Localizing agricultural impacts of 21st century climate pathways in data scarce catchments: A case study of the Nyando catchment, Kenya

Climate change is projected to increase the volatility of agricultural productivity within the Sub-Saharan Africa region. However, current knowledge of climate change impacts in this region is largely derived from coarse -grid global datasets that lack sufficient detail for local applications. The derived impacts are thus generalized across large spatial scales, with a limited representation the differential exposure across the region. It is thus necessary to conduct localized assessments to derive local vulnerabilities and develop context -specific mitigation strategies. This study utilizes downscaled outputs from regional climate models to quantify the effects of climate change on maize and sugarcane crops at catchment -scale, hereby the Nyando catchment in Kenya. The findings indicate that climate change will reduce the suitability of conditions to the growth of both crops, with sub -optimal conditions for maize increasing by up to 600%. The analysis of crop yields show that maize yields are projected to decline by about 23.9% under the RCP4.5 scenario and 29.4% under RCP8.5. Sugarcane yields are similarly projected to decrease by 17.0% and 28.6% for RCP4.5 and RCP8.5 respectively. The underlying climatic changes suggest that future warming outweighs the effects of precipitation in explaining crop yield declines. More broadly, the methodology applied in this study can be readily adapted and utilized for agricultural areas throughout the Sub-Saharan region. By adopting this localized impact assessment approach policymakers and sector players will be empowered with information at a higher spatial detail which empowers targeted, regionspecific adaptation strategies.