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

Drought monitoring and hydrological early warning system are important tools for
water resources management, and they must be further complemented by forecasting facilities that are well integrated with the EU’s Earth Observation data. In this project, based on Forootan and Mehrnegar's expertise, Bayesian-based Data Assimilation (DA) framework(s) will be developed to merge available satellite data with hydrological models to better understand and forecast the recent and future spatial-temporal changes in continental water storage and water fluxes.