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PROBLEM STATEMENT Recent flooding in the Bia watershed has affected the Ayamé 1 and 2 hydroelectric dams functionnality and caused damage in the Aboisso area. Studies have revealed that the threshold for observing these floods is estimated at 100 mm of rainfall. It therefore appears necessary to verify the link between the 100 mm rainy days trend and the floods recurrence on the Bia basin. OBJECTIVE This study aims at analyzing the trend of rain over a threshold 100 mm in the Bia watershed. METHODOLOGY The frequency of rainy days over a threshold 100 mm was constituted from 1941 to 2015 from the daily rainfall available over the same period at the stations Adiaké, Bianouan, Aboisso, Ayamé and Agnibilékro. The linear regression between these rainfall frequencies and time allowed us to assess the trend of rainfall days over threshlod 100 mm at each station. The slope of the regressions allowed us to appreciate the increasing or decreasing trends while the the t-test probability p applied to the regression slope highlights the highly significant (p < 0.01), significant (0.01 ≤ p RESULTS The daily rainfall over threshold the 100 mm frequency varies from 15 days in Agnibilékro to 120 days in Adiaké. The trend in these rainfall thresholds is characterized by an average decrease of 0.5% per decade. On an interannual scale, this negative trend was very significant in Adiaké and Bianouan, then significant in Aboisso and insignificant in Ayamé and Agnibilékro. An intermonthly observation, the decrease was very significant in May, June and July in Aboisso, Adiaké and Bianouan respectively. CONCLUSION The flooding recurrence in the Bia basin is not related to an increase in the frequency of threshold rains (100 mm) of flooding, it could be related to the vulnerability of the basin.

The African continent is probably the one with the lowest density of hydrometric stations currently measuring river discharge, despite the fact that the number of operating stations was quite important until the 70s. This new African Database of Hydrometric Indices (ADHI) is compiling data from different sources carefully checked for quality control. It includes about 1500 stations with at least 10 years of daily discharge data over the period 1950–2018. The average record length is 19 years and for over 100 stations complete records are available over 50 years. With this dataset spanning most regions of the African continent, several hydrometric indices have been computed, representing mean flow characteristics and extremes (low flows and floods), and are made accessible to the scientific community. The database will be updated on a regular basis to include more hydrometric stations and longer time series of river discharge. The ADHI database is available for download at: https://doi.org/10.23708/LXGXQ9 (Tramblay and Rouché, 2020).

International audience; Highlights:• Unprecedented report on 23 precipitation datasets reliability across West Africa.• Large discrepancies are observed between the precipitation datasets reliability.• The datasets reliability differ in space and according to the considered time step.• MSWEP is the most accurate dataset to represent the daily precipitation dynamic.• CHIRPS is the most accurate dataset to represent the monthly precipitation dynamic.Abstract: This study aims reporting on 23 gridded precipitation datasets (P-datasets) reliability across West Africa through direct comparisons with rain gauges measurement at the daily and monthly time scales over a 4 years period (2000-2003). All P-datasets reliability vary in space and time. The most efficient P-dataset in term of Kling–Gupta Efficiency (KGE) changes at the local scale and the P-dataset performance is sensitive to seasonal effects. Satellite-based P-datasets performed better during the wet than the dry season whereas the opposite is observed for reanalysis P-datasets. The best overall performance was obtained for MSWEP v.2.2 and CHIRPS v.2 for daily and monthly time-step, respectively. Part of the differences in P-dataset performance at daily and monthly time step comes from the time step used to proceed the gauges adjustment (i.e day or month) and from a mismatch between gauge and satellite reporting times. In comparison to the others P-datasets, TMPA-Adj v.7 reliability is stable and reach the second highest KGE value at both daily and monthly time step. Reanalysis P-datasets (WFDEI, MERRA-2, JRA-55, ERA-Interim) present among the lowest statistical scores at the daily time step, which drastically increased at the monthly time step for WFDEI and MERRA-2. The non-adjusted P-datasets were the less efficient, but, their near-real time availability should be helpful for risk forecast studies (i.e. GSMaP-RT v.6). The results of this study give important elements to select the most adapted P-dataset for specific application across West Africa.

Water quality studies in Nigeria are usually conducted at local scales and limited to a restricted number of chemical contaminants, while reliable data on trace metal concentrations (including arsenic) are relatively scarce. This study focuses on the quality of available renewable water resources in terms of major ion and trace element concentrations at selected sampling locations in the Lower River Niger basin and part of the Lagos region. A screening of water contamination by arsenic and heavy metals was carried out through water sampling at selected locations using in situ measurement and laboratory testing to estimate heavy metal concentrations and water type. The analysis reveals moderate trace element contamination of the water resources, with the exception of Pb, while Mn and, to a lesser extent, Al exceeded WHO quality standards, but the Arsenic concentrations are within drinking water quality standards and are safe for consumption and irrigation, while the water type is Bicarbonate.

The African continent has a very low density of rain gauge stations, and long time-seriesfor recent years are often limited and poorly available. In the context of global change, it is veryimportant to be able to characterize the spatio-temporal variability of past rainfall, on the basis ofdatasets issued from observations, to correctly validate simulations. The quality of the rainfall datais for instance of very high importance to improve the efficiency of the hydrological modeling,through calibration/validation experiments.The HydroSciences Montpellier Laboratory (HSM) has a long experience in collecting andmanaging hydro-climatological data. Thus, HSM had initiated a program to elaborate a referencedataset, in order to build monthly rainfall grids over the African continent, over a period of 60 years(1940/1999). The large quantity of data collected (about 7,000 measurement points were used in thisproject) allowed for interpolation using only observed data, with no statistical use of a referenceperiod. Compared to other databases that are used to build the grids of the Global HistoricalClimatology Network (GHCN) or the Climatic Research Unit of University of East Anglia, UK (CRU),the number of available observational stations (a was significantly much higher, including the end ofthe century when the number of measurement stations dropped dramatically, everywhere.Inverse distance weighed (IDW) was the chosen method to build the 720 monthly grids and amean annual grid, from rain gauges. The mean annual grid was compared to the CRU grid. The gridswere significantly different in many places, especially in North Africa, Sahel, the horn of Africa, andthe South Western coast of Africa, with HSM_SIEREM data (database HydroSciencesMontpellier_Syst&egrave, me d&rsquo, Information Environnementales pour les Ressources en Eau et leurMod&eacute, lisation) being closer to the observed rain gauge values. The quality of the grids computed waschecked, following two approaches&mdash, cross-validation of the two interpolation methods, ordinarykriging and inverse distance weighting, which gave a comparable reliability, with regards to theobserved data, long time-series analysis, and analysis of long-term signals over the continent,compared to previous studies. The statistical tests, computed on the observed and gridded data,detected a rupture in the rainfall regime around 1979/1980, on the scale of the whole continent, thiswas congruent with the results in the literature. At the monthly time-scale, the most widely observedsignal over the period of 1940/1999, was a significant decrease of the austral rainy season betweenMarch and May, which has not earlier been well-documented. Thus, this would lead to a furtherdetailed climatological study from this HSM_SIEREM database.

Climate change is a reality which affects many climatic variables, including precipitation. The objective of this article is to study the extreme rain variability from a historical database (1941 - 2000). For this purpose, eleven (11) rainfall indices were calculated at the Adiaké, Bianouan, Ayamé, and Agnibilekro rainfall stations in Côte d'Ivoire. Due to lack of data on daily rainfall on the Ghanaian section of watershed, nine (9) monthly precipitations indices were estimated from monthly rainfall at the Enshi and Buakuc stations. The trend analysis of the precipitations indices show that a generalized downward was most significant in Adiaké compared to other stations. Furthermore, indices extreme thresholding (P99, P99p, P99,5 and P99,5p) have experienced a stable trend and a stationary evolution. All steps were detected in the non-stationary indices mostly observed after 1980 (late break) and before 1960 (precocious break).

The climatic evolution of the Bani river watershed, the main tributary to the upper Niger River, is approached through the spatiotemporal variability of rainfall grids over the 1950-2006 period. The analyses are conducted, and their results compared, using four different methods of spatial interpolation of rainfall fields: the spline, kriging, weighted inverse distance, and nearest neighbor methods. The largest changes are observed for all of these grids, but differences-and in some cases divergent results-appear in the details. The analysis shows a substantial decline in rainfall, particularly marked in the center of the basin, during the 1970-2000 period with respect to the 1950-1969 period, and a slight upturn in the northern part, mainly since the beginning of the 1990s. The rainfall deficit can be attributed to a combination of factors: an earlier and drier end of the rainy season, less precipitation in the middle of the rainy season, more dry days and lower amounts of precipitation on rainy days. Two drought indices-the Effective Drought Index and Standardized Precipitation Index-revealed that the maximum duration of drought events increased most in the central part of the basin. Lastly, to supplement this comparison of methods of spatial interpolation of rainfall fields, the sensitivity of a hydrological model (GR2M) to rainfall data was tested. Given the distribution and density of rain gauge stations available in the Bani watershed, the kriging method is found to yield the best hydrological modeling performance.

La realisation d'une base de donnees de pluies mensuelles pour l'Afrique est une valorisation par le Laboratoire HydroSciences Montpellier-HSM d'un fond de donnees pluviometriques africaines, herite entre autres de l'Orstom, et de son experience en gestion de bases de donnees hydroclimatiques en zone intertropicale. Les grilles de donnees creees permettent de diffuser des donnees pluviometriques elaborees au demi-degre carre, utiles a la recherche en Afrique, tout en respectant la confidentialite des donnees brutes stationnelles qui restent la propriete des services nationaux. Les donnees brutes font l'objet d'une serie de critiques approfondies pour chaque poste pour corriger ou eliminer les informations fausses ou douteuses. Ce travail reponds a trois objectifs : i) proposer en ligne un inventaire des postes pluviometriques existants pour tous les pays ; ii) generer des series de donnees de pluies homogenes appelees « series de reference » ; iii) construire des grilles de pluies mensuelles au demi-degre carre pour le continent africain sur la periode 1900-2000, proposees en acces libre sur le site SIEREM : http://www.hydrosciences.fr/sierem.

Le bassin du Nakambe a Wayen (Burkina-Faso) occupe une surface de pres de 21 000 km 2 en domaine sahelien. Malgre la baisse de la pluviometrie depuis 1970, ses debits de pointe et ses coefficients d'ecoulement augmentent regulierement. Les crues sont plus precoces, en aout au lieu de septembre, et plus intenses. Cette augmentation est egalement observee pour d'autres cours d'eau saheliens voisins. Les debits journaliers maximums augmentent de pres de 100 %, mais le nombre de jours ou le debit est superieur a la moitie du debit maximum varie peu sur la meme periode, traduisant une crue peu etalee dans le temps. Cette augmentation des ecoulements est liee a la pression demographique et a la forte diminution des zones de vegetation naturelle, remplacees par des cultures et des sols nus, dont la capacite au ruissellement est superieure.

Monthly rainfall data in Burkina-Faso, West Africa, over a period of 77 years are extracted from three different gridded data sets, available either on the web: CRU (Climatic Research Unit, Norwich, UK), SIEREM (HydroSciences Montpellier, France), or from the National Meteorological Center of Burkina-Faso. With a view to modelling the runoff-rainfall relationship at the monthly time step, these data are used at the 0.5°∗0.5° scale. Despite mean, minimum, standard deviation and inter-annual variability being very similar for the period 1922 to 1998, the three gridded data sets used show an important spatial variability of values with time, and some differences are observed which lead to significantly different runoff-rainfall simulations. Comparison of the rainfall grids has shown that differences between the precipitation grids are more pronounced during years when the rainfall is lower; this also applies to areas where the rainfall is lower. The three different rainfall grids produce differences in mean rainfall of 4 to 11%, depending on the grids that are compared. While these results are obviously specific to the station networks and interpolation method used, they provide an indication of the differences that can arise.It is recommended that as many stations as possible are used to better assess areal rainfall. These biases have a strong influence on the results of the runoff-rainfall modelling (using the GR2M conceptual model): the Nash criteria show differences of about 20% and calculated flow of 30% to 40%. This study illustrates the levels of uncertainty when using available rainfall gridded data sets, for rainfall-runoff studies in West African developing countries, which is important in the context of predicting water resources for the future from the GCM outputs for the 21st century.Keywords: Burkina-Faso, database, runoff, rainfall, rainfall-runoff modelling, West Africa

International audience