水资源与经济社会发展时空匹配特征量化分析

Quantitative Analysis of Spatial-Temporal Matching Characteristics Between Water Resources and Economic and Social Development

为系统分析和精准量化地级市水资源与经济社会发展匹配特征,选取水资源总量、用水量和人口、GDP、耕地面积等典型要素,提出同时运用基于基尼系数和基于数列的匹配度计算方法进行量化研究的思路,以沙颍河沿线10个地级市为例,定量分析了其2009—2018年水资源与经济社会发展的时空匹配关系。结果表明:两种方法能够同时从整体时间/空间和单个地级市/时段的角度对水资源和经济社会两系统要素的匹配问题进行全面研究;各地级市时间基尼系数存在些许差异,但不同要素匹配程度基本一致且结果均较好;除水资源总量-GDP、用水量-GDP的时间匹配度呈现低—高—低的演进态势,其他要素的匹配度随时间呈现波动变化趋势;空间基尼系数在时间尺度上变化幅度不大,但不同匹配要素之间差异显著;空间匹配度在时间上基本保持一致,部分地级市匹配结果较差,尤以郑州、南阳和驻马店的问题最为突出。

In order to systematically analyze and accurately quantify the matching characteristics of water resources and economic and social development in prefecture-level cities,typical factors such as total water resources,water consumption,population,GDP and cultivated area were selected in this paper,and a new quantitative research idea that simultaneously applying the calculation methods of matching degree based on Gini coefficient and data sequence was proposed.Taking 10 prefecture-level cities along the Shaying River as examples,this paper quantitatively analyzed the spatial-temporal matching relationship between water resources and economic and social development from 2009 to2018.The results show that the application of the above two methods can comprehensively study the matching issue of the two systems elements from the perspective of the whole time/space and the single city/time.There are some differences in the temporal Gini coefficient among prefecture-level cities,but the matching degree of different elements is basically consistent and the results are all good.Except that the temporal matching degrees of total water resources and GDP,water consumption and GDP present a low-high-low evolution trend,the results of other elements present a fluctuation trend over time.The spatial Gini coefficient varies little on the time scale,while there are significant differences among different matching elements.The spatial matching degree is basically consistent in time and the results of some prefecturelevel cities are poor,especially in Zhengzhou,Nanyang and Zhumadian cities.