345-3 Simulating Integrated Impacts of Future Projected Climate Change and Variability on Crop Production in Eastern Southern Africa.
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K.P.C. Rao1, G. Sridhar1, Mary Kilavi2, Richard Mulwa3, Siza Tumbo4, Moses Tenywa5 and Araya Alemie Berhe6
Crop simulation models are widely applied to project the potential impacts of climate change and variability on future crop production and to examine the possible options for strategic crop adaptation. Compressive climate change impacts on smallholder agriculture was assessed in four of the East African countries - Ethiopia, Kenya, Tanzania and Uganda –using the protocols and tools developed by Agricultural Model Inter-comparison and Improvement Project (AgMIP). In each country, a study area of the size of a district/county representing at least three major agro-ecological zones of the country and having about 50,000 households was selected. Household surveys were conducted to obtain the required input data for crop and economic models. Projection of climate change impacts on food supply are largely based on climate and crop simulation modelling. The consistency of global climate models and their ability to project accurate climate change scenarios has direct implications for the assessment of the impacts of climate change on agricultural crop production. Global climate models with spatial resolution grids typically of the order of a hundred kilometres limits the confidence in addressing the potential impacts of climate change at regional scales. In contrast, developing location specific climate change scenarios using statistical downscaling techniques (delta method) to account regional climate variability and future projected mean changes in climate variables to provide most comprehensive climate change datasets. In the current study, 20 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models for Representative Concentration Pathways (RCPs) 4.5 and 8.5 were downscaled by delta method to generate location specific future climate change scenarios. Maize is one of the most staple cereal produced in the Eastern and the Southern African countries. Two crop simulation models Decision Support System for Agrotechnology Transfer (DSSAT) and Agricultural Production Systems sIMulator (APSIM) are calibrated and validated for a total of 10 maize varieties in four countries. Experimental data from maize grown under different nitrogen regimes for both major and minor seasons were used to parameterize and evaluate crop simulation models. Yields of maize under observed and future climates were simulated with DSSAT and APSIM crop models that were calibrated to simulate the locally relevant varieties and management practices. Diversity in the crop management employed by the farmers in the target region was captured by setting up runs for each of the 240 farmers in Ethiopia, 441 farmers in Kenya, 168 farmers in Tanzania and 383 farmers in Uganda involved in the survey. The downscaled location specific climate change scenarios indicted an increase in both maximum and minimum temperatures. The median value from the 20 GCM projections for maximum temperature is in the range of 3-5°C by end century under RCP 8.5 at different locations. Lowest increase of 3.1°C was predicted at Nazareth, Ethiopia and highest increase of 5.5°C was predicted for Dodoma, Tanzania. The changes projected for different locations indicate higher increase at locations away from equator compared to those located near equator. Further, higher increases are observed in case of locations that are south of equator within the four country study region. Projected changes in rainfall indicate a general increase in rainfall. Similar to temperature, the locations near equator are likely to get wetter compared to the away locations. The median values for rainfall change are 5% at Dodoma in the south, 34% at Nazareth in the centre and 14% at Adigudom in the north. Impacts of climate change varied from one agro-ecology to the other and from one season to the other and also the way the crops were managed. Projected impacts on maize crop varied from about +60% in Kenya to about -30% in Tanzania. Simulation results indicate that, climate change will have a positive impact on maize yields in all AEZs in Ethiopia and in UM2, UM3 and LM3 in Kenya and will have negative impact in all AEZs in Tanzania and Uganda. The simulation results indicated that it is possible to adapt to the projected changes in all AEZs in all countries by making simple adjustments to the current management practices. Adaptation packages involving optimal dates of planting, plant population, variety and fertilizer doses were developed for each AEZs. Simulations with adapted package of practices indicated that yields can be increased significantly from current levels in all AEZs in all countries. Results indicate that yields can be doubled in some AEZs by adopting these practices. Economic impacts of these changes in maize yields were assessed using TOA-MD under current and future RAPS based conditions. In general, they followed the trends observed in the maize yields. Net returns and per capita income are expected to increase in Ethiopia and Kenya and decrease in Uganda and Tanzania.
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