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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.

The production mode of “high input, high yield and high waste” in the agricultural system poses a serious threat to the environment and the quality of agricultural products. Accelerating the adoption of green agricultural technology (GAT) by farmers is an emergency measure. However, according to microsurvey data, many farmers give up GAT within a year after adopting it. The implementation of this measure has been anticlimactic. Based on a survey of 1138 kiwi growers in Shaanxi Province, China, this paper builds a theoretical model and conducts empirical exercises to gain insight into the effects of perceived value, government support and their interaction with kiwi growers’ sustainable application of GAT. We find that perceived value and government support have a significant impact on the sustainable application of GAT. Government support plays a moderating role in the influence of perceived value on the sustainable application of GAT. Furthermore, in order to overcome the potential endogeneity problem caused by the two-way causal relationship between subjective variables, “owning a smartphone” was selected as the instrumental variable. The 2SLS model was used for endogeneity analysis, and the OLS model was used for the robustness test. This paper discusses the relevant theories and policy implications of environmental management.

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.