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区域粮食虚拟水流动经济社会影响效应分析
引用本文:佟佳骏,孙世坤,马佳乐,阴亚丽,王玉宝,沈欣,许纪元. 区域粮食虚拟水流动经济社会影响效应分析[J]. 农业机械学报, 2024, 55(7): 345-356,385
作者姓名:佟佳骏  孙世坤  马佳乐  阴亚丽  王玉宝  沈欣  许纪元
作者单位:西北农林科技大学;全国农业技术推广服务中心
基金项目:国家自然科学基金项目(51979230、52122903)、博士后创新人才支持计划项目(BX20220255)和博士后科学基金面上项目(2022M712605)
摘    要:虚拟水流动是水资源在空间上再分配的一种重要表现形式,作为虚拟水的载体,粮食贸易运输过程中伴随着虚拟水的流动。中国人口和资源与粮食生产呈现明显的空间错位,虚拟水流动格局、水土资源分布、经济社会发展情况的空间匹配度较差。在现阶段虚拟水-实体水耦合分析探究粮食虚拟水流动资源环境效应的基础上,增添其对经济社会的影响效应分析,可以进一步优化资源调配,促进区域可持续发展。本研究以中国大陆31省份为研究区,以省级行政区划为研究单元,分析了1997—2021年间粮食虚拟水流动的时空演变格局;通过空间聚类分析以及虚拟水-经济社会化数据耦合分析明确了粮食虚拟水调运的空间聚类情况,解析了主要输入和输出省份粮食虚拟水的调运量与经济社会发展的相关关系;选取9个主要经济社会影响因子,将灰色关联度和集对分析方法结合探讨了经济社会影响因子对粮食虚拟水流动影响效应的空间差异。结果表明:粮食虚拟水流动总体呈现从“缺水”的北方流向“富水”的东南区域,从经济欠发达地区流向经济发达地区的趋势,且经济社会系统在一定程度上影响了粮食虚拟水的流动。根据经济社会因子对不同省份粮食虚拟水流动的影响效应,将各省份粮食虚拟水流动的经济社会关联类型划分为产业关联型、社会关联型和资源关联型。综上,促进区域间协调发展与产业结构优化将是解决我国粮食虚拟水流动伴生的自然环境与经济社会负反馈效应的重要解决途径。

关 键 词:粮食虚拟水流动  区域社会经济差异  灰色关联度分析  集对分析  影响效应分析
收稿时间:2023-11-05

Analysis of Socio-economic Driving Effect of Regional Grain Virtual Water Flow
TONG Jiajun,SUN Shikun,MA Jiale,YIN Yali,WANG Yubao,SHEN Xin,XU Jiyuan. Analysis of Socio-economic Driving Effect of Regional Grain Virtual Water Flow[J]. Transactions of the Chinese Society for Agricultural Machinery, 2024, 55(7): 345-356,385
Authors:TONG Jiajun  SUN Shikun  MA Jiale  YIN Yali  WANG Yubao  SHEN Xin  XU Jiyuan
Affiliation:Northwest A&F University;National Agro-Tech Extension and Service Center
Abstract:Virtual water flow is an important manifestation of spatial redistribution of water resources. As a carrier of virtual water, grain trade and transportation involve virtual water flow. China’s population and resources show obvious spatial dislocation with food production, and the spatial matching degree of virtual water flow pattern, distribution of land and water resources, and economic and social development is poor. Based on exploring the resource and environment effect of virtual water flow in the current stage, adding the impact effect analysis on economy and society can further optimize resource allocation and promote regional sustainable development. The spatiotemporal evolution pattern of virtual water flow in 31 provinces of China from 1997 to 2021 was analyzed. Spacetime clustering analysis and coupled analysis of virtual water-economic and social data clarified the existence of significant spatial clustering of grain virtual water transportation. The amount of virtual water transportation in the main input and output provinces of food virtual water showed a significant positive correlation with the economic and social development level. Based on this background, totally nine major economic and social impact factors were selected and their spatial differences in influencing food virtual water flow were explored. The types of impact effect on food virtual water flow in 31 provinces of China were classified into industrial correlation type, social correlation type, and resource correlation type. Relevant regulatory strategies were proposed according to the economic development level, natural resource endowment, and industrial structure development of each province to weaken or even avoid the negative impact of virtual water flow on the regional economic and social development and natural environment. The results showed that the overall virtual water flow presented a trend of flowing from “deficient” northern regions to “rich” southern regions, and from economic backward areas to economic developed areas. The economic and social system to some extent influenced the virtual water flow. According to the impact effect of economic and social factors on food virtual water flow in different provinces, the industrial, social, and resource correlation types of food virtual water flow in each province were classified into industrial correlation type, social correlation type, and resource correlation type. In summary, promoting regional coordinated development and optimizing industrial structure would be an important solution to address the negative feedback effects of food virtual water flow in China caused by environmental and economic factors.
Keywords:grain virtual water flow  regional socio-economic differences  grey correlation analysis  set pair analysis  influence effect analysis
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