EXTREME CLIMATE EVENTS PREDICTION OVER WESTAFRICA USING A COUPLED ATMOSPHERE-HYDROLOGY MODEL SYSTEM AND CLIMATE INDICES

Abstract

Rising temperature is one of the direct indicators of global climate change. To investigate how the rising global temperature will affect the spatial pattern of rainfall and consequent flood and drought in West Africa, precipitation and potential evapotranspiration variables from ten Global Climate Models (GCMs) under the RCP8.5 scenario were downscaled by the Rossby Centre regional atmospheric model (RCA4) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) and analysed at four specific global warming levels (GWLs) (i.e., 1.5℃, 2.0℃, 2.5℃, and 3.0℃) above the pre-industrial level. This study utilized four indices: the standardized precipitation evapotranspiration index (SPEI), the precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP) to explore the spatio-temporal variations in the characteristics of precipitation concentrations. Additionally, studying the impact of the four GWLs on consecutive dry days (CDD), consecutive wet days (CWD), and frequency of the intense rainfall events led to a better understanding of the spatiotemporal pattern of extreme precipitation. The onset of rainfall comes one month earlier in the Gulf of Guinea compared to the historical period, with increasing rainfall intensity in the whole study domain. To encourage adaptation to the various changes in climate in general, and particularly in respect of rainfall, the study proposes two adaptation methods that can be implemented at the local (country) level, as well as some mitigation and adaptation strategies at the regional level. More practically, to analyze flood events which became more frequent since 2000 in West Africa, this research improve on previous analysis by designing an experimental work using the coupled atmosphere-hydrology modeling system WRF-Hydro over Ouémé-river basin in Benin for the period 2008-2010. Such a coupled model allows exploring the contribution of viii atmospheric components into the flood event, and its ability to simulate and predict accurate streamflow. The potential of WRF-Hydro to correctly simulating streamflow in the Ouémé-river basin is assessed by forcing the model with operational analysis dataset from the ECMWF. Atmospheric and land surface processes are resolved at a spatial resolution of 5 km. The additional surface and subsurface water flow routing are computed at a resolution 1:10. Key parameters of the hydrological module of WRFHydro were calibrated offline and tested online with the coupled WRF/WRF-Hydro. As a result, WRF-Hydro was able to simulate the discharge in Ouémé river on offline and fully-coupled modes with a Kling-Gupta Efficiency (KGE) of 0.70 and 0.76 respectively. In fully-coupled modes, the model captures the flood event that occurred in 2010 in the catchments of interest. The uncertainty of atmospheric modeling on coupled results is assessed with the stochastic kinetic-energy backscatter scheme (SKEBS) by generating an ensemble of 10 members for three rainy seasons. It shows that the coupled model performance in terms of KGE ranges form 0.14-0.79 and 0.13- 0.75 at Savè and Bétérou respectively. This ability in realistically reproducing observed discharge in the Ouémé-river basin demonstrates the potential of the coupled WRFHydro modeling system for flood forecasting applications.