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评价跨界流域不同调水量的社会经济影响的系统动力学模型——以新疆为例。

System Dynamics Model for Evaluating Socio-Economic Impacts of Different Water Diversion Quantity from Transboundary River Basins-A Case Study of Xinjiang.

机构信息

Business School, Hohai University, Nanjing 211100, China.

National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Nanjing 210098, China.

出版信息

Int J Environ Res Public Health. 2020 Dec 5;17(23):9091. doi: 10.3390/ijerph17239091.

DOI:10.3390/ijerph17239091
PMID:33291432
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7730606/
Abstract

With the rapid development of social economy and global climate warming, scarce transboundary water resources, as one of the basic resources for socio-economic development, have increasingly become the focus of basin countries. To investigate the socio-economic impacts of different water diversion quantity from transboundary river basins, we used a system dynamics (SD) model to reflect interactions between population, water resources, and socio-economic development, and applied it to a case study in Xinjiang to simulate its change tendency from 2011 to 2030 from the temporal dimension. Then, four water diversion quantity of transboundary river basins and four alternative socio-economic development patterns were designed to comprehensively evaluate these impacts of water diversion quantity change on the socio-economy of the region along the river under different socio-economic development patterns. The results indicate that (1) there was a positive correlation between water diversion quantity and the economic output value of the region along transboundary river basins, and the marginal benefit of transboundary water resources would decrease gradually; (2) considering the difficulty of water diversion from transboundary river basins and the protection of downstream water use and ecological health of transboundary river basins, we believe that increasing the transboundary water resources by 20% was more conducive to the sustainable development of Xinjiang's socio-economy; (3) through the comparison of dynamic evolutions of socio-economic development and water impacts under four socio-economic development patterns, it is best for Xinjiang to plan its future development in the coordinated development of economic-resource scenario. Following this scenario, not only would the total output value of the socio-economy be better than other scenarios, but this also helps to alleviate the contradiction between the water supply and demand, which expected there would be a water shortage of 1.04 billion m in 2029 under 20% increase in water diversion quantity. Therefore, appropriate water diversion quantity, reasonable adjustment of industrial production growth rate, reduction of water consumption quotas of different industries and domestic water quota, and improvement of collection and treatment rate for sewage should be given priority in water resources management decision-making in Xinjiang or other arid regions along transboundary river basins.

摘要

随着社会经济的快速发展和全球气候变暖,跨界水资源作为社会经济发展的基本资源之一,日益成为流域国家关注的焦点。为了研究不同跨界河流调水量对社会经济的影响,我们采用系统动力学(SD)模型来反映人口、水资源和社会经济发展之间的相互作用,并将其应用于新疆的案例研究,从时间维度上模拟其 2011 年至 2030 年的变化趋势。然后,设计了四个跨界河流调水量和四个替代社会经济发展模式,以综合评估在不同社会经济发展模式下,调水量变化对流域沿线地区社会经济的影响。结果表明:(1)调水量与流域沿线地区经济产值呈正相关,跨界水资源的边际效益将逐渐降低;(2)考虑到跨界河流调水的难度以及保护下游流域的用水和生态健康,我们认为增加 20%的跨界水资源更有利于新疆社会经济的可持续发展;(3)通过比较四个社会经济发展模式下社会经济发展和水影响的动态演变,对于新疆来说,最好在经济-资源协调发展的情景下规划未来发展。在这种情景下,不仅社会经济的总产值会更好,而且有助于缓解供需矛盾,预计在调水量增加 20%的情况下,2029 年将出现 10.4 亿立方米的缺水。因此,在水资源管理决策中,应优先考虑适当的调水量、合理调整产业生产增长率、降低不同行业的用水量定额和居民生活用水量定额以及提高污水收集处理率,这在新疆或其他跨界河流流域干旱地区尤为重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/67558e6dca3e/ijerph-17-09091-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/8044317d203d/ijerph-17-09091-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/eb8740b3219d/ijerph-17-09091-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/44fd71f5602d/ijerph-17-09091-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/82cd8a517eac/ijerph-17-09091-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/77fc32ed50ce/ijerph-17-09091-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/d93061ef8607/ijerph-17-09091-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/ebf042a90ae9/ijerph-17-09091-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/2ed237b7f383/ijerph-17-09091-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/54051822721b/ijerph-17-09091-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/67558e6dca3e/ijerph-17-09091-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/8044317d203d/ijerph-17-09091-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/eb8740b3219d/ijerph-17-09091-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/44fd71f5602d/ijerph-17-09091-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/82cd8a517eac/ijerph-17-09091-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/77fc32ed50ce/ijerph-17-09091-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/d93061ef8607/ijerph-17-09091-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/ebf042a90ae9/ijerph-17-09091-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/2ed237b7f383/ijerph-17-09091-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/54051822721b/ijerph-17-09091-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1301/7730606/67558e6dca3e/ijerph-17-09091-g010.jpg

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