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在缺水地区的水利用效率的演变和驱动因素:以中国黄河Ω形地区为例。

Evolution and the drivers of water use efficiency in the water-deficient regions: a case study on Ω-shaped Region along the Yellow River, China.

机构信息

Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.

University of Chinese Academy of Sciences, Beijing, 100149, China.

出版信息

Environ Sci Pollut Res Int. 2022 Mar;29(13):19324-19336. doi: 10.1007/s11356-021-16969-7. Epub 2021 Oct 29.

Abstract

Enhancement of water use efficiency (WUE) is considered highly important to cope with the water scarcity challenges in dry regions. Therefore, this study evaluated spatiotemporal characteristics of WUE and its related drivers in the Ω-shaped Region along the Yellow River aiming to provide decision support information for alleviating water shortages in this region. We employed the SBM-DEA (slacks-based measure-data envelopment analysis) model to calculate the WUE considering undesired outputs, analyze temporal and spatial variation based on GIS and statistical methods, and investigate the various factors that influence WUE based on the generalized method of moment (GMM) model. The results are as follows. (1) The WUE followed an increasing-decreasing-increasing trend, suggesting that the expanding agricultural and the second industrial structures are largely dominated by water-intensive activities which add further pressure on the water resources. (2) The spatial discrepancy of WUE among the cities is significant; however, the spatial pattern changes were stable during 2010 to 2019. (3) Analysis of influencing factors provides solutions for improving WUE in the Ω-shaped Region. Irrigation system and water conservancy infrastructure development and the acceleration of industrial transformation are necessary for improving the WUE in the Ω-shaped Region.

摘要

提高水利用效率(WUE)被认为是应对干旱地区水资源短缺挑战的高度重要手段。因此,本研究评估了沿黄河Ω形区域 WUE 的时空特征及其相关驱动因素,旨在为缓解该区域的水资源短缺提供决策支持信息。我们采用 SBM-DEA(基于松弛的测度-数据包络分析)模型来计算考虑非期望产出的 WUE,利用 GIS 和统计方法分析时间和空间变化,并根据广义矩法(GMM)模型研究影响 WUE 的各种因素。结果表明:(1)WUE 呈增加-减少-增加的趋势,表明不断扩张的农业和第二产业结构主要由耗水活动主导,这给水资源带来了更大的压力;(2)城市间 WUE 的空间差异显著,但 2010 年至 2019 年期间空间格局变化稳定;(3)影响因素分析为提高Ω形区域 WUE 提供了解决方案。灌溉系统和水利基础设施的发展以及工业转型的加速对于提高Ω形区域的 WUE 是必要的。

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