMARTY et al. (2000) have

extended these approaches by considering individual drainage basins and

sub-catchments. The briefly described example tries to assess water

vulnerability to future climate change, population growth, and industrial

growth between 1985 and 2025 by examining the water infrastructure. The

authors investigate the topology of river systems and its use by humans

assuming that the mean annual run-off accumulated as river discharge

constitutes a sustainable water supply for a local population. The demand is

calculated as a ratio of water use to discharge. The industrial, domestic, and

agricultural demand was considered. For each region the ratio provides a

local index of water stress. The indicator shown in Fig. 7 is

Fig. 7: Maps of future changes in the water reuse index

relative to the contemporary situation predicted by a

coupling of a GCM and water balance model (Sc1),

population and economic development (Sc2) and both

(Sc3). A 20% threshold is used to highlight regions of

substantial change. Source: Vörösmarty et al. (2000).


B.VI-21

The so-called water re-use index ( DIA/Q) defining the ratio of aggregate

upstream water use relative to discharge.

For the analysis they had used a water balance model (WBM, 30’ grid) and

climate change scenarios from two models (HadCM2, CGCM1). For the

period from 1961-1990 the river discharge was reconstructed by using the

WBM and off-line forcing in the climate models. The future run-off varied in

response to climate and used model from < 1mm/yr (HadCM2/WBM) to 17

mm/yr (CGCM1). Focussing on the regional scale more substantial changes

for the catchments can be observed. From the World Resources Institute

they obtained population projections for the period from 1985-2025 applied

to a 1-km scale. Country statistics on water withdrawal were also used in

order to calculate water demand. However, the did not consider adaptation

of societies to changed situations in 2025.

VÖRÖSMARTY et al. (2000) found by their grid approach that 400 million

people live under conditions of relative water scarcity and approximately a

1.8 billion under severe water stress. This is in contrast to UN studies

estimating that on third of the world population lives under conditions of

relative water scarcity and only a half billion under severe water stress (UN

1997). These pattern will exacerbate 2025 (cf. Fig. 7). In many regions

which are today water-rich population pressure and future climate change

will induce changes in the regional constraints.

5.2.2.4 Syndromes of Global Change

The syndrome concept was proposed by the German Advisory Council on

Global Change to the Federal Government (WBGU 1994) and worked out,

improved and extended by several research groups. It tries to identify “hot

spots” of global change on earth under the assumption that the core

problems of global change, e.g. soil erosion, greenhouse gas emissions, loss

of biodiversity, etc. cannot analysed and described in a disciplinary and

sectoral manner. It is the highly interrelated entirety of these problems,

which distinguishes the current development as a crisis unique in mankind’s

history. Thus, it is the basic idea of the syndrome concept that the overall

phenomenon of Global Change shall not divided into regions, sectors, or

processes, but be understood as a co-evolution of dynamical partial

patterns. These pattern are bundles of interactive processes which appear

repeatedly and widely spread in typical combinations, the so-called

syndromes of global change (cf. SCHELLNHUBER et al. 1997). Currently 16 of

these pattern are defined, e.g. the Sahel Syndrome: Overuse of marginal

land (cf. Fig. 8, PETSCHEL-HELD et al. 1999); the Favela Syndrome: Socio-

ecological degradation through uncontrolled urban growth (KROPP et al.

2001); or the Overexploitation Syndrome: Overexploitation of natural

ecosystems (CASSEL-GINTZ & PETSCHEL-HELD 2000). Other syndrome deal

with singular anthropogenic environmental disasters (Disaster Syndrome)

or with a environmental degradation through an uncontrolled disposal of

waste (Waste Dumping Syndrome). For a brief overview confer to LÜDECKE

et al. (2004).

The central idea of this approach is to describe each of these syndromatic

pattern by a typical combination of so-called symptoms (approx. 80 are

defined, for an example, cf. Fig. 8). In the first place symptoms are defined

as qualities of Global Change which appear to play a major role in the


B.VI-22

ongoing problematic developments both in the natural environment and in

society. In other words they can also considered as trends. Based on the

syntax of these trends and possibly interactions pattern specific networks of

interrelations can be specified (cf. Fig. 8).

Indeed, these networks look like quite complex. Therefore, for each

syndrome core elements are identified (kernel) which are a necessary

precondition for an occurrence of a syndrome (Fig. 8, red symptoms). The

analysis of these pattern follows a two step strategy: (i) syndrome

diagnosis and (ii) syndrome prognosis. With respect to this issue the analyst

has to compile knowledge from several sectors in a formalized network. For

this goal two measures are defined and fuzzy logic concepts (cf. Fig. 9, top)

are utilized:

Fig. 8: Syndrome specific network of –transectoral-

interrelations for the Sahel Syndrome (Overuse of Marginal

Land). The arrows indicates a forcing the bullets a mitigation.

The red symptoms constitute the Sahel specific kernel which

must at least be active in order to detect a syndrome.

Source: Schellnhuber et al. 1997.

• Disposition: geographically explicit proneness, i.e. the disposition

refers to the process of identifying the susceptibility of entire regions

towards specific syndromes (cf. Fig. 9, upper and lower left panel).

• Intensity: measures the possibly outbreak and intensity of a

syndrome (Fig. 9, lower right panel).

Note, that disposition and intensity are diagnostic measurements

representing only static snapshot for a limited time interval (1990ties).

Regarding the dynamic development of a syndrome kernel further methods

are applied which allow a prognosis in time in particular (PETSCHEL-HELD et

al. 1999). Due to a variety of uncertainties interconnected with the analysis


B.VI-23

of global developments so-called qualitative differential equations are

employed allowing weak projection along the main lines of developments.

These projections allows to identify critical and safe developments and the

respective constraints. A major advantage is the analysis of concrete

policies.

Fig 9: Sahel Syndrome (0.5° x 0.5°), upper panel: Decision

tree for the natural and socio-economic dimension of the Sahel

disposition. The tree is stepwise evaluated by application of

different fuzzy logic indicators indicated by the black boxes.

Lower left panel: Global distribution of the disposition; lower

right panel: Intensity of the Sahel syndrome (grey: syndrome

not active). Note, that proneness not automatically implies an

occurrence of a syndrome, i.e. several regions of South

America are susceptible, but currently the mechanism is not

active. Thus, but measure could used as early warning index.

Source: Schellnhuber et al (1997), Cassel-Gintz et al. (1997).


B.VI-24

5.2.2.5 Advanced Terrestrial Ecosystem Analysis and Modelling

ATEAM’s (European Joint Project, final report available under www.pik-

potsdam.de/ateam/) objective was to assess the vulnerability of human

sectors relying on ecosystem services with respect to global change.

Vulnerability was considered to a function of potential impacts and adaptive

capacity to global change (cf. Fig. 10, upper panel).

The vulnerability assessment is twofold. First, it is tried to examine the

degree to which an ecosystem service is sensitive to global change. Second,

it was estimated to which degree a sector which relies on this service is

unable to adapt the changes (for details cf. SCHRÖTER et al. 2005). During

the project duration a common spatial scale of 10’x10’ was used. It was the

aim to produce spatially explicit vulnerability maps for the time slices of

1990, 2020, 2050, and 2080. As input data for the ATEAM integrated

assessment the following data were used:

• 17 climate scenarios based of 4 GCMs, 4 SRES scenarios (A1F, A2, B1, B2)

• CO2 concentration scenarios per used SRES scenario

• Nitrogen deposition per SRES scenario

• Terrain data and soil properties data set

• Land cover and land use data sets

• Land use scenarios for each of the for SRES scenarios

• Social indicators for adaptive capacity downscaled to the NUTS2 level

For the combination of the several indicators fuzzy logic methods are

employed.

Fig 10: Upper panel: schematic overview of the ATEAM

vulnerability assessment framework. Lower panel: ATEAM

vulnerability assessment for 2050 (from left to right):

Changes in ecosystem services (impacts), changes in

societies adaptive capacity, overall vulnerability. Source:

Schröter et al (2005).


B.VI-25

The main results are that the provision of essential ecosystem services will

change significantly with global change during the 21st century. In

particular, based on socio-economic and climatic changes an overall decline

in arable land in Europe will be a realistic scenario. In addition, climate

change will shift crop suitability in agricultural regions. On the other hand

the forest sector will be benefited from climate change, with the exception

that in the Mediterranean droughts and fires pose an increasing risk.

Regarding water availability climate change tends to increase the number of

catchments in southern Europe which will be affected by water scarcity.

Touristic seasons in the Alps will be shortened due to a decreasing snow

cover and in nature the extinction rate will be accelerated.

Comparing the overall vulnerability the Mediterranean regions will be most

vulnerable, because in southern Europe the potential multiple impacts are

combined with a low adaptive capacity (cf. Fig. 10, lower panel).

5.3 Most common damage potentials

All sectors of the natural environment and anthroposphere could be

affected. The damage potential cannot calculated, since regional extend and

magnitude of climate change and, in particular, weather extremes are

rather uncertain (cf. Sect 2.2ff).

6 Analysis of risk


Formally risk, in general, is defined as the product of the

probability/likelihood of occurrence and its magnitude. Thus, information

about the frequency of a “critical event” (often termed as hazard, cf. Sect.

3) and the magnitude of the likely consequences is needed. For climate

change as a process this is difficult, but it might be possible for weather

related extremes, e.g. heavy storms, flooding, heat waves, etc. With

respect to a broader the German Advisory Council on Global Change to the

Federal Government has proposed a concept, which allows a qualitative

assessment of risk classes (WBGU 2000).


Climate change risk assessment is often used synonymously to impact

(hazard) assessments that includes consideration of probability or

uncertainty associated with climate change or climate variability.

Nevertheless, probabilistic assessments of risks is rather problematic in

most cases (cf. Sects. 2.2ff, 3). Therefore, the primary purpose of

undertaking risk assessment is:

• Characterise the nature of risk;

• Provide qualitative (often) or quantitative (seldom) estimates of the

risk;

• Assess the consequences of uncertainties for decision options; and

• Compare sources of risk; including climate risks.


B.VI-26

The last point is important, since it allows to compare risks, e.g. with

respect to costs, etc.. It allows also derive management options. In general,

risk assessment is a tiered strategy, which begins with a risk screening,

followed by a generic quantitative risk assessment, and finalized by a

specific quantitative risk assessment. Due to inherent uncertainties (see

above) in climate and environmental research often scenarios applied. Two

strategies are common. The first considers consistent storylines used to

force model runs (cf. IPCC SRES scenarios). The obtained results are used

to assess future risk. The second is an inverse approach, based on

“normative borders”, i.e. it is considered what is acceptable for a society

and what is not. With respect to this tolerable window (or viability domain)

developments are checked whether they stay in this domain or not.

Subsequently, can be discussed which actions must be taken in order to

approach the defined targets (for examples cf. WBGU 1997, PETSCHEL-HELD

et al., 1999b, KROPP et al. 2004).

Quantitative risk assessment, e.g. by calculation of return period for floods

etc. is part of the third stage of risk assessment. As mentioned above this is

combined with a variety of methodological problems and a focus of ongoing

research (cf. COLES 2001, KATZ et al. 2002, BUNDE et al. 2004, BUNDE et al.

2005). From the current state of the art vulnerability assessments have a

greater importance in climate change research.

6.2.1 Qualitative and quantitative methods, direct and indirect risk

Not applicable as stated before.

6.2.2 Functions of risk analysis

Not applicable as stated before.


See, examples for vulnerability maps.

7 Risk managementThe focus of risk management in the climate change is about making

decisions concerning the management of rare and/or uncertain detrimental

events, for instance, avoiding the risks of extreme flooding, heavy storms,

storm surges etc.. This means climate change risk assessment focuses

more on adaptation, rather than on the calculation of an exact quantitative

risk measure (cf. risk definition). Although policy makers often ask for these

measures the present style of decision making is at least ostensibly based

on explicit quantified findings. Given the complexity of the system in

question, it is neither possible nor desirable to determine climate change

risks as a single figure. The reason for this point of view is rather simple: a

given, but apparent safety is always interconnected with a singular and

predefined trajectory which may allocate resources. In a case of a

misallocation, however, the reaction time for readjustments could be

possibly too small. Thus, uncertainty also allows a larger flexibility in

decision making (cf. REUSSWIG et al. 2004).


B.VI-27

8 Analysis of natural risks in relation to climatechange

An analysis of natural risks can be undertaken only for specific regions,

because this is, to some extend, a theoretical task. This means several

assumptions regarding potential regional climate change must be made.

Regarding landslide risk, for example, soil type characteristic, precipitation

pattern and amount and hill slope are relevant indicators for an analysis.

This already implies, that such an analysis cannot provided in general, but

needs a detailed and sophisticated research strategy.

All regions of the planet are potentially at risk from the hazards produced

by climate change. The amount of risk at any location will depend on the

nature of the changes in weather patterns and the characteristics of the

local environment. The Earth's cycles are so dynamic that it is presently not

possible to accurately predict the specific effects of climate change for a

specific location. It should be noted that "global warming" is not likely to be

global. That is, the average temperature of the Earth may increase, but

some locations may experience cooling. With regard to natural hazards,

climate change (warming or cooling) is the issue of greatest importance,

and it is most important at regional and local scales and must be

investigated for the distinct meteorological extremes and regions.

The climate changes induce the following impacts on regional scales:

1. a change in weather patterns

2. an increase in sea level rise

3. an increase in the number of landslides.

Increase in the amount and frequency of rainfall could cause more river

flooding, while decreases may cause drought. Land use, such as cropping

and forestry may need to change to suit new weather patterns, affecting

runoff, hillside and valley drainage as well as increasing fire risks due to

vegetation changes. The location of some industries, agriculture,

horticulture and tourism may also need to change.

Changing weather patterns may also threaten biodiversity, affecting our

ecosystems. Species that are already under threat or at the limit of their

climatic range may not be able to survive. New diseases and pests may

take hold. Tropical pests and tropical diseases like malaria may become

established in areas where they currently do not exist.

Predicted sea level rise affects low-lying areas and estuaries. This will

influence where people live, work and play and put even more pressure on

our coastal environment. Landslides may be triggered by heavy rain. In

regions with volcanic activity this risk may be very high since sediments

from volcanic outbursts are unstable.

People relocating inland to avoid coastal hazards such as flooding and

erosion may face an increased risk of large scale rock and/or soil slips in

marginal areas, due to the effects of changes in rainfall, drainage patterns

and land use on hill slopes.

All these events may also threaten lifeline services such as water, power,

telecommunication infrastructure and transportation networks.


B.VI-28

9 ConclusionIn this report the difficulties regarding an adequate derivation and

assessment of extremes are discussed. It was made clear the difference

between weather related singular disasters, e.g. flooding, droughts, etc.

and the smooth process of climate change. As discussed, there exists a

likely evidence that climate change will change probability and occurrence

of weather extremes, but up to now it is quite difficult to assess this. This

holds, in particular, with respect to small regional scales, e.g. calculation a

quantitative risk. Thus, results from examinations trying to do such kind of

research must be considered with care.

Focussing on risk/hazard/vulnerability assessment the situation is more

different. In general, the presented examples (cf. Sect. 5) show that any

kind of concrete vulnerability assessment depends on the question which

should be solved. This hold for static (diagnostic) purposes and as well as

for dynamical ones. Thus, from my point of view and with respect to the

above discussion it will be rather problematic to provide an European

Hazard Assessment Framework which includes standardized data as well as

standardized methodologies, since any kind of strategy depends on the

availability of data, decision maker’s problems, and the natural and

anthropogenic inventory. On the other hand it will be possible to provide

such an analysis for exemplified regions if one could defined an agreement

on time/scale and sectoral issues. The concept of vulnerability assessments

in climate/global change research, which has now already a history of

approximately two decades, could be a basis for such an approach.

Focussing more explicit on meteorological and climate extremes the current

problems are discussed in briefly in this report. The lack of knowledge is

noted and has caused the IPCC making extreme value assessment to a focal

point in the Fourth Assessment Report which is currently under preparation.

10 Glossary of all keywordsAdaptive capacity defines the ability of a system to adjust to climate

change, e.g. to moderate potential damages.

Climate change: a process including changes in natural variability and

anthropogenic induced climate (cf. IPCC and UNFCCC, Sect. 2.2.)

Climate adaptation indicates the process or outcome of a process that

leads to a reduction in harm or risk of harm, or realisation of benefits,

associated with climate variability and climate change ( mitigation)

Disposition of a syndrome: measures the proneness of an region against

a syndromatic pattern.

Extreme weather event: an event that is rare within its statistical

reference distribution at a particular place. Definitions of rare vary, but an

extreme weather event would normally be as rare as or rarer than the 10th

or 90th percentile.

Extreme value distribution: a particular family of probability density

functions (GEV/GPD) used to describe the probability of extremes. Their

usage is combined with some a priori assumptions which are partly not

given in empirical data sets.


B.VI-29

The exposure unit is defined by the nature of decision-maker’s problem. It

defines the system or parts of the system to be at risk. Risk assessment is

used to assist decision-makers to form an opinion of the likely sensitivity of

a particular area of responsibility or concern to potential changes in climate.

Hazard is a natural occurrence causing a damage (harm), i.e. comprised of

perturbations and stress and the consequences they produce. A

perturbation is a major spike in pressure (e.g., a tidal wave or hurricane)

beyond the normal range of variability in which the system operates.

Climate Change is not a hazard.

IID: identically and independently distributed data, a precondition for

extreme value statistics.

Impact means a beneficially or more usually detrimental consequence

Intensity of a syndrome: measures to what extend a region is affected by

a syndromatic pattern

IS92a indicates a business as usual emission scenario, reference point

1992.

Climate change risk assessment tries to determine how climate change

could affect outcomes in a sector (e.g. economy, ecosphere, etc.) and to

evaluate the effectiveness of decision regarding existing or new policies,

programmes and projects.

Mitigation: In the context of risk management any action that reduces the

probability and magnitude of unwanted consequences. In climate change

mitigation is a strategy to mitigate the risks associated with future changes

in climate.

Natural variability causes uncertainties that stem from inherent

randomness or unpredictability in the natural world. Variability can be

assessed by monitoring programmes etc., but the examined variability

under consideration depends also on the time scale (cf. Fig. 1

stationarity)

Precautionary principle: Principle defined by the Rio Declaration. Where

there are threats of serious or irreversible damage, lack of full scientific

uncertainty shall not be used as a reason for postponing cost-effective

measures to prevent environmental degradation.

Preparedness: The possibility of a society or system to cope with climate

change.

Risk is the product of probability of occurrence and magnitude of

consequences after a hazard (perturbation or stress)

Risk assessment means the structured analysis of hazards and impacts to

provide information for decisions. Risk assessment usually relates to an

exposure unit which may be individual (e.g. population, infrastructure,

environmental assets) and depends on the decision makers problem

( exposure unit)

Risk management indicates any action or portfolio of actions that aim to

reduce the probability and magnitude of unwanted consequences (cf. also

mitigation)

Scenario: A coherent, internally consistent and plausible description of a

possible future state of the world, usually based on specific assumptions

( SRES scenarios, IS92a).


B.VI-30

SRES-Marker scenarios: 35 IPCC scenarios (Special Report on Emission

Scenarios) describing different story lines used in order to estimate the

future development of climate. The scenarios are structured in 4 scenario

families: (A1) rapid economic growth and introduction of new an more

efficient technologies, sub-scenarios A1FI: fossil intensive, A1T non-fossil

future, A1B energy mix; (A2) heterogeneous world with a focus on local

traditional values; (B1) renunciation from materialism and introduction of

clean technologies; (B2) focal point on local solutions, economic and

ecological sustainability.

Sensitivity defines the degree to which an exposure unit would be

affected, either adversely or beneficially, by a change of a particular climate

variable (e.g. crop yield with respect to precipitation/temperature mean or

variability).

Syndrome of Global Change: transsectorally defined pattern of global

change, which can be considered as sub-dynamics of all global change

processes.

System means the social, economic and natural domain within risks arise,

produce consequences and in which risks are managed.

Stationarity: statistical concept that is needed as a priori assumption for

the statistical analysis of time series data. It indicates that the expected

value and variance and are constant over time. In the narrow sense this

holds only for stochastic processes. Climate, river-run off have stochastic

parts, but not in general. Thus extended assumptions, e.g. weak

stationarity, are used.

Tolerable climate change: The willingness to live with a particular level of

risk, in return for certain benefits, based upon a certain confidence that the

risk is being properly controlled or managed. Ex ante it is often defined

normative as an outcome of the public debate, ex post it is often

unavoidable to live with a specific level of risk ( climate change). In the

latter case climate adaptation becomes important.

Uncertainty means a characteristic of a system or decision where the

probability that certain states or outcomes may occur are not precisely

known. Uncertainty may have several sources: lack of process knowledge,

lack of data, model uncertainty.

Vulnerability defines the extent to which a system is susceptible to, or

unable to cope with, adverse effects of climate change, including variability

and extremes. It is a function of system's sensitivity, exposure, and its

adaptive capacity.


B.VI-31

11 Appendix:Operational Standards for Risk Assessmentaimed at Spatial Planning

11.1 Minimum standard (simplified model) for hazardmapping aimed at a legal directive

A setting of standards for hazard mappings from the perspective of climate

change on the current state of knowledge is rather impossible (cf. Sect.

2.2), since the scale used by planners are significant smaller than those

used in climate research. Nevertheless simple approaches are common and

already in use, cf. the Australian Disaster Mitigation Programme

(http://www.dotars.gov. au/naturaldisasters/index.aspx). A sub-

programme estimates based of historic flood events the necessity of flood

plain in river catchments (cf. Fig. 11).

Fig. 11: Map of Perth, Tasmania, Australia provided by the

Tasmania floodplain study. Levels of risk are indicated by an

in-depth survey of historic gauge levels. Climate Change is

not considered.


B.VI-32

With respect to the current knowledge and under consideration of

climate scenarios the following approach might be possible:

1. Determine levels of prone areas for river catchments or coastal

regions by the help of a terrain model (consider current flood

protection buildings!)

2. Perform a systematic stocktaking of the assets and their values in

these regions (regarding the problems, e.g. discounting, cf.

FANKHAUSER 1995)

3. Use a downscaled climate change scenario, local precipitation-run-off

models and build potential future run-off and precipitation scenarios

(regarding the difficulties cf. Sect. 2.2.1)

4. By utilization of adequate statistical methods and based on historic

measurements and those generated by model outputs probabilities

can be calculated for a hundred year flooding (with respect to

potential errors cf. Sect. 2.2.1.1)

After this procedure the major task is mitigation, e.g. with respect to

flooding, to avoid losses by keeping away the water from natural and

anthropogenic assets. This a typical “structural” approach. Currently also

“non-structural” and “response modification” strategies coming to be

modern. This approach recognises that people’s reactions to impending

floods and warnings have a substantial effect on the losses that

subsequently occur (cf. Tab. 3).

Structural Physical environment e.g. dams, channe l

improvements, flood plains,

flood gates

Property

Modification/Planning

e.g. building regulations,

land use planning, zoning,

Non-Structural

Response Modification e.g. education programmes,

preparedness, early warning

systems

Table 3: Classification of measure to reduce the losses of

flood events.

However, from the legal point of view any kind of successful hazard

assessment should consider that an adequate warning time is guaranteed

and that local authorities must be prepared to acquire land for public

purposes if necessary.

11.2 Various methodologies related to the 3 assumedscales of analysis in the light of a potentialharmonisation of hazard maps, based on a multi-hazard perspective

Which three scales? From climate research these scales make no sense,

because they are to small. Climate data are only available on coarser scales

(model scales!). Regarding history also point measures are common

(weather stations, river gauges). If these are available in an adequate

coverage interpolation routines can be used to provide maps. For the future


B.VI-33

only scenarios from model runs are available which can be downscaled by

various algorithms

11.3 Minimum standard (simplified model) for riskmapping aimed at spatial planning

Strategies to determine climate change risks are discussed above. For

singular cases risk assessment may be possible, but the relevance of results

depend on the availability of data, used methodology, and quality of model

runs. Due to this circumstance the outcomes should be interpreted with

care.

11.4 Multi-risk assessment perspective as element ofthe Strategic Environmental Assessment

Confer the vulnerability section, in the climate change community this is

used a standardized and strategic approach to assess environmental and

socio-economic risks. Up to now these approaches are slowly migrating into

other disciplines. In global change research the question how we can

mitigate risk is exactly the underlying idea of the vulnerability concept.

11.5 Methodologies, functions and outputs

A variety is used. Their choice depend on the questions which shall be

answered, in particular, to the decision makers problem (cf. discussion of

exposure unit, vulnerability). In general these header sounds a bit strange,

since the output depends on the definition of e.g. exposure units and last

but not least on the available data. In climate change research any kind of

vulnerability mapping can be understand as a support for policy making. It

is not a planning instrument (cf. to the uncertainty discussion Sect.

2.2.1.1).

12 References

Alexandersson H, Tuomenvirta H, Schmith T, Iden K (2000):Trends of

storms in NW Europe derived from an updated pressure data set Climate

Research 14: 71–73

Barnett TP, Hasselmann K, Chelliah M, Delworth T, Hegerl G, Jones P,

Rasmusson E, Roeckner E, Ropelewski C, Santer B, & Tett S (1999): Bull.

American Meteor. Soc. 12: 2631.

Bunde A, Eichner JF, Havlin S, Kantelhardt JW (2004): Return intervals of

rare events in records with long-term persistence. Physica A 342: 308-314

Bunde A, Eichner JF, Havlin S Kantelhardt JW (2005): Extreme value

statistics in the presence of long-term persistence: Stretched exponentials

and clustering of rare events. Physical Review Letters, submitted.

Cassel-Gintz MA, Lüdeke MKB, Petschel-Held G, Reusswig F, Plöchl M,

Lammel G, Schellnhuber HJ (1997): Fuzzy logic based global assessment of

the marginality of agricultural land use. Climate Research 8 135-150.


B.VI-34

Cassel-Gintz, M. and G. Petschel-Held (2000) GIS-based assessment of the

threat to world forests by patterns of non-sustainable civilisation nature

interaction. Journal of Environmental Management, 59: 279-298

Coles S (2001): An introduction to statistical modeling of extreme values.

London: Springer.

Croll J (1875): Climate and time in their geological relations: a theory of

secular changes of the earth’s climate. Daldy, Isbister, London.

Currie RG & O’Brien DP (1990): Deterministic signals in precipitation

records from the American corn belt. Int. J. Climatology 10: 179-189.

Cubasch U (2004): Perspektiven der Klimamodellierung mit aktuellen

Beispielen. In: Klimaveränderung und Kosequenzen für die

Wasserwirtschaft. KLIWA Berichte Heft 4, Bayerisches Landesamt für

Wasserwirtschaft, München.

Dai AK, Trenberth KE & Karl TR (1998): Global Variations in drought and

wet spells: 1900-1995. Geophys. Res. Lett. 25(17): 3367-3370.

Downing TE, Butterfield R, Cohen S, Huq S, Moss R, Rahman A, Sokaona Y

& Stephen L (2001): Climate Change Vulnerability: Toward a Framework for

comparing adaptability to Climate Change Impacts. Report to the United

Nations Environment Programme (UNEP), Oxford: Environmental Change

Institute & Nairobi: UNEP.

Fankhauser R (1995): Valueing Climate Change, Earthscan, London.

Füssel HM & Klein R (2005): Climate Change Vulnerability Assessments: An

Evolution of Conceptual Thinking. Climatic Change, forthcoming.

Fraedrich K & Schönwiese CD (2002): Space time variability of the

European Climate In: The Science of Disasters: Climate Disruptions, Heart

Attacks, and Market Crashes (A Bunde, J Kropp, HJ Schellnhuber, eds.),

Springer, Berlin.

Gleissberg W (1955): The 80-yr sunspot cycle. J. Br. Astronom. Assoc. 68:

148-152

Gumbel EJ (1941) The return period of flood flows. Ann Math

Stat.12:163–90.

Hale GE (1924): Sunspots as magnets and the periodical reversal of their

polarity. Nature 113: 105.

Haylock MR & Gooddess CM (2004): Interannual variability of European

extreme winter rainfall and links with mean large-scale circulation. Int. J.

Climatol. 24: 759–776.

Hasselmann K (2002): Is Climate predictable? In: The Science of Disasters:

Climate Disruptions, Heart Attacks, and Market Crashes (A Bunde, J Kropp,

HJ Schellnhuber, eds.), Springer, Berlin.

Hasselmann K (1997): Multi-pattern fingerprint method fro detection and

attribution of climate change. Climate Dynamics 13: 601-611.

IPCC (1990): Climate Change; The IPCC Scientific Assessment (JT

Houghton GL Jenkins, JJ Ephraums), Cambridge University Press,

Cambridge


B.VI-35

IPCC (1996): Climate Change 1995, The Science of Climate Change (JT

Houghton, LG Meira-Filho, BA Callander, N Harris, A Kattenberg, & K

Maskell), Cambridge University Press, Cambridge

IPCC (2001): Climate Change 2001: The Scientific Basis, Contribution of the

Working Group I to the Third Assessment Report to the Intergovernmental

Panel on Climate Change (JT Houghton, Y Ding, DJ Griggs, M Noguer, PJ

van der Linden & D Xiaosu), Cambridge University Press, Cambridge.

IPCC (2002): IPCC Workshop on Changes in Extreme Weather and Climate

Events, IPCC, Bejing

Kallache M, Rust H, Kropp J (2005): Trend Assessment: Applications for

Hydrology and Climate Research. Nonlinear Processes in Geophysics. 12:

201-210

Kallache M, Rust HW, Kropp J (2004): Trend Assessment of Correlated

Data. In: Pahl-Wostl C, Schmidt S, Rizzoli AE, Jakeman AJ (eds.)

Complexity and Integrated Resources Management, Trans. 2nd Biennial

Meeting Int. Environmental Modelling and Software Soc. Vol. III, p. 1517-

1522 Manno, Switzerland

Karl TR, Knight RW, Easterling DR and Quayle RG (1996): Indices of climate

change for the United States. Bull. American Meteor. Soc. 77: 279-291.

Katz RW, Parlange MB & Naveau P (2002): Statistics of extremes in

hydrology, Advances in Water Resources, 25: 1287-1304

Kropp J., Lüdeke MKB, Reusswig F. (2001): Global Analysis and Distribution

of Unbalanced Urbanization Processes: The Favela Syndrome. GAIA 10(2)

109-120.

Kropp J, Eisenack K, Scheffran J (2004): Sustainable Marine Resource

Management: Lessons from Viability Analysis. In: Pahl-Wostl C, Schmidt S,

Rizzoli AE, Jakeman AJ (eds.) Complexity and Integrated Resources

Management, Trans. 2nd Biennial Meeting Int. Environmental Modelling and

Software Soc. Vol I, 104-109. Manno, Switzerland

Kropp J., Block A., Reusswig F. & Schellnhuber HJ (2005): Semiquantitative

Assessment of Regional Climate Vulnerability: The North-Rhine Westphalia

Study Climatic Change, in press.

Lozan JL (2001): Influence of the climate on the history of the humankind.

In: Climate of the 21st century: changes and risks (Lozan J, Graßl H, Hupfer

P, eds.), p.86-92.

Lüdeke, M. K. B.; Petschel-Held, G.; Schellnhuber, H. J. (2004): Syndromes

of Global Change: The First Panoramic View. GAIA 13(1): 42-49.

Langenberg H & von Storch H (1996): Auswirkungen von Klimaänderungen

auf Sturmentwicklung und Extremwasserstände. Vechtaer Studien zur

Angewandten Geographie und Regionalwissenschaft 18: 193-194.

Lunkeit F, Fraedrich K, Bauer SE (1998): Storm tracks in a warmer climate:

sensitivity studies with a simplified global circulation model. Climate

Dynamics 14: 813-826.

Otte U (2000): Häufigkeit von Sturmböen in den letzen Jahren, Deutscher

Wetterdienst Klimastatusbericht 1999.


B.VI-36

Mann ME, Bradley RS, Hughes MK (1998): Global-Scale Temperature

Patterns and Climate Forcing Over the Past Six Centuries, Nature 392: 779-

787.

Mann M, Bradley RS, Hughes MK (2004): corrigendum: Global-scale

temperature patterns and climate forcing over the past six centuries. Nature

423: 105.

McGuffie K and Henderson-Sellers A (1996): A climate modeling primer,

Wiley, New York.

McIntyre S & McKitrick R (2003): Corrections to the Mann et. al. (1998)

proxy data base and northern hemispheric average temperature series.

Energy & Environment 14(6): 751-771:

Meehl GA, Zwiers F, Evans J, Knutson T, Mearns L, & Whetton P (2000):

Trends in extreme weather and climate events: issues related to the

modeling extremes in the projections of future climate change. Bull. Amer.

Meteorological Soc. 81(3): 427-436.

Meehl GA, Tebaldi C (2004): More Intense, More Frequent, and Longer

Lasting Heat Waves in the 21st Century. Science 305: 994-997.

Mende W & Stellmacher R (2001): Effect of the earth orbit and solar

variability on climate. In: Climate of the 21st century: changes and risks

(Lozan J, Graßl H, Hupfer P, eds.), p.27-33.

Milankovitch M (1938): Astronomische Mittel zur Erforschung der

erdgeschichtlichen Klimate. Handb. Geophys. 9: 593-69

MunichRe (2003): World of natural Disasters (Topiks, CD-ROM), Munich.

Noguer M,·Jones R &·Murphy J (1998): Sources of systematic errors in the

climatology of a regional climate model over Europe. Climate Dynamics

(1998) 14 : 691–712

North Greenland Ice Core Project (NGRIP) Members (2004): High-resolution

record of northern hemisphere climate extending into the last interglacial

period. Nature 431: 147-151

O’Brien K, Leichenko R, Kelkar U, Venema H, Aandahl G, Tompkins H, Javed

A, Bhadwal S, Barg S, Nygaard L, West J (2004): Mapping Vulnerability to

multiple stressors: climate change and globalization in India. Global

Environmental Change 14: 303.313.

Petschel-Held G, Block A, Cassel-Gintz M, Kropp J, Lüdeke MKB.,

Moldenhauer O, Reusswig F & Schellnhuber HJ (1999): Syndromes of Global

Change: A Qualitative Modeling Approach to support Global Environmental

Management. Environmental Modeling and Assessment 4(4): 295 - 314.

Petschel-Held, G., T. Bruckner, H.-J. Schellnhuber, F. Tóth, and K.

Hasselmann (1999b) The Tolerable Windows Approach: Theoretical and

Methodological Foundations. Climatic Change, 41(3/4): 303-331.

Reusswig F, Kropp J, Welp M. (2004): Vom Nutzen der Unsicherheit: Wie

wir unter Unsicherheit handeln können und sollen. Umwelt & Bildung 1: 19-

21.

Schröter D, Acosta-Michlik L, Arnell AW, Araújo MB, Badeck F, Bakker M,

Bondeau A, Bugmann H, Carter T, de la Vega-Leinert AC, Erhard M,


B.VI-37

Espiñeira GZ, Ewert F, Fritsch U, Friedlingstein P, Glendining M, Gracia CA,

Hickler T, House J, Hulme M, Kankaanpää S, Klein RJT, Krukenberg B,

Lavorel S, Leemans R, Lindner M, Liski J, Metzger MJ, Meyer J, Mitchell T,

Mohren F, Morales P, Moreno JM, Reginster I, Reidsma P, Rounsevell M Pla

E, Pluimers J Prentice IC Pussinen A, Sánchez A, Sabaté S, Sitch S, Smith

B, Smith J, Smith P, Sykes MT, Thonicke K, Thuiller W, Tuck G, van der

Werf G, Vayreda J, Wattenbach M, Wilson DW, Woodward FI, Zaehle S, Zierl

B, Zudin S & Cramer W (2005): Advanced Terrestrial Ecosystem Analysis

and Modelling (ATEAM), Final Report, Available under http://www.pik-

potsdam.de.

Schär C et al. (2004): The role of increasing temperature variability in

European summer heat waves. Nature 427: 332-336.

Schellnhuber H.J., Block A., Cassel-Gintz M., Kropp J., Lammel G., Lass W.,

Lienenkamp R., Loose C., Lüdeke M.K.B., Moldenhauer O., Petschel-Held G.,

Plöchl M. & Reusswig F. (1997): Syndromes of Global Change. GAIA 6(1):

19 - 34.

Stott PA, Stone DA, Allen MA (2004): Human contribution to the European

heatwave of 2003. Nature 432: 610-614

Storch, von H; Zorita E, Jones JM, Dimitriev Y, Gonza´lez-Rouco F, Tett SFB

(2004): Reconstructing Past Climate from Noisy Data. Science 306: 679-

682.

Thompson WF (1990): Time series analysis of Holocene climate data.

Philos. Trans. R. Soc. 330A: 601-616.

Turner BL II, Kasperson RE, Matson PA, McCarthy JJ, Corell RW,

Christensen L, Eckley N, Kasperson JX, Luers A, Martello ML, Polsky C,

Pulsipher A & Schiller A (2003): A framework for vulnerability analysis in

sustainability science. Proc Natl Acad Sci USA 100(14): 8074-8079.

UN (1997): Comprehensive Assessment of the Freshwater Resources of the

World, WMO, Geneva.

Vörösmarty CJ, Green P, Salisbury J & Lammers RB (2000): Global water

resources: vulnerability from climate change and population growth.

Science 289: 284-288.

Watson RT, Zinyowera MC, Moss RH, Dokken DJ (eds.) (1998): The regional

impact of climate change: an assessment of vulnerability. Special report of

the IPCC Working Group II, Cambridge University Press, Cambridge.

WBGU (1994): World in Transition: The threat to soils. German Advisory

Council on Global Change (WBGU, annual report 1994) Economica, Berlin.

WBGU (1997): Climate Protection. Special Report German Advisory Council

on Global Change, Berlin.

WBGU (2000): World in Transition: Strategies for Managing Global

Environmental Environmental Risks. German Advisory Council on Global

Change (WBGU, annual report 1998) Springer, Berlin.


B.VII-1

B.VIIPossible secondary effects of natural hazarddiscussed at the example of groundwaterpollution

Authors: Zuzana Boukalová, Radomír Muzikár, MarekSkalicky, CCSS

1 Physical definition of potential secondary hazards of

natural hazards – ground water pollution ....................... 3

1.1 Impact of natural events on groundwater regime..................3

1.1.1 Floods..................................................................................3

1.1.2 Earthquakes .........................................................................4

1.1.3 Landslides, erosion, heavy rainfall, forest fires, volcanic

activities..........................................................................................5

1.2 Potential sources of hazard risk for the groundwater originatedby the natural disasters ............................................................5

2 Hazard assessment.................................................... 6

2.1 Definition.........................................................................6

2.2 Current methodologies for analysing and representation of

hazard ....................................................................................6

2.3 Availability of the required data..........................................6

2.3.1 Required data .......................................................................6

2.3.2 Data source ..........................................................................8

3 Element at risk and exposure................................... 11

3.1 Typology of elements ......................................................11

3.2 Definition of exposure .....................................................11

4 Groundwater vulnerability and groundwater

vulnerability maps ....................................................... 12

4.1 Definition of groundwater vulnerability ..............................12

4.2 Methodologies for assessment of groundwater vulnerability .12

4.2.1 Hydrogeological setting........................................................12

4.2.2 The parametric methods ......................................................15

5 Analogical relations and numerical models............... 17

5.1 Problem of scale.............................................................17


B.VII-2

5.2 Examples of groundwater vulnerability maps and legends

referred to assumed scales......................................................18

5.2.1 Legend of groundwater vulnerability map...............................18

5.2.2 Examples of groundwater vulnerability maps..........................18

5.3 Groundwater vulnerability map production for risk maps ofnatural hazards......................................................................19

6 Analysis of risk........................................................ 20

6.1 Definition of risk.............................................................20

6.2 Methodologies for risk assessment....................................20

6.2.1 Identification and characterization of priority pollutants...........21

6.2.2 Identification of path ways and mechanism for chemical

migration.......................................................................................21

6.2.3 Quantity and space contamination distribution estimate

resulting in natural disasters ............................................................21

6.2.4 Identification and description of receptors..............................22

6.2.5 Risk characterization estimate ..............................................22

6.2.6 Evaluation of uncertainties ...................................................22

6.2.7 Recommended method ........................................................23

6.2.8 Conclusion of methodology for risk assessment ......................23

7 Risk management.................................................... 23

8 Glossary of all keywords.......................................... 24

9 Bibliography............................................................ 25

Annex 1: Assessment of groundwater vulnerability according

to GOD and drastic

Annex 2: Legend for groundwater vulnerability map

Annex 3: Categories of aquifer nature – assessment ofpotential contaminant spreading within aquifer

Annex 4: Example of groundwater vulnerability map in

regional scale (1:100 000)

Annex 5: Example of groundwater vulnerability map inregional scale (1:25 000)

Annex 6: Operational standards for groundwater vulnerability

maps aimed to spatial planning


B.VII-3

1 Physical definition of potential secondaryhazards of natural hazards – ground waterpollution

Groundwater is one of components of hydrological cycle, important source

for water supply and important part of environment influencing the status of

aquatic and terrestrial ecosystems. During most of natural hazards are

disturbed and damaged installations with the potential sources of

groundwater regime impact. Especially, the deterioration of groundwater

quality is serious. This is mostly no visible, is long-running due to

persistence of soluble chemicals arising as a result of our consumptive way

of life and occurring in long size contamination plume. The remediation is

very expensive and requires a long period of remediation.

Qualitative and quantitative impacts on groundwater are originated by of

most of natural hazards. Some following examples of the natural hazard

impacts are shown.

1.1 Impact of natural events on groundwater regime

1.1.1 Floods

The influence on ground water depends on the location of the area of

interest in the catchment. In the upper stream the flood pass over quickly

with the destructive power. The flood flow returns after short time back to

the riverbed. The floodplain stays longer period in the lower stream,

sometimes the weeks. It originates the long running impacts on

groundwater. The impacts are both qualitative and quantitative.

Qualitative impacts:

Leachate in contaminated sites and brownfields,

Leachate in the areas of the installations with the potentially

contaminating activities:

e.g. oil, fuel or chemical storage, hazardous chemical waste spills,

industry with effluent of organic wastes, inorganic wastes, airfields,

landfills, military establishments, slaughterhouses, mines, specially

abandoned mines, quarries, animal husbandries, livestock storage,

silage, cultivated areas with expected frequent and abundant use of

pesticides and fertilizers, etc.

Water penetration of flood water:

o Mines and quarries

o Wells

o Drainage pipes and sewages

Contamination of abstraction wells

Two pathways of contamination of abstraction wells could be identified. The

first is the direct penetration of floodwater into abstraction wells. It could

occur in the upper and lower stream. The second results in long-term

presence of floodwater over the cone of depression. This affects the primary

hazard – long-term leachate of pollutants of floodwater into aquifer and the

secondary hazard – leachate of the contaminant sediments transferred with

the floodwater. This is occurs rather in the lower stream. The abstraction


B.VII-4

wells contamination resulted in the floods in the River Moravia Basin (Q100 –

Q500) in Czech Republic in 1997 and in the River Label and Lava Basin (Q500

– Q1 000) in 2002. Organic substances, bacteria and microorganisms polluted

the groundwater. In addition, high turbidity and color of water occurred.

The presence of hazard substances was not detected. The groundwater

contamination was originated by the domestic wastewaters and by the

agriculture activities as livestock storage, silage etc.

Qualitative impacts:

Stream recharge to groundwater

Interruption of the discharge function of the receiving water course

(e.g. drainage, sewer pipes or pluvial pipes)

Consequences:

o Increase of groundwater level

o Increase of the vulnerability of groundwater in Quaternary

aquifers

o Temporally marshy land

Example: Interruption of the drainage discharge to a receiving pond

resulted in long term runway inundation at the airport in La Havana

(Cuba)

1.1.2 Earthquakes

The earthquakes have a variety of effects on groundwater. Most spectacular

are sudden rises of water levels in wells. The earthquake shocks produce

small raises and falls of groundwater levels in well penetrating the confined

aquifers. It is a sudden and short-lived process. Groundwater level returns

usually to the initial level. The short-lived fluctuations of groundwater level

were observed at a long distances of the earthquake centers. Examples:

The earthquake in Romania occurred the 3rd March 1977 originated the

short-lived fluctuation in Slatinice in Czech Republic up to in the range to

0,77 m and in Lithuania to 0,06 m. The earthquake in former Yugoslavia

occurred the 15th April 1979 originated the short-lived fluctuation of

groundwater level in the range up to 1,25 m in Slatinice in Czech Republic.

The impact of earthquakes on piezometric groundwater level is neglected.

The other effects on groundwater were observed as follows:

Increase of spring discharges (up to several fold)

Decrease of spring discharge up to zero discharge

Increase of the fissures

Disturbance of the protective function of the unsaturated zone

Changes of chemical composition in the springs

Influence of human activity on the earthquake production

Example: Elevated fluid pressures in disposal well of the depth about

3 700 m injecting wastewater from a chemical plant in Rocky

Mountain Arsenal (Colorado, USA) participated the occurrence the

earthquakes (Freeze, Cherry 1979)

Disturbance of pipe network with waste water, water supply or

drainage pipes

Disturbance of sludge lagoons, waste disposals, etc


B.VII-5

1.1.3 Landslides, erosion, heavy rainfall, forest fires, volcanicactivities

The effects on groundwater are similar to the foregoing natural events. The

common effect is damage of the installation with the potential sources of

groundwater regime impact.

1.2 Potential sources of hazard risk for thegroundwater originated by the natural disasters

Two sources of groundwater hazard are distinguished:

Natural sources

Potentially man induced sources

Natural sources:

Heavy metals

o Disturbance of the equilibrium of the system groundwater-rocks-

soil gas by the flow in the rocks

o Influence of the oxidation during the flow and acid rains results in

release of the heavy metals into groundwater

o Heavy metals release during mining in consequence of oxidation

Radionuclides

Potential sources of groundwater regime impact:

Industry

o Industry with effluent of organic biological and inorganic wastes

o Oil, fuel and chemical storage

o Pipelines with hazardous substances

o Contaminated sites (spills), brownfields

o Thermoelectric and nuclear power plants

Waste disposals

Highways, roads, airfields

Military establishments

Mining

Agriculture

o Animal husbandries

o Livestock storage

o Silage

o Cultivated areas with expected frequent and abundant use of

pesticides and fertilizers

o Drainages

Municipal

o Urban areas without sewerage network

o Main sever lines

o Treatment plants

o Hospitals

o Cemeteries


B.VII-6

2 Hazard assessment

2.1 Definition

A hazard is the intrinsic property of dangerous or physical situation with a

potential for creating damage to human health and/or the environment. It

does not necessarily led to harm, but there is a possibility of harm

occurring. In the context of groundwater hazard it results in damage of the

installations with the potential sources of groundwater regime impact. The

groundwater hazards could be both qualitative and quantitative. The

qualitative hazard is the direct input, percolation or leaching of hazardous

substances of damaged installations into groundwater. This affects the

deterioration of the status of groundwater body and leads to the exceeding

of the drinking water standards and to a potential impact to human health

and/or terrestrial and aquatic ecosystems. The quantitative hazard is the

impact to groundwater level affecting the temporally land water logging,

damage of buildings and also increasing the vulnerability of groundwater in

Quaternary aquifers.

2.2 Current methodologies for analysing andrepresentation of hazard

The groundwater hazard assessment resulting in natural disasters belongs

to the groundwater protection policy. A very important component of

groundwater policy goals are the vulnerability maps and inventory of the

potential sources, which are susceptible to affect the groundwater regime

(qualitative and quantitative) in consequence of the their damage after

natural disasters. A groundwater vulnerability map is a map showing a more

or less subjective view of the capacity of the subsurface environment to

protect groundwater. The vulnerability maps are used for the groundwater

protection planning, decision – making, land use planning and serve also as

the input data for the delineation of the groundwater source protection

zones. The vulnerability maps are modified for every purpose. This

influences the scale and content of map but also the availability of adequate

data. The vulnerability map with plotted potential sources of groundwater

regime impact is the base input data for the assessment of groundwater

hazard affected by the natural hazards.

2.3 Availability of the required data

The compilation of the groundwater vulnerability map requires profound

knowledge of hydrogeological data and location of the facilities, which are

susceptible to affect the groundwater regime (qualitative and quantitative)

in consequence of their damage after natural disasters.

2.3.1 Required data

The information on the vulnerability of groundwater is based on:

characteristics of soils of unsaturated zone (soils overlying the groundwater

level), saturated zone (aquifer) and other factors influencing the

groundwater regime. The content of required data is varying on the scale

and purpose of the vulnerability map.


B.VII-7

The unsaturated zone is very important element of groundwater protection

with the attenuation capacity. The main parameters are its thickness,

lithodology relating to the consolidation and stratification of the soil, content

of soil organic matter, clay mineral content, permeability etc. The thickness

of the unsaturated zone is distance between the land surface and the

groundwater level. In case of the subsurface potential source of

contamination it should be considered the depth of the groundwater level

under its base.

The main data on saturation zone are: geological and hydrogeological

structure, lithodology, geometry of aquifer, circulation of groundwater

(recharge and discharge areas), type of aquifer (unconfined, confined),

hydraulic parameters (conductivity, storage and transmisissivity),

groundwater flow velocity and direction, range of groundwater level

fluctuation, groundwater level contours, water divides, contact with other

aquifers, with the streamflows, etc. The affected groundwater regime by the

natural hazards can accelerate the migration of contaminated groundwater,

both of natural and artificial origin. Hence, the data on groundwater

contamination are required.

The other factors influencing the groundwater regime are natural and

artificial. The natural factor is climatologic data, topography (as slope

variability), and vegetative cover, hydrology and water chemistry. The

hydrological data are very important factor influencing the groundwater

regime in the aquifer adjacent to the streamflow. These consist of the

streamflow network and discharge capacity of stream channels, baseflow

etc. The artificial factors are following: groundwater abstraction for water

supply (location data on source and abstraction), dewatering wells and

elements as large drainage pipes, discharge location of large drainage pipes

and sewages to the receiving watercourses, impoundments at the

streamflows, land use etc.).

Besides the vulnerability, are very important data on installation with the

potential sources of groundwater regime impact.

The first rank occupy the installations relating to the potentially

contaminating activities as follows:

• Industry

o Industry with effluent of organic biological and inorganic wastes

o Oil, fuel and chemical storage

o Pipelines with hazardous substances

o Contaminated sites (spills), brownfields

o Thermoelectric and nuclear power plants

• Waste disposals

• Highways, roads, airfields

• Military establishments

• Mining

• Agriculture

o Animal husbandries

o Livestock storage

o Silage

o Cultivated areas with expected frequent and abundant use of

pesticides and fertilizers


B.VII-8

o Drainages

• Municipal

o Urban areas without sewerage network

o Main sever lines

o Treatment plants

o Hospitals

o Cemeteries

The second rank occupy the facility relating the quantitative impact as

follows:

• Large drainage pipes

• Discharge location of large drainage pipes and sewages to the

receiving watercourses

• Abstraction and dewatering wells

2.3.2 Data source

The methods, sources and techniques for the data collection and processing

are common for the skilled hydrogeologists. Every country stores the

necessary data in another way. But the storing is on principle common.

The base input sources are the available maps as follows:

• Topographic maps

• Groundwater vulnerability maps

• Hydrogeological maps

• Geological maps

• Soil maps

• Engineering geological maps

As was above mentioned, many groundwater vulnerability maps were

issued in different scales. These cover often only small areas and were

drawn up for different purposes and with different content. The systematical

published groundwater vulnerability maps are rather the exception.

The groundwater vulnerability maps published by the National Rivers

Authority in regional scale 1: 100 000 cover the territory of England and

Wales (see Annex 4). In other countries, there were issued the groundwater

vulnerability maps in different scales and for different purposes. For

example, in Czech Republic were issued the following groundwater

vulnerability maps: the groundwater protection maps in the scale 1: 200

000 (Olmer, Rezac 1974), in eighties of the last century were issued the

groundwater vulnerability maps in the scale 1: 50 000, but this edition was

not finished and the maps cover only part of Czech Republic, in nineties the

vulnerability maps were produced for the District studies of raw materials.

The groundwater vulnerability maps were often compiled for the delineation

of the groundwater source protection zones. The mentioned examples show

that the purpose of vulnerability maps and corresponding content is

different, but the main data – groundwater vulnerability are available in

every groundwater vulnerability map. Every existing type of groundwater

vulnerability map is useful for the natural risk map of natural hazards.

The other data sources for the groundwater vulnerability are as follows:

• Archives:

o State (data of geological investigation, e.g. GEOFUND)


B.VII-9

o Geological institutes (State Geological Survey)

o Consulting and drilling companies

• State administration:

o Environmental protection authorities, water management

authorities

o Public health

o Regional planning

o Institutes responsible for state monitoring network (e.g.

Hydrometeorological Institute)

o Other monitoring networks

o Water Authorities

o River Basin Authorities and water supply agencies

o Agriculture agencies and farmer organizations

The sources of the installations with the potential source of groundwater

regime impact are as follows:

• The main polluters and potential polluters

• Regional and Municipal Authorities

• Environment Inspection Authorities

• Water Authorities

• River Basin Authorities

In the EU countries are available other data source relating to the

potentially contaminating activities – list of installations belonging under

two EU Directives:

• 96/61/EC concerning integrated pollution prevention and control,

denominated IPPC

• 96/82/EC on the control of major-accident hazards involving

dangerous substances, with acronym Seveso

The purpose of the IPPC Directive is to achieve integrated prevention and

control of pollution arising from the activities referring to production or

inputs listed in Annex I of IPPC Directive. The mentioned activities refer to

the threshold values to production or inputs. IPPC Directive lays down

measures designed to prevent or, where that is not practicable, to reduce

emissions in the air, water and land from the mentioned activities, including

measure concerning waste, in order to achieve a high level of protection of

the environment. The main polluting substances to taken out if they are

relevant for fixing emission limit values are listed in the Annex III of IPPC

Directive. The information on the installations belonging under IPPC can

provide the competent authorities responsible under legal provisions of the

EU Member States for carrying out the obligations arising from the

Directive.

The acronym of the second mentioned EC Directive Seveso has origin in the

name of an Italian city, in which occurred a major accident with serious

damage of the human health and environment. The Seveso Directive is

aimed at the prevention of major accidents which involve dangerous

substances, and the limitation of the consequences for man and the

environment, with a view to ensure high levels of protection in a consistent

and effective manner. It is applied in establishments and installations in

which dangerous substances are produced, used, handled or stored. The

danger substances comprehending a substance, mixture or preparation are


B.VII-10

listed the Annex I, Part 1 and 2 of Seveso Directive. Under Seveso fall the

installations in which are present the listed danger substances as a raw

material, product, by-product, residue or intermediate exceeding the

qualifying qualities for the application mentioned in the Annex I, Part 1 and

2 of the Directive. Operators of the installations falling below the Seveso are

obligated to take all the measures necessary to prevent major accidents

and to limit the consequences for man and environment. Some of the

operator’s obligations are the drawing up the emergency plans with the

objectives of:

• Controlling the incidents so as to minimize the effects and to limit

damages to man, environment and property

• Implementing the measures necessary to protect man and the

environment effects of major accidents

• Communicating the necessary information to the public and to the

services authorities concerned in the area

• Providing for the restoration and cleaning-up of the environment

following a major accidents

The operators submit the document setting out the major prevention policy

and emergency plans to the competent authority responsible under legal

provisions of Seveso. The objective of preventing major-accidents and the

consequences of such accidents are to be taken into account in their land

use policies and/or other relevant policies. The information on the

installations falling under Seveso can provide the relevant competent

authorities responsible for carrying out the duties laid down the legal

provisions.

Both, the installations falling under IPPC and Seveso Directives have to take

in consideration besides the measures considering the hazard resulting in

current operations also the hazards resulting in the affects of the natural

hazards. The natural risk maps are very important tool in this respect.

The inseparable part of the data source is the field reconnaissance. The

objectives of it are:

• Checking of the obtained data

• Collection of missing data and actualization of the obtained data in

the concerned area

• Collection of data on contaminated sites

The last but not too much used method of data collection is the public

participation. The EC Directives encourage the active involvement of all

parties in implementation of the EC Directives especially in the environment

issues. The public information and consultation is very important tool for

the natural risk map production. This concerns all the types of natural

hazard.

A part on the PHARE project “Integrated decision making in environment

and support of public participation,” solved in Czech Republic in 2000, was

focused on public participation in the drawing up of the flood plans. During

the public information on the prepared floodplans the participants initiated

many useful suggests for flood mitigation measures to be included to the

flood plans. The public information meeting preceded the detailed

information on the flood plans using the mass media, small exhibitions,

poster and leaflet information.


B.VII-11

The volume of the collected information depends on the scale. The regional

scale requires less detailed information based especially on the existing map

data. The information relating to the installations with the potential

groundwater regime impact can be only general, not detailed (for example

the installation falling under Seveso and IPPC). The plotted selection

depends on grade of the hazard. The skilled hydrogeologist in the

groundwater protection and migration of contaminants in unsaturated and

saturated zone has to assess the selection of the potential sources to be

affected by the natural hazards for the vulnerability maps. The field

reconnaissance is very limited. The field reconnaissance takes a substantial

part of the work within the data collection for the maps in local scale. The

information on the plotted installations with the potential impact on

groundwater regime in the vulnerability maps has to contain the data on

the installation and hazardous substances. These data have to be shown in

the annexes of the vulnerability map.

3 Element at risk and exposure


The risk of the possible secondary effects of natural hazards on

groundwater is originated in the damage of the installations with potential

sources of groundwater regime impact. The impact of the individual natural

events on groundwater regime was described in the paragraph 1.1.

The summarized elements at risk could be as follows:

• Escapes of hazardous substances of the installations with the

potentially contaminating activities, where the dangerous substances

are produced, used, handled or stored (e.g. oil, fuel or chemical

storage industry with effluent of organic wastes, inorganic wastes,

airfields, landfills, military establishments, slaughterhouses, mines,

specially abandoned mines, quarries, animal husbandries, livestock

storage, silage)

• Leachate of contaminated sites, sites with the hazardous chemical

waste spills, brownfields, cultivated areas with expected frequent and

abundant use of pesticides and fertilizers, areas with the

contaminated soil and groundwater of natural origin

• Direct migration or infiltration of the inundated floodwater, lahars,

etc.

• Discharge facilities of the drainage, sewer pipes or fluvial pipes in the

receiving water course (interruption of the discharge function

resulting in increase of the water level in the receiving water course)

3.2 Definition of exposure

Exposure refers to chemicals or elevated groundwater levels by relevant

pathways.


B.VII-12

4 Groundwater vulnerability and groundwatervulnerability maps

4.1 Definition of groundwater vulnerability

Groundwater vulnerability is not an absolute property but rather a complex

indicator. It is a relative, non-measurable, dimensionless property. The

original concept of groundwater vulnerability was based on a simple

premise that the physical environment may provide some degree of

protection to groundwater with regard to contaminant entering the

subsurface. The earth materials has of function of a “natural filter” with

attenuation capacity. Water infiltrating to the unsaturated zone may be

contaminated but is naturally purified to the same degree as it percolates

through the soil and other fine-grained materials in the unsaturated zone.

The vulnerability is an intrinsic property of a groundwater that depends on

sensitivity of that system to human and/or natural impacts (Vrba and

Zaporozec 1994). The sensibility of aquifer is the intrinsic susceptibility of

migration of the contaminant to the aquifer of interest. It is a function of

the intrinsic characteristics of the geological material in question and the

overlying saturated and unsaturated materials. Two general types of

vulnerability are differentiated:

• Intrinsic vulnerability depending solely on hydrogeological factors

• Specific vulnerability depending on hydrogeological factors and

imposed contaminant load

4.2 Methodologies for assessment of groundwatervulnerability

The approach depends on the quantity and quality of available data, the

purpose of the study and scale. The three groups of the groundwater

vulnerability assessment methods could be distinguished: hydrogeological

setting methods, parametric methods and analogical relation and model

methods (Vrba, J., Zaporozec, A. et al. 1994).

4.2.1 Hydrogeological setting

Hydrogeological setting methods are more universal system suitable for

large areas with the variety natural features. The methods involve the

comparison of a study area to criteria judged to represent vulnerable

conditions. They are suitable for the regional scale. Considering the possible

universality of the selected information the thematic maps could be plotted.

The maps in regional scale (1:100 000 – 1:500 000) provide the limited

information, because the data are more generalized. The groundwater

vulnerability assessed for the “hydrogeological setting” method was

presented on the examples of different groundwater vulnerability maps.

The regional groundwater vulnerability maps issued by the National Rivers

Authority in England and Wells in nineties years of the last century serve as

a very instructive example. The maps contain the distribution of aquifers

subdivided the permeable strata and aquifer vulnerability assessed

according the data on the overlying strata. The National Rivers Authority


B.VII-13

(1992) defined the types of aquifers and of the vulnerability for the

groundwater protection policy. The mentioned classification was used in the

groundwater vulnerability maps 1:100 000. The colours represent the types

of aquifers and the shaded colours of relevant colour of concerned aquifer

represent the relevant vulnerability classes. The low vulnerability

corresponds to the lightest colour shade. The classification of the types of

aquifer considering contaminant spreading within aquifer is shown in Annex

3 and 4 (NRA 1992, Vrba – Zaporozec 1994):

• Major aquifers:

Highly permeable formations usually with the known or probable

presence of significant fracturing. Highly productive strata of regional

importance often used for large potable abstractions Examples: Chalk

and Jurassic limestones, Permo-triassic sandstones, Magnesian and

Carboniferous limestones

• Minor aquifers:

o Fractured or potentially fractured but with high intergranular

permeability. Generally only support locally important

abstractions.

Examples: Millstone grit, Old Red sandstones, some igneous and

metamorphic formations

o Variably porous/permeable but without significant fracturing.

Generally only support locally important abstractions.

Examples: gravels and sands (fluvial and Tertiary)

• Non-aquifers:

Formations with negligible permeability. Only support very minor

abstractions, if any.

Examples: all clays, shales, marls and siltstones. Most igneous and

metamorphic formations.

Groundwater vulnerability according to soil classification of unsaturated

zone used in the NRA vulnerability maps is presented in table 1.

Vulnerability class Nature of unsaturated zone Example

Extremely highIneffective and/or insignificantly

thick or discontinuous

Fissured or

highly karsticHigh

HighHighly permeable with unsaturated

zone < 2 m thick

Intermediate

Moderate permeability

(k=10-5–10-3 m/s).

Depth of g.w. level 2–20 m,

2–50 m in karst with low karstic

index

Commonly

unconsoli-

dated

formation

LowLow permeability.

Depth of g.w. level > 20 mLow

Very lowPractically impermeable and of

significant thickness

Clay or shale

Table 1: Classification of groundwater vulnerability

according the overlying strata according to NRA (Vrba,

Zaporozec 1994)

The regional maps involve a compromise between the representation of

natural complexity and ease interpretation of the map. Such compromises

place limitations on the resolution and precision of map information. In this

case, the variety of soils, geological strata and potential contaminants that

have to be covered is wide, and the classification should be generalized.


B.VII-14

Individual sites and circumstances always require further and more detailed

assessments to determinate the specific impact on groundwater resources.

The content of the groundwater vulnerability maps in the regional scale is

very similar and some used methods imply other elements to be plotted in

the maps. The Czech maps of groundwater protection 1:200 000 consider

the main natures of the aquifer (lithodology, structure or tectonics), which

are expressed by the colours and degree of regional protection of the

resources are expressed by the ornaments. The following degree of the

protection were defined:

• Areas with the intensive groundwater abstraction and areas with

perspective intensive abstraction (within 15 – 20 years) – strong

protection

• Significant hydrogeological areas – strong protection

• Areas with variable vulnerability, not requiring the strong protection –

partial protection. Individual abstraction well fields protected by the

groundwater protection zones

• Area with a low abstraction yield and very limited aquifers – the

protection of individual groundwater abstractions

• Protected recharge areas

The additional elements are plotted as follows: groundwater flow direction,

water divide, hydrogeological zone boundary, recharge areas, source

protection zones, hydrogeological function of the fractures etc. (Olmer,

Rezac, 1974).

The method of hydrogeological setting is available also for the vulnerability

or groundwater protection maps in local scale. In Czech Republic were used

the groundwater protection maps in the scale 1:25 000 (Vrana, 1981). The

following elements were plotted:

• Type of aquifer (expressed by the colour)

• The transmissivity of the aquifer (expressed by the shaded colours for

relevant aquifer colour). Richness of the relevant colour shade:

o 100%: more than 100 m2/day

o 75%: 11 – 100 m2/day

o 50%: 1 – 10 m2/day

o 25%: less than 1 m2/day

• Nature of the unsaturated zone (expressed by the ornaments); four

classes were defined: high permeable, moderate permeable, low

permeable and negligible permeable

• Other natures:

o Potential sources of contamination

o Ground and surface water data: groundwater abstraction wells

and fields, groundwater flow direction, groundwater contours,

groundwater source protection zones

o Other elements as: irrigated areas, drained areas, cemeteries,

pipelines (petroleum, chemicals, gas), storages (oil, fuel, service

stations, chemical storage), waste disposal, hazardous or toxic

spills, isolines defining contamination, etc


B.VII-15

4.2.2 The parametric methods

The are based on the vulnerability assessment of the selected parameters

using the following systems (Vrba, Zaporozec 1994):

• Matrix system

• Rating system

• Point count system models

The overall procedure for the various parametric systems is the same. It

begins selecting the parameters and their attributes representative for the

purpose of the study. Each of selected parameters has a given range, which

is subdivided into discrete hierarchical intervals. Each interval is assigned a

value reflecting the relative degree of vulnerability. The rating points are

summed and the final numerical score is divided into four or five segments

expressing relative degrees of vulnerability.

Matrix system

The matrix systems are based on the limited numbers of the estimated

parameters.

Unsaturated zoneVulnerability

rating Nature of strata L[m]

Extreme Outcropping bedrock < 3

Soil of intermediate permeability (e.g. sandy till) 3-10High

Soil of low permeability (e.g. clayey till, clay or peat) 3-5

Sandy till > 10Moderate

Clayey till, clay or peat 5-10

Low Clayey till, clay or peat > 10

Comment: L – the thickness of the unsaturated zone (depth of groundwater level below the land

surface)

Table 2: Classification of groundwater vulnerability

according to the type of the soils of unsaturated zone

for different thickens of unsaturated zone (Daley 1995)

The examples of the selected parameters:

• Flemish region in Belgium (Vrba, Zaporozec 1994):

o Three types of soils of unsaturated zone

o Two intervals of the thickness of unsaturated zone (table 1)

o Four types of aquifer

• National Rivers Authority in UK (1992):

o Three types of soil leaching potential (with 1 – 3 sub-classes)

o Depth of unsaturated zone

o Three types of aquifers (chapter 4.2.1, Annex 3)

• Ireland (Daley 1995), vulnerability rating is shown in the table 2:

o Nature of soils of unsaturated zone

o Depth of groundwater level

Rating system

A fixed range is given to any parameter that is judged necessary and

adequate for vulnerability assessment. Many parameters are used in the

rating systems. The following parameters are used most often:

characteristic of the soils of unsaturated zone, depth of groundwater level,

hydrogeological features, soil parameters (thickness, texture) and

groundwater level changes. Different rating systems were developed and


B.VII-16

used for groundwater vulnerability map production. Foster (1987) has been

proposed a very simple rating system known with the acronym GOD. The

acronym expresses the used parameters:

• G: groundwater occurrence (type of aquifer: artesian confined,

confined, semi-confined, semi-confined covered, unconfined

• O: overlying lithodology

• D: depth to groundwater level (unconfined aquifer), strike (confined

aquifer)

The classification of the groundwater vulnerability is assessed by means of a

nomogram (see Annex 1). Each step of assessment consists of the

estimation of the relevant rate of three mentioned parameters. All the rates

are multiplied and resultant product classifies the groundwater vulnerability.

Point count system models

Every assessed parameter is assessed according to rating, analogically as in

the rating system. In addition, weight of the parameter is assessed. The

weights reflect the relative importance of the each of selected parameter.

Both, ranting value and weight are multiplied and summed to obtain the

final numerical score that provides relative measure of the groundwater

vulnerability.

The most used point count system with acronym DRASTIC was developed

for the U.S. Environmental Protection Agency (Aller et al 1987). The higher

the score, the greater sensitivity of assessed area. The independent

parameter form the acronymic name of the method:

• D: depth to groundwater level

• R: recharge (net annual)

• A: aquifer media

• S: soil media

• T: topography (slope)

• I: impact of vadose zone (water occurring in the unsaturated zone –

above the groundwater table and bellow the soil horizon)

• C: Hydraulic conductivity of aquifer

The rating assigns each class of parameter a value, based on a scale of 1

(lest contamination potential) to 10 (highest contamination potential). The

weight varies in the rate of 1 – 5. The assigned weights and ranges of

rating values for groundwater vulnerability assessment are shown on the

table 3.

Parameter Rating Weigh

D Depth to groundwater level DR 1 – 10 DW 5

R Recharge (net annual) RR 1,2,4,5 RW 4

A Aquifer media AR 3 – 9 AW 3

S Soil media SR 4 - 10 SW 2

T Topographic slope TR 1- 5 TW 1

I Impact of the vadose zone IR 1- 5 IW 5

C Hydraulic conductivity CR 4 - 8 CW 3

Table 3: Assigned weights and ranges of rating values

for groundwater vulnerability (Aller et al 1987)

DRASTIC index DI qualifying the groundwater vulnerability is calculated by

the following equation:


B.VII-17

DI = DR.DW + RR.RW + AR.AW + SR.SW + TR.TW + IR.IW + CR.CW

The rating of some parameters is shown in Annex 1. The rating of the

parameters is often modified for the relevant hydrogeological conditions.

Some examples of application of parameters mentioned Hamerlink and

Arneson (1998), Kim and Hamm (1999) and Shahid S. (2000). The

examples of rating of the parameters are shown in the Annex 1.

Drastic index provides only a relative evaluation tool and is not provide

absolute answers. The procedure for implementing the DRASTIC method

involves:

• Collecting of hydrogeological data

• Standardizing and digitalizing of source data

• Constructing an environmental geologic database

• Calculating of the DRASTIC index for the hydrogeological settings

within study area

• Rating these areas as to vulnerability to contamination

Vulnerability assessment and mapping should be based on hydrogeological

evaluation, rather than on general, automatic procedures. A combination of

aquifer simulation models and geographical information systems offers a

unique opportunity to perform this task.

5 Analogical relations and numerical models

Analogical relations and numerical models are based on mathematical

symbols resulting in a vulnerability index. The vulnerability index estimated

by Marcolongo and Pretto Darcy-derived expression considering hydraulic

conductivity of unsaturated zone, its thickness, actual soil moisture and

infiltration rate per unit surface. Anderson and Gosk used two factors:

cleaning capacity of soils and restoration capability of aquifer. The first

factor was evaluated case by case, as a function of soil type and of

contaminants. It should be expressed as contaminant quantity removed by

the unit volume of soil. The second factor is the inverse of the travel time in

an aquifer (Vrba, Zaporozec 1994). The analogical relations and numerical

models are not commonly used.


The following vulnerability maps are drawn up in hydrogeology (Vrba,

Zaporozec 1994):

• General over view synoptical (1:500 000 or more): serving for the

general planning, decision making and setting policies in groundwater

protection on national or international level. The local details are lost.

• Schematic (1:500 000 to 1:100 000): serving for the regional

planning, groundwater protection management and regulation and

assessment of the diffuse contamination problems. Most of the local

details are still lost. These need to be followed by the specific

mapping.

• Operational (1:100 000 to 1:25 000): serving for the land use

planning and design of groundwater protection programme.

• Specific for special purpose (1:25 000 or less): serving for the single

purpose and site-specific maps foe local or city planning and


B.VII-18

abstraction well protection (groundwater source protection zones).

The local or site-specific groundwater vulnerability problems are

expressed.

The vulnerability maps (1: 1 000 to 1:100) are not available for site

engineering approach. Whereas the vulnerability maps shall serve for the

natural risk maps, the scale is conform to the scale used for the individual

natural events:

• Regional scale: 1:50 000 – 500 000

• Local scale: 1:5 000 – 50 000

• Detail scale: 1:500 – 5 000

The vulnerability is common for all the scales. The facilities, which are able

to affect the groundwater regime in consequence of their damage after

natural disasters and other specifying elements have to be plotted in the

maps of local and detail scale.

5.2 Examples of groundwater vulnerability maps andlegends referred to assumed scales

5.2.1 Legend of groundwater vulnerability map

The proposed legend adopts the international legend presented as

contribution to the International Hydrological Programme IHP IV (Vrba,

Zaporozec 1994). The legend is shown in the Annex 2.

5.2.2 Examples of groundwater vulnerability maps

Two examples of vulnerability maps are shown. One in regional scale and

one in local scale

Regional groundwater vulnerability map

The example of the regional vulnerability map was shown at a part of a

groundwater vulnerability map issued by the National Rivers Authority (UK)

at the scale 1:100 000 (see Annex 4). The maps were issued in conformity

with the “Practice for the Protection of Groundwater (NRA 1992) as a tool

for the protection and management of aquifers, land use planning to protect

the groundwater quality. The map contains the information considering the

type of aquifer and vulnerability of the unsaturated zone. The classification

of the aquifer importance considering the potential spreading of

contaminants within aquifer is shown in the Annex 3 and the classification

of the vulnerability of the unsaturated zone is shown in the table 1. The

map does not contain the information on the potential sources of

groundwater regime impact.

Local groundwater vulnerability map

The example of the local groundwater vulnerability map is a map serving as

input data for groundwater source zone of the Podluzi abstraction well field

in Czech Republic - see Annex 5 (Muzikar, Vrtek 2000). The map was

plotted at the topographic base 1:25 000. The type of aquifer was not

plotted, because one type of aquifer occurs at the area interest. The fluvial

gravels and sands of high permeability (coefficient of conductivity reaches

about 10-3 m/s) form the aquifer. The fluvial clays form the unsaturated


B.VII-19

zone. Three classes of vulnerability were estimated according to thickness

of the unsaturated zone”

• High: thickness < 2,0 m

• Moderate: thickness 2,0 – 3,5 m

• Low: thickness > 3,5 m

In addition, there were plotted the following data:

• Abstraction and monitoring wells

• Data on groundwater flow (flow direction, water level surface)

• Potentially contaminating activities

5.3 Groundwater vulnerability map production for riskmaps of natural hazards

Production of groundwater vulnerability map is a special hydrogeological

task requiring a thorough knowledge of hydrogeological conditions and

many detailed data, which are often not available. The above-mentioned

required data are optimal for the groundwater vulnerability assessment. The

mapmaker has to decide the most effective assessment of the available

data to provide reasonable and reliable estimation of groundwater

vulnerability using the available data.

The regional groundwater vulnerability maps have to contain the data on

groundwater vulnerability concerning both the unsaturated zone and type of

aquifer – the decisive parameters affecting the pollution migration. The

assessment of the vulnerability of the unsaturated zone can be based on

the nature of unsaturated zone and its thickness (table 1 or 2 or perhaps

GOD – Annex 1). The definition of type of aquifer can be influenced by the

local hydrogeological conditions. The definition used by NRA (paragraph

4.2.1 or Annex 3) is appropriate. The vulnerability assessment according to

DRASTIC (see paragraph 4.2.2. and Annex 1) considers also the type of

aquifer and the plotting of the aquifer type is not necessary. The elements

providing more detailed information on natural conditions such as e.g.

groundwater flow direction, water divide and those to be protected such as

large groundwater abstraction can be plotted if are available and if the

plotting is synoptic in the used scale. The potential sources of groundwater

regime impact should be plotted only these the most hazard e.g. these

belonging under IPPC and Seveso EC Directive.

The local groundwater vulnerability maps have to concern identically to

regional maps the decisive parameters affecting the pollution migration –

vulnerability zone and aquifer type. The local maps have to contain more

available data on natural conditions than in regional maps. The other

available date on natural conditions should be as follows: water divide,

groundwater contours and groundwater flow direction, abstraction well

fields, protection zones, etc. The potential sources of groundwater regime

impact is to be selected according the weight of impact. The selection of the

potentially contaminating activities depends on the nature, properties and

volume of hazardous substances in raw material, product, by-product or

residue in concerning establishment.

Many types groundwater vulnerability of maps has been developed since

1960s. Two methodological guides and revised model legend generalizing


B.VII-20

the long-term researches were elaborated in the frame of the forth phase

International Hydrological Programme of UNESCO:

• Vrba, Zaporozec (1994): “Guide on Mapping Groundwater

Vulnerability” International Contributions to Hydrogeology, Vol. 16,

International Association of Hydrogeologists, Verlag Heinz Heise

GmbH & Co KG, Hannover, 131 pp

• Struckmeier, Margat (1995): “Hydrogeological Maps: A guide and

Standard Legend” International Contributions to Hydrogeology, Vol.

17, International Association of Hydrogeologists, Verlag Heinz Heise

GmbH & Co KG, Hannover, 178 pp

The both guides will be used for the compilation of groundwater

vulnerability resulting in natural disasters. The international standard

legend was shown in both guided and this should be used also in the risk

map of natural hazards.

6 Analysis of risk


Risk is the potential for inflicting damage upon a receptor. In case of

possible secondary effects of natural hazards on groundwater quality it is an

approach used to evaluate risk and hazards to human health that are

attributable to escapes of hazardous substances of damaged installations.

Definition: Risk is an estimation of the probability that an adverse health

impact may occur as a result of exposure to hazardous substances in the

amount and by the pathways identified.


The methodology of risk assessment of the contaminated industrial sites

was developed in hydrogeology jointly with the health authorities. It is

widely used. The risk assessment is focused on evaluation of the

carcinogenic risks and no carcinogenic hazards to human health. It is one of

the input data for the determination of target concentrations for the

remediation and assignment of remediation projects.

Such risk assessment required mostly very costly investigations and

monitoring. The risk assessment of the hazards originated by the natural

hazards cannot collect available data for such assessment. The volume of

released quantities of hazard substance and space distribution and their

concentrations are unknown and other necessary data could not be

obtained in process of map compilation. The risk assessment has to be

carried out for every installation. Such approach could not be made for

maps of natural hazards. However, a brief description of the steps of such

risk assessment will provide the image on the mechanism of the origin,

migration and hazards of the groundwater pollution after natural hazards.

Risk assessment, in general, has a four components including:

• Identification and characterization of priority pollutants

• Identification of path ways and mechanisms for chemical migration


B.VII-21

• Quantity and space contamination distribution estimate resulting in

natural disasters

• Identification and description of receptors

• Risk characterization estimate

• Evaluation of uncertainties

6.2.1 Identification and characterization of priority pollutants

The information on the establishments liable to produce pollution has to

contain the list of priority pollutants with their quantity and the properties

as toxicity, sorption, solubility, volatility etc. Such data are variable and for

that reason have only the informative function on the hazards.

6.2.2 Identification of path ways and mechanism for chemicalmigration

When are damaged the facilities containing or handling with the hazardous

substances, the contaminant releases to groundwater can occur. There are

at least four pathways by which groundwater contamination occurs:

• Infiltration

• Direct migration

• Interaquifer exchange

• Recharge from surface water

Infiltration

Two paths of infiltration occur. Liquid released hazard substance slowly

infiltrates the soil through pore spaces in the soil matrix. It moves

downward under the influence of gravity. Once the saturated zone is

contacted, horizontal and vertical spreading of infiltrated substances occurs

in the saturated zone in the direction of groundwater flow.

A portion of water, which has fallen to the earth, induces the other path.

This slowly infiltrates the soil through pore spaces in the soil mix. As the

water moves downward, it dissolves materials, which it comes into contact.

Water and/or liquid hazard substances percolating downward though a

contaminated soil of unsaturated zone can dissolve contaminants, forming

leachate. The other movement of leachate is the as was described above.

Direct migration

The hazardous substances can migrate directly into groundwater from

belowground sources (e.g., storage tanks, pipelines), which lie within the

saturated zone.

Interaquifer exchange

Groundwater contaminated after the natural hazards can mix with the

uncontaminated groundwater through a process known as interaquifer

exchange in which one aquifer unit is in hydraulic contact with another.

6.2.3 Quantity and space contamination distribution estimateresulting in natural disasters

The quantity of hazardous substances released to soil and groundwater is to

be estimated. The forecast of the contaminants migration in groundwater

means the space distribution (so called contamination plume) and


B.VII-22

contaminant concentrations. The migration depends on many factors such

as geochemical processes, biochemical process (decomposition by

microorganisms), physical processes (as advection – movement of

contaminants caused by groundwater flow, filtration, adsorption) etc. The

transport models of contaminants are produced, requiring many data. But

the accuracy should be very low.

In case of the risk assessment of the hazard of groundwater pollution

resulting in natural events can be estimated only the probably affected

receptors without forecasting of the changes of the groundwater quality.

The estimation of the contaminant plume could be based on the

groundwater velocity. Such estimation is very approximate. Nevertheless,

the data on groundwater flow velocity are mostly not available.

The estimation could arrive from very proximately estimation of the

contaminant plume.

6.2.4 Identification and description of receptors

The extension of contaminant plume with forecasted contaminant

concentrations helps to determinate the receptors. The receptors are

population (human health) and environment components. The potential

affected populations could be expressed with its number.

6.2.5 Risk characterization estimate

Risk characterization is the process of estimating the incidence of a health

under various conditions of human or animal exposure described in the

exposure assessment. The soil and groundwater exposure is considered.

Soil ingestion, dermal exposure and inhalation of resuspended dust are the

potential soil exposure pathways. Factors that affect dermal exposure

include surface area, contact time and contact amount. The groundwater

used for water supply as drinking water is assessed considering the

exposure via ingestion and groundwater used for the bathing is assessed

considering the dermal and inhalation exposure. The contaminated

groundwater used for irrigation is potential source of contamination of the

agriculture products. In such cases the food exposure pathway have to be

assessed.

The contaminant space distribution and concentration together with the

target concentrations affects the remediation proposal. The influence of any

remedial action on the migration pathway has to be examined. This requires

the transport model solution.

6.2.6 Evaluation of uncertainties

The conceptual model underlying risk assessment is “source – pathway –

receptor”. The main uncertainty is the inadequate data on source of

contamination and following inadequate estimation of the quantity of

escaped hazardous substances. Other uncertainty is the low information on

hydrogeological data and contaminant concentration.


B.VII-23

6.2.7 Recommended method

The risk of groundwater contamination as possible secondary effects of

natural hazards is affected with lack of data and many uncertainties. Hence,

the assessment could be greatly simplified. The risk is based on the weigh

of the consequences and on the probability of the occurrence of event

leading to the considered consequence. Such approach is used in the

establishment belonging under Seveso. The risk can be expressed as:

Risk = Consequence X Probability

Consequence – it is considered the weigh of the consequence

Probability – it is considered the probability the occurrence of the event

leading to the relevant consequence

The estimation of the consequence can takes in account the following:

• Number of the people with damaged groundwater supply source

• Cost of source remediation, cost emergency water supply and/or

cost of new water supply system

• Cost of the restoration of damaged ecosystems

The probability depends on the on the probability of occurrence of individual

natural event and then the probability of damage of concerned installation

resulting in escape of the hazard substances.

6.2.8 Conclusion of methodology for risk assessment

The risk assessment of the potentially damaged installation has to be drawn

up for every installation. It means that every installation require the risk

assessment, what is too costly. In addition, the number of uncertainties

exceeds the available date. For that reason there are low probability to

elaborate the real, credible risk assessment. The best solution for the risk

map of natural hazards considering groundwater pollution as secondary

effect is the production of the groundwater vulnerability maps. These

identify the potential risk receptors.

7 Risk management

The emergency plans are the important tool for the risk management of the

accident prevention policy. The plans are required from the operators of the

establishments with the sources of groundwater regime impact. The risk

management in such establishments requires the operator information that

the concerned establishment is located in the risk area of the natural

events. The emergency plans are obligated for the establishments belonging

under Seveso. Besides other, the emergency plans are established with the

following objectives of:

• Containing and controlling incidents so as to minimize the effects to

limit the damages

• Providing for the restoration and clean-up of the environment

following an accident

The operators of the concerned establishments located within the risk area

of the natural events have to reassess the emergency plans with the


B.VII-24

consideration of the natural events hazards if these had not considered,

when the plans were drawn up.


Abstraction well field: a group of wells pumping the groundwater

Aquifer: permeable geologic formation in which occurs groundwater

Attenuation: break down or dilution of a contaminant in water

Brownfield: relating to the brownfield site. It means real property the

expansion, redevelopment or reuse of which may be complicated by the

presence or potential presence of a hazardous substance or pollutant (US

EPA definition).

Catchment: area that collects and drains rainwater

Cone of depression: The limit of influence of groundwater abstraction

(limit of the groundwater level drawdown)

Confined aquifer: aquifer where a substantial depth of impermeable strata

covers the permeable strata such that the cover prevents the infiltration

Exposure: exposure to chemicals or elevated groundwater levels by

relevant pathways

Fractures/fissures: natural cracks in rock that enhances rapid water

movement

Groundwater contour: a line on map connecting the same elevation of

groundwater levels relating to the sea level or reference point. Synonym:

groundwater surface

Groundwater divide: line on water table or piezometric surface across

which there is no groundwater flow and from which groundwater moves

away in both directions

Groundwater regime: characterizes the nature and recharge of

groundwater and changes of its quantity and quality in time and space.

Groundwater surface: a line on map connecting the same elevation of

groundwater levels relating to the sea level or reference point. Synonym:

groundwater contour

Groundwater vulnerability: intrinsic property of a groundwater that

depends on sensitivity of that system to human and/or natural impacts

Hazard: the intrinsic property of dangerous or physical situation with a

potential for creating damage to human health/or the environment

Hydraulic conductivity: measure of the permeability of rock

Hydraulic parameters: hydraulic conductivity and transmissivity

Infiltration: the flow of water downward from the land surface into soil

Leachate: liquor formed by the act of leaching

Leaching: removal of soluble substances by action of water percolating

through soil, waste or rock

Outcrop: where strata are at the surface, even though soil cover may

obscure them

Percolation: flow of water through earth material


B.VII-25

Plume: spreading of a contaminant in the direction of groundwater flow

from the point of origin to the point where contaminant falls bellow the

objective limits. The outer boundary is in some cases difficult to detect.

Recharge: water, which percolates from the land surface into groundwater

Risk: estimation of the probability that an adverse health impact may occur

as a result of exposure to hazardous substances in the amount and by the

pathways identified

Saturated zone: zone of aquifer where all fissures and pores contain water

Sensibility of aquifer: the intrinsic susceptibility of migration of the

contaminant to the aquifer of interest

Source: point of abstraction of groundwater (well, borehole, spring)

Thickness of unsaturated zone: distance between land surface and

groundwater level

Unconfined aquifer: aquifer with the water table forming a free upper

surface

Unsaturated zone: zone between the land surface and the water table

Vadose zone: water occurring in unsaturated zone (soil water, capillary

water)

9 BibliographyAdams D. et all (1994): Conversion of DRASTIC maps from fastcad

drawings to ArcInfo coverages.

http:/gis.esri.com/library/proc98/PROCEED/TO450/PAP402/P402.HTM

Aller L. et all (1987): DRASTIC: A standardized system for evaluation

groundwater pollution potential using hydrogeological settings. NWWA/EPA

Series EPA-300/2-87-035, US EPA, Ada, Oklahoma

Bekesi G., McConchie (2000): Empirical assessment of the influence of the

unsaturated zone on aquifer vulnerability, Manawatu Region, New Zealand.

Daley D. (1995): The role of geology and hydrogeology in selecting landfill

sites.

In: Proceedings of symposium “The role of geology and hyrogrology in

environmental protection”, Dublin, Geological Survey of Ireland, p.10

Focazio M.J. et al (2001): Assessing groundwater vulnerability to

contamination: providing scientifically defensible information for decision

makers. U.S. Geol. Survey, Water Resources Investigations report, 33 p.

Foster S.S.D. (1987): Fundamental concepts in aquifer vulnerability,

pollution risk and protection strategy. In: Vulnerability of soil and

groundwater to pollutants. TNO Committee on Hydrological Research, The

Hague, Proceedings and Information No. 38, p. 69 –86

Gogu R.C., Dessargues A. (2000): Sensitivity analysis for the EPIC method

of vulnerability assessment in a small karstic aquifer, southern Belgium.

Hydrogeology Journal, Vol. 8, p.337-345

Freeze R.A., Cherry J.A. (1979): Groundwater. Eagle Cliffs, N.J., Prentice

–Hall, 604 p.


B.VII-26

Hammerlinck J.D., Arneson Ch.S. (1998): Wyoming groundwater

vulnerability assessment handbook. Volume 1: Background, model

development sensitivity analysis. Spatial Data and Visualization Centre,

SDVC Report 98-01

Holman I.P. et al (2000): Using soil Quaternary geological information to

assess the intrinsic groundwater vulnerability of shallow aquifers: an

example from Lithuania. Hydrogeology Journal, Vol. 8, p.636 – 645

Kim Y.J. – Hamm S.Y. (1999): Assessment of the potential for groundwater

contamination using the DRASTIC/EGIS technique, Cheongju area, South

Korea. Hydrogeology Journal, Vol. 7, p.227- 235

Maxe L. – Johansson P.O. (1998): Assessing groundwater vulnerability

using travel time and specific surface as indicators. Hydrogeology Journal,

Vol. 7, p.441- 449

McBean E.A. (1991): Methodology for introducing risk into the design And

operation of landfills. In: Municipal Solid Waste Management. Making

Decisions in the face of Uncertainty. Institute for Risk Research, p.105-116

Muzikar R., Vrtek T. (2000): Podluzi groundwater abstraction well field –

hydrogeological assessment for the source protection zone. Brno, DHV CR,

MS

NRA (1992): Policy and practice for the protection of groundwater. Bristol,

National Rivers Authority, p. 52

Olmer M. – Rezac B. (1974): Methodical principles of maps for protection of

groundwater in Bohemia and Moravia, scale 1:200 000. In IAH Memoires,

Tome X, Congress de Montpellier, 1. Communications, p. 105-107

Shahid S. (2000): A study of groundwater pollution vulnerability using

DRASTIC, West Bengal, India, Journal of Environmental Hydrology. Vol. 8

Struckmeier, Margat (1995): “Hydrogeological Maps: A guide and Standard

Legend” International Contributions to Hydrogeology, Vol. 17, International

Association of Hydrogeologists, Verlag Heinz Heise GmbH & Co KG,

Hannover, 178 pp

Vrana M. (1981): Methodology for construction of groundwater protection

maps. In: International training course “Groundwater protection from

pollution and depletion”, UNESCO, Moscow, p. 1 – 19.

Vrba J. - Zaporozec A. (1994): “Guide on Mapping Groundwater

Vulnerability” International Contributions to Hydrogeology, Vol. 16,

International Association of Hydrogeologists, Verlag Heinz Heise GmbH & Co

KG, Hannover, 131 pp


B.VII-27

ANNEX 1

Assessment of groundwater vulnerability according to GODand drastic

Classification of Groundwater vulnerability according to GOD:

OVERLYING LITHODOLOGY

(Foster 1987, Vrba – Zaporozec 1997)

Classification of Groundwater vulnerability according to DRASTIC: (Aller et

al. 1987)

RATING

Rating of the factors is usually adapted to the local hydrogelogical

conditions. Some examples are shown bellow.

Depth to water table [m] Rating

0 –1,5 10

1,5 – 3 9

3 – 9 7

9 – 15 5

15 – 22 3

22 – 30 2

> 30 1

Table - factor (Aller et al. 1987)


B.VII-28

D Depth to water table: Rating of depth to water

R (recharge, net annual)

Net recharge is the effective infiltration of groundwater into groundwater. It

is the difference between total precipitation and the cumulative loss by

direct runoff and effective evapotranspiration.

A (aquifer media)

Rating of aquifer-media factor

RatingAquifer medium

Range Typical

Alluvium 6 - 9 8

Gneis 3 - 5 5

Schist 3 - 5 4

Granite 3 - 5 3

(Aller et al. 1987)

S (soil media)

Soil medium RATING

Poorly graded gravel and gravel-sand mixture (GP) 10

Poorly graded sand and gravely sand (SP) 9

Silty sand and poorly graded sand-silt mixture (SM) 8

Clayey sand and poorly graded sand-clay mixture (SC) 7

Silt and very find sand, silty or clayey fin sand (ML) 6

Rating of soil -media factor

T (topographic slope)

The rating for the topographic slope factor is range from 1 – 5. A steeper

topographic slope provides lesser opportunity for a pollutant to infiltrate and

the rating id lower.

I (impact of vadose zone)

Rating of vadose zone-media factor

VADOSE ZONE MEDIUM RATING VADOSE ZONE MEDIUM RATING

CONFINING LAYER 1SAND AND GAVEL WITHSIGNIFICANT SILT, CLAY

4-8

SHALE 2-5 METAMORPHIC/IGNEOUS 2-8

SILT/CLAY 2-6 EOLIAN SAND 7-9

LIMESTONE 2-7 SAND AND GRAVEL 6-9

EOLIAN SILT 5-7 VOLCANICLASTICS 3-9

SANDSTONE 4-8 BASALT 2-10

BEDDED LIMESTONE, SANDSTONE

AND SHALE4-8 CLINKER 8-10

COAL SEQUENCES 3-8 KARST LIMESTONE 8-10

(Aller et al. 1987)

C (impact of hydraulic conductivity)

Rating of hydraulic conductivity factor (adapted according to Aller et al.

1987 and Freeze, Cherry 1979)


B.VII-29

Rating 3 4 5 6 7 8 9 10

Coefficient of conductivity [m s-1] 10-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

Unconsolidated deposits

Glacial till

Silt, Loess

Silty sand

Clean sand

Gravel

Rocks

Sandstone

Limestone and dolomite

Fractur. igneous and metamorphic

Permeable basalt

Aquifer

mediu

m

Karst limestone


B.VII-30

ANNEX 2

Legend for groundwater vulnerability map

(Vrba, Zaporozec 1994)

Hydrogeological Features


B.VII-31

Objects of Protection


B.VII-32

Potentially Contaminating Activities


B.VII-33


B.VII-34

Current Quality Status of Groundwater


B.VII-35

ANNEX 3

Categories of aquifer nature – assessment of potentialcontaminant spreading within aquifer

(NRA 1992, Vrba – Zaporozec 1994)

NATURE OF AQUIFER ORNAMENT


B.VII-36

ANNEX 4

Example of groundwater vulnerability map in regional scale(1:100 000)

Part of the National Rivers Authority’s groundwater

vulnerability map of East Kent

1 : 100 000 (Vrba, Zaporozec 1994)


B.VII-37


B.VII-38

ANNEX 5

Example of groundwater vulnerability map in regional scale(1:25 000)


B.VII-39

ANNEX 6

Operational standards for groundwater vulnerability mapsaimed to spatial planning

Operational Standards for the Groundwater Vulnerability Maps

Aimed to Spatial Planning

The base for the assessment of the potential secondary effects of natural

hazards on groundwater regime (qualitative and quantitative) is the

groundwater vulnerability map. Content of map depends on the availability

of the representative input data and on the legibility of the map. The

groundwater vulnerability map will contain the following data:

• Groundwater vulnerability

• Supplementary data

• Installations with the potential impact on groundwater regime

Groundwater vulnerability

Two main factors characterizing the groundwater vulnerability will be

considered and plotted. The first is vulnerability of the unsaturated zone

influencing the vertical impact and second is the aquifer influencing the

spreading of the impact in groundwater. The classification of the type of

aquifer could be left out if the vulnerability classification considers both the

unsaturated zone and the type of aquifer (e.g. using DRASTIC method) or if

one type of aquifer occurs at the entire map. In second case the type of

aquifer will be presented in the legend.

The classes of vulnerability of the unsaturated zone will be presented by

colors. The colors are conform with the international legend (Vrba,

Zaporozec 1994):

• Extremely high: red orange

• High: rose

• Medium: yellow

• Low: light olive green

• Very low: dark olive green

The presentation of three classes of vulnerability:

• High: red orange

• Medium: yellow

• Low: olive green

The ornaments will express the type of aquifer by (see Annex 3).

The other recommended presentation of vulnerability is that used in

England and Wales (see Annex 4). The type of aquifer is presented with

color and the unsaturated zone with its shadow.

Supplementary data

The supplementary data provide the information on other natural and

artificial factors influencing the groundwater regime, which will affect the

spreading of the impact originated by the consequences of natural hazards.

The supplementary data are as follows: water divide, groundwater


B.VII-40

contours, groundwater flow direction, abstraction well fields, resource

protection zones, drained areas, etc.

The regional vulnerability maps usually do not plot the supplementary data.

The data such as water divide, groundwater flow direction and large

groundwater abstraction well fields provide very valuable information to

assess the natural events impacts.

Installation with potential impact on groundwater regime

The installations with potential impact on groundwater regime are both with

the qualitative and quantitative impact. The quantitative impact originates

these where hazardous substances are present in raw material, product, by-

product and residue. The regional maps will plot only the most hazard

installations (e.g. belonging under IPPS and Seveso EU Directives). The

selection of the potentially contaminating activities for the local maps will

depend on the nature, properties and volume of hazardous substances. The

examples of potential contaminating activities were shown in the legend of

vulnerability maps (Annex 2).

The installations with potential quantitative impact on groundwater regime

are as follows: large drainage pipes, location of the discharge of large pipes

and sewages to the receiving watercourses, impoundments on

watercourses, abstraction and dewatering wells.

Scale

The scale of the groundwater vulnerability maps will be conform to the scale

of the maps of individual natural events:

• Regional scale: 1:50 000 – 500 000

• Local scale: 1:5 000 – 50 000

• Detail scale: 1:2 000 – 5 000

The groundwater vulnerability maps with the scale less than 1: 2 000 are

not available.

C- 2

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

1 Floods

1.1 HazardMAP SCALE(FLOODS HAZARDSTATE OF ART)

CHARACTERISTICS AND USE DATA ACQUISITION ANDMAPPING PROCEDURES

HAZARD METHODOLOGY LEGEND

Site-specific(<1:1,000)

Provide maps and information thatare used at a very detailed level, forexample the construction of a newhousing development that covers afew hectares. They may cover onlya few hundred metres of the river.The characteristics of such mapsare dependent on the nature of therisk to be assessed. Such mapusually show the extent of floodingbut they can also show flood depthsand velocities.

Data required includes: detailedhydrological data ( includinginformation on historical floods);detailed topographic data of thefloodplain and also the watercourse;survey data for relevant hydraulicstructures such as weirs andbridges; observed water levels andflow with which to calibrate andverify hydrological and hydraulicmodelling. Flood water levels areestimated using a calibratedhydraulic model and flood extentsmapped using an accurate digitalterrain model of the floodplain.

The hazard methodology isdependent upon the how the risk isto be assessed. It should bepossible to map the flood extent,depth and velocity for a range ofdesign flood return periods. Anautomated process is usually usedto convert modelled flood depths toextents and depths within a GISenvironment.

Hazard expressed in terms of floodextents for a number of annualprobabilities or "return periods". Themost frequently used return periodstends to be 1 in 100 years (i.e. theflood with the 1% annual probabilityof occurrence). Other return periodsthat are some times used include 1in 5, 1 in 25 1 in 50, 1 in 100, 1 in200 and 1 in 1000.

Local (1:1,000 -1:10,000)

Provide maps and information thatare used at a detailed level. Theymay cover only a few kilometres ofthe river. The characteristics of suchmaps are dependent on the natureof the risk to be assessed. Suchmap usually show the extent offlooding but they can also showflood depths and velocities.

Data required includes: detailedhydrological data ( includinginformation on historical floods);detailed topographic data of thefloodplain and also the watercourse;survey data for relevant hydraulicstructures such as weirs andbridges; observed water levels andflow with which to calibrate andverify hydrological and hydraulicmodelling. Flood water levels areestimated using a calibratedhydraulic model and flood extentsmapped using an accurate digitalterrain model of the floodplain.

The hazard methodology isdependent upon the how the risk isto be assessed. It should bepossible to map the flood extent,depth and velocity for a range ofdesign flood return periods at thisscale. An automated process isusually used to convert modelledflood depths to extents and depthswithin a GIS environment.


C- 3

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

MAP SCALE(FLOODS HAZARDSTATE OF ART)



Regional(1:10,000 -1:50,000)

Provide maps and information thatare used that are often used at acatchment level for catchmentplanning. They usually cover thewhole of the river catchment. Suchmap usually show the extent andsometimes the depth of the flooding.

Data required includes: topographicdata covering the whole of thecatchment. Cross-sections of thewatercourse are also required Floodwater levels are estimated usingbroad scale hydraulic models thatcover the whole of the catchment.Flood extents are mapped using thedigital terrain model of thecatchment.

The hazard methodology isdependent upon the how the risk isto be assessed. It should bepossible to map the flood extent,depth and possibly velocity for arange of design flood return periodsat this scale. An automated processis usually used to convert modelledflood depths to extents and depthswithin a GIS environment across theentire catchment.


National(>1:50,000)

Provide a general overview of theareas susceptibility to flooding mapswith a relatively low level of detail.Often flood extents are mappedapproximately without takingaccount of flood+C11 mitigationmeasures (e.g. flood walls)>However, such maps are useful tonational policy makers, watermanagement agencies, theinsurance industry and the generalpublic.

Data required includes: topographicdata covering the whole of thecountry often such a digital terrainmodel has a low vertical resolutionbut at a national level this is oftenacceptable. Flood water levels areestimated using simple methods ofconverting flood flows to water levels(for example Manning's equation).Flood extents are mapped using thedigital terrain model of thecatchment.

The hazard methodology isdependent upon the how the risk isto be assessed. It should bepossible to map the flood extent anddepth for a range of design floodreturn periods at this scale. Anautomated process is usually usedto convert modelled flood depths toextents and depths within a GISenvironment across the entirecountry.


1.2 VulnerabilityMAP SCALE(FLOODS HAZARDSTATE OF ART)


VULNERABILITYMETHODOLOGY

LEGEND


Provide detailed characteristics ofreceptors such as buildings andpeople to floods. Used in detailedplanning of flood mitigationschemes

Types of commercial and residentialproperties, people and their socio-economic characteristics (forexample, wealth, health, age etc) allgeoreferenced.

D e t a i l e d i n v e n t o r y a n dcharacteristics of elements that areat risk from flooding. Methodologiesare available to assess thevulnerability of people to flooding.The "vulnerability" of buildings toflooding is taken into account of inthe floodwater depth versus damagecurve.

Type of properties, type of land use,distribution of people with respect totheir vulnerability to flooding.

C- 4

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1




LEGEND

Local (1:1,000 -1:10,000)

Provide detailed characteristics ofreceptors such as buildings andpeople to floods. Used in planningof flood mitigation schemes



Regional(1:10,000 -1:50,000)

Provide characteristics of receptorssuch as buildings and people tofloods. Used in planning of floodmitigation policies at a catchmentlevel.



National(>1:50,000)

Provide an overview of thecharacteristics of receptors such asbuildings and people to floods.Used in planning of flood policies ata national level.


D e t a i l e d i n v e n t o r y a n dcharacteristics of elements that areat risk from flooding. Methodologiesare available to assess thevulnerability of people to flooding.The "vulnerability" of buildings toflooding is taken into account of inthe floodwater depth versus damagecurve.


1.3 RiskMAP SCALE(FLOODS HAZARDSTATE OF ART)


RISK METHODOLOGY LEGEND


Local (1:1,000 -1:10,000) Provides a detailed assessment of

risks in terms of economic andsocietal impacts. A risk assessmentat this level is often required whenassessing a flood mitigationscheme, for example a flooddefence wall or a flood reliefchannel.

Data sets required: Commercialand residential properties (includingtype and location, floor area);information relating to agriculturalland use (e.g. crop type, area, cropyield); socio-economic data (e.g.number of people in the floodplain,characteristics of people). At a1:1,000 scale very detailed data onagr i cu l tu re and p roper t ycharacteristics will be required tomake the most accurateassessment of the damageincurred.

Use of flood depth versus economicdamage curves for different types ofcommercial and resident ialproperties and also land use.Assessment of the number ofpeople located in the floodplain andtheir vulnerability to flooding interms of their socio-economicstatus.

Direct economic damage forcommercial and residential propertiesexpressed in € for each return periodand the Average Annualised Damage(AAD) also expressed in €. Directeconomic damage for agricultural landproperties expressed in € per hectarefor each return period and theAverage Annualised Damage (AAD)also expressed in € per hectare.Number of people at risk of floodingand an expression of the vulnerabilityon terms of their age/wealth/health.

C- 5

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1




Regional(1:10,000 -1:50,000)

Provides a catchment wideassessment of risks in terms ofeconomic and societal impacts. Arisk assessment at this level is oftenrequired when assessing a floodmitigation policies at a rivercatchment scale.

Catchment wide data sets arerequi red: Commercia l andresidential properties (includingtype and location, floor area);information relating to agriculturalland use; socio-economic data (e.g.number of people in the floodplain,characteristics of people). At thisscale the data on agriculturecharacteristics required can bequite broad.

N a t i o n a l ( >1:50,000)

Provides a national assessment ofrisks in terms of economic andsocietal impacts. A risk assessmentat this level is used by nationalpolicy makers to formulate nationalflood management strategies andinvestment.

National data sets required:Commercial and residentialproperties (including type andlocation, floor area); informationrelating to agricultural land use;socio-economic data (e.g. numberof people in the floodplain,characteristics of people).

Use of flood depth versus economicdamage curves for different types ofcommercial and resident ialproperties and also land use.Assessment of the number ofpeople located in the floodplain andtheir vulnerability to flooding interms of their socio-economicstatus.

Direct economic damage forcommercial and residential propertiesexpressed in € for each return periodand the Average Annualised Damage(AAD) also expressed in €. Directeconomic damage for agricultural landproperties expressed in € per hectarefor each return period and theAverage Annualised Damage (AAD)also expressed in € per hectare.Number of people at risk of floodingand an expression of the vulnerabilityon terms of their age/wealth/health.

2 Seismic risk

2.1 HazardMAP SCALE(SPATIALPLANNING)

MAP SCALE(FLOODSHAZARD STATEOF ART)



Site-specific (<1:1,000)

The evaluation of landslideshazard (such as slides and flowsor as falls) triggered byearthquakes, consists in landslidestability analysis or in slope staticcondition analysis, both inpseudostatic conditions and,then, in dynamic conditions.

Local effects can be distinguishedin: instability effects and siteeffects, so the local hazard isinvestigated by using geologicaland morphological card, thatreproduce conditionscharacterizing a specific area (i.e. topological irregularity,deposits, landslides.

Hazard conditions can beanalysed adopting differentmethodologies, which bringdifferent results: they arequantitative, semi-quantitativeand qualitative approaches.

To analyse local effects the detailscale consents to microzone thearea. This way it is possible tocharacterize the individualphenomenon, such as a landsubject to landslides or a deposit.

C- 6

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

MAP SCALE(SPATIALPLANNING)




Local scale(< 1:5,000)

Local (1:1,000- 1:10,000)

Local scale studies allow to findand analyse in depth the localhazard factors present in one ormore municipalities .

Having P.G.A. and vulnerabilityvalues for each event, it ispossible to find out the damagescosts expected value for unit ofvolume, which could becompared to the entity of thephysical damage too.

Damage scenario evaluation cansupply indicators about damagescenario regarding direct costs ofbuildings damages (physical andeconomic); number of thebuildings expose to collapse riskand number of potential victimsand wounded people.

Damage level ratio, as cost ofdamage / value of the newbuilding to investigate the risk.

Local scale(1:5,000 -1:50,000)

Regional(1:10,000 -1:50,000)

At the regional scale it ispossible to investigate thehazard for areas including a bignumber of municipalities and it isuseful to classify the territory inseismic areas or not (as ithappens at the national scaletoo, but more in detail that in thenational scale). This type ofclassification is of use for draft amore or less hazardous areaslist.

Basic Seismic hazard isanalysed using deterministicmodels to investigate attendedshock in a selected area.

At this scale several objectivescan be pursued, like identifyingsource areas and the eventscharacterized by differentrecurrence periods. In this way itis possible to calculate (using aspecific attenuation model) theexpected shaking at the site.

Expected Maximum Accelerationvalues (Amax (g)) for differentReturn Periods.

Regional/Strategic scale(> 1:50,000)

National(>1:50,000)

In this scale of representation itis possible to have a full pictureof the national hazard, then it isuseful to classify the nationalterritory in seismic areas or not.

Examination and classification ofthe territory on the basis ofd e t e c t e d s e i s m i c r i s kclassification.

The Italian legislation foreseenterritorial diversification byidentifying and classifyingseismic zones. The basic criteriafor dividing regions are describedin the Technical Codes, thatindicate different horizontalacceleration values of anchoringof elastic response spectrum andplanning and building rules toapply.

Seismic Hazard Map of thenational territory with differntreturn periods.

C- 7

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

2.2 VulnerabilityMAP SCALE(SPATIALPLANNING)





Analyse the specific site anderify which and how many kinds ofbjects and people are present, andow vulnerable they are dependingn the particular local conditionvestigated (i.e. slide)

It is possible to draw up for thestructural typology investigatedan appropriate vulnerability cardto assess structural seismicvulnerability, based on severali n fo rma t i on abou t t heconstitutive elements. In thisway it is possible to obtain avu lnerab i l i ty index thatconstitutes a conventionalmeasurement of the propensityto damage.

Existent techniques to supplydata about vulnerability can bev a r i o u s l y d i v i d e d .They can be based on theresults produced, on themeasurement method usedeach time, using the mainin fo rmat ion source , o rdepending on the organism towhich a building is assimilated

Starting from the results of thesurvey card it is possible toassign a vulnerability indexvalue to every structuralt ypo logy and p roducevulnerability maps.

Local scale(1 :5 ,000 -1:50,000)

Regional(1:10,000 -1:50,000)

Subdivide the patrimony to valueon the basis of more factors(such as the structural typology,the age of building, the state ofmaintenance) and reach atdefine a vulnerability index fordifferent structures considered.

The most direct process toestablish the built environmentvulnerability is to make use ofvulnerability investigations. Forthe Italian case, the assessmentof vulnerability derives from thecombined use of two data-sets:ISTAT census data and the datacollected in different occasionsusing vulnerability cards byG.N.D.T.

Vulnerability at the Regionalscale is analyzed by using directmethods as vulnerability surveysor by means of approximateevaluations combining differentavailable data.

With the support of a table orusing density probability curvesderived by data regression it ispossible to assign a vulnerabilityindex value to every class andproduce vulnerability maps.

Regional/Strategic scale (>1:50,000)

National(>1:50,000)

Examination of the exposedelents and classification of theterritory on the basis of thed e t e c t e d s e i s m i c r i s kclassification.

Characterization of areas thatneed analysis of expecteddamages, meant to territorialseismic unit of measurement.

Materials and methods usedhave been di rected tocharacterize and decreaseuncertainty elements, as well asprotection of more vulnerableterritorial elements.

Damage level ratio, as cost ofdamage / value of the newbuilding to investigate the risk

C- 8

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

2.3 RiskMAPSCALE(SPATIALPLANNING)





Evaluation of site risk isrepresented by interaction ofseismic waves with particularlocal condition and of instabilityeffects such as collapses ormovement of big soil masses,being different depending onpresent condition in site,interconnected with objects andpeople present, and howvulnerable they are.

First, data about the basicseismic hazard are valued, andthen local seismic hazard andvulnerability are investigated

Punctual analysis are used bothto zoning the region in study andto give indications about thestructural protection levels toadopt for different consideredelements.

Quanti tat ive r isk classesexpressed as physical andeconomical potential damages.

Local scale(<1:5,000)

Local (1:1,000- 1:10,000)

To investigate the risk at thelocal scale: for the hazardcomponent it is concerned touse a deterministic input model,while vulnerable elements aredistinct between the onesinferable from ISTAT cataloguesand the ones that involvedpopulation and buildings or otherstructures.

Data available for studyearthquakes can be collectedunder three categor ies,correlated with three differentapproaches:a . Damage e f fec t ; b .Seismometric registrations; c.Accelerometric registrations.Then, the local vulnerability levelmust be investigated

The local scale is used both tozoning the region in study and togive indications about thebuildings protection levels toadopt.

In the map, the local hazard isrepresented by P.G.A. values,that decrease getting away fromthe epicentre.

Local scale(1 :5 ,000 -1:50,000)

Regional(1:10,000 -1:50,000)

Expected Maximum Accelerationvalues (Amax (g)) for differentReturn Periods to assesshazard; and Damage level ratio,as cost of damage / value of thenew building to investigate therisk

Regional/Strateg ic sca le(>1:50,000)

National(>1:50,000)

To investigate the risk at theregional scale: for the hazardcomponent it is concerned touse a deterministic input model,while vulnerable elements aredistinct between the onesi n f e r a b l e f r o m I S T A Tcatalogues.

A simplified model for riskmapping needs of twocomponents:1. a deterministic input to definethe hazard;2. vulnerability data to assessthe vulnerability component.

It is possible to implement ad e t e r m i n i s t i c m o d e l .Minimum data required forincrease this model are:1 Historical recorded eventscatalogue; 2 Source zones; 3Attenuation model.

Seismic Hazard Map of thenational territory with differentreturn periods; and Damagelevel ratio, as cost of damage /value of the new building toinvestigate the risk

C- 9

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

3 Landslides


MAP SCALE(LANDSLIDEHAZARD STATEOF ART)



Site-specific(< 1:1,000)

Provide absolute hazard classesand variable safety factor relatedto specific triggering factors. Themaps are used for implementingand design landslide hazard andrisk mitigation projects.

Data are related to slopestability modelling parameters(i.e. stratigraphy, geotechnicalproperties, hydrological data,seismic input).

Deterministic approaches (i.e.geotechnical modelling).

Hazard classes expressed asfailure probability (affected area,return time, intensity) or safetyfactor range.

Local scale (<1:5,000)

Local(1 :1 ,000 -1:10,000)

Provide an overview of potentialunstable slopes for largeengineering structures, roads,urban areas, soil protection(detailed studies). Absolutehazard and/or relative hazardshould be evaluated according tolandslide types occurring in thestudy area.

Data collection should supportthe production of detailed multi-temporal landslide distributionmaps and provide informationabout the various parametersrequired in the adoptedmethodology.

Deterministic approaches (i.e.geotechnical modelling coupledwith hydrological analysis).S t a t i s t i c a l m o d e l l i n g .Geomorphological approach.Indexed maps. Hazard maps arepossible only when thegeomorphic and geologicconditions, as well as landslidetypes, are fairly homogeneousover the whole study area.

Rarely, when the study area ishomogeneous in terms ofgeological, morphological andlandslide types, hazard ispossible and can be expressedas landslide probability (affectedarea, return time, intensity) orsafety factor range. Generally, arelative hazard is provided inqualitative scales that depictspatial and/or temporal probabilityof occurrence (i.e. low, medium,high, very high).

Local scale(1 :5 ,000 -1:50,000)

Regional(1:10,000 -1:50,000)

Identify landslide relative hazardor susceptibility maps. Theinvestigations may cover quitelarge areas and for large areasthe required map detail ismedium-low. The maps aregenerally addressed to largeprojects (feasibility studies) orregional developments.

Detailed data collection forindividual factors (i.e. landslideinventory, lithology, structuralsetting, land use), mostlyderived by remote sensingtechniques and bibliography inorder to delineate homogeneousterrain units.

S t a t i s t i c a l m o d e l l i n g .Geomorphological approachbased on a detailed landslideinventory. Indexed maps.Hazard maps are possible onlywhen the geomorphic andgeologic conditions, as well aslandslide types, are fairlyhomogeneous over the wholestudy area.

A relative hazard is provided inqualitative scales that depictspatial probability of occurrence(i.e. low, medium, high, veryhigh).

C- 1

0

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1






National(>1:50,000)

Provide a general inventory oflandslide areas or susceptibilitymaps with low level of detail. Themaps are useful to national policymakers and the general public.

National summary of regionallandslide inventories and mapproducts.

Susceptibility maps derivedfrom: geomorphological approachbased on spatial distribution oflandslides, landslide density,landslide activity; indexed maps;descriptive statistical analysis.

A relative hazard is provided inqualitative scales that depictspatial probability of occurrenceaccording to expert judgement(i.e. low, medium, high, very high).






Provide absolute hazard classesand variable safety factor relatedto specific triggering factors. Themaps are used for implementingand design landslide hazard andrisk mitigation projects.

Data are related to slopestability modelling parameters(i.e. stratigraphy, geotechnicalproperties, hydrological data,seismic input).

Deterministic approaches (i.e.geotechnical modelling).

Hazard classes expressed asfailure probability (affected area,return time, intensity) or safetyfactor range.


Local (1:1,000- 1:10,000)

Provide an overview of potentialunstable slopes for largeengineering structures, roads,urban areas, soil protection(detailed studies). Absolutehazard and/or relative hazardshould be evaluated according tolandslide types occurring in thestudy area.

Data collection should supportthe production of detailed multi-temporal landslide distributionmaps and provide informationabout the various parametersrequired in the adoptedmethodology.

Deterministic approaches (i.e.geotechnical modelling coupledwith hydrological analysis).S t a t i s t i c a l m o d e l l i n g .Geomorphological approach.Indexed maps. Hazard maps arepossible only when thegeomorphic and geologicconditions, as well as landslidetypes, are fairly homogeneousover the whole study area.

Rarely, when the study area ishomogeneous in terms ofgeological, morphological andlandslide types, hazard is possibleand can be expressed aslandslide probability (affectedarea, return time, intensity) orsafety factor range. Generally, arelative hazard is provided in qualita-tive scales that depict spatial and/ortemporal probability of occurrence(i.e. low, medium, high, very high).

Regional/Strategic scale(>1:50,000)

National(>1:50,000)

Provide a general inventory oflandslide areas or susceptibilitymaps with low level of detail. Themaps are useful to nationalpolicy makers and the generalpublic.

National summary of regionallandslide inventories and mapproducts.

Susceptibility maps derived from:geomorphological approachbased on spatial distribution oflandslides, landslide density,landslide activity; indexed maps;descriptive statistical analysis.

A relative hazard is provided inqualitative scales that depictspatial probability of occurrenceaccording to expert judgement(i.e. low, medium, high, very high).

C- 1

1

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

3.3 RiskMAP SCALE(SPATIALPLANNING)





Provide rigorous risk classes relatedto probabilistic landslide occurrenceand potential damage. Maps areused for implementing and designlandslide risk mitigation projects.

Data are related to hazard andvulnerability classes or valuesand their combination.

Quant i ta t i ve ana lys is : r igorousassessment.

Quant i ta t ive r isk c lassesexpressed as worth or number ofpotential losses.


Local (1:1,000- 1:10,000)

Provide absolute or relative risk.The maps are used forimplementing and designlandslide risk mitigation projects.


Quantitative analysis: potentialdamage, specific risk.

Quantitative risk classes expressed asworth or number of potential losses.Qualitative risk classes according tosocial and economic consequences.

Local scale(1 :5 ,000 -1:50,000)

Regional(1:10,000 -1:50,000)

Provide relative risk. The mapsare used for depicting landsliderisk scenarios at regional levels.


Qualitative analysis: damagepropensity or risk susceptibility.

Qualitative risk classes according tosocial and economic consequences.


National(>1:50,000)

Provide relative risk. The maps areused for depicting landslide riskscenarios at regional/national levels.


Qualitative analysis: damagepropensity or risk susceptibility.

Qualitative risk classes according tosocial and economic consequences.

4 Forest fire






Normally not used NA NA NA


Local (1:1,000- 1:10,000)

Detailed map produced for sitespecific design and location of pre-vention measures e.g. firebreaks,water reservoirs, look out points etc.Also used for setting up manage-ment rules for individual settlementsand / or specific ecosystems (fuel-/forest management etc.)

Basic GIS layers normally requiredfor this kind of map: DEM, fuel modelmap, settlements, road network,weather patterns, administrativeboundaries. If available fireperimeters of past 5-10 years or firefrequency in the municipalities ofpast 10-15 years might be used.

Fire behaviour potent ialassessment with fire simulationmodels

Quantitative legend that shows theaverage potential f ire l inei n t e n s i t i e s u n d e r g i v e nmeteorological scenarios.

C- 1

2

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1





Local scale(1:5,000 -1:50,000)

Regional(1:10,000 -1:50,000)

Typical scale for local firem a n a g e m e n t p l a n s .The map is aimed to thespatialization of protectionpriorities, the identification ofprevention measure and thesetting up of managementguidelines at landscape level

The following basic GIS layersare normally required for thiskind of map: DEM, fuel modelmap, settlements, road network,weather patterns, administrativeboundaries. If available: fireperimeters of past 5-10 years orf i re f requency in themunicipalities of past 10-15years.

Fire occurrence: buffers of givendistances from roads and/orsettlements.Fire behaviour potent ialassessed with fire simulationmodels

Quantitative legend that shows theaverage potential f ire l ineintensities (in classes) under givenme teo ro l og i ca l s cena r i os ,combined with 2-3 expected fireoccurrence pattern (qualitative).

Regional/Strategic scale(>1:50,000)

National(>1:50,000)

Scale used for regional firemanagement plans.It supports the spatialization ofgeneral fire protection priorities,the definition of protectionstrategies, the allocation ofprotection resources and thesetting up of general firemanagement guidelines

The following basic GIS layersare normally required for thiskind of map: DEM, land use,fuel types, fire data (last 10-15years), administrative boundaries,cl imatic data, biocl imaticregions, Wildland Urban Interfaceareas, (settlements, road network,socio-economic variables)

Fire occurrence: kernel densityprobability based estimates orfire frequency distribution analysisat municipality level. Fire behaviourpotential: based on fire simulationmodels or ad hoc empiricalmethods derived from statisticalanalysis of local environmental andanthropogenic factors.

Quantitative legend that shows theaverage potential f ire l ineintensities (in classes) under givenme teo ro l og i ca l s cena r i os .Qualitative classes are moreconveniently applied for fireoccurrence. The final overall legendwould be qualitative, with e.g. 5classes of fire hazard.

4.2 VulnerabilityStandard methods to assess and map forest fire vulnerability are still in a research phase. No operational examples can begiven in this section.

C- 1

3

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

5 Volcanic risk

5.1 HazardMAP SCALE(FLOODS HAZARDSTATE OF ART)

CHARACTERISTICS AND USE DATA ACQUISITION AND MAPPING PROCEDURES HAZARDMETHODOLOGY

LEGEND


For a given volcano define the areas which can beinterested by volcanic phenomena, characterizedby a limited impact on the territory (e.g. some kindsof lava flows, lava domes, some lateral blasts, lowmobility pyroclastic density currents, small laharsand debris avalanches, volcanic gases, volcanicearthquakes, lightning strikes). The maps are usedfor local management of volcanic crisis.

Geological investigations focused at defining the past beha-viour and the present state of a given volcano and at evalua-ting paleomorphology and current topography; volcano monito-ring providing an indication of when and where future activitymay occur and insights into the likely style of activity and pos-sible areas affected; comparisons with similar volcanoes, provi-ding an indication of possible activity either unprecedented ornot preserved in the geologic record at the volcano in question.

Evaluation of possiblephenomenologies; determi-nistic approach (e.g. dyna-mic pressure, temperature);statistic approach (probabi-lity); numerical modelling.Maps not available. Analy-sis still experimental.

Hazard classesexpressed as areas atdifferent probability tobe affected by theexamined phenome-nologies. Maps notavailable. Analysis arestill experimental.

Local (1:1,000 -1:10,000)

For a given volcano, define the areas whichcan be interested by volcanic phenomena,characterized by a limited extended impacton the territory (e.g. some kinds of lava flows,lava domes, some lateral blasts, low mobilityand dilute and turbulent pyroclastic densitycurrents, intermediate scale lahars and debrisavalanches, volcanic gases, volcanicearthquakes, lightning strikes, small scaletsunamies). The maps are used for localmanagement of volcanic crisis and have to beinserted in the framework of nationalemergency plans.

Geological investigations, focused at defining the pastbehaviour and the present state of a given volcano andat the evaluation of paleomorphology and currenttopography; Structural analysis aimed at theidentification of the nature and mechanisms of pastdeformation events, such as caldera collapse andcaldera resurgence. Volcano monitoring, which providesan indication of when and where future activity mayoccur, and insights into the likely style of activity andpossible areas affected. Comparisons with similarvolcanoes, which provides an indication of possibleactivity that may be either unprecedented or notpreserved in the geologic record at the volcano inquestion.

Evaluation of possiblephenomenologies;deterministic approach(e.g. dynamic pressure,temperature); statisticapproach (probability);numerical modelling

Hazard c lassesexpressed as areasa t d i f f e r e n tprobability to beaffected by theexaminedphenomenologies;

C- 1

4

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1


CHARACTERISTICS AND USE DATA ACQUISITION AND MAPPING PROCEDURES HAZARDMETHODOLOGY

LEGEND

Regional(1:10,000 -1:50,000)

For a given volcano, define the areas which canbe interested by volcanic phenomena,characterized by an extended impact on theterritory (e.g. some kinds of lava flows, ash andlapilli fallout, ballistic projectiles, some energeticlateral blasts, high mobility pyroclastic flows andsurges, lahars and debris avalanches, debrisflows and mud flows, volcanic gases, volcanicearthquakes, intermediate scale tsunamies).Depending on the type of the volcano the mapsare used for national planning of volcanicemergencies or regional management ofvolcanic crisis. In this case these maps have tobe inserted in the framework of nationalemergency plans.

Evaluation of possiblephenomenologies;deterministic approach (e.g.load on the ground,dynamic pressure,temperature); statisticapproach (probability);meteorological data onwind strength and direction;numerical modelling

National(>1:50,000)

For a given volcano, or more than one volcano,define the areas which can be interested byvolcanic phenomena, characterized by a veryextended impact on the territory (e.g. somekinds of high mobility lava flows, ash and lapillifallout, high mobility pyroclastic flows andsurges, large debris avalanches, volcanicgases, tsunamies). The maps are used fornational planning of volcanic emergencies.

Geological investigations, focused at defining the pastbehaviour and the present state of a given volcano andat the evaluation of paleomorphology and currenttopography; Structural analysis aimed at theidentification of the nature and mechanisms of pastdeformation events, such as caldera collapse andcaldera resurgence. Volcano monitoring, which providesan indication of when and where future activity mayoccur, and insights into the likely style of activity andpossible areas affected. Comparisons with similarvolcanoes, which provides an indication of possibleactivity that may be either unprecedented or notpreserved in the geologic record at the volcano inquestion.

Evaluation of possiblephenomenologies;deterministic approach (e.g.load on the ground,dynamic pressure,temperature); statisticapproach (probability);meteorological data onwind strenght and direction;numerical modelling

Hazard c lassesexpressed as areasa t d i f f e r e n tprobability to beaffected by theexamined phenome-nologies; isopachsand isopleths mapsof pyroclastic fallout,related to variablevalues of load on theground, dependingo n b u i l d i n g stypologies.

5.2 VulnerabilityMAP SCALE(FLOODS HAZARDSTATE OF ART)

CHARACTERISTICS AND USE DATA ACQUISITION AND MAPPINGPROCEDURES


LEGEND


Maps are not available. These analyses are stillexperimental.

Data are related to all the characteristics of theexposed elements (i.e. typology, worth,potential damage) at the highest possibleresolution.

Detailed analysis of thevulnerability of buildings forspecific volcanic phenomena.

Maps are not available. Theseanalyses are still experimental.

Local (1:1,000 -1:10,000)

Maps are not available. These analyses are stillexperimental.

Data are related to the characteristics of theexposed elements which affect theirvulnerability.

Detailed analysis of thevulnerability of buildings forspecific volcanic phenomena.


C- 1

5

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1


CHARACTERISTICS AND USE DATA ACQUISITION AND MAPPINGPROCEDURES


LEGEND

Regional(1:10,000 -1:50,000)

Provide an overview of homogeneous areas.The maps are used for vulnerabilityreduction.

Data are related to all the characteristicsof the exposed elements (i.e. typology)with resolution related to group ofelements.

Vulnerability is related to thetypology of the exposedelements (population, landuse, buildings) and to thetype of volcanic hazardconsidered.

Qualitative vulnerability classesfor each typology of element atrisk (i.e. population, structures,economic activities).

National (>1:50,000)

Provide an overview of homogeneous areas.The maps are used for vulnerabilityreduction.

Data are related to categories of theexposed elements (i.e. typology, worth)with low resolution.

Vulnerability indicators: all theelements exposed aresupposed to be vulnerable(population and GDP percapita, simplified typology ofland use).

Qualitative vulnerability classesfor each typology of element atrisk (i.e. population, structures,economic activities).



CHARACTERISTICS ANDUSE

DATA ACQUISITION ANDMAPPING PROCEDURES


Site-specific(< 1:1,000)


Local (1:1,000- 1:10,000)

Provide rigorous risk classesrelated to potential damage ofbuildings. These kind ofanalyses are still experimental.

Data are related to singlebuildings or infrastructure

Quantitative analysis: potentialdamage.


Local scale(1:5,000 -1:50,000)

Regional(1:10,000 -1:50,000)

Provide absolute and relativerisk. The maps are used todefine volcanic risk scenariosat regional levels.

Data are related to hazard,population density and land use.

Qualitative analysis: The riskcan be defined overlapping thelevels of vulnerable peopleexposed and the economicvalue for each kind of volcanicphenomenon considered.

Qualitative risk classesaccording to social andeconomic consequences.

Regional/Strategic scale (>1:50,000)

National (>1:50,000)

Provide relative risk. The mapsare used for volcanic riskanalyses at regional/nationallevel.

Data are related to hazard,population density, GDP percapita, simplified land useclasses.

Quantitative analysis: potentialsimplified damages. Qualitativeanalysis:overlapping of layersreferred to population density,presence of infrastructures andstrategic facilities and simplifiedland use

Qualitative risk classesaccording to social andeconomic consequences.

C- 1

6

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

6 Groundwater pollution







Loca l sca le(<1:5,000)

Local (1:1,000- 1:10,000)

Loca l sca le( 1 : 5 , 0 0 0 -1:50,000)

Regional(1:10,000 -1:50,000)

Regional/Strategicscale (>1:50,000)

National(>1:50,000)

In fo rma t i on on t hegroundwater vulnerabilityand potential sources ofgroundwater regime impactsusceptible originate thegroundwater regime impactafter damage affected by thenatural hazards.

Data related to the characteristicsof soils of unsaturated andsaturated zone, factors influencingthe groundwater regime and dataon installations with the potentialsources of groundwater regimeimpact . Assessment andclassification of groundwatervulnerability

Groundwater vulnerability, typeof aquifer, elements withdetailed information on naturalconditions and potential sourcesof groundwater regime impact.








Local (1:1,000- 1:10,000)

Loca l sca le( 1 : 5 , 0 0 0 -1:50,000)

Regional(1:10,000 -1:50,000)


National(>1:50,000)

I n f o r m a t i o n o n t h egroundwater vulnerability andpo ten t i a l sou rces o fgroundwater regime impactsusceptible originate thegroundwater regime impactafter damage affected by thenatural hazards.

Data related to characteristics ofsoils of unsaturated and saturatedzone, factors in f luencinggroundwater regime and data oninstallations with potential sourcesof groundwater regime impact.Assessment and classification ofgroundwater vulnerability

Groundwater vulnerability, typeof aquifer, elements withdetailed information on naturalconditions and potential sourcesof groundwater regime impact.

C- 1

7

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1








Local (1:1,000- 1:10,000)

Loca l sca le( 1 : 5 , 0 0 0 -1:50,000)

Regional(1:10,000 -1:50,000)


National(>1:50,000)

I n f o r m a t i o n o n t h egroundwater vulnerability andpo ten t i a l sou rces o fgroundwater regime impactsusceptible originate thegroundwater regime impactafter damage affected by thenatural hazards.

Data related to the characteristicsof soils of unsaturated andsaturated zone, factors influencingthe groundwater regime and dataon installations with the potentialsources of groundwater regimeimpact . Assessment andclassification of groundwatervulnerability

Groundwater vulnerability,type of aquifer, elements withdetailed information on naturalconditions and potentialsources of groundwaterregime impact.

7 Meteorological extreme events


MAP SCALE(METEOROLOGICAL EXTREMESHAZARD STATE OFART)




Hazard assessment is notcommon concept in meteorologyand climate research. Nocommon scale are available for"meteorological hazards" since itdepends on regional settingsand to their relation to other"events"

Data which can be possiblyused are all meteorologicalvariables. A hazard measurewill only make sense in thecontext with other measures(data amalgamation), and has,in particular, also a normativebias

No common methodologyavailable

No hazard measures available, sincehazards are concrete events and adefinition thing. In climate and meteorologythe risk and vulnerability concept ispreferred


Local (1:1,000 -1:10,000)

see above see above see above see above

Loca l sca le( 1 : 5 , 0 0 0 -1:50,000)

Regional(1 :10 ,000 -1:50,000)



National(>1:50,000)


C- 1

8

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1


MAP SCALE(METEOROLOGICAL EXTREMESHAZARD STATE OF ART)




Question specific: Useful forany scale. However,commonly any measure isassociated with uncertainty,which can be related to thel a c k o f k n o w l e d g econcerning outcomes, animprecise knowledge of risk,or to a chosen modelconcept (e.g. interpolation,downscaling procedure, etc.)

Provides a grid or regionalunit based overview ofintegrated vulnerabil i tymeasures, i.e. identify theregions which may bevulnerable against potentialweather extremes/climatechange

Data characterizing thesocioeconomic inventory(political regional structure),data characterizing thenatural inventory (gridded,depend on downscaling andquality of source data; pointmeasures). With respect toasked questions all data areused which can be relatedto the respective exposureunits

Vulnerability is a function of thesusceptability (coping/adaptivecapacity) against adverse climateeffects, sensitivity (degree towhich an exposure unit isaffected) and of an exposure unititself (decision maker problem).Methods used for integration are,e.g. fuzzy techniques, beliefnetworks, etc. The outcome is anregional integrated vulnerabilitymeasure (depends on the chosengrid scale)

Q u a l i t a t i v e a n dquantitative vulnerabilitya s s e s s m e n t s a r ecommon. They dependon the definition of theconcrete exposure unit.Vulnerability assessmentsin the most cases have aprospective character.Sometimes they are usedin order to assess thestate of art of a system

Local scale(<1:5,000)Local scale( 1 : 5 , 0 0 0 -1:50,000)Regional/Strategicscale (>1:50,000)

C- 1

9

ARM

ON

IA PR

OJE

CT (C

ontract n

° 511208) D

eliverable 2

.1

7.3 RiskMAP SCALE(SPATIAL PLANNING)

MAP SCALE (METEOROLOGICALEXTREMES HAZARD STATE OF ART)

CHARACTERISTICSAND USE



Question specific: In climateresearch a yardstick not a commonconcept, since data are either pointmeasures (empirical) or grid based(climate models are gridded!). Thus,data values are associated todifferent grid sizes (if not the sameas the model resolution they areinterpolated or downscaled), e.g.1km x 1km, 10'x10' or 0.5° x 0.5°(depends on data quality anddownscaling method). Thus, thestatements mentioned here arevalid for all scales (but clearlyassociated by various degrees ofuncertainties).

Retrospective: riskassessments are suitableto some extend, sincedamages and probabilitiesof occurrence can beestimated.

Prospective: Quality depends ondownscaling methods and usedmodel scenarios. Regional modeloutputs currently too uncertain.Specific assumptions have to bemade, since models are notdesigned to calculate extremes.

Retrospective: By utilization ofextreme value distributions(GEV/GPD) a forecasting ofreturn periods and extremes oflow probability events, such asextreme rainfall, river levels, ortemperature is performed. Qualityof data and used methods areoften not sufficient. Aim ofintensive research, utilizedmethods comprise stochasticmodelling which provided suitableextreme value distributions, etc.

Quantitative risk assessmentsbased on return intervals ofrare events and probabilitydistributions (only for themeteorol. extremes). Damagepotentials assessedqualitatively (cf. below)


Prospective: Difficulties tovalue the damages in thefuture, Scenarioassessments

Prospective: It is tried toreconstruct properties (moments,correlation type and strength) ofempirical measurements by moresophisticated methods. Due to thefiniteness of measurementuncertainty measures are underdevelopment which allows anassessment of the results.

Local scale(1:5,000 -1:50,000)

Retrospective: Time series dataof meteorological variables, pointmeasures obtained frommeteorological stations.Interpolations of extremes to aregional scale are problematic.For some meteorologicalvariables regional distributions ofextremes are providedsometimes, for example, formonthly maxima - eitherretrospective or prospective,differences are expressed byisolines. Validity of results dependon the quality of underlying data

Potential damages are estimatedqualitatively or semi-quantitativelyand depend on inventory of theexamined area

Qualitative risk assessment - ifquantiles cannot estimatedsufficiently - e.g. by expertjudgement and elicitation,scenario analysis. Damagecosts can be estimated onlyretrospective (less explanatorypower, since assets changes);additionally the exactlocal/regional occurrence of aweather extreme cannotestimated sufficiently, sincetheir impact depend on largescale circulation pattern,specific orographic settings,and further factors.


Documents

Report on current availability and methodology for natural risk map