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

Understanding Hydrologic Processes

Our research addresses two key questions: What are the generation mechanisms of hydrologic extreme events like floods and droughts, and what are the dominant hydrologic processes in different landscapes? We classify events and assess their changes in occurrence and magnitude under climate change. Also, we identify the dominant hydrologic processes in various landscapes, providing a foundation for developing regionally tailored hydrologic models.

Advancing Hydrologic Modeling

Our research focuses on two key areas: watershed delineation and parameter estimation. In watershed delineation, we aim to enhance the division of watersheds into grids or hydrologic response units (HRUs) to more effectively capture spatial heterogeneity. For parameter estimation, we work to improve the efficiency of sensitivity analysis and calibration in large-domain and complex models.

Enhancing Hydrologic Forecasting and Risk Management

We develop machine learning models to improve streamflow forecasting. We integrate hydrologic and hydraulic models to enhance flood mapping. Furthermore, our research places a strong emphasis on uncertainty quantification. We work to quantify the observational uncertainties in streamflow and meteorological data, and develop methods to incorporate these uncertainties into hydrologic modeling and forecasting.