Hongli Liu

Hongli Liu serves as Assistant Professor in the Civil and Environmental Engineering Department at the University of Alberta's Faculty of Engineering. Her research focuses on advancing hydrologic modeling for extreme event prediction and climate change impact assessment.

Education:

• PhD, Civil Engineering (Collaborative Water Program), University of Waterloo, 2019
• MSc, Environmental Science, Beijing Normal University, 2014
• BSc, Geography, Shandong Normal University, 2011

Dr. Liu leads the Computational Hydrology Group, integrating machine learning with process-based hydrologic modeling to address critical water challenges. Her research tackles driving factors behind extreme hydrologic events, dominant hydrologic processes across regions, watershed delineation improvements, observational data uncertainty incorporation, and climate change impacts on water systems. The group utilizes in situ and remote sensing data while conducting large-domain simulations on supercomputers.

Her publication portfolio demonstrates expertise in uncertainty quantification, ensemble methods, and sensitivity analysis within hydrological modeling. Current research trends emphasize machine learning integration with physical models and large-scale hydrological prediction under global change scenarios.

Dr. Liu actively contributes to the scientific community through co-editing special issues including Advances in Large-Scale Hydrological Modeling and Prediction under Global Change (Water Resources Research) and Every Drop Matters: Resolving New Challenges in Flood and Drought Analyses and Forecasting (Meteorological Applications).

The Computational Hydrology Group develops open-source tools including pyVISCOUS global sensitivity analysis toolbox, Parameter estimation toolbox for SUMMA, Watershed discretization toolbox, and Ensemble dressing of North American land data assimilation version 2 (EDN2), reflecting commitment to reproducible and collaborative research.