## 4 Discussion  
### Spatio-Temporal Variations of WUE  
This paper used MODIS ET and GPP products to estimate WUE in QM and HC. The spatial variation of WUE ranged from 0.01 to 2.63 gC kg\({}^{-1}\) H\({}_{2}\)O. The average of WUE was 0.60 \(\pm\) 0.36 gC kg\({}^{-1}\) H\({}_{2}\)O during 2001-2021, lower than the global WUE average of 1.89 gC kg\({}^{-1}\) H\({}_{2}\)O and 1.71 gC kg\({}^{-1}\) H\({}_{2}\)O calculated by flux and RS, respectively [4]. The multi-year average of WUE in HC (1.09 \(\pm\) 0.34 gC kg\({}^{-1}\) H\({}_{2}\)O) was lower than that in Central Asia (2.56 gC kg\({}^{-1}\) H\({}_{2}\)O) [59], also an arid desert region. It may be associated with the fact that cultivated vegetation predominates in HC [60]. Compared with Central Asia, the WUE in HC was more impacted by human activities, such as fertilization and irrigation [34; 61]. The multi-year average WUE in QM was 0.5 \(\pm\) 0.327 gC kg\({}^{-1}\) H\({}_{2}\)O, lower than the average WUE (1.14 gC kg\({}^{-1}\) H\({}_{2}\)O) calculated by [PERSON] et al. [62] using MODIS data for grassland across the Tibetan Plateau and closer to the WUE of 0.4-1.38 gC kg\({}^{-1}\) H\({}_{2}\)O using data from three flux towers in the Tibetan Plateau during 2003-2006 [63].  
This study found an overall downward trend in WUE over the last 20 years in the study area. While an increase in atmospheric CO\({}_{2}\) concentration led to an increase in temperature and WUE [64], excessive temperature also suppressed photosynthesis and promoted evaporation, which ultimately led to a decrease in WUE [65]. It differed from the study of WUE for grassland on the Tibetan Plateau [62], mainly due to the different spatial extent and periods. Our spatial extent, including QM and HC, differs from that of the Tibetan Plateau, although QM is a part of the Tibetan Plateau. In addition, the period was slightly different.  
A monthly plot was used to investigate the seasonal pattern shift of WUE from 2002 to 2021 (Figure 15). The monthly plots represent the 12 monthly subseries of the WUE for each year from 2002 to 2021. The subseries fluctuates around the monthly mean. The monthly plots illustrate the long-term trends of the WUE for each month. We found an intriguing variation in the seasonal pattern: WUE tended to decrease from May to July (the early and mid-growing seasons), while the trend reversed to a slight increase from September to October (late growing season). It is almost certain that the reduction in WUE resulted from the reduction in WUE from May to July. This phenomenon may be due to changes in vegetation phenology and temperature [26]. In the early and middle of the growing  
Figure 14: Factor detector-based explanatory power ranking of bio-meteorological variables for WUE in different vegetation types. AT: air temperature; PR: precipitation; HUM: specific humidity; WS: wind speed; SR: shortwave radiation; VT: vegetation type; SM: soil moisture; LAI: leaf area index.  
season, GPP and ET showed an increasing trend due to higher temperature and earlier phenology [32; 66]. Still, ET increased faster than GPP, resulting in a decreasing trend in WUE. In the late growing season, the delay in phenology kept WUE at a relatively high level, and WUE showed a slightly increasing trend. The regularity of seasonal pattern shift contradicts that in the northern hemisphere [67] and Luanhe River Basin [68], the typical semi-arid region in China, which shows that the shift in the seasonal pattern of WUE differed across areas.