Spatial Variation and Trend of Extreme Precipitation in West Africa and Teleconnections with Remote Indices

Extreme precipitation is a great concern for West Africa country, as it has serious consequence on key socio-economic activities. We use high resolution data from the Climate Hazards Group InfraRed Precipitation Stations (CHIRPS) to determine the spatial variability, trend of 8 extreme precipitation indices in West Africa and their relationship to remote indices. Spatial variability of extreme is characterized by maximum precipitation over the orographic regions, and in southern Sahel. The trend analysis shows a decrease of dry condition in Sahel and Sahara, and an increase tendency of wet indices over western Sahel and southern Sahel. The correlation analysis reveals that extreme precipitation in Sahel is strongly teleconnected to the Eastern Mediterranean Sea (EMS), whereas western and western-north Sahel is associated with both Atlantic Meridional Mode (AMM), Maiden Julian Oscillation phase 8 (MJO8), El Niño 3.4 index (NINO.3.4), and Trans-Atlantic-Pacific Ocean Dipole Index (TAPODI) but with different characteristics or directions. Guinean coast extreme precipitation is highly associated with Atlantic zone 3 SST anomaly (ATL3), Northern Cold Tongue Index (NCTI), TAPODI but also with an opposite sign with NINO.3.4 and in somewhat with the MJO8

Analyse des écoulements dans le bassin du fleuve Sénégal de 1960 à 2008

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

Characterization of the starting conditions of the rainy season in Senegal: highlighting the constraints of crop establishment

International audienceThe start of the rainy season in Senegal is characterized by critical variability, resulting in many crop failures after seed planting when a long dry spell occurs. The objective of this study is to characterize the starting conditions of the rainy season in different areas of Senegal in relation to crop success at the early stage. An analysis of four seasonal components determined from a daily rainfall database of 95 stations from 1950 to 2015. These seasonal components are the sowing date (Sowing), the Onset of the rainy season date (Onset), the length of the longest dry spell (DryMax), and the total rainfall (TotRain) during the 30 days after sowing. Statistical methods of time series homogeneity determination such as the Pettitt test, the Buishand test, the Von Newmann test, and the segmentation method have been applied to determine actual breakpoints and to obtain the most recent and homogeneous period to define the component in each site. The results indicate that these components have not exhibited statistically significant changes since 1950. Indeed, 3% of the stations show breakpoints for the Sowing, 4% for the TotRain, and 2% for the Onset. The start of the season follows a South East-North West gradient. It begins in the extreme South-East part of the country in the second decade of June while the first waves of sowing take place in the South-East center part from the second half of June. The north zone remains exposed to false start events with important seasonality. In the Northern and Central zones, the early or late character of the sowing passes more on the DryMax than the TotRain. It would be interesting to elucidate the effects of the rainfall regime at the early stage on the rainy season profile to gain better control of the pluvial crop yields

Combining multi-sensor satellite imagery to improve long-term monitoring of temporary surface water bodies in the Senegal river floodplain

International audienceAccurate monitoring of surface water bodies is essential in numerous hydrological and agricultural applications. Combining imagery from multiple sensors can improve long-term monitoring; however, the benefits derived from each sensor and the methods to automate long-term water mapping must be better understood across varying periods and in heterogeneous water environments. All available observations from Landsat 7, Landsat 8, Sentinel-2 and MODIS over 1999–2019 are processed in Google Earth Engines to evaluate and compare the benefits of single and multi-sensor approaches in long-term water monitoring of temporary water bodies, against extensive ground truth data from the Senegal River floodplain. Otsu automatic thresholding is compared with default thresholds and site-specific calibrated thresholds to improve Modified Normalized Difference Water Index (MNDWI) classification accuracy. Otsu thresholding leads to the lowest Root Mean Squared Error (RMSE) and high overall accuracies on selected Sentinel-2 and Landsat 8 images, but performance declines when applied to long-term monitoring compared to default or site-specific thresholds. On MODIS imagery, calibrated thresholds are crucial to improve classification in heterogeneous water environments, and results highlight excellent accuracies even in small (19 km2) water bodies despite the 500 m spatial resolution. Over 1999–2019, MODIS observations reduce average daily RMSE by 48% compared to the full Landsat 7 and 8 archive and by 51% compared to the published Global Surface Water datasets. Results reveal the need to integrate coarser MODIS observations in regional and global long-term surface water datasets, to accurately capture flood dynamics, overlooked by the full Landsat time series before 2013. From 2013, the Landsat 7 and Landsat 8 constellation becomes sufficient, and integrating MODIS observations degrades performance marginally. Combining Landsat and Sentinel-2 yields modest improvements after 2015. These results have important implications to guide the development of multi-sensor products and for applications across large wetlands and floodplains