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Decision Support System for Agricultural Applications of Climate Forecast in West Africa

Investigators

University of Florida:

Shrikant Jagtap and Jim Jones (Principle Investigators), Agricultural and Biological Engineering Department
Ken Boote (Agronomy Department)
Peter Hildebrand (Food and Resource Economics)

Ghanian Research Team

Samuel G.K. Adiku (Leader, Soil-Crop-Climate Modeler) Department of Soil Science, University of Ghana, Legion, Accra, Ghana
J.B. Naab (Agronomist and Soil Scientist) Savanna Agricultural Research Institute, Wa Office, Ghana (SARI)
Steve Tonah (Social Scientist) Department of Sociology, University of Ghana, Legion Accra
Michael Tanu, (Agro-meterologist) Meteorological Services Department, Accra, Ghana

The message conveyed by West African Farmers to date is that the long-lead climate forecasts are potentially valuable for agricultural planning. However, this potential is currently underutilized due to failure of support services (i.e. meteorological services, ministry of agriculture, financial institutions and extension agencies) to provide the necessary downscaled forecast and the appropriate forecast-dependent logistic support (inputs, credit facilities, and advice) to the benefit of the farmers. It appears that the support services sector is unaware of the advances in climate science involving ENSO teleconnections and do not seem to understand nor appreciate the implications and possibilities associated with this new information. Peanut is not only a major high-protein and major vegetable oil food in the Ghanaian diet, but it is also a cash crop and the cake remaining after oil extraction offers high quality feed for animals. Because local and international markets exist for peanuts, they provide an essential opportunity for small-scale subsistence farmers, many of whom are women, to generate income and improve living standards for themselves and their families. We are proposing a research project for developing climate-forecast-based decision support systems that will enable support services to routinely evaluate risks and opportunities for peanut production in Ghana and we will use the results and facilities from these projects to supplement activities and lower costs. The end goal of our participatory project would be a climate-forecast dependent decision support system for the agricultural sector in Ghana by harnessing modern knowledge of atmospheric and agricultural sciences and empirical knowledge of the complex farming systems. We will explore, with the model, how various responses to ENSO events might affect peanut production. The second purpose for various responses to ENSO events might affect peanut production. The second purpose for model analyses is to assess the potential added value of providing more information to support services and farmers than is currently available through climate forecasting. The goal of this activity is to couple climate forecast information with further model analyses to provide a better context for decision makers and producers, and then ask if this more elaborate information gives them any more flexibility and decision options than the climate data alone. Third, using these discussions, we will design the type of decision aid that would be needed by support services to they can provide logistical support to farmers. We intend to use this project to have a wide-ranging operational impact on activities of support services as well as productivity and profitability of agricultural commodities in general and peanuts in particular through improved understanding and use of climate forecasts. Improved climate and weather information will lead to more informed management decisions and reduced risks for yield losses.