Precipitation projections from regional climate models in West Africa are attributed with significant biases with respect to the observed. This study aims at evaluating of six methods of precipitation bias correction on four RCM (CCLM, CRCM, RACMO and REMO) outputs in the Ouémé basin. The bias correction methods used are classified into three namely: the Delta approach, the Linear Scaling method and the quantile approaches. Corrected and uncorrected RCM precipitation data were compared with the observed using Mean Absolute Error (MAE) and Root Mean Square error (RMSE). The findings showed that raw outputs of regional climate models (RCMs) are characterized with several biases. In general, the models overestimate precipitation. For daily precipitation correction, the quantile approaches assuming a gamma distribution for daily precipitation were not able to reduce the biases of precipitation. The empirical quantile mapping and the adjusted quantile mapping are the most effective in correcting the biases of daily precipitation. Thus the adjusted quantile mapping can be used to correct biases of precipitation projections for modeling the future availability of water resources.

This study analyzed trends in extreme precipitation based on daily rainfall data provided by Bénin Méteo Agency for the Upper Ouémé valley in Benin over the period 1951–2014. Eleven indices divided into two groups were considered. The first group consists of frequency indices: number of heavy rainfall days, very heavy rainfall days and extremely heavy rainfall days; and maximum number of Consecutive dry days and wet days. The second group concerns intensity: daily maximum rainfall (RX1day), maximum five-day rainfall (RX5day), annual total wet-day rainfall (PRCPTOT), simple daily intensity index (SDII), very wet day (R95P) and extremely wet day rainfall (R99P). The non-parametric Mann-Kendall test was used to assess trends in those indices. The results show that only 30% of the stations experienced decreasing trends for the number of heavy rainfall days (R10mm) and daily maximum rainfall (RX1day). For the annual total wet-day rainfall (PRCPTOT), the simple daily intensity index (SDII) and the very wet day rainfall (R95P), 20% of stations faced significant negative trends. In addition, the decreasing trends are observed for 10% stations considering the number of very heavy rainfall days (R20mm), the maximum five-day rainfall (RX5day) and the extremely wet day rainfall (R99P). About the increasing trend, 10% stations are identified for the number of consecutive dry days (CDD), very heavy rainfall days (R20mm), the daily maximum rainfall (RX1day), the simple daily intensity index, and the extremely wet day rainfall (R99P). These results show the absence of clear trend of climate indices evolution in almost all stations. Consequently, uncertainties in the evolution of rainfall indices must be taken into account in the definition of adaptation strategies for flood or drought risks. Similarly, these results show a slight drop in the dry sequences of the 1970s and 1980s revealed in the region by previous studies.

This study analyzed the trends of extreme daily rainfall indices over the Ouémé basin using the observed data from 1950 to 2014 and the projected rainfall of regional climate model REMO (REgional MOdel) for the period 2015–2050. For future trends analysis, two Intergovernmental Panel on Climate Change (IPCC) new scenarios are considered, namely RCP4.5 and RCP8.5. The indices considered are number of heavy rainfall days, number of very heavy rainfall days, consecutive dry days, consecutive wet days, daily maximum rainfall, five-day maximum rainfall, annual wet-day total rainfall, simple daily intensity index, very wet days, and extremely wet days. These indices were calculated at annual and seasonal scales. The Mann-Kendall non-parametric test and the parametric linear regression approach were used for trends detection. As result, significant declining in the number of heavy and very heavy rainfall days, heavy and extremely heavy rainfall, consecutive wet days and annual wet-day rainfall total were detected in most stations for the historical period as well as the future period following the scenario RCP8.5. Furthermore, few stations presented significant trends for the scenario RCP4.5 and the high proportion of stations with the inconsistence trends invites the planners to get ready for an uncertain future climate following this scenario.

This work focuses on impacts of climate change on Ouémé River discharge at Bonou outlet based on four global climate models (GCM) over Ouémé catchment from 1971 to 2050. Empirical quantile mapping method is used for bias correction of GCM. Furthermore, twenty-five rain gauges were selected among which are three synoptic stations. The semi-distributed model HEC-HMS (Hydrologic Modeling System from Hydrologic Engineering Center) is used to simulate runoff. As results, HEC-HMS showed ability to simulate runoff while taking into account land use and cover change. In fact, Kling–Gupta Efficiency (KGE) coefficient was 0.94 and 0.91 respectively in calibration and validation. Moreover, Ouémé River discharge is projected to decrease about 6.58 m³/s under Representative Concentration Pathways (RCP 4.5) while an insignificant increasing trend is found under RCP 8.5. Therefore, water resource management infrastructure, especially dam construction, has to be developed for water shortage prevention. In addition, it is essential to account for uncertainties when designing such sensitive infrastructure for flood management.

Participatory approaches to water management, and specifically to transboundary river management, have been widely applied over recent decades. Regarding transboundary rivers, the active involvement of key actors in policy planning is of great importance. In this context, a participatory approach has been used to identify sectors of interest and priorities related to water and development in the Mékrou transboundary River Basin involving three countries: Benin, Burkina Faso and Niger. We conducted a web-based survey to quantify expert opinion on sectors of water management policy and priorities for the Mékrou River Basin. The same set of questions was then put to a sample of local stakeholders living in this river basin. Our analysis reveals some points of convergence and some discrepancies between the opinions of experts and local stakeholders. Overall, it provides a comparative analysis of how experts and local stakeholders prioritize water policy measures, which could influence decision-making.

This study evaluates the impacts of land use and climate changes on daily discharge in Ouémé river basin at Bétérou outlet. Observed rainfall and temperature over 2002–2008 and land use data of 2003 and 2007 were used. Corrected rainfall and temperature data, under RCP4.5 and RCP8.5 scenarios from regional climate model REMO were considered. Two land use scenarios from RIVERTWIN project were used. The first one, Land Use A (LUA), is characterized by stronger economic development, controlled urbanization, implementation of large-scale irrigation schemes, and 3.2% population growth per year. The other one, Land Use B (LUB), is characterized by a weak national economy, uncontrolled settlement, and farmland development as well as 3.5% population growth per year. Four climate and land use combined scenarios (LUA + RCP4.5, LUA + RCP8.5; LUB + RCP4.5, and LUB + RCP8.5) were used for forcing LISFLOOD hydrological model to estimate future discharges at 2050. As a result, during calibration and validation, the LISFLOOD model showed high ability to reproduce historical flows of Ouémé River at Bétérou outlet with Nash–Sutcliffe efficiencies greater than 90%. Future discharges simulations show general increase for all land use and climate combined scenarios for all time horizons until 2050. The increase is more exacerbated under the combined scenarios using LUB than the ones using LUA. Increase of river discharge varies between 7.1% and 52% compared to the mean of the reference period 2002–2004. These findings highlight growing challenges for water resources managers and planners. Moreover, they emphasize the need to address potential climate and land use changes’ impact on water resources. Then, developing water management plans, strategies to reduce flooding risks must be considered.