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基于水资源稀缺价值分析的水权交易价格动态调整模型。

Dynamic Adjustment Model of the Water Rights Trading Price Based on Water Resource Scarcity Value Analysis.

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. 2021 Feb 25;18(5):2281. doi: 10.3390/ijerph18052281.

DOI:10.3390/ijerph18052281
PMID:33669014
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7967718/
Abstract

The formation of the water rights trading price is an important part of the water rights trading system. In order to continuously and dynamically reflect the social-economic development changes and water resource scarcity, herein, we discuss the dynamic adjustment of the water rights trading price from the perspective of water resource scarcity value analysis. First, we constructed the water resource scarcity evaluation index system from the four dimensions of the water resource natural endowment, the water resource supply, the water resource demand, and the water environment, and then we constructed the water resource scarcity index calculation model of the transferor, the transferee, and the comprehensive water resource scarcity index calculation model of both parties of the trading. Second, by analyzing the 30 comparable water rights trading cases in China since 2016, we established the response function of the water rights trading price to the water resource scarcity index, and then we analyzed the impact mechanism of the water resource scarcity index on the water rights trading price. Third, based on the two factors of "the water resource scarcity value" and "the capital time value," we constructed a dynamic price adjustment model of water rights trading for different adjustment factors, so as to adjust the water rights trading price scientifically. Finally, we took the water rights trading in Helan County (Helan) of Ningxia Hui Autonomous Region (Ningxia) as an example. The research shows that: (1) During the trading period of water rights in Helan, the water resource scarcity index rises, and the water rights trading price should be increased year-by-year. Additionally, there are certain differences in the water rights trading price changes with the adjustment of different elements. Among them, considering the adjustment of "the water resource scarcity value" element, the water rights trading price of Helan should be increased from 1.0940 to 2.8574 CNY/m³ during the water rights trading period; (2) there are differences in the water rights trading cost under different payment modes, among which the annual payment mode increased the most, i.e., from 2.7350 × 10 to 7.4500 × 10 CNY. This study suggests exerting a regulating effect of the water scarcity value on the water rights trading price, so as to promote the construction of a more equitable and long-term water rights trading market.

摘要

水权交易价格的形成是水权交易制度的重要组成部分。为了不断动态地反映社会经济发展变化和水资源稀缺性,本文从水资源稀缺价值分析的角度探讨水权交易价格的动态调整。首先,从水资源自然禀赋、水资源供给、水资源需求和水环境四个维度构建了水资源稀缺评价指标体系,然后构建了转让方、受让方的水资源稀缺指数计算模型和双方综合水资源稀缺指数计算模型。其次,通过分析中国 2016 年以来的 30 个可比水权交易案例,建立了水权交易价格对水资源稀缺指数的响应函数,并分析了水资源稀缺指数对水权交易价格的影响机制。再次,基于“水资源稀缺价值”和“资金时间价值”两个因素,构建了不同调整因素的水权交易动态价格调整模型,从而科学调整水权交易价格。最后,以宁夏回族自治区贺兰县(贺兰)的水权交易为例。研究结果表明:(1)在贺兰水权交易期间,水资源稀缺指数上升,水权交易价格应逐年上涨。此外,不同要素调整下水权交易价格的变化存在一定差异。其中,考虑“水资源稀缺价值”要素调整,贺兰水权交易价格在水权交易期间应从 1.0940 元/m³增加到 2.8574 元/m³;(2)不同支付方式下的水权交易成本存在差异,其中年付方式增加最多,即从 2.7350×10^8 元增加到 7.4500×10^8 元。本研究建议对水权交易价格施加水资源稀缺价值的调节作用,以促进更加公平和长期的水权交易市场建设。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/d75aa9fe9bf7/ijerph-18-02281-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/a649cc9c9ce0/ijerph-18-02281-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/0bf4b063f727/ijerph-18-02281-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/dbc4e24c9623/ijerph-18-02281-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/62ec76cbe90e/ijerph-18-02281-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/f59ad09cef77/ijerph-18-02281-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/d75aa9fe9bf7/ijerph-18-02281-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/a649cc9c9ce0/ijerph-18-02281-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/0bf4b063f727/ijerph-18-02281-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/dbc4e24c9623/ijerph-18-02281-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/62ec76cbe90e/ijerph-18-02281-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/f59ad09cef77/ijerph-18-02281-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5920/7967718/d75aa9fe9bf7/ijerph-18-02281-g006.jpg

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Ecological Vulnerability Assessment Based on Fuzzy Analytical Method and Analytic Hierarchy Process in Yellow River Delta.
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Int J Environ Res Public Health. 2018 Apr 25;15(5):855. doi: 10.3390/ijerph15050855.
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