Assessment of Satellite-Based Rainfall Products for Flood Modeling in the Ouémé River Basin in Benin (West Africa)

Reliable rainfall data are critical for managing hydrometeorological hazards in West Africa, yet they are often sparse and temporally inconsistent. The current study assessed the accuracy of four near real-time satellite-based rainfall data, namely IMERGv7 Late, IMERGv6 Early, GSMAP-NRT and PERSIANN-DIR Now, for rainfall estimation and hydrological modeling in the Ouémé basin. These datasets were compared with ground-based rainfall data, bias-corrected and used to calibrate and validate the hydrological model HBV light. While they demonstrated qualitative accuracy, their quantitative estimation shows obvious discrepancies on a daily scale, varying across subdomains. The original IMERGv7 product outperforms others in capturing the rainfall pattern and amount (KGE > 0.6), while GSMAP performs moderately (KGE ≈ 0.51) and IMERGv6 and PERSIANN show lower reliability with KGE < 0.5. Quantile mapping emerges as the most effective bias-correction method, improving the performance of all satellite products, with RMSE reductions ≤ 15%. The results of hydrological simulations demonstrate the potential of satellite-based rainfall, particularly IMERGv7 and corrected IMERGv6 (NSE > 0.75), for near real-time flood monitoring and water management in the study area. This study underscores their suitability as valuable alternatives to ground-based data for flood management decision making in the Ouémé basin.