Sustainable Management of Agricultural Water Resources: Applying Water Footprint Theory to an Arid Inland Region in Northwest China

Water resources are essential to sustainable agriculture. In pursuing sustainable agricultural development, this study addresses the critical need for accurately assessing water resources on the Northern Slope of the Tianshan Mountains (NSTM), an arid region in Northwest China facing significant water scarcity challenges. The primary objective is to develop and apply a comprehensive agricultural water sustainability index (AWSI) to evaluate the sustainability of agricultural water resources that integrates three key attributes: fairness, efficiency and safety. Utilizing water and land resource matching coefficients, a super slack-based measure model, and water footprints (blue water, green water and grey water), we developed three indices: the agricultural water equity index (AWEI), water use efficiency index (WUEI) and water ecological security index (WESI). These indices were integrated using the weighted Euclidean distance to develop a comprehensive AWSI. Through partial least squares regression analysis (PLSR), we explored the influence of various factors on agricultural water sustainability (AWS) across 26 cities in the NSTM. The key findings revealed that (1) Urumqi, Changji and Muli demonstrated high AWSI values ([Formula: see text]), indicating strong sustainability. Meanwhile, 16 cities had AWSI values between 0.4 and 0.6, indicating moderate sustainability. The overall mean AWSI was 0.58, suggesting a reasonable but not optimal level of sustainability and underscoring the need for targeted interventions. (2) The following indicators significantly influenced AWS, each with varying impacts. The WUEI demonstrated the strongest positive influence, suggesting that improvements in water use efficiency are crucial for enhancing sustainability. In contrast, WESI and AWEI negatively impacted AWS, indicating that ecological risks and uneven water distribution hinder sustainability. This AWSI model, which uses the Euclidean distance for weight assignment, provides a novel approach to resource management. These findings inform targeted water management strategies in the NSTM and offer best practices applicable to other arid regions facing similar challenges.