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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.

The Okavango catchment in southern Africa is subject to environmental as well as socio-economic transformation processes such as population growth and climate change. The degradation of soil and vegetation by deforestation and overgrazing is one of the downsides of this development, reducing the capacity of the land to provide ecosystem functions and services. In this study, climate simulations are brought together with secondary socioeconomic, pedologic and remote-sensing data in a GIS-based assessment of the factors commonly associated with land degradation risk. A high resolution overview is provided for decision-makers and stakeholders in the region by identifying priority intervention areas where a long-term decline in ecosystem function and land productivity is most likely to occur. The approach combines 19 risk factors into seven individual ratings for topography, landcover, soil, demography, infrastructure, livestock pressure and climate. These ratings are then weighted and combined into an integrated degradation risk index (DRI). The results show that the land degradation risk is quite heterogeneously distributed in the study area and caused by different factors. Three hot-spots are identified and compared, one of which is in the far northwestern part of the catchment, one around the local center Rundu and one on the outskirts of the Okavango Delta. We conclude that the approach is suitable to give an overview on degradation risk in the study area, although the classification process is a crucial procedure that should be standardized for further research. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]