Ph.D, associate professor, lead of the SHUD project



Dr. Shu is an associate professor at Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (NIEER, CAS). He obtained a Ph.D. degree in Water Resource Engineering and a minor degree of Computational Science from Pennsylvania State University in 2017. He is the lead developer of the Simulator for Hydrologic Unstructured Domains(SHUD) model. His major interests are computational hydrologic model, hydrologic data mining, and integrated Coupled Nature-Human System modeling.


  • Hydrological response under stress of climate and landuse change
  • Hydrology/remote-sensing data informatics
  • Spatial heterogeneity and homogeneity and their sensitivity to controls
  • High-performance/parallel computing in hydrologic models
  • Coupled Nature-Human watershed modeling


  • Ph.D in Water Resources Engineer and Computational Science, 2017

    Pennsylvania State University

  • M.S. in Remote Sensing, 2009

    University of Chinese Academy of Sciences (Lanzhou, China)

  • B.S in Geography Information System, 2005

    Lanzhou University (Lanzhou, China)

Recent Posts

Recent Publications

From concept to practice to policy: modeling coupled natural and human systems in lake catchments

Recent debate over the scope of the U.S. Clean Water Act underscores the need to develop a robust body of scientific work that defines the connectivity between freshwater systems and people. Coupled natural and human systems (CNHS) modeling is one tool that can be used to study the complex, reciprocal linkages between human actions and ecosystem processes. Well-developed CNHS models exist at a conceptual level, but the mapping of these system representations in practice is limited in capturing these feedbacks. This article presents a paired conceptual-empirical methodology for functionally capturing feedbacks between human and natural systems in freshwater lake catchments, from human actions to the ecosystem and from the ecosystem back to human actions. We address extant challenges in CNHS modeling, which arise from differences in disciplinary approach, model structure, and spatiotemporal resolution, to connect a suite of models. In doing so, we create an integrated, multi-disciplinary tool that captures diverse processes that operate at multiple scales, including land-management decision-making, hydrologic-solute transport, aquatic nutrient cycling, and civic engagement. In this article, we build on this novel framework to advance cross-disciplinary dialogue to move CNHS lake-catchment modeling in a systematic direction and, ultimately, provide a foundation for smart decision-making and policy.
From concept to practice to policy: modeling coupled natural and human systems in lake catchments