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

Area of Science:

• Environmental Science
• Water Resource Management
• Regional Planning

Background:

• Regional water resources carrying capacity (WRCC) is crucial for addressing water scarcity and informing water management policies.
• Analyzing spatial disparities and driving factors of WRCC is essential for implementing effective water control strategies like 'spatial balance'.

Purpose of the Study:

• To develop and apply an integrated model for evaluating regional WRCC and diagnosing its spatial differences and key driving factors.
• To provide a robust framework for enhancing the comparability and analytical depth of WRCC assessments.

Main Methods:

• Evaluation indicators selected from water resources, socio-economic, and environmental aspects.
• Indicator weights determined using fuzzy analytic hierarchy process with accelerated genetic algorithm (FAHP-AGA).
• WRCC evaluation and spatial difference analysis performed using set pair analysis (SPA).

Main Results:

• Anhui Province's WRCC showed an increasing trend from 2011 to 2020, with average city increases exceeding 0.3.
• Spatial disparities in WRCC diminished, evidenced by a decrease in the Gini coefficient from 0.16 to 0.08.
• Identified key drivers of spatial WRCC differences: water module, water use efficiency (per 10,000 yuan GDP), water use structure equilibrium, per capita GDP, population density, forest cover, and fertilizer application.

Conclusions:

• The developed FAHP-AGA-SPA model offers improved comparability and multi-factor interaction analysis for WRCC evaluation.
• Findings provide critical insights for formulating regional WRCC regulations and implementing the 'spatial equilibrium' water management policy.
• The study highlights the interplay of hydrological, economic, and environmental factors in shaping regional water resource capacity.