中国省级水贫困的测算及空间关联效应

邓光耀; 张鑫

doi:10.13961/j.cnki.stbctb.2024.05.022

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中国省级水贫困的测算及空间关联效应

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- 中国省级水贫困的测算及空间关联效应
- Calculation and Spatial Correlation Effects of Water Poverty in Various Provinces of China
- 水土保持通报 2024年43卷第5期页码：204-213
- 作者机构：
  
  1. 兰州财经大学一带一路经济研究院,甘肃,兰州,730020
  2. 兰州财经大学统计与数据科学学院,甘肃,兰州,730020
- 作者简介：
- 基金信息：
  
  国家自然科学基金地区项目“增加值贸易视角下虚拟水国际贸易的核算、网络特征及影响因素研究”(72363021);甘肃省陇原青年英才项目“增加值贸易视角下中国省级虚拟水贸易网络的特征及影响因素研究”(2022);兰州财经大学丝绸之路经济研究院重点科研项目“黄河流域各省环境效率的空间关联网络特征及其影响因素研究”(JYYZ202102)。
- DOI：10.13961/j.cnki.stbctb.2024.05.022
  中图分类号： F205
- 纸质出版：2024
- 稿件说明：
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邓光耀, 张鑫. 中国省级水贫困的测算及空间关联效应[J]. 水土保持通报, 2024,43(5):204-213.

Deng Guangyao, Zhang Xin. Calculation and Spatial Correlation Effects of Water Poverty in Various Provinces of China[J]. Bulletin of Soiland Water Conservation, 2024, 43(5): 204-213.
邓光耀, 张鑫. 中国省级水贫困的测算及空间关联效应[J]. 水土保持通报, 2024,43(5):204-213. DOI： 10.13961/j.cnki.stbctb.2024.05.022.

Deng Guangyao, Zhang Xin. Calculation and Spatial Correlation Effects of Water Poverty in Various Provinces of China[J]. Bulletin of Soiland Water Conservation, 2024, 43(5): 204-213. DOI： 10.13961/j.cnki.stbctb.2024.05.022.

摘要

[目的] 测度中国各省(市)的水贫困情况，并进行社会网络分析，为缓解中国水贫困窘境提供决策依据。[方法] 采用熵权法和社会网络分析方法，对2010—2021年中国各个省(市)的水贫困程度进行测算并分析其空间关联效应。[结果] ①中国省级水贫困指数在考察期内整体呈上升趋势，水贫困程度逐步下降，但空间非均衡特征也比较明显。②省级水贫困网络整体呈现出显著的空间关联性和复杂的结构形态，所有地区都关联其中，但这种关联性的紧密程度不高。③根据块模型分析结果，北京、天津等5个省(市)被归类为“净受益”板块，湖南、海南等13个省(市)则被归类为“净溢出”板块，广东、重庆等4个城市则被归类为“双向溢出”板块；而内蒙古、黑龙江等9个省(市)则被归类为“经纪人板块”。此外，板块内关系稀疏，板块间联系紧密。④核心边缘密度分析表明，核心地区的数目频繁波动，边缘地区的数目则先增加后减少。[结论] 国家应全面认识水贫困指数的空间关联关系和网络结构特征，制定并推行区域差异化的政策和策略，以协同促发展，充分发挥政府和市场作用，有效改善水贫困窘境，提升水安全保障。

Abstract

[Objective] The water poverty in China’s provinces (cities) was measured and social network analysis was conducted in order to provide a decision-making basis for alleviating China’s water poverty dilemma. [Methods] The entropy weight method and social network analysis were employed to measure and analyze the spatial correlation effects of water poverty in various Chinese provinces (cities) from 2010 to 2021. [Results] ① The water poverty index of Chinese provinces has shown an overall upward trend during the inspection period

and the degree of water poverty has gradually decreased. However

the spatial non-equilibrium characteristics remain quite evident. ② The provincial water poverty network exhibits significant spatial correlation and complex structural forms as a whole

with all regions interconnected; however

the degree of closeness of this correlation is not high. ③ According to the block model analysis results

5 provinces (cities) including Beijing and Tianjin are classified as the “net beneficiary” group

13 provinces (cities) including Hunan and Hainan as the “net spillover” group

4 provinces (cities) including Guangdong and Chongqing as the “two-way spillover” group

and 9 provinces (cities) including Inner Mongolia and Heilongjiang as the “broker” group. In addition

the relationships within the plates are sparse

whereas the connections between the plates are strong. ④ Analysis of the core-edge density shows that the number of core areas fluctuates frequently

while the number of edge areas initially increases and then decreases. [Conclusion] The State should develop a comprehensive understanding of the spatial correlation and network structure characteristics of the Water Poverty Index

formulate and implement regionally differentiated policies and strategies

promote coordinated development

give full play to the roles of the government and market

effectively address the challenges of water poverty

and enhance water security.

关键词

Keywords

references

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