Donghui Xu 🌏
Donghui Xu

Earth Scientist

About Me

I am a reserach scientist at the Pacific Northwest National Laboratory.

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Interests
  • Hydrology
  • Earth System Modeling
  • Hydrodynamic Modeling
Education
  • PhD Civil Engineering

    University of Michigan - Ann Arbor

  • MS Applied Mathematics

    University of Michigan - Ann Arbor

  • MS Civil Engineering

    University of Michigan - Ann Arbor

  • BS Hydrology and Water Resources Engineering

    Hohai University

💧My Research☀️
My research focuses on advancing our understanding and prediction of hydrological systems in the context of climate change and increasing human activity. With global warming and extreme events like floods, droughts, and heat waves posing growing threats to both ecosystems and communities, I aim to enhance the modeling of the hydrological cycle and assess its sensitivity to a changing climate from regional to global scales. By leveraging process-based hydrological models, Earth System Models (ESMs), and statistical approaches, my work seeks to improve the accuracy of predictions that inform critical decisions in water resources management, energy system resilience, and climate adaptation. My research not only addresses fundamental questions in hydrology but also aims to develop practical solutions that contribute to resilience in the face of evolving climate and environmental challenges.
Featured Publications
Recent News
Recent Publications
(2026). Systematic evaluation of atmospheric forcing, surface datasets, and mesh effects on kilometer-scale land surface and river modeling. Journal of Hydrology.
(2026). Significant Rural Contributions to Severe Coastal Urban Flooding Through Flow Connectivity. Geophysical Research Letters.
(2026). Integrating Maximum Entropy Production Theory and Machine Learning to Improve Global Evapotranspiration Modeling. Water Resources Research.
(2026). An Integrated Modeling Framework for Sediment Dynamics During Urban Flooding: Application to Hurricane Harvey in Houston. Water Resources Research.
(2026). The Value of Forecasters-in-the-Loop in Real-Time Flood Forecasting in the Age of Machine Learning. Geophysical Research Letters.