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Simulator for Hydrologic Unstructured Domains (SHUD 1.0): Numerical modeling of watershed hydrology with the finite volume method

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.

Integrating fast and slow processes is essential for simulating human–freshwater interactions

Integrated modeling is a critical tool to evaluate the behavior of coupled human–freshwater systems. However, models that do not consider both fast and slow processes may not accurately reflect the feedbacks that define complex systems. We evaluated current coupled human–freshwater system modeling approaches in the literature with a focus on categorizing feedback loops as including economic and/or socio-cultural processes and identifying the simulation of fast and slow processes in human and biophysical systems. Fast human and fast biophysical processes are well represented in the literature, but very few studies incorporate slow human and slow biophysical system processes. Challenges in simulating coupled human–freshwater systems can be overcome by quantifying various monetary and non-monetary ecosystem values and by using data aggregation techniques. Studies that incorporate both fast and slow processes have the potential to improve complex system understanding and inform more sustainable decision-making that targets effective leverage points for system change.

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.

Integrated modeling environment and a preliminary application on the Heihe River Basin, China

We designed and implemented an integrated modeling environment (HIME) for hydrological and land surface modeling purpose in a much extendable, efficient and easy use manner. With such design, a physical process was implemented as a module, or component. A new model can be generated in an intuitive way by linking module icons together and establishing their relationships. Following an introduction to the overall architecture, the designs for module linkage and data transfer between modules are described in details. Using XML based meta-information, modules in either source codes or binary form can be utilized by the environment. As a demonstration, with the help of HIME, we replaced the evaporation module of TOPMODEL with the evapotranspiration module from the Noah land surface model which explicitly accounts for vegetation transpiration. This example showed the effectiveness and efficiency of the modeling environment on model integration.