基于DPSIR-TOPSIS模型的青海省生态承载力评价

李小勇; 贾海发; 赵万梅

doi:10.13961/j.cnki.stbctb.2022.02.023

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基于DPSIR-TOPSIS模型的青海省生态承载力评价

试验研究

- 基于DPSIR-TOPSIS模型的青海省生态承载力评价
- Evaluation of Ecological Carrying Capacity in Qinghai Province Based on DPSIR-TOPSIS Model
- 水土保持通报 2022年42卷第2期页码：166-173
- 作者机构：
  
  1. 青海大学土木工程学院,青海,西宁,810016
  2. 青海省建筑节能材料与工程安全重点实验室,青海,西宁,810016
  3. 青海省国土空间规划研究院,青海,西宁,810016
- 作者简介：
- 基金信息：
  
  2021年度青海省哲学社会科学规划一般项目“基于DPSIR模型的青海省生态承载力评价及空间分异研究”(21005)
- DOI：10.13961/j.cnki.stbctb.2022.02.023
  中图分类号： X171.1
- 纸质出版：2022
- 稿件说明：
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李小勇, 贾海发, 赵万梅. 基于DPSIR-TOPSIS模型的青海省生态承载力评价[J]. 水土保持通报, 2022,42(2):166-173.

Li Xiaoyong, Jia Haifa, Zhao Wanmei. Evaluation of Ecological Carrying Capacity in Qinghai Province Based on DPSIR-TOPSIS Model[J]. Bulletin of Soiland Water Conservation, 2022, 42(2): 166-173.
李小勇, 贾海发, 赵万梅. 基于DPSIR-TOPSIS模型的青海省生态承载力评价[J]. 水土保持通报, 2022,42(2):166-173. DOI： 10.13961/j.cnki.stbctb.2022.02.023.

Li Xiaoyong, Jia Haifa, Zhao Wanmei. Evaluation of Ecological Carrying Capacity in Qinghai Province Based on DPSIR-TOPSIS Model[J]. Bulletin of Soiland Water Conservation, 2022, 42(2): 166-173. DOI： 10.13961/j.cnki.stbctb.2022.02.023.

摘要

[目的] 定量测度青海省以及各市州生态承载力，并揭示其时空演变特征，为青海省可持续发展提供科学参考。[方法] 基于DPSIR模型，从驱动力、压力、状态、影响和响应5个方面构建生态承载力评价指标体系，运用熵值法确定指标权重系数，采用TOPSIS模型和障碍度模型，对2008—2019年青海省及其各市州的生态承载力，以及影响因素进行测算与分析。[结果] 从时间维度来看，2008—2019年青海省及各市州的生态承载力呈上升趋势，承载水平明显提升；从空间维度来看，青海省各市州间的生态承载力存在一定的差异性，空间分布大致呈现出“东部两市高于其他地区”的特征；从障碍度来看，2008—2019年青海省生态承载力的主要影响因素整体上经历了社会发展—环境污染—人口压力和经济增速的转变。[结论] 2008—2019年青海省生态承载力显著增强，但生态形势仍然严峻。应积极落实生态保护的各项政策，加快社会经济的发展速度，综合提升各市州生态承载力，从而实现青海省高质量的可持续发展。

Abstract

[Objective] The ecological carrying capacity of Qinghai Province and its cities and prefectures were quantitatively measured to reveal its spatial and temporal evolution characteristics

in order to provide a reference for the sustainable development of Qinghai Province. [Methods] The ecological carrying capacity evaluation index system was constructed using the DPSIR model and considering five factors: driving force

pressure

state

impact

and response. The entropy value method was applied to determine the weight coefficients of the indexes. The TOPSIS model and the obstacle degree model were used to measure and analyze the ecological carrying capacity and the impact factors for Qinghai Province and its cities and prefectures from 2008 to 2019. [Results] Ecological carrying capacity of Qinghai Province and its cities and prefectures increased significantly from 2008 to 2019. Ecological carrying capacity of cities and prefectures in Qinghai Province differed spatially

with the two eastern cities having greater carrying capacity than other regions. The main factors influencing ecological carrying capacity in Qinghai Province from 2008 to 2019 have generally undergone a transformation that follows the pattern of social development-environmental pollution-population pressure and economic growth rate. [Conclusion] The ecological carrying capacity of Qinghai Province has increased significantly during 2008—2019

but the ecological situation remains severe. Policies regarding ecological protection should be actively implemented

the speed of social and economic development should be accelerated

and the ecological carrying capacity of cities and prefectures should be comprehensively improved in order to achieve high-quality sustainable development in Qinghai Province.

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