What question did this study set out to answer?

The research aims to assess the WRF-Hydro model's performance with different rainfall data inputs to enhance hydrological simulations.

February 8, 20260 citationsOpen Access

Evaluation of the WRF-Hydro model output based on different rainfall input data over the upper basin of the Senegal River

ANAssane Salame NdiayeWest African Science Service Centre on Climate Change and Adapted Land Use JAJoël ArnaultKarlsruhe Institute of Technology MMMamadou MbayeZiguinchor University

Key Points

The research aims to assess the WRF-Hydro model's performance with different rainfall data inputs to enhance hydrological simulations.
Evaluated WRF-Hydro model using IMERG, ERA5-LAND, and WRF precipitation datasets.
Conducted calibration and validation for the model over the upper Senegal River Basin from 2011 to 2020.
Measured model accuracy using KGE scores and PBIAS for different datasets.
The uncoupled WRF-Hydro model achieves a KGE score of 0.78 during calibration and validation.
IMERG and WRF datasets show strong agreement with observed streamflows with KGE scores of 0.78 and 0.73, respectively.
ERA5-LAND leads to significant underestimation of streamflows with a PBIAS of -56%.

Abstract

This study examines the performance of the uncoupled WRF-Hydro model under different precipitation inputs, highlighting its importance for water management in data-scarce West African regions. This study primarily uses IMERG precipitation data to calibrate and validate the WRF-Hydro model, aiming to fine-tune parameters for the accurate simulation of observed hydrological processes. ERA5-LAND and WRF precipitation datasets were also analyzed for comparison. A comparison was conducted to identify the dataset delivering the most accurate results in the uncoupled WRF-Hydro model. The 2011–2020 analysis shows the uncoupled WRF-Hydro model performs well in the upper Senegal River Basin, achieving strong KGE scores (KGE = 0.78) during calibration and validation. Both IMERG (KGE = 0.78; PBIAS = −18%) and WRF (KGE = 0.73; PBIAS = −4%) datasets show strong agreement with observed streamflows, while using ERA5-LAND as inputs results in a significant underestimation of streamflows (PBIAS = −56%). WRF precipitation proves more reliable, especially during rainy seasons.

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