Spatiotemporal Dynamics and Driving Mechanisms of Resource–Environment Carrying Capacity in the Yellow River Basin

Xin Xiang, Yi Xiao, Yongxiang Chen and Huan Huang ()
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Xin Xiang: College of Management Science, Chengdu University of Technology, Chengdu 610059, China
Yi Xiao: Business School, Chengdu University of Technology, Chengdu 610059, China
Yongxiang Chen: College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China
Huan Huang: Business School, Chengdu University of Technology, Chengdu 610059, China

Land, 2025, vol. 14, issue 6, 1-24

Abstract: Understanding the spatiotemporal dynamics of resource–environment carrying capacity (RECC) is essential for balancing ecological protection and socioeconomic development in river basins. This study applied various methodologies, including Panel Vector Autoregression (PVAR), Geographically Temporally Weighted Regression (GTWR), and Random Forest, to analyze in the Yellow River Basin from 2011 to 2021. PVAR quantifies dynamic interactions among RECC subsystems (population, resources, environment, and economy), while Random Forest identifies nonlinear drivers, and GTWR captures spatiotemporal heterogeneity. Results show RECC performance has continually improved, while subsystem and regional differences have been observed. Downstream regions exhibit higher RECC due to advanced infrastructure, whereas upstream areas face ecological constraints. PVAR results reveal bidirectional relationship among population, resource and economy subsystems, with unidirectional environmental pressure from economic activities. In terms of influencing factors analysis, which are classified into three sections, including geography, socioeconomic, and technological innovation. The random forest model identified that the economic development level has higher importance. The GTWR results expanded the spatiotemporal heterogeneity analysis: socioeconomic factors show significant regional variation. These findings provide a transferable paradigm for complex human–environment system analysis, offering policy-responsive zoning strategies that balance SDG implementation with basin-specific ecological constraints.

Keywords: resource–environment carrying capacity; PVAR; random forest regression; GTWR; Yellow River Basin (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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