Water Policy (Aug 2021)
Study on the spatial distribution of water resource value in the agricultural system of the Yellow River Basin
Abstract
To analyze the spatial distribution characteristics of water resource value in the agricultural system of the Yellow River Basin, this paper takes the Yellow River Basin as its research object and studies the spatial distribution characteristics and influencing factors of water resource value in the agricultural system using the emergy theory and method, the spatial autocorrelation analysis method, and the spatial regression model. The results show the following. (1) The value of water resources in the agricultural system ranges from 0.64 to 0.98 $/m3, and the value in the middle and lower reaches of the basin is relatively high. (2) The Moran index of the water resource value in the agricultural system is 0.2772, showing a positive spatial autocorrelation feature. Here, ‘high-high (high value city gathering)’ is the main aggregation mode, which is mainly concentrated in the middle and lower reaches of the basin. (3) The spatial error model, moreover, has the best simulation effect. The cultivated land area, total agricultural output value, agricultural labor force, and total mechanical power have a significant positive impact on the agricultural production value of water resources in the Yellow River Basin; the altitude, annual average temperature, and agricultural water consumption have a negative impact. Overall, this study shows that guiding the distribution of water resources according to their value and increasing agricultural water use in the middle and lower reaches of the basin will help improve the overall agricultural production efficiency of water resources in the basin. HIGHLIGHTS Spatial distribution analysis provides a basis for the formulation of water resources management policies.; Water resource value in the agricultural system is quantified based on the emergy theory.; The spatial autocorrelation analysis method is used to analyze the spatial distribution of water resources value.; The spatial regression model is used to identify the main influencing factors of water resources value.;
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