Assessment of future agricultural conditions in southwestern Africa using fuzzy logic and high-resolution climate model scenarios

Abstract

Climate change is expected to have a major impact on the arid savanna regions of southwestern Africa, such as the Okavango Basin. Precipitation is a major constraint for agriculture in countries like Namibia and Botswana and assessments of future crop growth conditions are in high demand. This GIS-based approach uses reanalysis data and climate model output for two scenarios and compares them to the precipitation requirements of the five most important crops grown in the region: maize, pearl millet, sorghum, cassava and cow pea. It also takes into account the dominant soil types, as plant growth is also limited by nutrient-poor soils with unfavorable physical and chemical properties. The two factors are then combined using a fuzzy logic algorithm. The assessment visualizes the expected shifts in suitable zones and identifies areas where farming without irrigation may experience a decline in yields or may even no longer be possible at the end of the 21st century. The results show that pearl millet is the most suitable crop in all scenarios while especially the cultivation of maize, sorghum and cow pea may be affected by a possible reduction of precipitation under the high-emission scenario.