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Flooding constitutes a major problem for the inhabitants of Douala City in general and those of the Tongo Bassa watershed (TBW) in particular. Faced with this situation, public authorities need to put in place measures to mitigate the vulnerability of populations to these disasters. This article aims to map flooding risk areas in the TBW using the geographic information system, field data (historical flood points), remote sensing data (Sentinel II image) and the frequency ratio model. The map produced shows that 1.41, 8.88, 28.51, 33.86 and 27.33% of the basin area are respectively delimited into very low, low, medium, high and very high flood vulnerability classes. High and very high flooding risk areas (those where flooding is most likely to occur) occupy more than half of the basin (61.19%). These areas are characterized by significant imperviousness, low altitudes, weak slopes, significant proximity to watercourses and clayey soils. Most of the houses in the basin (66.92%) are located in areas affected by these two levels of exposure (high and very high). With respective success and prediction accuracy rates of 89 and 96.78%, a certain confidence deserves to be placed on the map of flooding risk areas produced. HIGHLIGHTS Flood susceptibility mapping is addressed through the geographic information system, remote sensing and the frequency ratio model.; A flooding risk areas map with five levels of exposure is proposed.; The number of houses included in each flood exposure level is summarized.;

Study region: Mbakaou and Bamendjing basins (Sanaga River sub-basins). Study focus: In this study, the availability of water resources was assessed over the period 2002–2019, based on the SWAT (Soil and Water Assessment Tool) hydrological model and certain meteorological and spatial reference data available for the region (Merra2, Landsat, etc.). Forecasts of its evolution were then made with the same tool (SWAT) over two futures periods (near 2024–2035 and medium: 2036–205) based on data from four (04) regional climate models (RCMs) (CCCma, HIRHAM5, RCA4 and REMO) and future land use and land cover (LULC) data simulated using the CA-Markov procedure. To separate the impact of climate variability (CV) and land use and use and land cover changes (LULCCs) on future water resources, two evolution scenarios (experiments) were established: (1) the impact of the CV, by associating future climate data with LULC from the historical period; (2) the impact of LULCCs, by combining future LULC maps with climate data from the historical period. New hydrological insights for the region: The performances of the SWAT model are satisfactory in calibration and validation on the two basins with R2, NSE and KGE greater than 0.68. Two models (CCCma and REMO) predict a decline in water resources in these basins, and two others (HIRHAM5 and RCA4) the opposite. The REMO model seems the most reliable. It predicts a drop in precipitation and runoff (SURQ) in the two basins that do not respectively exceed –19% and –31%. CV is the only forcing whose impact will be visible in the dynamics of future water resources, given the insignificant changes expected in the evolution of LULC patterns. The results of this study could contribute to improving the management of water resources in the studied basins and the region.

Due to climate and environmental changes, sub-Saharan Africa (SSA) has experienced several drought and flood events in recent decades with serious consequences on the economy of the sub-region. In this context, the region needs to enhance its capacity in water resources management, based on both good knowledge of contemporary variations in river flows and reliable forecasts. The objective of this article was to study the evolution of current and future (near (2022–2060) and distant (2061–2100)) flows in the So'o River Basin (SRB) in Cameroon. To achieve this, the Pettitt and modified Mann–Kendall tests were used to analyze hydrometeorological time series in the basin. The Soil and Water Assessment Tool (SWAT) model was used to simulate the future flows in the SRB. The results obtained show that for the current period, the flows of the So'o decrease due to the decrease in precipitation. For future periods, a change in precipitation in line with the predictions of the CCCma model will lead to a decrease in river discharge in the basin, except under the RCP8.5 scenario during the second period (2061–2100), where we note an increase compared to the historical period of approximately +4%. Results from the RCA4 model project an increase in precipitation which will lead to an increase in river discharge by more than +50%, regardless of the period and the scenario considered. An increase in discharges was noted in some cases despite a drop in rainfall, particularly in the case of discharges simulated for the second period (2061–2100) from the outputs of the CCCma model. This seems to be a consequence of the increase in impervious spaces, all the more the runoff increases during this period according to the model. Results from this study could be used to enhance water resources management in the basin investigated and the region. HIGHLIGHTS Impact of current climate change and anthropization on river discharge in equatorial central Africa.; Impact of future climate change and anthropization on river discharge in equatorial central Africa.;