Satellite-Enhanced Flood Modelling for the Niger River Basin using a Synergy of Hydrological Modelling and Earth Observation Data

Accurate water cycle representation in data-scarce and flood-prone regions like the Niger River Basin demands stronger integration between remote sensing and hydrological modelling. Spanning ten water-stressed nations, this basin faces critical challenges under climate change, requiring robust water-budget assessments to guide resilience strategies. We employ DHI’s Global Hydrological Model (DHI-GHM) to simulate key hydrological components of the regional water cycle. Model outputs for surface and root-zone soil moisture (SSM and R-ZSM) and terrestrial water storage (TWS) are systematically compared against satellite observations (GRACE/GRACE-FO and multiple soil moisture products) to identify discrepancies and enhance the understanding of regional hydrological behavior. A near real-time SSM data assimilation scheme is implemented to enhance spatiotemporal accuracy of surface and top-soil interactions, particularly beneficial in the flood-sensitive Inner Niger Delta. Post-assimilation hydrological outputs are coupled with the CaMa-Flood surface hydraulic model to simulate inundation dynamics, enabling improved flood prediction and supporting risk management. Finally, we pursue two-way coupling of hydrological and hydrodynamic models by integrating river flow–storage feedbacks to advance flood forecasting and sustainable water-resources planning.