A Novel Synergy of Physics-based and Data-driven Methods for Reliable Hydrological Predictions under Changing Climate

Improving predictions of extreme hydrometeorological events is essential for reaching sustainable goals under climate change. To meet this demand, I will develop novel frameworks to combine ensembles of hydrological models with various satellite and in-situ Earth observations through physics-based calibration/assimilation and data-driven methods. This project will provide new scientific insights into processes that lead to floods and droughts. The grant will fund two Ph.D. students and one postdoc.