## 4 Conclusions  
It is of great importance to analyze the spatiotemporal changes in NPP and WUE to enable suitable management measures to be applied for water resources and agriculture, and thus ensure the sustainable provision of essential ecosystem services. In the present work, NPP in the TMS from 2000 to 2020 was calculated using the CASA model, and ET was estimated using the SEBS model. This enabled WUE to be easily obtained using the NPP and ET values. The spatiotemporal variations in the annual values and slopes of NPP, ET, and WUE were further investigated and discussed. These results provide important spatially explicit information for decision making and sustainable development in TMS.  
Annual NPP in the study area ranged from 147.9 to 189.4 gC\(\cdot\)m\({}^{-2}\), annual ET ranged from 212.5 to 285.8 mm, and annual WUE ranged from 0.66 to 0.78 gC\(\cdot\)kg\({}^{-1}\cdot\)H\({}_{2}\)O in the TMS during 2000-2020. During the study period, both NPP and ET exhibited an increasing  
Figure 5: Spatial distribution of the correlation coefficients between WUE and temperature (**a**), precipitation (**b**), wind speed (**c**), sunshine duration (**d**), solar radiation (**e**) and TVDI (**f**) during 2000–2020 over the TMS.  
trend with some fluctuation, whereas WUE showed the opposite tendency. The annual NPP and ET values showed a similar spatial pattern, with remarkable changes in some regions of the TMS from 2000 to 2020. The number of areas where WUE decreased was larger than that where _WUE_ increased, indicating that WUE experienced a decreasing trend in the TMS during 2000-2020. Our results demonstrate that the decrease in WUE was primarily because of the increase in ET. Obvious differences were found for WUE under different land-use types, caused by NPP and ET. However, the interannual variation in WUE showed a small fluctuation, and the dynamic process of _WUE_ in each land-use type showed good consistency. The correlations between WUE, climate factors, and drought were investigated. For example, temperature and wind speed had positive influences on WUE in the central and eastern 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 TVDI, and the slopes of WUE and the TVDI presented good consistency in their spatial distribution, suggesting that drought had a significant impact on ecosystem WUE. Thus, in future, it will be necessary to analyze the mechanism by which drought influences WUE, in addition to making field observations. This will improve the understanding of the WUE in ecosystems and enhance the scientific basis for water resource management in the TMS.  
J.C.: Investigation, Data. L.C.: Methodology, Writing, Review and Editing. All authors have read and agreed to the published version of the manuscript.  
This study was supported National Natural Science Foundation of China (No.41901129; No.42101100); the Nature Science Foundation of Shaanxi Province (No.2021)Q-313), the China Postdoctoral Science Foundation (2020M673334).  
Not applicable.  
This work was partially supported by National Natural Science Foundation of China (No.41901129; No.42101100); the Nature Science Foundation of Shaanxi Province (No.2021)Q-313); the China Postdoctoral Science Foundation (2020M673334); Open fund from Anhui Engineering and Technology Research Center for Smart City. We are also grateful to the editor and anonymous reviewers for their constructive comments and suggestions leading to improvement of this paper.  
The authors declare no conflict of interest.