自然资源学报 ›› 2019, Vol. 34 ›› Issue (5): 934-944.doi: 10.31497/zrzyxb.20190503

• 资源利用与管理 • 上一篇    下一篇

中国水足迹强度空间关联格局及影响因素分析

张凡凡1(), 张启楠2, 李福夺3, 傅汇艺1, 杨兴洪1()   

  1. 1. 贵州大学管理学院,贵阳 550025
    2. 中南林业科技大学经济学院,长沙 410004
    3. 中国农业科学院农业资源与农业区划研究所,北京 100081
  • 收稿日期:2018-09-26 修回日期:2019-02-17 出版日期:2019-05-28 发布日期:2019-05-28
  • 作者简介:

    作者简介:张凡凡(1992- ),女,山西太原人,硕士,研究方向为农业经济理论与政策。E-mail: 805637038@qq.com

  • 基金资助:
    贵州省教育厅硕士点项目(2018ssd04);贵州省教育厅大学生项目(2018dxs03)

The spatial correlation pattern of water footprint intensity and its driving factors in China

Fan-fan ZHANG1(), Qi-nan ZHANG2, Fu-duo LI3, Hui-yi FU1, Xing-hong YANG1()   

  1. 1. School of Management of Guizhou University, Guiyang 550025, China
    2. School of Economics, Central South University of Forestry and Technology, Changsha 410004, China
    3. Institute of Agricultural Resources and Agricultural Zoning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2018-09-26 Revised:2019-02-17 Online:2019-05-28 Published:2019-05-28

摘要:

水资源短缺已成为制约经济社会发展的重要因素,科学审视水资源利用现状、探索水资源可持续发展的有效动力具有重要的理论和现实意义。基于水足迹视角分别测算2006-2015年中国31个省域的水足迹强度,利用探索性空间数据分析(ESDA)对其时空格局演变特征进行解析,考虑到该方法空间描述的粗略性,通过引入时空跃迁测度法进行细化,并借助空间杜宾模型探讨其影响因素。结果表明:中国水足迹强度空间集聚效应显著且具有跃迁性,但主要以类型Ⅵ为主,其空间结构具有一定的路径依赖特征;人口数量仍然是当前中国水足迹强度的一个主要驱动因子,而城镇化率和对外开放程度则对降低水足迹强度起积极作用;中国水足迹强度存在“倒N型”的Kuznets曲线,且大部分省份水足迹强度处于第一个拐点与第二个拐点之间,北京、天津、上海等区域已越过第二个拐点,处于水足迹强度下降阶段,而部分西部欠发达地区仍未跨越第一个拐点。

关键词: 水足迹强度, 探索性空间数据分析, 时空跃迁测度法, 空间杜宾模型

Abstract:

Shortage of water resources has become an important factor that restricts economic and social development. It is of great theoretical and practical significance to examine the current situation of water resources utilization and explore the effective driving force for sustainable development of water resources. Based on the water footprint perspective, this paper calculates the water footprint intensity of 31 provinces in China from 2006 to 2015 respectively. The spatial data analysis (ESDA) is used to examine the evolution of space-time pattern. Considering the rough nature of the spatial description of the method, the spatial Dubin model is introduced to refine and with the help of the model, we analyse the influencing factors. The result shows that the spatial agglomeration effect of water footprint intensity in China is significant and with transition, however, it is mainly based on type VI, and its spatial structure has a certain path dependence. Currently, population quantity is still a major driving factor of water footprint intensity in China, while the urbanization rate and the degree of opening to the outside world play an active role in reducing the water footprint strength. There is an "inverted N" Kuznets curve in China's water footprint intensity In most provinces, the intensity of water footprint is between the first and second inflection points. Beijing, Tianjin, and Shanghai have crossed the second inflection points, and they are in the stage of the decline of footprint intensity, while some of the underdeveloped areas in the western region have not crossed the first turning point.

Key words: water footprint intensity, exploratory spatial data analysis, space-time transition measure method, spatial Dubin model