# Spatiotemporal Analysis of Evapotranspiration and Effects of Water and Heat on Water Use Efficiency
## 3 Results and Discussion
### WUEs Responds to Temperature and Precipitation Thresholds  
Numerous studies have shown that climatic condition is an important environmental factor that affects the water use efficiency of terrestrial ecosystems [52; 53]. There is a threshold effect of both temperature and precipitation on WUEs. [PERSON] et al. (2015) found that WUE was positively correlated with air temperature when the temperature was below 18.5 \({}^{\circ}\)C (\(p<0.05\)), and it significantly decreased when the temperature was between 18.5 and 25.7 \({}^{\circ}\)C (\(p<0.05\)) [54]. However, this study indicates that the response of diverse types of water use efficiency to temperature fluctuation is different in semi-arid area. Figure 8b,d,f show that water use efficiency is proportional to temperature. Due to the increased stomatal conductance of vegetation leaves, the increase in photosynthetic rate is greater than that the transpiration rate, resulting in an increase in WUE. The temperature thresholds of WUEs in different hydrological processes are different. Figure 8b,d,f show that the temperature, when around \(-\)10-2 \({}^{\circ}\)C, is proportional to eWUE. However, when the temperature is greater than 2 \({}^{\circ}\)C, the correlation between temperature and eWUE fluctuates. Temperature is also proportional to tWUE when it is within the range of \(-\)10-7 \({}^{\circ}\)C. Similarly, the pWUE and eWUE thresholds are basically the same. The thresholds of this paper differ from those of [PERSON] et al. [54], which is mainly because different regional climates influence the changes in thresholds. The study by [PERSON] et al. (2015) on Chinese terrestrial ecosystems shows that most of the vegetation WUE has a positive response threshold of 500 mm to precipitation [55]; however, our study does not find such a pattern, and this may be due to the influence of arid climate characteristics. There is a positive correlation between eWUE and precipitation, which indicates that precipitation has a positive response to eWUE. From Figure 8a,c,e, it can be seen that for eWUE, when precipitation is less than 300 mm, precipitation is proportional to eWUE; when precipitation is greater than 300 mm, precipitation is negatively correlated with eWUE. For tWUE, when precipitation is less than 200, precipitation has a positive relationship with tWUE; when precipitation is greater than 200 mm, precipitation and eWUE exhibit a negative correlation. The pWUE and eWUE threshold are basically the same. The standard precipitation threshold in this paper is different from that of [PERSON] et al. [55]. This is mainly because the small average annual precipitation in Xinjiang affects the change of threshold value. The sensitive coefficient in Figure 9 shows the response of WUEs to climate factors. From Figure 9a,e it can be seen that tWUE has the largest response to temperature (\(Sp=0.4\)) (Figure 9a); tWUE has the greatest response to precipitation (\(Sp=1.0\)) (Figure 9e). tWUE \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Trend of WUEs**} & \multicolumn{4}{c}{**Mean Annual of WUEs**} \\ \hline Class & LD & RI & MI & RHI & HI & 0–0.2 & 0.2–0.4 & 0.4–0.6 & 0.6–0.8 & \(>\)0.8 \\ eWUE & 31.57 & 66.87 & 0.81 & 0.31 & 0.19 & 65.25 & 23.64 & 5.18 & 1.68 & 4.24 \\ tWUE & 34.77 & 41.32 & 3.00 & 2.43 & 3.31 & 23.66 & 26.78 & 15.04 & 8.86 & 25.66 \\ pWUE & 18.54 & 80.13 & 1.34 & 0 & 0 & 67.11 & 22.72 & 5.81 & 1.92 & 2.44 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Trend change and mean annual of WUEs percentage (units: %). responds more quickly to precipitation but responds more slowly to temperature. This shows that the effect of temperature on vegetation has a lag effect. The red line in Figure 8 shows the constraint analysis of all metadata in the semi-arid region. It was surprising to find two symmetrical \"triangular\" relationships between precipitation, temperature, and water use efficiency in the point distribution.