###### Abstract  
Water-use efficiency (WUE) is a crucial physiological index in carbon-water interactions and is defined as the ratio of vegetation productivity to water loss. The variation in climatic variables and drought have the most significant effects on WUE and evapotranspiration (ET). Nevertheless, how WUE varies with climate factors and drought processes in the Tianshan Mountains (TMS) is still poorly understood. In the present work, we analyzed the spatiotemporal variations in WUE, and investigated the correlations between WUE, climate factors, and drought, in the study area. The results showed that, in the TMS during 2000-2020, annual net primary productivity (NPP) ranged from 147.9 to 189.4 gC-m\({}^{-2}\), annual ET was in the range of 212.5-285.8 mm, and annual WUE ranged from 0.66 to 0.78 gC-kg\({}^{-1}\)-H\({}_{2}\)O. Both NPP and ET exhibited an increasing trend with some fluctuation, whereas WUE showed the opposite tendency during the study period. The obtained results demonstrated that the decrease in WUE was primarily because of the increase in ET. There were obvious differences in WUE, under different land-use types, caused by NPP and ET. However, the interannual variation in WUE showed small fluctuations and the dynamic process of WUE in each land-use type showed good consistency. Temperature and wind speed had a positive influence on WUE in the middle and eastern regions of the TMS. Precipitation also played a mainly positive role in enhancing WUE, especially on the northern slope of the TMS. There was strong spatial heterogeneity of the correlation coefficient (0.68, \(p<\) 0.05) between WUE and the temperature vegetation drought index (TVDI). Moreover, the slopes of WUE and TVDI showed good consistency in terms of spatial distribution, suggesting that drought had a significant impact on ecosystem WUE. This work will enhance the understanding of WUE variation, and provide scientific evidence for water resource management and sustainable utilization in the study area. water-use efficiency; climate factor; spatiotemporal variation; drought; Tianshan Mountains 2022148191. 1891. 1891.  
component of the energy-water balance in agriculture ecosystems. It is also widely regarded as the quantity of water consumed by vegetation to provide ecosystem services [8]. NPP is a crucial indicator for evaluating ecological health, and is also important for estimating the carbon sink and ecological change. NPP is defined as the new carbon stored in living plants per unit time (annually) per unit surface area. Compared with GPP and NEP, the NPP index deducts organic carbon consumed by plant respiration, and can objectively reflect the net cumulative organic carbon. Therefore, it is of great significance to investigate the spatiotemporal variation in ET and NPP. Several models and studies have been proposed to calculate NPP at different scales (global, regional, or local), which can be classified into climate-related models, process-based models, and light-use efficiency models [9]. Climate-related and process-based models have been extensively applied in previous research. Nevertheless, process-based models (e.g., the LPJ-GUESS model) are not inappropriate for calculating NPP in areas disturbed by frequent and significant human activity [10]. By comparison, climate-related models (e.g., the Miami model) can be used to evaluate the potential vegetation productivity [11]. In contrast, the theoretical model of the Carnegie-Ames-Stanford Approach (CASA) was developed based on light-use efficiency, and includes temperature, precipitation, solar radiation, the Normalized Difference Vegetation Index (NDVI), and land cover as input variables [12; 13]. The CASA model has been well demonstrated in some areas and can accurately calculate NPP [11; 14; 15]. More importantly, it has been proven that the CASA model is suitable for estimating activity in Xinjiang, China [14; 15].