The modeling framework of the coupled human and natural systems in the Yellow River Basin

A mechanistic understanding and modeling of the coupled human and natural systems (CHANS) are frontier of geographical sciences and essential for promoting regional sustainability. Modeling regional CHANS in the Yellow River Basin (YRB) featuring high water stress, intense human interference, and a...

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Main Authors: Shan Sang, Yan Li, Shuang Zong, Lu Yu, Shuai Wang, Yanxu Liu, Xutong Wu, Shuang Song, Xuhui Wang, Bojie Fu
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Geography and Sustainability
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666683925000331
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author Shan Sang
Yan Li
Shuang Zong
Lu Yu
Shuai Wang
Yanxu Liu
Xutong Wu
Shuang Song
Xuhui Wang
Bojie Fu
author_facet Shan Sang
Yan Li
Shuang Zong
Lu Yu
Shuai Wang
Yanxu Liu
Xutong Wu
Shuang Song
Xuhui Wang
Bojie Fu
author_sort Shan Sang
collection DOAJ
description A mechanistic understanding and modeling of the coupled human and natural systems (CHANS) are frontier of geographical sciences and essential for promoting regional sustainability. Modeling regional CHANS in the Yellow River Basin (YRB) featuring high water stress, intense human interference, and a fragile ecosystem has always been a complex challenge. Here, we propose a conceptual modeling framework to capture key human-natural components and their interactions, focusing on human-water dynamics. The modeling framework encompasses five human (Population, Economy, Energy, Food, and Water Demand) and five natural sectors (Water Supply, Sediment, Land, Carbon, and Climate) that can be either fully interactive or standalone. The modeling framework, implemented using the system dynamics (SD) approach, can well reproduce the basin's historical evolution in human-natural processes and predict future dynamics under various scenarios. The flexibility, adaptability, and potential for integration with diverse methods position the framework as an instructive tool for guiding regional CHANS modeling. Our insights highlight pathways to advance regional CHANS modeling and its application to address regional sustainability challenges.
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spelling doaj-art-54cd2340cf4e40cabce5c4c71336a30a2025-08-20T02:58:03ZengElsevierGeography and Sustainability2666-68392025-08-016410029410.1016/j.geosus.2025.100294The modeling framework of the coupled human and natural systems in the Yellow River BasinShan Sang0Yan Li1Shuang Zong2Lu Yu3Shuai Wang4Yanxu Liu5Xutong Wu6Shuang Song7Xuhui Wang8Bojie Fu9State Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; Corresponding authors: Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, PR China.State Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaInstitute of Carbon Neutrality, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, ChinaState Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Corresponding authors: Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, PR China.A mechanistic understanding and modeling of the coupled human and natural systems (CHANS) are frontier of geographical sciences and essential for promoting regional sustainability. Modeling regional CHANS in the Yellow River Basin (YRB) featuring high water stress, intense human interference, and a fragile ecosystem has always been a complex challenge. Here, we propose a conceptual modeling framework to capture key human-natural components and their interactions, focusing on human-water dynamics. The modeling framework encompasses five human (Population, Economy, Energy, Food, and Water Demand) and five natural sectors (Water Supply, Sediment, Land, Carbon, and Climate) that can be either fully interactive or standalone. The modeling framework, implemented using the system dynamics (SD) approach, can well reproduce the basin's historical evolution in human-natural processes and predict future dynamics under various scenarios. The flexibility, adaptability, and potential for integration with diverse methods position the framework as an instructive tool for guiding regional CHANS modeling. Our insights highlight pathways to advance regional CHANS modeling and its application to address regional sustainability challenges.http://www.sciencedirect.com/science/article/pii/S2666683925000331Coupled human-natural systems (CHANS)System dynamicsRegional modelingYellow RiverSustainable development
spellingShingle Shan Sang
Yan Li
Shuang Zong
Lu Yu
Shuai Wang
Yanxu Liu
Xutong Wu
Shuang Song
Xuhui Wang
Bojie Fu
The modeling framework of the coupled human and natural systems in the Yellow River Basin
Geography and Sustainability
Coupled human-natural systems (CHANS)
System dynamics
Regional modeling
Yellow River
Sustainable development
title The modeling framework of the coupled human and natural systems in the Yellow River Basin
title_full The modeling framework of the coupled human and natural systems in the Yellow River Basin
title_fullStr The modeling framework of the coupled human and natural systems in the Yellow River Basin
title_full_unstemmed The modeling framework of the coupled human and natural systems in the Yellow River Basin
title_short The modeling framework of the coupled human and natural systems in the Yellow River Basin
title_sort modeling framework of the coupled human and natural systems in the yellow river basin
topic Coupled human-natural systems (CHANS)
System dynamics
Regional modeling
Yellow River
Sustainable development
url http://www.sciencedirect.com/science/article/pii/S2666683925000331
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