3.2.3. Evapotranspiration

Spatial patterns of the ET trend over the TRHR were detected from 1982 through 2015. There were significant di fferences in the ET between the southeastern and northwestern parts of the region. Figure 8a shows that the ET has increased, on average, by 3.34 mm/decade over the TRHR, which corresponded to the expected acceleration associated with rising air temperature. About 26.5% of the pixels showed a significant increasing trend over the TRHR, while only 3.81% of the pixels showed a significantly decreasing trend (*p* < 0.05). A significant positive ET trend was mainly distributed

in the core of the Sanjiangyuan National Nature Reserve, namely, the east and west regions of the TRHR, with a linear tendency of 1.2 mm/year per decade, while the Dari and Banma counties showed a negative ET trend.

**Figure 8.** (**a**) Spatial distributions of the ET trends; (**b**) Interannual and seasonal variability of the ET trends. The inset panel shows the area where the ET trend was statistically significant (*p* < 0.05). Red represents a significant increase and blue represents a significant decrease.

As shown in Figure 8b, the spatially averaged ET has increased, on average, by 3.3 <sup>W</sup>/m<sup>2</sup> per decade (*p* < 0.05) over the entire TRHR during 1982–2015. The value of ET has obviously fluctuated since 2000, indicative of strong regional variations controlled by the monsoon climate system and the arid climate system. Considering the seasonal difference in climatic conditions, we further calculated the trend of ET across four seasons. Figure 8c illustrates that the ET trend in winter had a significant increase with a linear tendency of 0.154 (*p* < 0.05), while in other seasons, the ET presented a slight increasing trend with no statistical significance (*p* > 0.05). It is evident that the temperature warming in winter had a significant positive effect on water cycling. The trend magnitudes of the annual and seasonal terrestrial biophysical variables are summarized in Table 2.


**Table 2.** The Mann–Kendall test results for the terrestrial biophysical variable trends.


**Table 2.** *Cont.*

R: reject hypothesis H0; A: accept hypothesis H0.

#### *3.3. Vegetation Greening and ET Variation Response to Climate Change*

Correlation analysis was used to investigate the relationship between each climate factor (Ta, P, RH, Rs) and the NDVI over the TRHR during 1982–2015. We found that over 57.54% of the area of the TRHR had a moderate positive correlation between the NDVI and Ta, and the maximum coefficient was about 0.89 (Figure 9a). When water was the limiting factor for vegetation growth in the western part of the TRHR, a strong correlation existed between the NDVI and P with a maximum coefficient of 0.74 (Figure 9b). The relationship between the NDVI and P was much weaker than that between the NDVI and Ta, which indicated that increasing temperature appeared to be the driving factor for vegetation greening, and better at explaining this phenomenon in comparison to P. Compared with Ta and P, no strong coherent spatial patterns were found in the relationship between the NDVI and annual Rs and annual RH, with a negative correlation coefficient of 0.3 (Figure 10).

We further conducted a correlation analysis between the ET and each energy- or water-limiting factor (Ta, P, RH, Rs, NDVI, potential ET (PET), and soil moisture (SM)) (Figure 11). The results showed that SM was the primary factor in controlling ET change in the western TRHR during the period 1982–2015. Given the fact that this area is located at arid and semi-arid climatic zones, the terrestrial moisture limitation is expected to be the most important driver of ET variation [58]. Similarly, over 55.21% of pixels showed a moderate positive correlation between precipitation and ET (Figure 11b), which can be attributed to the fact that ET corresponds well with surface moisture supply in a region with scarce water. The infrequent rainfall causes shortages in soil moisture and further feedbacks to the decreases in ET.

**Figure 9.** Maps of the relationship between the NDVI and climate variables: (**a**) temperature; (**b**) precipitation; (**c**) relative humidity; (**d**) downward shortwave radiation.

**Figure 10.** The frequency of correlation coefficient with (**a**) NDVI, (**b**) ET. The degree correlation was classified into six ranks: Strong Negative (−1 < R < −0.7); Moderate Negative (−0.7 < R < −0.3); Weak Negative (−0.3 < R < 0); Weak Positive (0 < R < 0.3); Moderate Positive (0.3 < R < 0.7); and Strong Positive (0.7 < R < 1).

In the relatively humid area of the TRHR, ET showed a positive correlation with Ta, accounting for approximately 55.3%. Ta was the primary indicator governing ET variation in the unrestricted water region, where ET corresponded well to atmospheric energy demand. The NDVI was also an important dominant factor in controlling the increasing ET in the southern part of the TRHR. The relatively higher plant transpiration and canopy conductance contributed to the increment of ET [59]. As shown in Figure 10c, the decline of RH has continuously contributed to the decrease in ET over the southeastern part of the TRHR. The rising temperature was expected to feedback to the atmosphere and consequently decreased the RH and ET, which implied that this area is projected to be drier. Previous studies have proposed that there is a complementary relationship in the ET and potential ET (PET) [60]. Zhang et al. [61] point out that vapor transfer power was suppressed due to the low Ta and vapor pressure deficit (VPD) in the TRHR. The negative correlation between the ET and PET revealed by this study supports their findings.

**Figure 11.** Maps of the spatial distribution of correlation coefficient (**r**) between annual ET: (**a**) temperature, (**b**) precipitation, (**c**) relative humidity, (**d**) downward shortwave radiation, (**e**) potential evapotranspiration, (**f**) NDVI, (**g**) soil moisture, (**h**) spatial distribution of most related driving variables for annual ET during 1982–2015 over the TRHR.

Land use and land cover change can also have substantial influences on the biophysical variables in hydrologic processes and terrestrial energy exchange by affecting the patterns of ET. We further investigated responses in the distribution of the multiyear average ET to the difference of land cover and use type. As shown in Figure 12, cropland had the highest ET values. The lowest annual ET occurred in the artificial surface and bare land. For each vegetation type, forest had the highest ET, followed by grassland and shrubland. This can be explained by forest ecosystems having relatively higher total root biomass and deeper effective rooting depth, thereby having the potential to create positive transpiration forcing [62]. The ET value of cropland was generally higher than that of forest, where it was noted that artificial management, e.g., agriculture irrigation, has a nonnegligible impact on the variation of ET.

**Figure 12.** Box plots of per pixel annual average ET (mm/year) for each land cover type from 1982 to 2015 over the TRHR. CRO: cropland; FOR: forest; GRA: grassland; SHR: shrubland; BAR: bare land; ART: artificial surfaces.
