Abstract:
Understanding the impacts of climate change on water resources is of utmost importance
to successful water management and further adaptations strategies. The objective of this paper is to
assess the impacts of climate change on river discharge dynamics in Oueme River basin in Benin.
To this end, this paper used the distribution based scaling approach to improve usability of regional
climate model projections for hydrological climate change impacts studies. Hydrological simulations
in Bétérou and Bonou sub-catchments of the Oueme River were carried out with a lumped conceptual
hydrological model. The main contribution of this paper is to use the hydrological model based on
the least action principle (HyMoLAP), which is designed to minimize uncertainties related to the
rainfall-runoff process and scaling law, for this assessment. The bias correction approach allows
reducing the differences between the observed rainfall and the regional climate model (HIRHAM5
and RCA4) rainfall data. Corrected and raw HIRHAM5 and RCA4 rainfall data were compared
with the observed rainfall using Mean Absolute Error (MAE) and Root Mean Square error (RMSE).
The results of the bias correction show a decrease in the RMSE and MAE of the raw HIRHAM5 and
RCA4 rainfall data of approximately 91% to 98% in both catchments. The results of the simulation
indicate that the HyMoLAP is suitable for modelling river discharge in the Oueme River basin. For the
future projection based on RCP4.5 scenarios, the projected mean annual river discharge by using
HIRHAM5 and RCA4 in Bétérou and Bonou decrease with the magnitude ranging respectively from
−25% to −39% and −20% to −37% in the three time horizons 2020s (2011–2040), 2050s (2041–2070)
and 2080s (2071–2100), representing the early, middle and late of 21st century. As regards the future
projection based on RCP8.5 scenarios, the projected mean annual river discharge by using HIRHAM5
and RCA4 in Bétérou and Bonou decrease with the magnitude ranging respectively from −15% to
−34% and −18% to −36% in the three time horizons. The model uncertainties projections indicated
that the entire discharge distribution shifted toward more extreme events (such as drought) compared
to the baseline period.
