Targeting Climate Forecasts for Agricultural Applications in Sub-Saharan Africa: Situating Farmers in User-Space

Several meteorological services in Africa now issue seasonal climate forecasts on an operational basis. However, the failure to develop a comprehensive profile of users has resulted in a considerable gap between the information that is likely to be useful to farmers and that provided and disseminated by these services. The present study develops a methodology to characterize smallholder production systems in order to identify farmer groups who may adopt and benefit from the climate forecast information in sub-Saharan Africa. Through an extensive literature review, data and information was derived from a national household survey of 1540 smallholders in 1995–1997 by the Kenya Agricultural Research Institute and spatial georeferenced data from leading world data centers. The data were analysed and synthesized using the GIS. Considerable opportunities exist for farming communities to improve their profitability using climate forecasts. Although the needs and demand for climate forecasts vary according to the production systems and market forces that determine credit, demand and input availability and, thus, the usability of forecasts depend on the characteristics of the farmers and their place in space. Based on production strategies and options available to farmers, three zones were identified grouping farmers with highly probable, probable and less probable potential of adopting climate forecasts to alter their production practices. Although a climate forecast may be useful to all farmers in the region considered, due to different options available to individual groups of farmers, however, the benefits derived from its use may not be equitable. Some of the options available to farmers in Kenya were considered in this study with a view to highlighting why some may benefit more than others. The methodology demonstrated here could be adopted for other parts of the world for: (1) selecting survey sites to determine the benefits of climate forecasts using farmers participatory rapid rural appraisals and simulation approach, and (2) target climate information where it would be most useful.