Machine-Learning Surrogates for Hydrologic Prediction
Team
These surrogate models emulate WRF-Hydro streamflow outputs to speed up scenario testing and support explainable analysis of climate, land-use, and hydrologic controls.
From this research area
- Street-to-pipe diagnosis of compound rain–tailwater flooding (2026)
- Hydrological extremes heighten vulnerability to schistosomiasis (2024)
- A methodological framework for improving the performance of data-driven models (2023)
- Editorial: Coastal Flooding: Modeling, Monitoring, and Protection Systems (2022)
- Generalization of Runoff Risk Prediction (2022)