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Potential value of GCM-based seasonal rainfall forecasts for maize management in semi-arid Kenya

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  • Hansen, James W.
  • Mishra, Ashok
  • Rao, K.P.C.
  • Indeje, Matayo
  • Ngugi, Robinson Kinuthia

Abstract

We estimate the potential value of general circulation model (GCM)-based seasonal precipitation forecasts for maize planting and fertilizer management decisions at two semi-arid locations (Katumani and Makindu) in Southern Kenya. Analyses combine downscaled rainfall forecasts, crop yield simulation, stochastic enterprise budgeting and identification of profit-maximizing fertilizer N rates and stand densities. October-February rainfall predictions were downscaled from a GCM, run with both observed and forecast sea surface temperature boundary conditions - representing upper and lower bounds of predictability - and stochastically disaggregated into daily crop model inputs. Simulated interactive effects of rainfall, N supply and stand density on yield and profit are consistent with literature. Perfect foreknowledge of daily weather for the growing season would be worth an estimated 15-30% of the average gross value of production and 24-69% of average gross margin, depending on location and on whether household labor is included in cost calculations. GCM predictions based on observed sea surface temperatures increased average gross margins 24% at Katumani and 9% at Makindu when labor cost was included. At the lead time used, forecasts using forecast sea surface temperatures are not skillful and showed near-zero value. Forecast value was much more sensitive to grain price than to input costs. Stochastic dominance analysis shows that farmers at any level of risk aversion would prefer the forecast-based management strategy over management optimized for climatology under the study's assumptions, despite high probability (25% at Katumani, 34% at Makindu) of lower returns in individual years. Results contribute to knowledge of seasonal forecast value in a relatively high-risk, high-predictability context; utility and value of forecasts derived from a GCM; and risk implications of smallholder farmers responding to forecasts.

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  • Hansen, James W. & Mishra, Ashok & Rao, K.P.C. & Indeje, Matayo & Ngugi, Robinson Kinuthia, 2009. "Potential value of GCM-based seasonal rainfall forecasts for maize management in semi-arid Kenya," Agricultural Systems, Elsevier, vol. 101(1-2), pages 80-90, June.
  • Handle: RePEc:eee:agisys:v:101:y:2009:i:1-2:p:80-90
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    1. Ingram, K. T. & Roncoli, M. C. & Kirshen, P. H., 2002. "Opportunities and constraints for farmers of west Africa to use seasonal precipitation forecasts with Burkina Faso as a case study," Agricultural Systems, Elsevier, vol. 74(3), pages 331-349, December.
    2. Maria Carmen Lemos & Lisa Dilling, 2007. "Equity in forecasting climate: Can science save the world's poor?," Science and Public Policy, Oxford University Press, vol. 34(2), pages 109-116, March.
    3. de Wit, C. T., 1992. "Resource use efficiency in agriculture," Agricultural Systems, Elsevier, vol. 40(1-3), pages 125-151.
    4. Unknown, 2004. "Modelling Nutrient Management in Tropical Cropping Systems," ACIAR Proceedings Series 135389, Australian Centre for International Agricultural Research.
    5. Hadar, Josef & Russell, William R, 1969. "Rules for Ordering Uncertain Prospects," American Economic Review, American Economic Association, vol. 59(1), pages 25-34, March.
    6. Unknown, 2004. "Using seasonal climate forecasting in agriculture: a participatory decision-making approach," Technical Reports 113923, Australian Centre for International Agricultural Research.
    7. Thornton, P. K. & MacRobert, J. F., 1994. "The value of information concerning near-optimal nitrogen fertilizer scheduling," Agricultural Systems, Elsevier, vol. 45(3), pages 315-330.
    8. Carla Roncoli & Christine Jost & Paul Kirshen & Moussa Sanon & Keith Ingram & Mark Woodin & Léopold Somé & Frédéric Ouattara & Bienvenue Sanfo & Ciriaque Sia & Pascal Yaka & Gerrit Hoogenboom, 2009. "From accessing to assessing forecasts: an end-to-end study of participatory climate forecast dissemination in Burkina Faso (West Africa)," Climatic Change, Springer, vol. 92(3), pages 433-460, February.
    9. Hammer, G. L. & Hansen, J. W. & Phillips, J. G. & Mjelde, J. W. & Hill, H. & Love, A. & Potgieter, A., 2001. "Advances in application of climate prediction in agriculture," Agricultural Systems, Elsevier, vol. 70(2-3), pages 515-553.
    10. Anderson, Jock R. & Dillon, John L. & Hardaker, Brian, 1977. "Agricultural Decision Analysis," Monographs: Applied Economics, AgEcon Search, number 288652, July.
    11. Oecd, 2009. "Climate Change and Africa," OECD Journal: General Papers, OECD Publishing, vol. 2009(1), pages 5-35.
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    8. Carla Roncoli & Benjamin Orlove & Merit Kabugo & Milton Waiswa, 2011. "Cultural styles of participation in farmers’ discussions of seasonal climate forecasts in Uganda," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 28(1), pages 123-138, February.
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