Climate, Water and Agriculture: Impacts and adaptation in Africa

1
Climate, Water and Agriculture Impacts and
adaptation in Africa

• Core funding from GEF plus complementary funding
  from others (WBI Finish Trust, NOAA, CEEPA
  McArthur, WB ARD, IWMI, FAO)
• 2002 - 2005
• WWW.CEEPA.CO.ZA/CLIMATE CHANGE
• EEE Program Seminar, ICTP June 10, 2003
• Rashid Hassan, CEEPA

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Motivation

• Agro-ecosystems in Africa most vulnerable to
  climate change (CC)
• Climate already hot in most parts of Africa
• productivity decline with warming - crop yields
• More pressure
• Higher demand for land conversion
• More water for irrigation
• Increased intensification (pollution, erosion,
  etc.)
• Introduction of GM plants and animals
  (biodiversity)
• High dependence on agriculture livelihoods
• Low ability of African farmers to adapt
• Limited access to capital and technological
  options
• Poor public infrastructure (roads, information,
  research, extension)

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Objectives

• Improve the capacity of research and policy in
  participating countries and the region to
• Assess the impacts of CC on agro-ecosyst.
• Evaluate alternative adaptation options
• Generate improved information and knowledge on
  impacts of CC and possible options for adaptation

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Scope

• Covers 11 countries from north, south, east and
  west Africa
• Burkina Faso, Cameroon, Egypt, Ethiopia, Ghana,
  Kenya, Niger, Senegal, South Africa, Zambia and
  Zimbabwe (work began in 8)
• Involves collaboration with a number of
  institutions on country level and regional
  analyses
• IWMI, FAO, YALE working with multidisciplinary
  country teams

5
Approach and Methods

• Three approaches integrated
• Ricardian approach to economic impact assessment
• River basin hydrology models for assessing
  impacts on runoff and availability of water
• Crop-water response simulation models for
  assessing the biological impacts (crop yields)

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The Ricardian Approach 1

• Based on the hypothesis that impacts of changes
  in climate attributes (temperature, rainfall)
  like other long-term economic phenomena are
  capitalized in land values
• CC affects crop yields and hence farm revenues
  capitalized in land value changes over time
  (present value of the stream of future revenues)
• Regression of land values on various determinants
  of net revenue including climate variables
• VLt ?t NRt (1 ?)-t
• NRt F(RFt, TMt, Zt, Xt, TKt)

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The Ricardian Approach 2

• Difficult to have long time series on land values
  or net revenue by region and all regressors
• Cross-sectional data reflecting spatial diversity
  in climate attributes and all other determinants
  of land value (NR) alternatively used
• Partially controls for adaptation (substitution
  between inputs in production)
• Other adaptation missed (crop switching,
  transitory adjustment costs capital goods)

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Water-crop response simulation models 1

• Describe crops behavior (physiological and
  development) as a function of
• Climate (weather) factors
• Soil conditions (fertility, water holding
  capacity, etc.)
• Other determinants under farmer control and
  management (planting dates and input levels)
• Simulate yield response to variability in climate
• Other response variables such as crop water
  consumption and irrigation requirements as
  climate changes (evapotranspiration, soil
  moisture, water excess-deficit at critical stages
  of growth, etc.)

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Water-crop response simulation models 2

• Compliments the cross-sectional analysis
  Ricardian (both spatially implemented)
• Overestimates impacts no control for adaptation
  (recent modifications to allow)
• Crop specific and location specific
• Experimental real world replications of
  conditions (calibrations to actual locations
  data)

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River basin Hydrology

• Models how CC affects agriculture also indirectly
  through impacts on basin hydrology (runoff)
• Rainfall, temp. and evaporation affect seasonal
  patterns of river flow and hence availability of
  water for agriculture
• Compliments the cross-sectional analysis
  Ricardian method
• Both spatially-based

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Data and Plans of analyses 1

• District level data
• Farm survey data at district level (same year
  2002) aggregated by country and region (river
  basins)
• Crop yields, prices and production costs (NR)
• Other agric. response variables ( land under
  crops)
• Climate and soil attributes data by district
  again aggregated at river basin
• Other data at district level (population,
  proximity to markets, literacy and disease rate,
  etc.)
• Regional data-base to sport the cross-country
  assessment of economic impacts

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Data and Plans of analyses 2

• Hydrology models analyses generate input
  variables to the Ricardian regression by district
• Change in runoff, soil moisture, etc.
• Crop water response models calibrate the
  biological response of crops to CC by district
• Yield
• Water requirements
• The Ricardian analyses of the economic impact
  applied at both country and district levels
• First Year
• Surveys designed and data collection instruments
  developed and tested in the various countries
• Training on the three methods and approaches
  conducted