Djibo A. G. auteur aut IRD Karambiri H. auteur aut IRD Seidou O. auteur aut IRD Sittichok K. auteur aut IRD Philippon N. auteur aut IRD Paturel Jean-Emmanuel auteur aut IRD Saley H. M. auteur aut IRD text journalArticle eng text/pdf reformatted digital access Since the 90s, several studies were conducted to evaluate the predictability of the Sahelian rainy season and propose seasonal rainfall forecasts to help stakeholders to take the adequate decisions to adapt with the predicted situation. Unfortunately, two decades later, the forecasting skills remains low and forecasts have a limited value for decision making while the population is still suffering from rainfall interannual variability: this shows the limit of commonly used predictors and forecast approaches for this region. Thus, this paper developed and tested new predictors and new approaches to predict the upcoming seasonal rainfall amount over the Sirba watershed. Predictors selected through a linear correlation analysis were further processed using combined linear methods to identify those having high predictive power. Seasonal rainfall was forecasted using a set of linear and non-linear models. An average lag time up to eight months was obtained for all models. It is found that the combined linear methods performed better than non-linear, possibly because non-linear models require larger and better datasets for calibration. The R-2, Nash and Hit rate score are respectively 0.53, 0.52, and 68% for the combined linear approach; and 0.46, 0.45, 61% for non-linear principal component analysis. specialized rainfall forecasting neural network non-linear principal component analysis Sirba basin West African monsoon air temperature NIGER SAHEL 062 3 3 727-752 2015 2225-1154 https://www.documentation.ird.fr/hor/fdi:010068846 10.3390/cli3030727 2225-1154 [F B010068846] https://www.documentation.ird.fr/hor/fdi:010068846 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers17-05/010068846.pdf IRD - Base Horizon / Pleins textes 2017-04-04 2017-08-23 fdi:010068846 fre