## 1 Introduction  
Agriculture, as the world's largest water consumer, accounts for 69% of global water withdrawals. In arid regions with typical irrigated farming systems, cropland irrigation alone consumes more than 80% of total agricultural water, with persistently low water-use efficiency becoming the primary constraint on agricultural production [1, 2]. Water-use efficiency (WUE) is typically defined as the ratio of gross primary productivity (GPP) to evapotranspiration (ET) [3, 4, 5], serving as a key parameter that reflects the integrated effects of water, energy, and carbon cycles on ecosystem processes [6]. It is essential for understanding the coupling of ecosystems and carbohydrates and for addressing climate change. Cropland water-use efficiency (WUEc) is a specific application of WUE in agriculture, focusing on the efficiency of water use in croplands within particular environments [7]. To date, extensive scholarly attention has been paid to WUE studies in grasslands and forests, while research on WUEc in arid regions remains relatively limited [8; 9; 10]. In the context of expanding agricultural scale and intensifying water supply conflicts, a comprehensive investigation of the spatiotemporal patterns of WUEc and its driving factors in arid regions is critical for the rational allocation of farmland water and soil resources, improving irrigation efficiency, reducing water consumption per unit yield, and ensuring both agricultural and ecological security [11; 12; 13]. Furthermore, in the context of escalating global water scarcity and generally low WUE, it is increasingly urgent to identify the key factors driving the spatiotemporal variability of WUE and their relative contributions. The exploration of the spatiotemporal patterns of WUE and its primary influencing factors has attracted widespread attention from researchers [14; 15; 16; 17]. Empirical studies show that WUE dynamics are primarily governed by meteorological factors temperature (T), precipitation (Pre), and vapor pressure deficit (VPD) and the vegetation parameters leaf area index (LAI) [18; 19; 20]. Moreover, human activities directly affect ecosystem WUE by altering the composition and cover of vegetation involved in transpiration and photosynthesis, as reflected by the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) [21]. In arid and semi-arid regions, a global consensus has yet to be reached on the dominant factors influencing crop WUE. For example, [PERSON] et al. [22] utilized the LPJ-vegetation and soil moisture joint assimilation (LPJ-VSJA) product along with multiple and partial correlation analyses to investigate the primary factors regulating carbon-water flux dynamics across different spatial scales in Asia's semi-arid regions. Their results indicate that vegetation type contributed more substantially to WUE's spatial heterogeneity than climatic variables. Likewise, [PERSON] et al. [23] developed annual WUE time-series data by integrating FLUXNET eddy covariance data with the GLASS remote sensing product. Their analysis using structural equation modeling and partial correlation reveals that VPD is the most critical climatic factor constraining WUE improvement in global drylands. Notably, conflicting results have also been reported within the same arid region. In the Shiyang River Basin, northwest China, [PERSON] et al. conducted continuous field observations of water and carbon fluxes across four crop rotation cycles, finding a negative correlation between temperature and WUE [24]. Conversely, [PERSON] et al. used MODIS remote sensing data and partial correlation analysis to report a positive temperature-WUE relationship in the same region [25]. These discrepancies underscore the complexity of WUE dynamics and the urgent need for further investigation into both the influencing factors and the methodologies used to identify WUE drivers across diverse arid regions.