Hongli Liu, PhD

Area of Study / Keywords

hydrology machine learning climate change

About

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

Research

Our Computational Hydrology Group (Website) aims to advance process-based hydrologic modeling, and its application in extreme event predictions (e.g., floods and droughts) and impact assessment under climate change. 

Recent Publications

• Gharari, S. Whitfield, P.H., Pietroniro, A., Freer, J., Liu, H. and Clark, M.P., 2024. Exploring the provenance of information across Canadian hydrometric stations: implications for discharge estimation and uncertainty quantification. Hydrology and Earth System Sciences, 28, 4383–4405. https://doi.org/10.5194/hess-28-4383-2024
• Liu, H., Clark, M.P., Gharari, S., Sheikholeslami, R., Freer, J., Knoben, W.J., Marsh, C.B. and Papalexiou, S.M., 2024. An improved copula‐based framework for efficient global sensitivity analysis. Water Resources Research, 60(1), p.e2022WR033808. https://doi.org/10.1029/2022WR033808
• Tang, G., Clark, M.P., Knoben, W.J., Liu, H., Gharari, S., Arnal, L., Beck, H.E., Wood, A.W., Newman, A.J. and Papalexiou, S.M., 2023. The impact of meteorological forcing uncertainty on hydrological modeling: A global analysis of cryosphere basins. Water Resources Research, p.e2022WR033767.  https://doi.org/10.1029/2022WR033767
• Liu, H., Wood, A.W., Newman, A.J. and Clark, M.P., 2022. Ensemble dressing of meteorological fields: using spatial regression to estimate uncertainty in deterministic gridded meteorological datasets. Journal of Hydrometeorology, 23(10), pp.1525-1543. https://doi.org/10.1175/JHM-D-21-0176.1
• Liu, H., Tolson, B.A., Newman, A.J. and Wood, A.W., 2021. Leveraging ensemble meteorological forcing data to improve parameter estimation of hydrologic models. Hydrological Processes, p.e14410.  https://doi.org/10.1002/hyp.14410
• Han, M., Mai, J., Tolson, B.A., Craig, J.R., Gaborit, É., Liu, H. and Lee, K., 2020. Subwatershed-based lake and river routing products for hydrologic and land surface models applied over Canada. Canadian Water Resources Journal, 45(3), pp.237-251. https://doi.org/10.1080/07011784.2020.1772116
• Liu, H., Thiboult, A., Tolson, B., Anctil, F. and Mai, J., 2019. Efficient treatment of climate data uncertainty in ensemble Kalman filter (EnKF) based on an existing historical climate ensemble dataset. Journal of Hydrology, 568, pp.985-996. https://doi.org/10.1016/j.jhydrol.2018.11.047
• Liu, H., Tolson, B.A., Craig, J.R. and Shafii, M., 2016. A priori discretization error metrics for distributed hydrologic modeling applications. Journal of Hydrology, 543, pp.873-891. https://doi.org/10.1016/j.jhydrol.2016.11.008

Open-source Datasets and Toolboxes

• pyVISCOUS global sensitivity analysis toolbox. link
• Parameter estimation toolbox for SUMMA. link
• Watershed discretization toolbox. link
• Ensemble dressing of North American land data assimilation version 2 (EDN2). link
  

 A PhD Opportunity

We are looking for a highly motivated PhD student to join our research group starting in September 2025. The successful candidate will have the opportunity to work on cutting-edge research in hydrologic modeling and prediction. For more information, please visit our group website.

Call for Papers for Two Special Issues 

I am pleased to announce two special issues that I am co-editing, each focusing on important advances in hydrology and climate sciences. We welcome your contributions!

1. Advances in Large-Scale Hydrological Modeling and Prediction under Global Change

• Journals: Water Resources Research, Journal of Advances in Modeling Earth Systems, and JGR: Atmospheres 
• Submission deadline: August 1, 2025

2. Every Drop Matters: Resolving New Challenges in Flood and Drought Analyses and Forecasting

• Journal: Meteorological Applications 
• Submission deadline: December 31, 2025

CIV E 321 - Principles of Environmental Modeling and Risk

Introduction modeling environmental processes to predict the movement of water and fate of contaminants in the hydrologic cycle. Principles of mass transfer, conservation of mass, environmental transformations, nutrient enrichment and depletion are developed. Introduction to storm events, rainfall, runoff, stream discharge and stormwater management. Applications of modeling results to the quantification of risk using examples from hydrology, water pollution and health protection and development of environmental regulations. Prerequisite: CIV E 221. Corequisite: CIV E 330.

CIV E 641 - Advanced Surface Water Hydrology

Precipitation, evaporation, infiltration. Streamflow and hydrograph analysis. Hydrologic systems. Hydrologic routing. Simulation models. Statistical methods.

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