**3. Results**

### *3.1. ETa Estimation and Its Change Characteristics*

ETa was calculated using Equation (3). Compared with the observations from the flux stations (Figure 2), both the observed and estimated ETa were found to increase significantly with increased precipitation in the region where P < 600 mm. Furthermore, when P ≥ 600 mm, the observed ETa first increased and then decreased with increasing P, although the estimated ETa still increased significantly with increased P. Many factors affect ETa, the most important of which are water and energy conditions. In arid and semiarid regions, the amount of precipitation is relatively small, but the energy is sufficient. The main factor affecting ETa is water, and a change in P largely determines the change in ETa. In the semi humid region, increased P makes energy the controlling factor of ETa instead of water, and the rate at which ETa increases with P slows down. In humid areas with abundant rainfall, ETa no longer increased with increasing P. Due to more precipitation, energy conditions limit ETa, and higher P results in smaller ETa. Earlier studies confirmed the switch of the ETa controlling factor from water to energy with increased precipitation [70]. Equation (3) does not consider this switch when estimating the ETa in the humid region and does not reflect its energy constraint. Estimates are largely dependent on precipitation, which exaggerates the results. We further used P = 600 and P = 1400 mm as the boundaries and conducted regression corrections on the estimated ETa. The specific regression equation is given by Equation (8).

$$\begin{aligned} \text{ET}\_{a\\_new} = \begin{cases} \text{ET}\_{\text{a}} \text{if } \text{Pre} \le 600 \text{mm} \\ 0.815 \ast \text{ET}\_{\text{a}} + 26.2 \text{ if } 600 \text{ mm} < \text{Pre} \le 1400 \text{mm} \\ -0.615 \ast \text{ET}\_{\text{a}} + 1249.8 \text{ if } \text{Pre} > 1400 \text{mm} \end{cases} \text{(r} = 0.82, \text{a} < 0.01) \end{aligned} \tag{8}$$

**Figure 2.** Distribution of observed and estimated ETa with P.

The improved ETa in the southern humid region is significantly smaller than the ETa before improvement (Figure 3). Regions with the highest ETa move north from the southeastern coastal area to the middle and lower reaches of the Yangtze River. To further verify the accuracy of the improved ETa model, we compared the estimated values with

the ETa observations from the flux stations during the validation period and the ETa from GLDAS during the same period. This comparison showed that the improved ETa is highly consistent with the observed and GLDAS ETa (Figure 4). The correlation coefficients were 0.95 and 0.85, respectively, and the standard deviation between the estimated and observed values was much smaller than that between the GLDAS assimilation and observed values. GLDAS data are sparser in the high evapotranspiration regions, and the values are too large. Wang et al. [71] also identified an overestimation in the high ETa regions of southern China in the GLDAS data. Hence, our improved ETa model can simulate the ETa in the study region more accurately.

**Figure 3.** ETa distribution (1981–2010 average) before (**a**) and after (**b**) improvement.

**Figure 4.** Comparison of the improved ETa values (ETanew\_simu) with the observed and GLDAS ETa values.

Over the past 58 years (1960–2017), the ETa trend was roughly bounded by 103◦ E, with ETa increasing to the west and decreasing to the east (Figure 5a). ETa in the arid region is the smallest, with an average of 68.8 mm and a fluctuation range of 21.3–142.7 mm. ETa in the transition zone is 350.2 mm with a 79.2–485.0 mm fluctuation range. The ETa fluctuation range in the humid region is between 439.8 and 745.6 mm, with an average of 602.5 mm. Over the past 58 years, ETa in the arid region increased at an average rate of 2.9 mm·10 a<sup>−</sup>1. The amount of water expenditure in the region increased, and this increase was significant in some areas. The ETa in the humid area decreased at a rate of −1.7 mm· 10 a<sup>−</sup>1. Moreover, the ETa in the transition zone generally shows a slight overall decrease, and the regional differences are obvious (Figure 5b).

**Figure 5.** ETa trend (1960–2017) and (**a**) distribution of average values and trends in sub regions and (**b**) +indicates that the trend was significant at the 0.05 level.

### *3.2. NPP Estimation and Change Characteristics*

Figure 6 shows the estimated annual NPP before and after ETa improvement. As depicted, the NPP in China is small in the northwest and large in the southeast, which is consistent with previous study [72]. The NPP of the southern humid region obtained before the improvement of the ETa model was between 1400 and 1700 <sup>g</sup>·m<sup>−</sup>2·a<sup>−</sup>1. Precipitation is proportional to the NPP. In some regions of the southeast coast, the NPP is above 1700 g· <sup>m</sup><sup>−</sup>2·a<sup>−</sup>1. The improved NPP range was 22–1510 <sup>g</sup>·m<sup>−</sup>2·a<sup>−</sup>1. The region of maximum NPP shifts northward and is located south of the Yangtze River. The annual average NPP was above 1400 <sup>g</sup>·m<sup>−</sup>2·a<sup>−</sup>1. In arid regions, water has a positive effect on vegetation productivity, which means that productivity increases with improved water conditions.However, in humid regions with sufficient water supply, NPP tends to be saturated and is no longer controlled by water [73]. In addition, this region is the cloudiest region in China [74], which is generally proportional to the light stress on vegetation growth. In coastal regions with abundant rainfall, vegetation growth is more likely to be regulated by radiation. Before the improvement, the ETa model did not consider the energy constraint in the south, the estimated NPP was overly dependent on precipitation, and the estimated values were too large. The improved NPP better reflects the response of vegetation growth to the regional climate.

**Figure 6.** NPP distribution before (**a**) and after(**b**) improvement.

A comparison between the estimated NPP values (average values from 2000 to 2017) and the MOD17A3 multiyear average data shows that the estimated NPP after improvement is significantly correlated with the MOD17A3 NPP (R = 0.67, *p* < 0.001) (Figure 7). In the arid region, the MOD17A3 NPP was larger than the estimated NPP. However, in the humid region, the MOD17A3 NPP was relatively small. Due to estimation errors regarding reflectance, maximum light-use efficiency, and radiation, MODIS NPP products are overestimated in low-productivity regions and underestimated in high-productivity regions [75]. In addition, different methods and scale conversions can also lead to different comparisons. Therefore, the estimated NPP in this study has a certain rationality and superiority.

**Figure 7.** Comparison of estimated NPP and MOD17A3 NPP (average values from 2000 to 2017).

The distribution of the average values and trends of the NPP in the sub regions in China from 1960 to 2017 are shown in Figure 8. Over the past 58 years, the NPP increased to the west of 103◦ E, while it decreased to the east. NPP in arid regions typically increases,with a rate of 4.3 <sup>g</sup>·m<sup>−</sup>2·<sup>10</sup> a<sup>−</sup>1. NPP in the transition zone generally exhibits a slight decrease. However, the regional differences are large. NPP in the humid region typically displays a decreasing trend of −3.3 <sup>g</sup>·m<sup>−</sup>2·<sup>10</sup> a<sup>−</sup>1. The distribution of the average NPP in different climatic regions shows that the NPP gradually increases from arid to humid regions. The main vegetation types in arid regions are desert grassland and lowland meadows. The soil is severely desertified and salinized in regions with low vegetation coverage. The annual average NPP is 140.4 <sup>g</sup>·m<sup>−</sup>2·a<sup>−</sup>1. The NPP fluctuation range in the humid region is the smallest, with an average of 1287.9 <sup>g</sup>·m<sup>−</sup>2·a<sup>−</sup>1. The average NPP in the transition zone is 807.2 <sup>g</sup>·m<sup>−</sup>2·a<sup>−</sup>1, ranging from 226.6 to 1084.8 <sup>g</sup>·m<sup>−</sup>2·a<sup>−</sup>1, thereby exhibiting the largest regional difference, which is related to the complex and diverse climate types and vegetation types in the area.

**Figure 8.** NPP trend (1960–2017) and (**a**) distribution of average values and trends in sub regions and (**b**) +indicates that the trend was significant at the 0.05 level.

### *3.3. Spatial Distribution and Temporal Variation in PUE*

The distribution of the multiyear average PUE presents a "low-high-low" band from northwest to southeast (Figure 9). PUE is relatively low in arid and humid regions and is the lowest in extremely arid and extremely humid regions. The transition zone exhibited the highest PUE. PUE reached its highest value of 2.2 <sup>g</sup>·m<sup>−</sup>2·mm<sup>−</sup><sup>1</sup> in the area where the annual precipitation was 414 mm. The regional differences in PUE distribution are closely related to the regional topography, landform, and water expenditure modes. Arid regions have sparse precipitation, sufficient energy, and low and sparse vegetation, and water is

mostly spent in the form of soil evaporation. Therefore, vegetation PUE is low. Humid regions have abundant precipitation, but there are many rainstorms of large intensity [76]. Precipitation is dissipated in the form of runoff, canopy interception, and soil evaporation, which may produce more ineffective water. In addition, in the humid region, there are mostly mountainous and hilly land forms with large surface runoff. Hence, PUE is also low there.

**Figure 9.** Spatial distribution of mean precipitation-use efficiency (PUE) in China during 1981–2010.

Figure 10 shows the PUE trend in China from 1960 to 2017 and the distribution of average values and trends in the sub regions. Over the past 58 years, PUE in the arid region increased at a rate of 0.014 <sup>g</sup>·m<sup>−</sup>2·mm<sup>−</sup>1·10a−1, indicating that the ability of vegetation in those regions to convert water and nutrients into biomass has increased. PUE in the transition zone was the highest, with an average of 1.92 <sup>g</sup>·m<sup>−</sup>2·mm<sup>−</sup>1, and generally showed a slight decreasing trend. In the western part of the transition zone (i.e., west of 103◦ E), PUE decreases and ecology deteriorates, which is consistent with current grassland degradation in the upper reaches of the Yellow River [77]. In the middle of the transition zone (i.e., between 103 and 120◦ E), PUE increases. PUE in the eastern part (i.e., east of 120◦ E) decreases. Most of the PUE in the humid region exhibits a decreasing trend of −0.003 g· <sup>m</sup><sup>−</sup>2·mm<sup>−</sup>1·10 a<sup>−</sup>1. In recent years, rainstorm intensity in humid regions has significantly increased, as has the proportion of rainstorms in annual precipitation [76].Rainstorms are more likely to form runoff. Hence, this change in precipitation intensity is one of the reasons for the PUE decrease in the region.

**Figure 10.** Precipitation-use efficiency (PUE) trend (1960–2017) and (**a**) distribution of average values and trends in the sub regions and (**b**) +indicates that the trend was significant at the 0.05 level.

#### *3.4. Driving Force of PUE Changes and Its Corresponding Conversion Characteristics*

Fluctuations in environmental factors have a significant effect on the PUE. Here, we selected Tmean, Rn, U, Rh, and soil moisture (SM) as influencing factors to characterize the energy, dynamic, and water statuses, respectively. Regression models between regional environmental factors and PUE were established (Table S1). Based on the trends and sensitivity analysis, the contribution of each factor to the PUE change was obtained.

Figure 11 shows the trends of environmental factors from 1960 to 2017. Over the past 58 years, Tmean in China exhibited a significant increasing trend. Air-temperature increases in the arid region and transition zone are particularly evident. Rn, U, and Rh exhibited decreasing trends. Among them, Rn decreased most significantly in the eastern transition zone and the humid region, especially in Beijing-Tianjin-Hebei and the lower reaches of the Yangtze River, which is closely related to increased aerosols in these areas [78]. U also decreased most significantly in the eastern transition zone and east of the humid region. In addition, U exhibited significant decreasing trends in most of the arid regions. Rh change is more complicated. Rh in the western Tianshan Mountains, which are located in an arid region, exhibited an increasing trend because the climate in the region tends to be warm and humid [50]. Rh decreased in most of the rest of the country. SM changes differed from east to west. The arid region and western transition zone exhibited significant SM increases, whereas the Middle Eastern transition zone and humid region exhibited SM decreases. Overall, soil tended to become arid.

**Figure 11.** Trends of each environmental factor from 1960 to 2017, (**a**) Tmean, (**b**) Rn, (**c**) U, (**d**) Rh, (**e**) SM, +indicates that the trend was significant at the 0.05 level.

PUE changes in different regions caused by changes in environmental factors are shown in Figure 12. In the arid region, PUE increased by 6.5% over the past 58 years. The Tmean increase reduced the PUE by 9.3%. The SM increase and U decrease increased the PUE by 8.4% and 6.1%, respectively. Rn and Rh increased the PUE by 1.3 and 1.9%, respectively. SM was the main driving force of regional PUE increases. In the humid region, PUE decreased by 3.5% over the past 58 years. The relative change rates of PUE caused by changes in Rn, U, Tmean, Rh, and SM were −15.3, 13.0, −3.2, −1.3, and 1.6%, respectively. Rn changes were the main driving force of regional PUE decreases. Over the

past 58 years, atmospheric aerosols in humid regions increased significantly, whereas net radiation decreased significantly [78]. As a result, vegetation photosynthesis is inhibited, vegetation productivity decreases, and PUE decreases accordingly. The impact of climate factors on PUE in the transition zone is more complicated. From the regional average sequence, the positive contribution of the Tmean increase and the U decrease to PUE offset the adverse effects of the Rn and SM decreases, which makes the PUE change insignificant. However, the PUE change in the transition zone exhibited obvious regional differences. The PUE decrease in the western plateau area was dominated by a significant SM increase. The PUE increase in the central regions was mainly due to the positive effect of a U decrease. PUE in the eastern and northeastern regions of the transition zone was dominated by Rn, which means that a significant Rn decrease can reduce the PUE. Overall, the PUE trend was dominated by water in the northern and arid regions and by energy in the southern and humid regions of China.

**Figure 12.** Contribution of environmental factors to precipitation-use efficiency (PUE). Tmean is air temperature, Rn is the net radiation, U is the wind speed at 10 m, Rh is the relative humidity, and SM is soil moisture.

The contribution of the factors is consistent or opposite depending on the factor and region. Rn exhibits a negative effect in southern humid regions and a positive effect in northern arid regions. Rh exhibits a positive effect in northern arid regions and a negative effect in southern humid regions. Furthermore, the effects of Tmean, SM, and U follow apparent "V" shapes, with positive and negative directions or turns from large to small and subsequently to large in the transition zone. To further reveal the turning characteristics of the PUE responses to water, energy, and dynamics and to clarify the precipitation climate zone where turning occurs, the multiyear average precipitation at each station was taken as a spatial climate type at every 200 mm. For example, the P100 climate type represents a spatial climate type with average annual precipitation between 0 and 200 mm. The NPP and PUE responses to changes in Tmean, SM, and U in different precipitation climate types were further analyzed.

Figure 13 shows the distribution patterns of annual NPP and PUE with ΔT, ΔSM, and ΔU changes in different precipitation climate types. Therefore, ΔT, ΔSM, and ΔU are the increments of Tmean, U, and SM, expressed as ΔX = X − Xmin, where X is T, SM, or U, and Xmin is the minimum value of each factor. In the arid region and transition zone (i.e., P100, P300, and P500), NPP and PUE were the most sensitive to various factors, especially ΔSM (Figure 13b,e). NPP and PUE increased significantly with positive ΔSM. In the humid region, NPP and PUE changed slightly with ΔSM. However, in the extremely humid area (i.e., P ≥ 1400), NPP and PUE decreased with positive ΔSM. Soil moisture in the arid region and transition zone is close to the withering humidity. Vegetation growth is affected mainly by water factors. Soil moisture in the humid region always maintains a relatively high value. However, vegetation is less sensitive to soil moisture. Hence, extremely humid soil can restrict the oxygen supply to vegetation roots and soil microorganisms due to excessive

moisture. The NPP and PUE responses to a positive ΔSM range from significantly increased to decreased between the arid and extremely humid regions, respectively. The NPP and PUE responses to ΔT and ΔU also have conversion characteristics (Figure 13a,c,d,f). Water available for evapotranspiration in arid regions is limited. Changes in NPP and PUE with ΔT were not obvious. However, in the transition zone, more obvious air temperature increases resulted in stronger water restriction for vegetation growth and smaller PUE. In the humid region, NPP and PUE were less sensitive to ΔT, but they increased slightly with positive ΔT in the extremely humid region, which reflects the promotion of vegetation growth in extremely humid regions by improved energy conditions. Wind velocity had the greatest impact on vegetation growth in the arid region and transition zone. Increased wind velocity was more conducive to evapotranspiration, thereby causing faster water loss and decreased NPP and PUE. In the humid region, a positive ΔU resulted in more favorable evapotranspiration of super humid water vapor, which indirectly promoted NPP and PUE.

**Figure 13.** Trends of annual NPP and PUE with ΔT (**<sup>a</sup>**,**d**), ΔSM (**b**,**<sup>e</sup>**), and ΔU (**<sup>c</sup>**,**f**) in different precipitation climate types.
