Statistical seasonal rainfall and streamflow forecasting for the Sirba watershed, West Africa, using sea surface temperatures

International audience The ability of various statistical techniques to forecast the Jul-August-September (JAS) total rainfall and monthly streamflow in the Sirba watershed (in West Africa) was tested in this paper. First, multiple linear regression was used to link predictors derived from the Atlantic and Pacific sea surface temperature (SST) to JAS rainfall in the watershed up to 18 months ahead; then, daily precipitation was generated using temporal disaggregation; and finally, a rainfall-runoff model was used to generate future hydrographs. Different combinations of lag times and time windows on which SSTs were averaged were considered. Model performance was assessed using the Nash-Sutcliffe coefficient (Ef), the coefficient of determination (R2) and a three-category hit score (H). The best results were achieved using the Pacific Ocean SST averaged over the March-June period of the year before the rainy season and led to a performance of R2 = 0.458, Ef = 0.387 and H = 66.67% for JAS total rainfall and R2 = 0.552, Ef = 0.487 and H = 73.28% for monthly streamflow.