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Watershed System Model: The Essentials to Model Complex Human‐Nature System at the River Basin Scale
Author(s) -
Li Xin,
Cheng Guodong,
Lin Hui,
Cai Ximing,
Fang Miao,
Ge Yingchun,
Hu Xiaoli,
Chen Min,
Li Weiyue
Publication year - 2018
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2017jd028154
Subject(s) - watershed , nexus (standard) , computer science , watershed management , multidisciplinary approach , decision support system , scale (ratio) , environmental resource management , data science , systems engineering , environmental science , geography , engineering , artificial intelligence , cartography , sociology , machine learning , social science , embedded system
Watershed system models are urgently needed to understand complex watershed systems and to support integrated river basin management. Early watershed modeling efforts focused on the representation of hydrologic processes, while the next‐generation watershed models should represent the coevolution of the water‐land‐air‐plant‐human nexus in a watershed and provide capability of decision‐making support. We propose a new modeling framework and discuss the know‐how approach to incorporate emerging knowledge into integrated models through data exchange interfaces. We argue that the modeling environment is a useful tool to enable effective model integration, as well as create domain‐specific models of river basin systems. The grand challenges in developing next‐generation watershed system models include but are not limited to providing an overarching framework for linking natural and social sciences, building a scientifically based decision support system, quantifying and controlling uncertainties, and taking advantage of new technologies and new findings in the various disciplines of watershed science. The eventual goal is to build transdisciplinary, scientifically sound, and scale‐explicit watershed system models that are to be codesigned by multidisciplinary communities.