Spatiotemporal distribution and driving factors of water use efficiency in the Yangtze River Delta urban agglomeration under the background of sustainability

IF 7 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Ecological Indicators Pub Date : 2025-09-04 DOI:10.1016/j.ecolind.2025.114159

Liang Tang , Hengkai Zhao , Zhuofan Zhou , Zixi Qian , Shanshan Hou , Bo Liu

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Abstract

As a key economic strategic region in China, the Yangtze River Delta urban agglomeration plays a crucial role in national sustainable development. Exploring the spatiotemporal distribution and influencing factors of water use efficiency (WUE) in this region is of great significance for promoting sustainable water resource utilization. This study employs a comprehensive methodological framework, including the Super-SBM model with undesirable outputs, Moran’s I, Gini coefficient, convergence analysis, geographic detector, and Tobit regression model, to investigate the spatiotemporal characteristics and driving factors of WUE in the Yangtze River Delta (YRD). The results reveal that: (1) The overall trend of WUE in the region follows a “U-shaped” pattern, first declining and then rising, with a spatial hierarchy of Jiangsu (0.737) > Shanghai (0.662) > Anhui (0.631) > Zhejiang (0.608). The difference in hypervariable density is identified as the primary source of regional disparities in WUE. (2) Convergence analysis indicates a significant spatial β-convergence of WUE across cities in the region, suggesting that cities with relatively lower efficiency are gradually narrowing the gap with those performing at higher levels. This is consistent with the findings derived from the Gini coefficient. (3) Economic development and technological innovation significantly promote WUE, while factors such as industrial structure, water resource endowment, waterway transportation, urbanization level, and per capita water consumption exert negative impacts. Moreover, the interaction effects among these factors demonstrate a stronger driving influence on WUE than any single factor alone. The findings of this study not only deepen the understanding of WUE dynamics but also provide valuable insights for formulating strategies to enhance water resource efficiency both in the YRD and across China.

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可持续发展背景下长三角城市群水资源利用效率时空分布及驱动因素分析

长三角城市群作为中国重要的经济战略区域，在国家可持续发展中起着至关重要的作用。研究该地区水资源利用效率的时空分布特征及其影响因素，对促进水资源的可持续利用具有重要意义。本研究采用带不良产出的Super-SBM模型、Moran’s I、基尼系数、收敛分析、地理探测器和Tobit回归模型等综合方法框架，探讨长三角地区水资源利用效率的时空特征及其驱动因素。结果表明：①区域水资源利用效率总体呈先降后升的“u”型格局，空间层次为江苏（0.737）、上海（0.662）、安徽（0.631）、浙江（0.608）；高变密度的差异被认为是WUE区域差异的主要来源。(2)收敛性分析表明，区域城市用水效率存在显著的空间β-收敛性，表明效率相对较低的城市与效率较高的城市之间的差距正在逐渐缩小。这与从基尼系数得出的结论是一致的。(3)经济发展和技术创新对用水效率有显著促进作用，而产业结构、水资源禀赋、水路运输、城市化水平和人均用水量等因素对用水效率有负向影响。此外，这些因素之间的相互作用对WUE的驱动作用比任何单一因素都更强。本研究结果不仅加深了对水资源利用动态的理解，而且为制定提高长三角和中国水资源效率的战略提供了有价值的见解。

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来源期刊

Ecological Indicators 环境科学-环境科学

CiteScore

11.80

自引率

8.70%

发文量

1163

审稿时长

78 days

期刊介绍： The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.