A novel approach for quantifying water resource spatial equilibrium based on the regional evaluation, spatiotemporal heterogeneity and geodetector analysis integrated model

人均 城市化 资源(消歧) 空间异质性 可持续发展 中国 驱动因素 索引(排版) 水资源 环境资源管理 基尼系数 环境科学 大洪水 自然资源经济学 地理 计算机科学 经济 生态学 经济增长 人口 经济不平等 人口学 考古 社会学 万维网 数学分析 生物 不平等 数学 计算机网络
作者
Yu Lu,Xiaohua Yang,Dehui Bian,Yajing Chen,Yan Li,Zixing Yuan,Kaiwen Wang
出处
期刊:Journal of Cleaner Production [Elsevier BV]
卷期号:424: 138791-138791 被引量:33
标识
DOI:10.1016/j.jclepro.2023.138791
摘要

The distribution focuses of water resources, socio-economic development and environmental maintenance are usually mismatched, leading a gap between regional resources and the environment, as well as the disharmony of development. Water resource spatial equilibrium (WRSE) is an important yardstick for guiding regional water resource planning and sustainable utilization. However, research on the spatiotemporal heterogeneity and driving factors of WRSE is extremely lacking, and few existing studies have considered drought and flood disasters as the important reflection of WRSE. Therefore, this paper proposes a systematic integrated model for WRSE including regional evaluation, spatiotemporal heterogeneity and geodetector analysis functions, and constructs the evaluation index system considering droughts and floods. First, the performance of WRSE is quantified using the general deprivation index (GDI) innovatively. Then, combined with the Moran's I, the spatial patterns and regional differences of WRSE are analyzed. Last, the geographical detector models are employed to perform driving analysis of WRSE. The effectiveness of the model is verified in China. Results show that (1) from 2009 to 2021, the national average of WRSEI exhibits a declining trend from 0.879 in 2009 to 0.789 in 2021. (2) The areas with high WRSEI values are mainly distributed in the western provinces, whereas the eastern region has a higher percentage of imbalanced provinces. (3) Water resources per capita, added value of tertiary industry, urbanization rate and GDP per capita are key driving factors of China’ WRSE. The study provides a novel insight for WRSE improvement and is greatly helpful for developing differentiated management measures to optimize resource allocation.
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