Spatial-temporal Pattern Evolution and Driving Factors of Agricultural Grey Water Footprint Efficiency in Yellow River Basin

Guo Wei; Hu Xiwu

doi:10.13961/j.cnki.stbctb.2024.02.043

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Spatial-temporal Pattern Evolution and Driving Factors of Agricultural Grey Water Footprint Efficiency in Yellow River Basin

- Spatial-temporal Pattern Evolution and Driving Factors of Agricultural Grey Water Footprint Efficiency in Yellow River Basin
- Bulletin of Soiland Water Conservation Vol. 44, Issue 2, Pages: 437-445(2024)
- 作者机构：
  
  1. 青海民族大学经济与管理学院,青海,西宁,810007
  2. 天津大学-青海民族大学双碳研究院,青海,西宁,810007
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2024.02.043
  CLC： TV213.4;F323.21
- Published：2024
- 稿件说明：
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Guo Wei, Hu Xiwu. Spatial-temporal Pattern Evolution and Driving Factors of Agricultural Grey Water Footprint Efficiency in Yellow River Basin[J]. Bulletin of Soiland Water Conservation, 2024, 44(2): 437-445.
DOI：

Guo Wei, Hu Xiwu. Spatial-temporal Pattern Evolution and Driving Factors of Agricultural Grey Water Footprint Efficiency in Yellow River Basin[J]. Bulletin of Soiland Water Conservation, 2024, 44(2): 437-445. DOI： 10.13961/j.cnki.stbctb.2024.02.043.

摘要

[目的

]

探讨农业灰水足迹效率时空格局演变与驱动因素，为协同推进农业用水节约集约和水污染综合治理、实现黄河流域农业高质量发展提供科学参考。 [方法

]

以黄河流域9省区为研究对象，利用灰水足迹模型、泰尔指数和对数平均迪氏指数等研究方法对2000—2021年农业灰水足迹效率进行测算，并探讨其时空演变格局和驱动因素。 [结果

]

①2000—2021年黄河流域农业灰水足迹效率呈上升趋势，年均效率为0.235 8元/m

，内蒙古效率最高为0.467 0元/m

，青海效率最低为0.026 3元/m

。 ②农业灰水足迹效率地区内部差距多年平均贡献率为80.11%，上游地区差距年均贡献率为75%，是造成黄河流域农业灰水足迹效率差距较大的主要原因。 ③黄河流域农业灰水足迹效率总效应为正向效应0.202 4元/m

，耕地资源效应和农业环境效应分别是促进和抑制农业灰水足迹效率的主要因素，二者贡献值分别为0.442 7和-0.440 6元/m

。 ④黄河流域农业灰水足迹效率驱动效应可分为4种模式，不同模式地区提升农业灰水足迹效率的方式不同。 [结论

]

黄河流域9省区应采用因地制宜的发展策略，优化农业结构，减少化肥农药的高强度使用，加强农业水环境治理，提升农业灰水足迹效率。

Abstract

[Objective] The spatiotemporal pattern evolution and driving factors of agricultural grey water footprint efficiency were explored in order to provide a scientific reference for promoting agricultural water conservation and comprehensive water pollution control

and high-quality agricultural development in the Yellow River Basin. [Methods] A grey water footprint model

the Theil index

and the log-average Dietscher index were used to estimate the efficiency of agricultural grey water footprint for nine provinces in the Yellow River basin from 2000 to 2021

and the spatial-temporal evolution pattern and driving factors were discussed. [Results] ① The agricultural grey water footprint efficiency during 2000—2021 in the Yellow River basin showed an overall upward trend over time

with an average annual efficiency of 0.235 8 yuan/m3. Inner Mongolia had the highest efficiency (0.467 0 yuan/m3)

and Qinghai had the lowest efficiency (0.026 3 yuan/m3). ② The annual average contribution rate of the regional gap in agricultural grey water footprint efficiency was 80.11%

and the annual contribution rate of the upstream gap was 75%

which was the main reason for the large gap in agricultural grey water footprint efficiency in the Yellow River basin. ③ The total effect of agricultural grey water footprint efficiency was 0.202 4 yuan/m3

and the cultivated land resource effect and agricultural environment effect were the main factors in promoting and inhibiting the agricultural grey water footprint efficiency

with contribution values of 0.442 7 yuan/m3 and -0.4406 yuan/m3

respectively. ④ The driving effect of agricultural grey water footprint efficiency in the Yellow River basin can be divided into four models. Different models have different ways of improving agricultural grey water footprint efficiency in different regions. [Conclusion] The nine provinces in the Yellow River basin should adopt different development strategies according to local conditions

optimize the agricultural structure

reduce the intensive use of fertilizers and pesticides

strengthen agricultural water management

and improve agricultural grey water footprint efficiency.

关键词

Keywords

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