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.

Location: Hohai Univeristy (Nanjing, Jiangsu) Time: 2022/09/23 - 09/24 Title: Quick, Reproducible, and Open Global Hydrological Data Cloud

Location: Summit Co.，Xi’an Time: 2022/06/27 - 07/01

Location: 腾讯会议 Time: 2022年10月15 Title: Wandering in Hydrological Models ——From the old friends to the new Video: https://mp.weixin.qq.com/s/GgjKowbyNNOqd4C3JSJNFg

Location: Wuhan University Online: Bilibili.com，武大水院学工办，Room Number:22060156 Time: 2022/2/15，10:00 - 12:00，

2021-03-02, Lanzhou

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’.

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.

In this study we applied two spatially explicit models to the problem. One is the Penn State Integrated Hydrologic Model (PIHM), a hydrologic model that partitions the water balance in space and time over the urban catchment. The other is the Cellular Automata Land Use Change Model (CALUC), a land use change model, which simulates the evolution of land use classes based on physical measures associated with population change and land use demand factors. We selected two study sites, one modern and one ancient, to highlight the capability of coupling catchment hydrology with land use change models. The goal is to assess the role of hydrologic change in urbanizing watersheds and to evaluate the contemporaneous impacts of climate change. The modern sites are the Conestoga watershed and the Lancaster PA urban center; the historical site is the ancient Maya city of Tikal in Peten region of Guatemala. In each setting, the essential data was developed and the models were used to evaluate how urbanization and land use change gradually altered the entire water balance often in unexpected ways.

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.