Potential of the Coupled WRF/WRF-Hydro Modeling System for Flood Forecasting in the Ouémé River (West Africa)

Abstract

Since the beginning of the 2000s, most of the West-African countries, particularly Benin, have experienced an increased frequency of extreme flood events. In this study, we focus on the case of the Ouémé river basin in Benin. To investigate flood events in this basin for early warning, the coupled atmosphere–hydrology model system WRF-Hydro is used, and analyzed for the period 2008–2010. Such a coupled model allows exploration of the contribution of atmospheric components into the flood event, and its ability to simulate and predict accurate streamflow. The potential of WRF-Hydro to correctly simulate streamflow in the Ouémé river basin is assessed by forcing the model with operational analysis datasets from the European Centre for Medium-Range Weather Forecasts (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 of 500 m. Key parameters of the hydrological module of WRF-Hydro are calibrated offline and tested online with the coupled WRF-Hydro. The uncertainty of atmospheric modeling on coupled results is assessed with the stochastic kinetic energy backscatter scheme (SKEBS). WRF-Hydro is able to simulate the discharge in the Ouémé river in offline and fully coupled modes with a Kling–Gupta efficiency (KGE) around 0.70 and 0.76, respectively. In the fully coupled mode, the model captures the flood event that occurred in 2010. A stochastic perturbation ensemble of ten members for three rain seasons shows that the coupled model performance in terms of KGE ranges from 0.14 to 0.79. Additionally, an assessment of the soil moisture has been developed. This ability to realistically reproduce observed discharge in the Ouémé river basin demonstrates the potential of the coupled WRF-Hydro modeling system for future flood forecasting applications.

WRF-Hydro for Streamflow Simulation in the MATOPIBA Region within the Tocantins/Araguaia River Basin—Brazil: Implications for Water Resource Management

“…After identifying the optimal value for the infiltration factor, tests for the surface retention depth scaling parameter (RETDEPRTFAC) begin, using the best REFKDT value obtained in the previous test and default values for the other two parameters. Similarly, tests are performed for the scaling parameter (OVROUGHRTFAC) and then for the MannN parameter [19,20,44,47,49].…”

“…The calibration procedure for hydrological parameters was based on several studies in the literature [16,17,19,20,49]. Sensitivity tests were initially conducted for the Manuel Alves Pequeno River using discharge data from the Itacajá station, focusing first on the REFKDT parameter that controls the hydrograph volume.…”

“…A critical aspect of our study involves delving into four pivotal parameters: the infiltration factor (REFKDT), surface retention depth (RETDEPRT), surface roughness (OVROUGHRT), and channel roughness (MannN). Prior research has underscored the significance of these parameters in the nuanced calibration and optimization of the model to capture hydrological responses accurately, especially in scenarios characterized by extreme rainfall and flooding events [16][17][18][19][20]. While previous studies have conducted numerous simulations in various global regions, the utilization of the WRF-Hydro model in the MATOPIBA region of Brazil remains largely unexplored.…”

“…treme rainfall and flooding events [16][17][18][19][20]. While previous studies have conducted numerous simulations in various global regions, the utilization of the WRF-Hydro model in the MATOPIBA region of Brazil remains largely unexplored.…”

Flood Forecasting and Warning System: A Survey of Models and Their Applications in West Africa

“…In Africa, several studies have been done using deterministic models for flood forecasting issues. The physical models required lot of input data associated, making its use complicated while data driven models required less data and there is no need for physical equations and parameters, or catchment characteristics leading to the static of the model which cannot evaluate the changes such as land use land changed (Quenum et al, 2022). Despite the impacts and catastrophes induced by flood, West Africa, the central area of this research is unfortunately not well documented that topic.…”