Research on Temporal and Spatial Differentiation and Impact Paths of Agricultural Grey Water Footprints in the Yellow River Basin

Abstract

The scientific evaluation of water pollution in the Yellow River Basin was directly related to the sustainable utilization of water resources and the green development of the agricultural economy in this region. In this study, we focused on the planting industry, and measured the agricultural grey water footprint of 73 prefecture-level cities in the Yellow River Basin from 2000 to 2019. We used spatial autocorrelation analysis to reveal temporal and spatial differentiation characteristics, and we used the path analysis method to study the factors influencing the temporal evolution and spatial distribution. Taking 2015 as the study period, the agricultural grey water footprint showed a trend of first rising and then falling. The values and growth rates of the agricultural grey water footprint in different regions were quite different. According to the natural breakpoint method, the agricultural grey water footprints were divided into low, middle, high, and very high groups. There were obvious spatial differences in the agricultural grey water footprints, and these differences gradually decreased. Generally, the H–L and the L–L types were dominant. From 2000 to 2019, most prefecture-level cities maintained the same transition changes as those in the neighboring regions. Crop yield, economic scale, population scale, urban and rural structure, and technological innovation were found to be the key elements of spatiotemporal variation in the agricultural grey water footprint.

Decoupling Agricultural Grey Water Footprint from Economic Growth in the Yellow River Basin

“…Kong et al also found that China's AGWF showed a downward trend from 2015 to 2019 [6]. Xu et al further found that the AGWF of prefecture-level cities in the YRB continued to decline from 2015 to 2019 [50]. The research conclusions of this paper are consistent with those of Kong et al and Xu et al [6,50].…”

“…Xu et al further found that the AGWF of prefecture-level cities in the YRB continued to decline from 2015 to 2019 [50]. The research conclusions of this paper are consistent with those of Kong et al and Xu et al [6,50]. The reason why the AGWF in the YRB decreased at first and then rose slowly during 2016-2021 may be that the implementation of the highquality development strategy in the YRB had a strong promotion effect on reducing the agricultural grey water footprint and improving agricultural water use efficiency in the region in 2016 and for the following three years.…”

Analysis of community based industrial waste treatment to control river water pollution

“…Therefore, we require a method to manage water pollution. In the Yellow River Basin, Xu et al (2022) conducted a study of a similar nature, however they came to two distinct results on the spatial differences in the AGWFs across the cities. (1) There are stark differences in the amount of GWF planted in prefecture-level cities.…”

“…Because this study solely looked at the GWF of the planting industry, there are some differences between it and Xu et al (2022) on specific uses of water.…”

Investigating the temporal and spatial evolution of bank performance and its impact pathways in the context of financial technology development

“…4 show the temporal and spatial distribution patterns of financial technology and bank performance plotted separately before this paper's standard deviation ellipse analysis. The method used is the natural breakpoint method, which is based on Xu et al [ 42 ] and Zhang et al [ 43 ] to classify and analyze the distribution of the two at 2012, 2015, 2018, and 2021 to classify their ranks and analyze their distribution characteristics.

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