UKRAINIAN AGRICULTURAL WEATHER

RISK MANAGEMENT

WORLD BANK COMMODITY RISK MANAGEMENT GROUP

Ulrich HessJoanna Syroka PhD

January 20 2004

UKRAINIAN AGRICULTURAL WEATHER

RISK MANAGEMENT

WORLD BANK COMMODITY RISK MANAGEMENT GROUP

IFC PEP Ukraine

Ulrich HessJoanna Syroka PhD

January 22 2004

Developments in Flood Index Insurance

COMMODITY RISK MANAGEMENT GROUPThe World Bank

December 2007

ERIN BRYLABased on work by William Dick, Alex Lotsch, and Ornsaran

Manuamorn

Flood is the major natural risk impacting GDP

Flood is a key risk in South East Asia

World Bank interest in flood World Bank has a focus on disaster relief and

reduction and one of the major issues is the risk of flood

The World Bank hotspot analysis identifies four major areas as flood prone including:

South/Central America Southern/Eastern Europe South East Asia South Asia

Primary interest is in poverty reduction and agriculture is key

There is a need to expand applications of flood insurance from property to agriculture

WB is developing innovative instruments to help farmers and agricultural banks to manage flood risk

New products harness technology including flood modeling and remote sensing

Focus on flood modeling

FLOOD MODELING

FLOOD WARNING

FLOOD MITIGATION

INSURANCE FOR PROPERTY

INSURANCE FOR

AGRICULTURE

FLOOD MANAGEMENT

Property catastrophe facility: example of Romania

WB assisting in development of Romanian Catastrophe Insurance Program

• Earthquake and flood

• National flood risk modeling and vulnerability/asset assessment

• Addition of cat perils to conventional property policies

Source: RMSI

Clients for agricultural flood insurance

Micro level insurance product Insured is the individual farmer, or a group of

farmers, in homogenous risk areas A micro product would identify flooded areas at high

resolution and reduce basis risk Challenge: can flood risk zones, and flood loss

assessment, be developed to allow micro insurance product ?

Macro level insurance product Insured is a holder of aggregate risk, e.g. agricultural

bank, micro-finance organisation, or processor Index based on wider indicator of flood, e.g. river

gauge data Aggregator sets rules for application of claims

payouts

Example Flood Risk Management for Agriculture: Implementing Index

Insurance Challenge

Design an alternative, efficient and cost-effective crop failure insurance program that facilitates risk transfer and is feasible for small farmers in low-income countries.

Index Insurance Suited to some widespread catastrophe perils Overcomes many problems of traditional insurance Main shortcoming is “basis risk”

Index insurance experience to date Mainly for drought risk (rainfall deficit index) Micro applications - individual farmer contracts Limited macro experience for aggregate risk transfers Not developed yet for flood insurance

Index Based Flood - Work in Progress

Thailand – CRMG technical assistance- Pasco Study 2006- Flood index – additional development in progress

Vietnam- ADB funded development project leading to macro product design for agricultural bank- CRMG collaborating for implementation of pilot

Bangladesh - CRMG- Feasibility study undertaken 2006

Technical study – CRMG and subcontractors- Product design, underwriting, loss assessment and technical requirements

Conceptual approach

Test parametric approach for flood Design flood index to proxy crop losses Harness technology to support insurance

underwriting and operation Flood Modeling (FM) Earth Observation (EO) Geographic Information Systems (GIS)

Design a flood index to proxy losses caused to crop

In Thailand rice has been chosen as the strategic crop most exposed to flood

Flood impact is dependent on variety, time of occurrence, depth and duration of flood water

Combining the Technology Components

FM+EO+GIS Define flood risk zones and pricing, farm locations

FM + AMM Design a flood index that proxies rice loss

EO+ GIS Loss adjustment for payout determination according to the index

IND

EX

DE

SIG

NO

PE

RA

TIO

NA

L P

HA

SE

Steps in product design

1. Defining the Hazard FM: define the flood risk zones EO: validate FM output with archive EO imagery

2. Defining the Vulnerability AMM: flood parameters and extent of yield loss according

to crop growth phase and planting date

3. Design options for index phases and payouts Design index thresholds, incremental payouts, limits Economic data: Review the required insured values

(production cost or output values) by crop phase

4. Pricing the index FM: time series of flood extent and duration for each zone

5. Validating the index Correlate against other known damage or yield data

Objectives of Flood Analysis

Support design of ‘mircro’ insurance scheme

Simulate historical floods Define flood risk zones Define critical rainfall

levels Agric. loss assessment

with remote sensing

“High Risk” Pricing Zone

“Medium Risk” Pricing Zone

Pasak

River

LA4

LA2

LA3

LA1

LA5

“Low Risk” Pricing Zone

Petchaboon

Risk Zoning for Pricing and Loss Adjustment

Flood Detection using Satellites

Land Use Stratification

Surface water estimates

Inundated Paddy

A PROTOTYPE FLOOD INDEX

Payout Index

Days of inundation of 60 cm. flood

Yield Damage

3 days No damage

4 days 20% loss

5 days 60% loss

6 days 80% loss

7 days 100 % loss

Claim Eligibility Trigger

One time excess of “Bench Mark Level” at 115.89 cm. at the Pasak River Water

Gauge station (ID: S4:B)

OR177 mm. from average 4 day rainfall at 3 stations

(Upper: 379002; Middle: 379401; Lower: 379201)

Data Requirements: How Met Office Can HelpData Needs (Source, years,

integrity)

Flood Modeling Historical rainfall data, real time data feeds from gauges throughout catchments

Agro-meteorological Modeling Reliable crop models, including damage factors from flood

Earth Observation Historical satellite data series (in order to validate the modeling), timely post event definition of extent and duration of flooding

GIS Geo-referencing databases of insured households to allocate to flood risk zones

CHALLENGES Flood Risk Zoning --Using

a flood model to zone flood risk for insurance pricing on agricultural land

Validation of Model -- Creating objective methods which are acceptable for international risk transfer to reinsurers (e.g. river gauges, or earth observation)

Modeling Flood Risk -- Complexity of flood risk and flood modeling (inundation flood, cyclone/coastal flood, flash flood…)

Digital Terrain Data Hydro-meteorological and

streamflow data Computation and Model

Choice

Meet needs for flood insurance for agriculture

Could provide insurance to smaller farmers and businesses

Could support objective disaster payments outside formal insurance

Settlement could made on an objective trigger (EO)

The cost of reaching farmers drops significantly

BENEFITS