Factors Influencing Water Use Efficiency in Agriculture: A Case Study of Shaanxi, China

Enhancing agricultural water use efficiency can support Shaanxi Province’s transition to a sustainable agricultural economy. Using the data envelopment approach (DEA), we evaluated the water use efficiency in agriculture of various cities in the Shaanxi Province of China. Moran’s I and Dagum Gini coefficients were used to reveal spatial and temporal characteristics of agricultural water use efficiency. Furthermore, the geographically and temporally weighted regression (GTWR) model was used to investigate the effects of the agricultural economy, level of water-saving irrigation, cropping structure, environmental factors, and water supply structure on agricultural water use efficiency. The findings demonstrate that the average agricultural water use efficiency from 2011 to 2020 is low (0.796) in Shaanxi Province. Spatially there is considerable variation in water use efficiency between cities, with some highly efficient and some with very low efficiency. There is a strong negative spatial correlation between cities, with high efficiency cities tending to be adjacent to low efficiency cities. Moreover, the spatial differences in agricultural water use efficiency have increased over time, with the most significant increase within the northern region and between the north and central areas. Each influencing factor has a different impact from year to year and from city to city. Overall, the level of water-saving, the level of agricultural economics, the structure of the water supply, and environmental factors primarily have a negative influence. In contrast, the planting structure primarily has a favorable function. Therefore, to support the coordinated growth of agricultural water use efficiency, Shaanxi Province should improve its city-to-city cooperation and exchange of water use technology and experience, as well as develop differentiated water use measures appropriately for the development of each city according to local conditions.