Lele Shu is a postdoctoral researcher in the Department of Land, Air and Water Resources, UC Davis. 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 research interests include computationally distributed hydrological modeling, integrated modeling of the Coupled Nature-Human system, the impact of landuse and climate change, and hydrology/remote-sensing data informatics.
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)
This paper introduces the design of SHUD, from the conceptual and mathematical description of hydrological processes in a watershed to computational structures. To demonstrate and validate the model performance, we employ three hydrological experiments: the V-Catchment experiment, Vauclin's experiment, and a study of the Cache Creek Watershed in northern California, USA.
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.
Talks, Poster, Workshop, …