Human activities and climate change have profound impacts on the ecological environment of oases in Xinjiang, and it is of great significance to explore the spatial and temporal evolution patterns of ecological environment quality in this region for the sustainable development of Xinjiang. The remote sensing ecological index (RSEI) was extracted from the Google Earth Engine (GEE) platform from 2000 to 2020, and the coefficient of variation and Hurst index were used to reveal the spatial and temporal characteristics and stability of the ecological environment quality of the artificial oasis and natural oasis in Xinjiang. The key factors affecting the ecological environment quality are explored through correlation analysis and geoprobes. The results show that the distribution of the ecological environment in Xinjiang oases is high in the north and low in the south, and the overall quality shows a fluctuating downward trend from 0.210 to 0.189. Artificial oases have higher RSEI values, stability, and sustainability than natural oases. The RSEI in the study area was mainly influenced by humidity, followed by greenness and heat, and dryness had the least influence on the RSEI model. Based on the geodetector, the top three highest contributors were found to be precipitation (PRE) (0.83) > relative humidity (RHU) (0.82) > evapotranspiration (ET) (0.57). Climate is the main factor affecting the ecological quality of oases, and the RSEI can be improved by increasing the proportion of artificial oases. The study aims to provide a scientific basis for the sustainable development of oases in arid zones.

Water scarcity and ecological degradation in arid zones present significant challenges to regional ecological health. Despite this, integrating the water supply–demand balance and water supply security (SEC) into ecological health assessments—particularly through composite indicators—remains underexplored in arid regions. In this study, we assessed the ecological health changes in Xinjiang by utilizing multivariate remote sensing data, focusing on the balance between water supply and demand, the degree of SEC, and ecosystem resilience (ER). Our results indicate that while water supply and demand remained relatively stable in northern Xinjiang between 2000 and 2020, the conflict between supply and demand intensified in the southern and eastern agricultural regions. SEC evaluations revealed that 73.3% of the region experienced varying degrees of decline over the 20-year period. Additionally, ER assessments showed that 7.12% of the region exhibited a significant decline, with 78.6% experiencing overall reductions in ecological health. The indicators’ response to drought demonstrated that improvements in ecological health during wet conditions were less pronounced than declines during droughts. This study underscores the necessity of prioritizing areas with lower ecological health in future water allocation strategies to optimize water resource utilization.

Agricultural water footprint is an important indicator for assessing water-use efficiency and resource carrying capacity in agricultural systems, especially in arid regions. From the perspective of ecological function zones, this study examines the spatiotemporal dynamics of the agricultural water footprint in Xinjiang, China, and evaluates its adaptability to socioeconomic factors. The blue and green water footprints of crop production and the water footprint of animal products during 2000–2020 were quantified to estimate the total agricultural water footprint. The Gini coefficient and imbalance index were used to quantitatively evaluate the spatial adaptability between the agricultural water footprint and socioeconomic factors, including sown area, population, and agricultural Gross Domestic Product (GDP) across different ecological function zones. The results indicate that the agricultural water footprint increased from 2.54 × 10¹⁰ m³ to 5.85 × 10¹⁰ m³, with a clear spatial gradient characterized by higher values in southwestern Xinjiang and lower values in the northeastern region. Crop production accounted for more than 85% of the total footprint, with cotton as the dominant contributor, while beef consumption drove the growth in the animal product water footprint. The adaptability between the agricultural water footprint and sown area improved overall, whereas coordination with population distribution remained weak, and notable regional differences were observed in water footprint intensity relative to agricultural GDP. These findings indicate that the spatiotemporal differentiation of the agricultural water footprint is closely linked to resource endowments and development characteristics across ecological function zones, providing support for region-specific agricultural water management in arid areas.

Under high-intensity agricultural development, understanding the spatial allocation and scarcity pressure of agricultural water and land resources is critical for regional sustainability. Using water footprint and remote sensing data in Aksu, this study applies the spatial mismatch index, Gini coefficient, and scarcity indices to assess water–land matching and pressure dynamics and traces the migration of pressure center of gravity using the standard deviation ellipse model. The results show: (1) Water footprint and irrigated area increased over 2000–2020, with matching Gini coefficient fluctuating upward and severe mismatches in the northeast and southwest. (2) Resource scarcity indices fluctuated significantly; relative water scarcity peaked in 2015, and both pressure centers shifted eastward. (3) Economic factors are the primary drivers of water footprint and irrigated area changes, while water–land pressure correlates strongly with economic and production conditions. We conclude that Aksu’s water–land matching underwent a phased transition from relative balance to significant imbalance and then to gradual improvement, with 2015 as the critical turning point; the pressure centers migrated eastward (but at different distances); and economic factors dominate this evolution. These findings provide a scientific basis for differentiated waterland regulation in arid oasis agriculture.