The SHUD model description paper is published on the Geoscientific Model Development. Total readers is more than 300 after the preprint. Web page: https://www.geosci-model-dev.net/13/2743/2020/ PDF link: https://www.geosci-model-dev.net/13/2743/2020/gmd-13-2743-2020.pdf Thanks to the editor Dr.

The release of SHUD v1.0 on GitHub(https://github.com/SHUD-System/SHUD). The conceputal and procedual design of the SHUD model can be found in our model description paper at Geoscientific Model Development Model https://www.geosci-model-dev-discuss.net/gmd-2019-354/.

The website https://shud.netlify.com is online now. The independent domain www.shud.xyz will be ready in a week.

In coming AGU fall meeting in San Francisco, Dr. Shu will present the “Quick and reproducible automated watershed modeling with the SHUD: Essential data, simulation, applications and visualization” on Friday, Dec 13, 2019.

The coronavirus that is currently causing severe respiratory illness worldwide has now been named SARS-CoV-2, and the disease is COVID-19. When the virus first emerged last December, it was generally described in medical journals as the ‘2019 novel coronavirus’.

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.

Your view that China’s re-vegetation of its deserts could exacerbate water shortages risks oversimplifying an incredibly complex eco-restoration problem (Nature 573, 474–475; 2019). Far from just planting trees in arid areas, China’s re-vegetation codes vary for different regions and greening programmes.

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.

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.