{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T02:59:56Z","timestamp":1768791596887,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T00:00:00Z","timestamp":1671408000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"La Fiducie pour la recherche en hydrologie, Qu\u00e9bec","award":["6314E\/2021, 4192\/2016"],"award-info":[{"award-number":["6314E\/2021, 4192\/2016"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The high variability of rainfall in the Sahel region causes droughts and floods that affect millions of people every year. Several rainfall forecasting models have been proposed, but the results still need to be improved. In this study, linear, polynomial, and exponential models are developed to forecast rainfall in the Bani and Senegal River basins. All three models use Atlantic sea surface temperature (SST). A fourth algorithm using stepwise regression was also developed for the precipitation estimates over these two basins. The stepwise regression algorithm uses SST with covariates, mean sea level pressure (MSLP), relative humidity (RHUM), and five El Ni\u00f1o indices. The explanatory variables SST, RHUM, and MSLP were selected based on principal component analysis (PCA) and cluster analysis to find the homogeneous region of the Atlantic with the greatest predictive ability. PERSIANN-CDR rainfall data were used as the dependent variable. Models were developed for each pixel of 0.25\u00b0 \u00d7 0.25\u00b0 spatial resolution. The second-order polynomial model with a lag of about 11 months outperforms all other models and explains 87% of the variance in precipitation over the two watersheds. Nash\u2013Sutcliffe efficiency (NSE) values were between 0.751 and 0.926 for the Bani River basin and from 0.175 to 0.915 for the Senegal River basin, for which the lowest values are found in the driest area (Sahara). Results showed that the North Atlantic SST shows a more robust teleconnection with precipitation dynamics in both basins.<\/jats:p>","DOI":"10.3390\/rs14246397","type":"journal-article","created":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T08:41:41Z","timestamp":1671439301000},"page":"6397","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Development and Assessment of Seasonal Rainfall Forecasting Models for the Bani and the Senegal Basins by Identifying the Best Predictive Teleconnection"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6613-3610","authenticated-orcid":false,"given":"Luis","family":"Balc\u00e1zar","sequence":"first","affiliation":[{"name":"Instituto Interamericano de Tecnolog\u00eda y Ciencias del Agua (IITCA), Universidad Aut\u00f3noma del Estado de M\u00e9xico, Toluca 50200, Mexico"},{"name":"Direcci\u00f3n de Posgrado, Universidad T\u00e9cnica de Cotopaxi, Av. Sim\u00f3n Rodr\u00edguez s\/n Barrio El Ejido Sector San Felipe, Latacunga 050108, Ecuador"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1710-5653","authenticated-orcid":false,"given":"Khalidou M.","family":"B\u00e2","sequence":"additional","affiliation":[{"name":"Instituto Interamericano de Tecnolog\u00eda y Ciencias del Agua (IITCA), Universidad Aut\u00f3noma del Estado de M\u00e9xico, Toluca 50200, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6245-070X","authenticated-orcid":false,"given":"Carlos","family":"D\u00edaz-Delgado","sequence":"additional","affiliation":[{"name":"Instituto Interamericano de Tecnolog\u00eda y Ciencias del Agua (IITCA), Universidad Aut\u00f3noma del Estado de M\u00e9xico, Toluca 50200, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6313-9187","authenticated-orcid":false,"given":"Miguel A.","family":"G\u00f3mez-Albores","sequence":"additional","affiliation":[{"name":"Instituto Interamericano de Tecnolog\u00eda y Ciencias del Agua (IITCA), Universidad Aut\u00f3noma del Estado de M\u00e9xico, Toluca 50200, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4666-2248","authenticated-orcid":false,"given":"Gabriel","family":"Gaona","sequence":"additional","affiliation":[{"name":"Departamento de Recursos H\u00eddricos y Ciencias Ambientales, Universidad de Cuenca, Cuenca 010203, Ecuador"},{"name":"Institute for Landscape Ecology and Resources Management (ILR), Justus Liebig University Giessen, 35390 Giessen, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7093-3146","authenticated-orcid":false,"given":"Saula","family":"Minga-Le\u00f3n","sequence":"additional","affiliation":[{"name":"Instituto Interamericano de Tecnolog\u00eda y Ciencias del Agua (IITCA), Universidad Aut\u00f3noma del Estado de M\u00e9xico, Toluca 50200, Mexico"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,19]]},"reference":[{"key":"ref_1","first-page":"299","article-title":"Drought in the Sahel","volume":"48","author":"Agnew","year":"1999","journal-title":"Geo J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"727","DOI":"10.3390\/cli3030727","article-title":"Linear and Non-Linear Approaches for Statistical Seasonal Rainfall Forecast in the Sirba Watershed Region (SAHEL)","volume":"3","author":"Karambiri","year":"2015","journal-title":"Climate"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1155\/2013\/453521","article-title":"The West African Sahel: A Review of Recent Studies on the Rainfall Regime and Its Interannual Variability","volume":"2013","author":"Nicholson","year":"2013","journal-title":"ISRN Meteorol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1002\/for.3980100104","article-title":"Prediction of Seasonal Rainfall in the Sahel Region Using Empirical and Dynamical Methods","volume":"10","author":"Folland","year":"1991","journal-title":"J. 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