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基于 WF-GTWR 模型的中国农业用水绿色效率的演进趋势、区域差异及影响因素。

Evolutionary Trends, Regional Differences and Influencing Factors of the Green Efficiency of Agricultural Water Use in China Based on WF-GTWR Model.

机构信息

College of Economics and Management, Northwest A & F University, Yangling 712100, China.

出版信息

Int J Environ Res Public Health. 2023 Jan 20;20(3):1946. doi: 10.3390/ijerph20031946.

DOI:10.3390/ijerph20031946
PMID:36767309
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9914811/
Abstract

Improving the green efficiency of agricultural water use is a key way to promote the sustainable utilization of agricultural water resources and sustainable development of economy and society. This work calculated and analyzed the evolution trend, regional differences and driving factors of the green efficiency of agricultural water use in China from the perspective of the water footprint. The results show that the green efficiency of agricultural water use in China shows a fluctuation trend of first declining and then rising from 1997 to 2020, after which the average efficiency dropped from 0.538 in 1997 to 0.406 in 2009, and then rose rapidly to 0.989 in 2020, with an average annual growth rate of about 3.6%. From a regional perspective, the green efficiency of agricultural water use in the eastern region was the highest (0.594), above the national average (0.538), followed by the western region (0.522), with the central region in last (0.491), with significant regional differences. The spatial differences in the green efficiency of available agricultural water in China shows a fluctuating downward trend. The Gini coefficient fluctuated from 0.271 in 1997 to 0.182 in 2020, with an average annual growth rate of about -1.4%. The main source of this regional difference was super-variable density, followed by the difference between the eastern and the central regions. The influence of urbanization level, water-saving level and agricultural trade on the green efficiency of agricultural water use was always positive and the influence of industrialization level was always negative; among them, the urbanization level, water-saving level and industrialization level had a greater impact on Northeast China, and agricultural trade had a greater impact on Southeast China. Therefore, this work puts forward relevant policy recommendations.

摘要

提高农业用水绿色效率是促进农业水资源可持续利用和经济社会可持续发展的关键途径。本工作从水足迹的角度计算和分析了 1997 年至 2020 年中国农业用水绿色效率的演变趋势、区域差异和驱动因素。结果表明,中国农业用水绿色效率呈先降后升的波动趋势,1997 年平均效率从 0.538 降至 2009 年的 0.406,随后迅速上升至 2020 年的 0.989,年均增长率约为 3.6%。从区域来看,东部地区农业用水绿色效率最高(0.594),高于全国平均水平(0.538),其次是西部地区(0.522),中部地区最低(0.491),区域差异显著。中国有效农业用水绿色效率的空间差异呈波动下降趋势。基尼系数从 1997 年的 0.271 波动下降至 2020 年的 0.182,年均增长率约为-1.4%。区域差异的主要来源是超变密度,其次是东部和中部地区的差异。城镇化水平、节水水平和农业贸易对农业用水绿色效率的影响始终为正,工业化水平的影响始终为负;其中,城镇化水平、节水水平和工业化水平对东北地区的影响较大,农业贸易对东南地区的影响较大。因此,本工作提出了相关政策建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/dd759932e09e/ijerph-20-01946-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/526e2181cb4d/ijerph-20-01946-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/133b434686c2/ijerph-20-01946-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/1b6af51b00dd/ijerph-20-01946-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/e5f829304b6a/ijerph-20-01946-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/481394d856b8/ijerph-20-01946-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/699766c3ff6a/ijerph-20-01946-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/dd759932e09e/ijerph-20-01946-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/526e2181cb4d/ijerph-20-01946-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/133b434686c2/ijerph-20-01946-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/1b6af51b00dd/ijerph-20-01946-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/e5f829304b6a/ijerph-20-01946-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/481394d856b8/ijerph-20-01946-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/699766c3ff6a/ijerph-20-01946-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/735e/9914811/dd759932e09e/ijerph-20-01946-g007.jpg

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