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L’hydrologie du fleuve Sénégal est tributaire de l’influence cumulée de la variabilité climatique et des barrages de Diama et de Manantali depuis la mise en service de ces derniers. Aujourd’hui, dans la vallée du fleuve, on assiste à une recrudescence des inondations. C’est dans ce contexte que nous nous proposons d’étudier l’évolution du régime hydrologique du fleuve Sénégal afin d’appréhender, à la fois, l’effet de la variabilité climatique et des barrages sur les écoulements. Une approche statistique associant plusieurs méthodes complémentaires (indices centrés et réduits, tests de détection de ruptures des moyennes et procédure de segmentation des séries) a été utilisée. Nos analyses nous ont permis de constater, sur le bassin du fleuve Sénégal, la rupture climatique des années 1970 qui s’est traduite par une diminution de l’écoulement moyen annuel mais aussi des cotes maximales annuelles et minimales annuelles. Cependant, une reprise significative des écoulements moyens annuels est observée à partir des environs de l’année 1994, ce qui atteste l’entrée dans une nouvelle période climatique plus humide que celle des décennies 1970 et 1980 à l’échelle du bassin du fleuve Sénégal. En outre, dans la vallée du fleuve, l’écoulement moyen annuel est renforcé, depuis la fin des années 1980 et le début des années 1990, par l’effet cumulé des barrages (par leurs impacts sur l’occupation du sol) et de la variabilité climatique. En effet, les barrages ont entraîné une hausse des crues maximales annuelles à la station de Bakel depuis 1994 et un soutien considérable des étiages dans toute la vallée du fleuve Sénégal.Since the commissioning of Diama and Manantali dams, the hydrological regime of the Senegal river depends on the cumulative impact of climate variability and dams. Nowadays, in the valley of the river there is an increase in flooding. The aim of this research was to analyze the evolution of the hydrological regime of the Senegal River in order to determine the effect of both climate variability and the dams on stream flows. A statistical approach combining several complementary methods (standard scores indices, tests for statistical ruptures and a segmentation series procedure) was used. Our analysis revealed that in the Senegal River Basin, a climatic break in the 1970s resulted in a decrease in the mean annual discharge and also in the annual maximum and minimum water levels. However, a significant recovery of the average annual flow is observed from around 1994, demonstrating the occurrence of a new climatic period, wetter than the 1970s and 1980s, across the Senegal River basin. In addition, in the river valley, the yearly mean of the flow is supported, since the late 1980s and early 1990s, by the cumulative effect of the dams (by their impact on land use) and climate variability. Furthermore, dams have led to an increase of the maximum annual flood levels at the Bakel station since 1994, and to a considerable support of low flows across the entire Senegal River Valley

Temporary water bodies' dynamics play an important role in the epidemiological chain-borne diseases such as Rift Valley fever as they are the main breeding habitats for mosquitoes. During the rainy season, hundreds of these temporary water bodies appear and grow in the Ferlo region (Senegal). The purpose of this research is to generate historical and future time series water levels and areas at three temporary ponds located in the environment and health observatory of Barkedji. A simple lumped hydrological model was developed for that purpose. It describes each pond watershed as three interconnected reservoirs: canopy, surface storage and soil storage and uses a linear relation to describe infiltration, percolation and baseflow (out of the soil reservoir). Given the depth of the water table in the region, percolation out of the soil surface is considered lost. Evapotraspiration was calculated using the Penman equation and withdraws water from the canopy and surface water reservoirs. Excess runoff from the soil storage is turned into runoff using a triangular unit hydrograph. The calibration was done using two years of hydrological and climatic data collected during the 2011 and 2012 rainy seasons. The calibration was successful and water level in the two ponds was simulated with a Root Mean Square Error (RMSE) of 11.2 to 15 cm. Because of the short duration of the observation, no validation could be done. Given the excellent agreement of the simulated and observed water levels during the calibration phase, the modeling exercise was considered to be successful. The developed models were used to generate historical time series of pond areas and correlate these to mosquitoes' infestation in the region. Future time series of pond areas were also generated using downscaled outputs of three regional climate models from the AMMA ENSEMBLES experiment. The generated pond levels and areas are being M. Bop et al. 742 used to assess the evolution of the disease in the next 40 years.

This study proposes a short term forecasting of solar irradiation with multi horizons in the north-west of Senegal. The multilayer artificial neural network (ANN), based on the Levenberg Marquardt algorithm and the meteorological data are used. The latter are measured in real time on the study site. The variables of interest are: mean solar irradiation, maximum temperature and measurement time; they are selected using Weka software. The forecasting horizons are: 0.5 hour, 1 hour, 1.5 hours, 2 hours, 2.5 hours, 3 hours, 3.5 hours, 4 hours, 4.5 hours, 5 hours, 5.5 hours and 06 hours. They are proposed with the corresponding statistical criteria. The results show that, the solar energy forecasting can be extended over a six-hour horizon with a correlation coefficient of 0.97 and root mean square error of 0.07. These results will make it possible to complete the forecasting tools in the solar energy sector in Senegal, and help investors to choose the most suitable horizons for energy forecasting in photovoltaic solar power plants.