Computational Hydrology Group

Our research enhances the understanding, modeling, and prediction of hydrologic processes under climate change.

As part of our research, we ask the following types of questions:

• What drives extreme hydrologic events, such as floods and droughts?
• What are the dominant hydrologic processes across various landscapes?
• How to improve watershed delineation for more realistic modeling?
• How to enhance parameter estimation efficiency?
• How to quantify and incorporate observational uncertainties into forecasting?
• How to better predict extreme hydrologic events under climate change?

Our research uses in situ and remote sensing data, integrates machine learning with process-based hydrologic modeling, and runs large-domain simulations on supercomputers. We are passionate about conducting open, reproducible, and collaborative research. Our research outcomes will help improve the usefulness of hydrologic observations and models in water engineering and interdisciplinary problems.