## 5 Discussion
However, due to natural disturbance, as well as the self-adaption, in forests, Lorey's height and the FAI are apt to defy the regressions. For example, as a result of self-thinning adaption, matured or over-matured forests would definitely change SD (trees-ha\({}^{-1}\)) so that ecosystem balance is maintained, causing an increase in forest height and a decrease in forest AGB. As understood, forest AGB levels should obey a parabolic relationship between forest AGB and forest age. In this study, regression models based on measurements without forest age information would be biased, because, in practice, different forest heights exist in stands that have a similar forest AGB level but various stand densities. Additional studies should take forest stand age and forest SD into account in their analyses. Alternatively, continuous national forest inventories using a five-year interval and upcoming active spaceborne remote sensing (_i.e._, the Chinese high-resolution satellite constellation with SAR and LiDAR sensors on board) with the ability to derive multi-temporal forest vertical parameters could also be helpful for calibrating bias for local forest vertical information. According to the statistics of the dynamics of interannual forest ET and meteorological data obtained from the downscaled WRF, local forest ET is the most sensitive to a vapor pressure deficit (VPD), then temperature, precipitation, and downwelling short wave radiation (DSR). VPD, temperature, and precipitation yielded negative correlation to forest ET while DSR yielded a positive correlation. For example, for the 13 years analyzed, the highest forest ET occurred during 2003, the year with the second lowest VPD, the low temperature, the least amount of precipitation, and a sufficient DSR; while the lowest forest ET was determined for 2009 that had the second highest VPD and temperature, moderate precipitation, and a low DSR. As shown in Table 3, the ratio of ET to precipitation during 2003 was higher than one, implying that during this driest year soil moisture contributes the most positive \"green water\" (the water mainly used by the ecosystem itself [84]) to the forest ecosystem. In forested areas with altitudes from 2600 to 3300 m, surface soil with a field water capacity of more than 50% [85] is largely covered by moss and litter with a very high porosity and a low bulk density, resulting in a high evapotranspiration rate and hydraulic conductivity. Thus, the _Picea crassifolia_ forest has the greatest potential water retention capacity [86]. The water storage capacity of the soil in this area was determined to be 39.14%, and 37.38% higher within the _Picea crassifolia_ forest than in _Sabina przevalsk_ forest and shrubs, respectively, at a similar soil depth [87]. The higher soil water content may result in a higher plant transpiration rate, as indicated in the study of [PERSON] _et al._, [85] who stated that the relationship between sap flow and soil moisture content was a logistic function. Overall, the performance of the SEBS in this study is promising and the results are comparable to those of other studies [49, 88, 89, 90]. For example, based on the input data retrieved from multiple sensors onboard NASA Earth Observing Satellites (EOS) and the AVHRR sensor, as well as model-derived surface pressure and winds from NASA's Global Modeling and Assimilation Office, daily global ETs were estimated by [PERSON] _et al._[88] using the SEBS, the Penman-Monteith (P-M), and the Priestley-Taylor (P-T) models for the years 2003-2006. Evaluations using an inferred ET estimate based on a long-term water balance residual of precipitation minus runoff for large river basins and on a global scale yielded a good correlation (the mean correlation--the [PERSON]'s \(\tau\) from 0.72 to 0.79). The study of [PERSON] _et al._[89], that reported long-term global ET estimations for 1984-2007 using the SEBS, P-M, and P-T models, indicated a downward trend for global ET after 1998.