Advancing Large-Scale Water Cycle Understanding in the Danube River Basin by GRACE/-FO Data Assimilation

Extreme events such as droughts and floods can have severe socioeconomic and ecological impacts, particularly in transboundary basins like the Danube - the most international river basin in the world. Accurate water monitoring in this region is essential for effective water management and risk mitigation. Hydrological models play a key role in simulating these processes. However, their accuracy is often limited by structural uncertainties, parameterization errors, and imperfect forcing data. Data assimilation (DA) frameworks have proven effective in reducing these uncertainties, especially for terrestrial water storage (TWS) and its individual components. In this study, we assimilate satellite-derived TWS anomalies from the Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE-FO into the WaterGAP Global Hydrology Model (WGHM) for the highly regulated Danube River Basin. Our results indicate that assimilating GRACE/-FO data into WGHM leads to notable improvements in water storage representation across the entire basin, reducing model uncertainties and aligning simulations more closely with independent observations. For example, high correlations of around 0.90 are observed for both the groundwater and soil water components after DA (0.82 and 0.93 for open loop run, respectively) indicating accurate representation of drying and wetting patterns. Although DA does not significantly improve streamflow simulations, they still exhibit reasonable Nash-Sutcliffe Efficiency (NSE) values of around 0.50. These findings highlight the potential of satellite-based DA frameworks to strengthen large-scale hydrological modeling and to support sustainable water resource management in transboundary basins.