Factors Influencing Water Resource Levels Under the Water Resource Carrying Capacity Framework: A Dynamic Qualitative Comparative Analysis Based on Provincial Panel Data

被引:0
作者
Li, Zehua [1 ,2 ]
Wu, Yanfeng [3 ]
Li, Zhijun [1 ,2 ]
Zhang, Wenguang [3 ]
Yuan, Yuxiang [3 ]
机构
[1] Heilongjiang Univ, Sch Hydraul & Elect Power, Harbin 150080, Peoples R China
[2] Heilongjiang Univ, Cold Reg Groundwater Res Inst, Harbin 150080, Peoples R China
[3] Chinese Acad Sci, Northeast Inst Geog & Agroecol, State Key Lab Black Soils Conservat & Utilizat, Harbin 100045, Peoples R China
关键词
water resource carrying capacity; subsystem interaction; dynamic qualitative comparative analysis; Yangtze River Economic Belt; ECOLOGICAL FOOTPRINT; SYSTEM DYNAMICS; CLIMATE-CHANGE; LAND-USE; DISCRIMINATION; METHODOLOGIES; ECOSYSTEM; IMPACTS; REGION; ENERGY;
D O I
10.3390/w16203006
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Most existing evaluation frameworks for water resource carrying capacity (WRCC) neglect the interdependencies between subsystems. To fill this gap, we introduce a dynamic qualitative comparative analysis (QCA) model to evaluate WRCC and apply it to a vital economic development corridor, the Yangtze River Economic Belt (YREB). Ecological, social, and economic subsystems are defined as condition subsystems, while the water resource subsystem is defined as the outcome subsystem. The entropy weight method is used to calculate and calibrate the comprehensive score of each subsystem. By analyzing the necessity of a single condition subsystem and the sufficiency of condition subsystem configuration via a dynamic QCA, we qualitatively analyze the impact extent and pathways of the ecological, social, and economic subsystems on the water resource subsystem within the WRCC framework. The results reveal generally stable water resource levels despite regional variances, thereby pinpointing the influence pathways, including ecological-social and ecological-economic configurations. The 2011-2015 period saw poor stability, which subsequently improved until 2019 before declining in 2020 in the YREB. The middle-reach urban cluster showed the highest stability, which was less impacted by condition subsystems. These findings could enable provinces and municipalities to tailor policies and enhance subsystem levels for better water resource management.
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