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Stochastic bio-economic modeling
                                              approach to assess climate change
                                                   impacts in Central Asia
                                                               Ihtiyor Bobojonov1, Aden Aw-Hassan2
  Background
  Agricultural production forms the backbone of Central Asian (CA) economies. The contribution of agriculture to GDP is lowest at 11% in Kazakhstan and highest at
  38% in Kyrgyzstan. Land degradation inherited from the Soviet times is still a major problem in all CA countries where land salinization affected about 12% of the total
  irrigated area in Kyrgyzstan, 50-60% in Uzbekistan and even more than 90% in Turkmenistan. Climate change is adding additional dimension to the existing problems
  in the region and aggravating the uncertainty in agricultural production and rural poverty.
  Objective
  The study objectives were to elaborate risk aspects into whole farm context instead of analyzing climate change impacts on isolated farm activities, and to provide more
  accurate estimates of climate change impacts at sub-national levels than those available at regional or global scales in the literature.


Figure 2: Expected Utility change, in percent
                                                                      Methodology
compared to the baseline scenario*                                    Bio-economic farm model with risk component was
                                                                      developed to assess climate change impacts on farm
a) A1b scenario for the period 2071-2100                              income volatility in Central Asia: Uzbekistan, Kazakhstan,
                                                                      Tajikistan and Kyrgyzstan. Integrated modeling                                             Figure 1: Model components
                                                                      framework, combining economic analysis with results of
                                                                                                                                                        Household             Crop experiment              CC projection
                                                                      climate module, crop growth simulations, was applied                             surveys in CA                data                   downscaling

                                                                      (Figure 1). Climate change impacts on yields were
                                                                      obtained by CropSyst and DSSAT crop simulations                                   Long term              CropSyst, DSSAT
                                                                                                                                                        price and                simulations
                                                                      calibrated with the experimental data from representative                         yield data

                                                                      agro-ecological zones (AEZ) using downscaled climate
                                                                      data. Expected Utility model was developed to assess the                                                   Stochastic
b) A2 scenario for the period 2071-2100                               climate change impacts on farm income volatility in ten
                                                                                                                                                                             optimization model



                                                                      representative farms from different AEZs in the four                                             Certainty equivalent, crop areas,
                                                                      countries. The model was calibrated for three main crops                                                 input use levels

                                                                      such as cotton, wheat and potatoes as the main
                                                                      agricultural activities in CA. Elaboration of yield-price
                                                                      covariance in the stochastic farm model enables the
                                                                      consideration of natural hedging effect of climate change
                                                                      on agricultural producers’ welfare.
c) A1b scenario for the period 2071-2100,
30% reduction of irrigation water                                     Results                                                                       Conclusions
                                                                      The farm revenues in many AEZs is expected to stay close                      Adoption of more efficient irrigation methods
                                                                      to currently observed levels in the near future scenarios                     could be one of the most effective adaptation
                                                                      (2010-2040). Very significant changes are observed for late                   measures to reduce farmers’ vulnerability under
                                                                      future scenarios (2071-2100) as presented in Figure 2. The                    climate change in arid and semiarid regions of
                                                                      direction of the change differ depending on agro-ecological                   Central Asia.
                                                                      zones and socio-economic aspects of the farming systems.                      Governments should establish policies for creating
                                                                      The revenues in Uzbekistan are expected to decline in the                     incentives for adoption of these technologies
                                                                      late future (2070-2100) due to increasing temperatures and                    especially through improving farm advisory services
d) A2 scenario for the period 2071-2100,                              risk of increasing water deficit, especially if availability of               and raising the awareness on climate change effects.
30% reduction of irrigation water                                     irrigation water from transboundary rivers decline.                           The availability of the insurance programs also may
                                                                      Farmers in sub-humid zones of Kazakhstan are expected to                      play an important role to cope with increasing
                                                                      benefit from increasing temperature and precipitation. Sub-                   sequence of weather extremes.
                                                                      humid and humid areas in Tajikistan and Kyrgyzstan will                       The analysis of changing occurrence of weather
                                                                      benefit while arid and semiarid regions will be negatively                    extremes in the future need to be further investigated
                                                                      affected.                                                                     in order to improve the results of this study.

                                                                                  1  International Center for Agricultural Research in the Dry Areas (ICARDA), present affiliation: Leibniz Institute of
                                                                                   Agricultural Development in Central and Eastern Europe (IAMO)
*The spatial distribution is extrapolated from the                                 2 Corresponding author, International Center for Agricultural Research in the Dry Areas (ICARDA), a-aw-hassan@cgiar.org

representative farm level only for better visualization purposes   Presented at the Global Science Conference on Climate-Smart Agriculture. UC Davis, 20-22 March, 2013

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Stochastic bio-economic modeling approach to assess climate change impacts in Central Asia

  • 1. Stochastic bio-economic modeling approach to assess climate change impacts in Central Asia Ihtiyor Bobojonov1, Aden Aw-Hassan2 Background Agricultural production forms the backbone of Central Asian (CA) economies. The contribution of agriculture to GDP is lowest at 11% in Kazakhstan and highest at 38% in Kyrgyzstan. Land degradation inherited from the Soviet times is still a major problem in all CA countries where land salinization affected about 12% of the total irrigated area in Kyrgyzstan, 50-60% in Uzbekistan and even more than 90% in Turkmenistan. Climate change is adding additional dimension to the existing problems in the region and aggravating the uncertainty in agricultural production and rural poverty. Objective The study objectives were to elaborate risk aspects into whole farm context instead of analyzing climate change impacts on isolated farm activities, and to provide more accurate estimates of climate change impacts at sub-national levels than those available at regional or global scales in the literature. Figure 2: Expected Utility change, in percent Methodology compared to the baseline scenario* Bio-economic farm model with risk component was developed to assess climate change impacts on farm a) A1b scenario for the period 2071-2100 income volatility in Central Asia: Uzbekistan, Kazakhstan, Tajikistan and Kyrgyzstan. Integrated modeling Figure 1: Model components framework, combining economic analysis with results of Household Crop experiment CC projection climate module, crop growth simulations, was applied surveys in CA data downscaling (Figure 1). Climate change impacts on yields were obtained by CropSyst and DSSAT crop simulations Long term CropSyst, DSSAT price and simulations calibrated with the experimental data from representative yield data agro-ecological zones (AEZ) using downscaled climate data. Expected Utility model was developed to assess the Stochastic b) A2 scenario for the period 2071-2100 climate change impacts on farm income volatility in ten optimization model representative farms from different AEZs in the four Certainty equivalent, crop areas, countries. The model was calibrated for three main crops input use levels such as cotton, wheat and potatoes as the main agricultural activities in CA. Elaboration of yield-price covariance in the stochastic farm model enables the consideration of natural hedging effect of climate change on agricultural producers’ welfare. c) A1b scenario for the period 2071-2100, 30% reduction of irrigation water Results Conclusions The farm revenues in many AEZs is expected to stay close Adoption of more efficient irrigation methods to currently observed levels in the near future scenarios could be one of the most effective adaptation (2010-2040). Very significant changes are observed for late measures to reduce farmers’ vulnerability under future scenarios (2071-2100) as presented in Figure 2. The climate change in arid and semiarid regions of direction of the change differ depending on agro-ecological Central Asia. zones and socio-economic aspects of the farming systems. Governments should establish policies for creating The revenues in Uzbekistan are expected to decline in the incentives for adoption of these technologies late future (2070-2100) due to increasing temperatures and especially through improving farm advisory services d) A2 scenario for the period 2071-2100, risk of increasing water deficit, especially if availability of and raising the awareness on climate change effects. 30% reduction of irrigation water irrigation water from transboundary rivers decline. The availability of the insurance programs also may Farmers in sub-humid zones of Kazakhstan are expected to play an important role to cope with increasing benefit from increasing temperature and precipitation. Sub- sequence of weather extremes. humid and humid areas in Tajikistan and Kyrgyzstan will The analysis of changing occurrence of weather benefit while arid and semiarid regions will be negatively extremes in the future need to be further investigated affected. in order to improve the results of this study. 1 International Center for Agricultural Research in the Dry Areas (ICARDA), present affiliation: Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO) *The spatial distribution is extrapolated from the 2 Corresponding author, International Center for Agricultural Research in the Dry Areas (ICARDA), a-aw-hassan@cgiar.org representative farm level only for better visualization purposes Presented at the Global Science Conference on Climate-Smart Agriculture. UC Davis, 20-22 March, 2013