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MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby ing (partners): 1 Coarse scale modelling (WP leader : University o y of Leeds, Department of Geography, United Kingdom llege London (KCL), Department of Geography, London, United Kingdom 2 Fine scale modelling (WP leader : King’s College llege London (KCL), Department of Geography, London, United Kingdom “Desertification” (ROSELT/OSS coordination), Maison de la Télédétection, Montpellier, des Regions Arides (IRA), Médenine, Tunisia Suivi Ecologique (CSE), Dakar, Senegal Recherche Forestière (CRF), BP 763 Rabat-Agdal Morocco e des Sciences et de la Technologie Houari Boumediene, Faculte des Sciences Biologiques cologie et Environment, Algeria nks: .3 Integration and dynamic systems modelling in LUS (John Thornes) .3 Geomatic based land condition assessment (Joachim Hill) .2 Developing the surveillance system prototype (RIKS)

MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

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Page 1: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT

Module leader : Mike Kirkby

Comprising (partners):WP 1.4.1 Coarse scale modelling (WP leader : University of Leeds)(1) University of Leeds, Department of Geography, United Kingdom(2) King’s College London (KCL), Department of Geography, London, United Kingdom

WP 1.4.2 Fine scale modelling (WP leader : King’s College London)(1) King’s College London (KCL), Department of Geography, London, United Kingdom(2) IRD Unité “Desertification” (ROSELT/OSS coordination), Maison de la Télédétection, Montpellier, France(3) Institut des Regions Arides (IRA), Médenine, Tunisia(4) Centre de Suivi Ecologique (CSE), Dakar, Senegal(5) Centre de Recherche Forestière (CRF), BP 763 Rabat-Agdal Morocco(6) Universite des Sciences et de la Technologie Houari Boumediene, Faculte des Sciences Biologiques, Laboratorie Ecologie et Environment, Algeria

Main links:MODULE 1.3.3 Integration and dynamic systems modelling in LUS (John Thornes)MODULE 1.5.3 Geomatic based land condition assessment (Joachim Hill)MODULE 1.8.2 Developing the surveillance system prototype (RIKS)

Page 2: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

Estimated Annual Erosion (t/ha/yr)

masked data

no erosion

0 - 1

1 - 3

3 - 10

10 - 30

30 - 100

100 - 10,000

Estimated European Water Erosion: Annual

PESERA – Pan European Soil Erosion Assessment

Page 3: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

Components of PESERA model

Land Cover

Soil Type

Climate

Topography

Storm Runoff

Threshold

Distribution of Storm and Non-storm

Runoff

Saturated Subsurface

Flow, Snowmelt and Frozen Ground

Runoff

Erodibility

Relief

Accumulated Erosion

Hydrology andsoil erosion1000m resolution,regional to continental extent‘

Page 4: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

The MedAction DSS, incorporating the PATTERN model

Hydrology,soil erosion, vegetation growth, yield and dynamics, salinisation100m resolution,local to regional extent‘

Page 5: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

PATTERN : BIOPHYSICAL model

H: Erosion and deposition

H: Infiltration

H: Recharge

H: Soil MoistureH: Runoff

H: Precipitation & Irrigation

H: Interception

H: Evapotranspiration

H: Seal

PLANT GROWTH

WATER RESOURCES

W&C: Solar radiation

W&C: Temperature

DYNAMIC SUITABILITY

SALINISATION

GIS

W&C: Rainfall

SEDIMENTATION

WATER DEMANDS

Page 6: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

LEIS Local Environmental Information System MODEL for ROSELT OBSERVATORIES

Human use of environmental resources and resource balances.Combined human and biophysical. Accounting for spatial structure of land use.

Page 7: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

AIM OF DESURVEY 1.4

Main deliverables:•Model application database for ROSELT sites in North Africa

•Coupled biophysical/socio-economic land condition model

•Cross scale integration experiments (PATTERN, PESERA, remote sensing)

•Model delivery, training and demonstration, integration with surveillance system.

•To use an improved and integrated PATTERN-LEIS and PESERA models to investigate processes and scenarios of desertification at the ROSELT observatories (North and west Africa) for policy support, learning what we can from the application of the models in Europe. All the important processes and issues from the ROSELT observatories will be taken into account in the model.

•To ensure that the tool(s) can be applied (and further developed) at ROSELT observatories by the in-country teams.

Page 8: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

OBJECTIVES of DESURVEY WP 1.4

•To apply PATTERN with the local teams to observatories Menzel Habib and Jeffara in Tunisia, Ferlo in Senegal, Oued Mird in Morocco, and Mecheria in Algeria

•To apply PESERA with the local teams at larger scales to the same areas

•To develop the PATTERN (and PESERA) models to suit the local conditions in the observatories (e.g. jessour, wind erosion, grazing…)

•To couple the PATTERN model with LEIS for dynamic human-environmental land condition dynamics

•To test/validate the behaviour of the coupled model in the four observatories under current conditions

• In the demonstration phase to use the coupled model to better understand desertification processes and drivers and the possibilities for mitigation of impacts through the applicatin of policy options

Page 9: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

INTEGRATION

PATTERN FINE SCALE MODEL

Estimated Annual Erosion (t/ha/yr)

masked data

no erosion

0 - 1

1 - 3

3 - 10

10 - 30

30 - 100

100 - 10,000

Estimated European Water Erosion: Annual

PESERA COARSE SCALE MODEL

COARSE AND FINE SCALE REMOTE SENSING

Cross scale integration

LEIS SOCIO-ECONOMIC MODEL

drivers

responses

Page 10: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

Image © Blue Marble Next Generation, NASA Earth Observatory)

Ferlo (43668 km2), Senegal

Oued Mird (1264 km2), Morocco

Mecheria (3395km2), Algeria

Menzel Habib (2082 km2) and Oum Zessar (349km2), Tunisia

Guadalentin (3321 km2), Spain

STUDY CATCHMENTSThe North African ones are long term ROSELT observatories.

The Guadalentin is data rich and has previous application of the models.With such a wide range of site conditions the models should be applicable

elsewhere in Europe and Africa.

Page 11: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

PROGRESS : TRAINING AND DISSEMINATION

Dissemination completedExchange of PESERA, PATTERN and LEIS models

Training completedPCRaster / PATTERN) / PESERA Training Course, 13th -17th February 2006, King's College London. 13 participants from 7 countries.

Deliverables completed1.4.2.1 Protocol for coupled LEIS-PATTERN model and report outlining data availability for application, calibration and validation of the coupled model along with a strategy for the collection of the necessary data

1.4.2.2 Online GIS/RS database of processed existing historical datasets for LEIS-PATTERN parameterisation, calibration and validation

Page 13: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

Oued Mird

Mecheria

Oum Zessar Ferlo

Menzel HabibPROGRESS : DATABASE

Page 14: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

PROGRESS : DATABASE : CLIMATE

OUM ZESSAR

Page 15: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

Oum Zessar (Jeffara)Oued Mird

Ferlo

PROGRESS : DATABASE : LAND COVER/USE

Page 16: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

PROGRESS : MODELS

PESERA – initial run for Tunisia

Majority of work so far has been preparing the database for use with the models. Now the model development and application stages begin.

The online meeting with coordinator and M1.5 discussing measures of land condition and RS/modelling strategy for vegetation.

Tunisia (2005) and London (2006) meetings, defined desertification issues in African sites and additional processes need to be incorporated into the models.

Page 17: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

WP 1.1.1 Climatic forcing (provision of current and future climate data). Tom Holt.  Discussions on climate and climate change datasets and availability for North and west Africa

WP 1.3.3 Integration and dynamic systems modelling in land use systems vulnerability. John Thornes. We need to ensure that our modelling approaches are compatible or complementary and do not duplicate effort.  

WP 1.5.3 Geomatic based land condition assessment. Joachim Hill.We need to ensure that our conceptualisations of vegetation are compatible and that we make best use in the modelling of the remote sensing products that will be produced by DESURVEY.

WP 1.8.2 Developing the surveillance system prototype. RIKS.We need to ensure that the systems we develop are ready for integration within the surveillance System and application in Europe as well as Africa

DISCUSSIONS NEEDED IN VASTO

Page 18: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University
Page 19: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University
Page 20: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University
Page 21: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University
Page 22: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

 Main land uses: olives, almonds, figs, grazing (goats)….The main profitable soils are located within the Natural Park areaMain desertification issues: Wind (MH) and water erosion (Jeffara), Salinisation (water and soil), Rainfall variability, overgrazing.Scenarios to use: Climate variation and change, population increase, market prices, Policy options: Water management eg Jessour, dams and water distribution, animal fodder(barley) taxation/subsidising, changes to land tenure/land use planning, incentives for irrigation, incentives to cultivate salt tolerant crops to remove salinity from the soils. Changes required of PATTERN New crops e.g. dates, Jessour and Tabia, immersion irrigation, handle both shallow and deep aquifers, grazing, wells, variability of olive spacing Changes required of LEIS

For discussion : Application to Tunisia

Page 23: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

 Main land uses: Grazing and scattered irrigation land Main desertification issues: Water erosion on steeplands, flooding, woodcutting, overgrazing, seasonal wind erosionScenarios to use: Climate variability and land use change, locustsPolicy options: Settling and infrastructure program (population change), protection (conservation), recharge checkdams, water harvesting techniquesChanges required of PATTERN: New crops (henna, palm), locustsChanges required of LEIS:

For discussion : Application to Morocco

Page 24: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

Main land uses: Peanuts, millets, beans (rainfed 3 months a year only). Forages : cows, goats, Main desertification issues: Climate variability, overgrazing around wells, bushfires, gulley erosion, wind erosion, population growth, woodcutting, povertyScenarios to use: Climate variability and change, population change, market prices, herds (cattle?) changePolicy options: Water charging, cooking alternatives, incentives for wells, land use planning, erosion prevention, digging out closed basins, ponds management, incomes greasingChanges required of PATTERN Grazing, (closed basin) waterholes, fire, wind erosion, wood cutting. New species e.g. Millet, beans, peas, acacia, immersion irrigationChanges required of LEIS: Extension of agriculture/livestock (pastoral) areas

For discussion : application to Senegal

Page 25: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

Main land uses: grazing (transhumant goats), dryland cereals (barley), some rare irrigation Main desertification issues: Wind erosion, water (sheetflow) erosion, low vegetation cover (<10%), mainly caused by overgrazing, little salinisationScenarios to use: rainfall declines, grazing increases, climate changePolicy options: reducing sheep counts, fencing off areas, digging/damming of recharge lakes (later sedimentation), irrigation

Changes required of PATTERN Grazing, wind erosion, fencing off, recharge lakes

For discussion : application to Algeria

Page 26: MODULE 4 GROUND-BASED LAND CONDITION ASSESSMENT Module leader : Mike Kirkby Comprising (partners): WP 1.4.1 Coarse scale modelling (WP leader : University

Mecheria, Algeria