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Analysis Of Virtual Water Flow Driving Mechanism And Risk Assessment

Posted on:2022-03-20Degree:MasterType:Thesis
Country:ChinaCandidate:Y D ZhangFull Text:PDF
GTID:2492306494952389Subject:Physical geography
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Virtual water trade and virtual water strategy theory provide theoretical guidance for water-scarce countries or regions to ensure water resources and food security.Due to the spontaneity of trade and the flow of resources,China’s virtual water flows from the water-poor northern areas to the water-rich southern areas.With the export of a large number of virtual water resources,it not only intensified the pressure on regional water resources and the ecological environment,but also caused huge obstacles to economic development,which in turn affected the food security of the input area and caused two-way risks in virtual water trade.This paper selection of virtual water flow impact indicators from six aspects of nature,ecology,environment,society,economy and water use,use entropy method and K-means clustering to classify China’s main grain virtual water flow drive types.Select typical representative regions of each driving type as the research object,and combined with the PLS structural equation model to construct a research framework of virtual water flow driving mechanism,to deeply analyze the complex driving mechanism of virtual water flow.And then based on the research of virtual water flow driving mechanism,combined with Bayesian network to evaluate and analyze the virtual water flow risk in typical areas,and propose relevant adjustment countermeasures for the government and related departments to promote the reasonable flow of virtual water.The main research conclusions are as follows:(1)There are obvious differences in the main influencing factors of virtual water flow in various regions.Based on the measurement results of the weight of each influencing factor,China’s 31 provinces(municipalities and autonomous regions)are divided into four types of virtual water flow: ecological economy,ecological environment,ecological water use,and comprehensive.The typical representative regions of each drive type are Zhejiang,Heilongjiang,Xinjiang and Shanghai.(2)Among them,social factors directly affect the virtual water flow in the 4 types of areas,and the virtual water flow has a direct impact on the nature,environment,and economy of the4 types of areas.At the same time,the virtual water flow in the ecological economy,ecological water use and comprehensive typical areas has an economic impact water consumption,and only water consumption in ecological environment-based areas has a direct impact on virtual water flow.(3)The direct risk impact of virtual water flow on the three typical regions of Zhejiang,Heilongjiang,and Xinjiang is represented by environment>nature>economy,and the direct risk impact on Shanghai is represented by nature>environment>economy.The direct risk impact of virtual water flow on nature is represented as Xinjiang>Heilongjiang>Shanghai>Zhejiang,the direct risk impact on the environment is represented by Xinjiang>Heilongjiang>Zhejiang>Shanghai,and the direct risk impact on the economy is represented by Xinjiang/Zhejiang/ Shanghai> Heilongjiang.In addition,the indirect risk impact caused by virtual water flow on water use is Xinjiang>Zhejiang>Shanghai,and the indirect risk impact on ecology is Xinjiang>Heilongjiang>Shanghai.Combining the research results of the virtual water flow driving mechanism and the risk assessment,this article from the social,water,nature,environment,and economic aspects,put forward relevant adjustment countermeasures and suggestions for the government and related departments to promote the reasonable flow of virtual water,so as to realize that the virtual water flow theory can maintain the national agricultural water resources security,promote social stability and sustainable development provide a theoretical basis,and provide regional support for agricultural water resources security research.
Keywords/Search Tags:virtual water, driving mechanism, risk assessment, PLS structural equation, bayesian network
PDF Full Text Request
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