MuSe-BDA · Multi-Sensor Bayesian Data Assimilation for Large-Scale Drought Monitoring System (MuSe-BDA)

Multi-Sensor Bayesian Data Assimilation for Large-Scale Drought Monitoring System (MuSe-BDA)

Reliable assessment of droughts and freshwater availability requires accurate knowledge of how water is stored and exchanged between the land surface, soil, and groundwater. However, current global monitoring systems still face major challenges. Hydrological models simulate these processes continuously but often miss important spatial details and underestimate uncertainty. Satellite missions such as GRACE and GRACE-FO observe large-scale variations in total water storage, yet they cannot separate the contributions from individual components such as soil moisture or groundwater. Remote-sensing products, while increasingly available, differ in coverage, depth sensitivity, and noise characteristics. These inconsistencies make it difficult to generate high-resolution and physically consistent pictures of the water cycle needed for reliable drought assessment. The MuSe-BDA project (Multi-Sensor Bayesian Data Assimilation for Large-Scale Drought Monitoring Systems) was established to overcome these limitations. It developed an innovative Bayesian Data Assimilation (BDA) framework that merges multi-sensor Earth-observation data with a hydrological model to improve the estimation of terrestrial water storage and its components. The system integrates satellite gravimetry (GRACE/GRACE-FO), soil-moisture observations, and climate-driven model simulations within a probabilistic optimization scheme that quantifies uncertainty and ensures physically realistic and continuous estimates of water-storage changes through time. Although the approach is globally applicable, validation focused on Europe and the United States, where dense observational networks exist for independent evaluation. These regions were used to calibrate and test the method before extending it globally. MuSe-BDA ultimately produced global drought maps and indices that reveal how drought intensity, extent, and recovery vary across continents. By advancing global hydrological monitoring capabilities, the project contributes to international climate-resilience efforts and supports European leadership in digital Earth-system modeling and sustainable water management.

Data: CORDIS, © European Union