The Ouémé River basin extends over almost half of Benin's territory, entirely located in a humid tropical climate. This river system includes a deltaic zone (delta of the Ouémé) known for its high agricultural potential and thus subject to a socio-economic development agenda. The Ouémé delta is facing recurrent floods that maintain rural agricultural population into a retrograding crisis with significant damages such as losses of properties. The objective of this study is to improve decision-making in the Ouémé basin through the simulation of exceptional floods using the HEC-RAS model. The HEC RAS model is a conceptual model, which works through mathematical and physical formulas to implement environmental phenomena for forecasting, understanding and analysis purposes. The model inputs used are basin GIS data, hydro-meteorological data, characteristics of existing hydraulic structures, etc. The targeted outputs include 1D/2D/3D view plans with support of satellite images, tables, graphs and curves. It is worth mentioning that the model provides outputs compatible with other tools, such as civil engineering (Civil 3D, Revit, Infraworks, etc.) and GIS, that help to expand the valorization fields. The implementation of the model in the Ouémé basin has made it possible to note: (i) that the recurring effect of losses and damages is justified by the settlement of the population on the river banks; (ii) that there is an important agricultural production in areas of high flood risk; (iii) that depending on the occurrence of the phenomenon, the flooded extent and the height of submersion remains variable, and more important for extreme flooding; (iv) about 12.07 % occurrence of river flood against 13.24 % for flash flood at a return period of 30 years. Moreover, it is very relevant to note that most of flood waters converge to the western part of the basin (an area with a low risk of flooding, stretched over 63.68 km²) and to the eastern part around the Damè-Wogon depression (an area at high risk of flooding, stretched over 10.49 km²).

Water resource management in the Sahelian-Sudanian transition zone faces growing uncertainty under climate change, yet hydrological projections remain scarce for the Oti-Pendjari basin (West Africa). This study develops an integrated modelling chain combining CMIP6 multi-model evaluation, bias correction, and GR4J hydrological modelling to project streamflow changes under SSP2-4.5 and SSP5-8.5 over 2021–2100. Eleven CMIP6 models were evaluated against ERA5 reanalysis data (1960–2014) using NSE, KGE, and MAE; the three best-performing models were bias-corrected using Linear Scaling, Variance Scaling, Quantile Mapping, and Quantile Delta Mapping. Linear Scaling proved most effective, with CMCC-ESM2 best reproducing observed precipitation (NSE and KGE up to 0.9), while the multi-model approach performed best for temperature. The GR4J model, calibrated at Porga, Mandouri, and Mango (KGE: 0.609–0.668), satisfactorily reproduces intermediate flows and flood dynamics, although structural limitations persist for low flows (KGE [1/Q]: −0.65 to −0.71). Projections reveal a marked divergence between scenarios: SSP2-4.5 yields September peak flow increases of +5.7% to +16.7%, whereas SSP5-8.5 leads to slight decreases of −1.1% to −3.6%, likely driven by increased potential evapotranspiration partially offsetting precipitation gains. These findings underscore the critical importance of scenario selection and model uncertainty in regional water resource planning.