Spatial difference analysis and driving factor diagnosis for regional water resources carrying capacity based on set pair analysis

Rongxing Zhou; Juliang Jin; Yuliang Zhou; Yi Cui; Chengguo Wu; Yuliang Zhang; Ping Zhou

Heliyon (Oct 2024)

Spatial difference analysis and driving factor diagnosis for regional water resources carrying capacity based on set pair analysis

Rongxing Zhou,
Juliang Jin,
Yuliang Zhou,
Yi Cui,
Chengguo Wu,
Yuliang Zhang,
Ping Zhou

Affiliations

Rongxing Zhou: School of Environment and Energy Engineering, Anhui Jianzhu University, Hefei, 230601, China; School of Civil Engineering, Hefei University of Technology, Hefei, 230009, China
Juliang Jin: School of Civil Engineering, Hefei University of Technology, Hefei, 230009, China
Yuliang Zhou: School of Civil Engineering, Hefei University of Technology, Hefei, 230009, China
Yi Cui: School of Civil Engineering, Hefei University of Technology, Hefei, 230009, China; Corresponding author. School of Civil Engineering, Hefei University of Technology, Hefei 230009, China.
Chengguo Wu: School of Civil Engineering, Hefei University of Technology, Hefei, 230009, China
Yuliang Zhang: School of Civil Engineering, Hefei University of Technology, Hefei, 230009, China
Ping Zhou: School of Civil Engineering, Hefei University of Technology, Hefei, 230009, China

Journal volume & issue: Vol. 10, no. 20
p. e38251

Abstract

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Studying regional water resources carrying capacity (WRCC) is an important way to find out and solve regional water resources problems. Analyzing the spatial difference of WRCC and diagnosing its driving factors is the basis for the implementation of the water control policy named “spatial balance”. This study selects evaluation indicators for WRCC from three aspects: water resources, social economy, and ecological environment. The weights of indicators were determined by fuzzy analytic hierarchy process based on accelerated genetic algorithm (FAHP-AGA), and an evaluation method for WRCC was constructed based on set pair analysis (SPA). On this basis, the spatial difference analysis of regional WRCC and its key driving factor diagnosis model was established, and the empirical study was carried out in Anhui Province as an example. The results show that from 2011 to 2020, the WRCC of Anhui Province was increasing, with the average increase of each city reaching more than 0.3. The spatial difference of WRCC decreased, and the Gini coefficient decreased from 0.16 to 0.08. The key driving factors leading to the spatial difference of WRCC in Anhui Province include water resources module, water consumption per 10,000 yuan of GDP, equilibrium degree of water use structure, per capita GDP, population density, percentage of forest cover, and amount of chemical fertilizer applied per unit of effective irrigated area. Compared with common WRCC evaluation models, this model improves the comparability of the evaluation results. In addition, this model can further analyze the influence of multiple factor interactions on the evaluation results based on the common single factor analysis. The driving factor diagnosis results can provide theoretical guidance for the formulation of regulation measures for regional WRCC and the implementation of the “spatial equilibrium” water control policy.

Published in Heliyon

ISSN: 2405-8440 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Science: Science (General); Social Sciences: Social sciences (General)
Website: https://www.cell.com/heliyon/home

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