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 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.

This work focuses on trend analysis of rainfall, evaporation, temperature, relative humidity, wind speed, and sunshine duration over the Ouémé Delta in Bénin. Eight temperature based indices and fifteen rainfall based indices are computed from 1960 to 2016. Moreover, maximum 1, 2, 3, 5, and 10 days precipitation indices were computed at the monthly scale. Trends are detected at 0.05 confidence level, using a combination of Mann-Kendall and prewhitened Mann-Kendall test. Partial correlation and stepwise regression are used to detect the set of meteorological variables that influence pan evaporation in Ouémé Delta. Results showed intensification of heavy rainfall over Ouémé Delta. Moreover, a significant increasing trend is detected in temperature. As consequence, diurnal temperature significantly decreases as proof of the global warming. Average pan evaporation showed a significant slither increasing trend over the area. Change in pan evaporation can be explained by wind speed and sunshine duration that hold almost 50% of pan evaporation variance. As future temperature is going to be increasing, pan evaporation may increase considerably. So, adaptation measures have to be reinforced in the Ouémé Delta area where farmer are used to rainfed agriculture for food security. Moreover, Ouémé Delta plan have to be developed for it resources sustainability.

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.