###### Abstract
Further, many studies have shown that VPD is insufficient to fully explore the spatiotemporal heterogeneity of water stress on plant photosynthesis [17; 18; 28]. Therefore, it is difficult to directly using VPD to accurately indicate the water stress for alpine plants on the QTP. The LSWI is an RS index reflecting the impact of canopy water content on plant photosynthesis. However, the instantaneous vegetation water status observed by RS cannot determine whether the vegetation is really in a state of water shortage because the same canopy water may be caused by stomatal closure due to a real water shortage or by high soil moisture content with a large stomatal cycle for alpine plants [27]. Therefore, LSWI cannot accurately reflect the real state of the water received by the photosynthesis of alpine vegetation [17; 29; 30; 31]. Studies have shown that SM determines the ecosystem's carbon sink [32; 33], and the SM rather than the stomatal conductance limits plant photosynthesis [34; 35], particularly for the alpine ecosystem, where the root system is more developed than that of low-altitude vegetation [27]. The effect of SM on the NPP has been estimated using a normalized method [36; 37], a one-layer bucket method [38; 39; 40], a contextual approach [41], a machine learning method [32], etc. These methods quantified the constraints on the NPP, probably by directly using SM. However, reliable and continuous global or regional RS soil moisture products with relatively high resolution are currently lacking [42; 43; 44; 45]. The VPD is still the most commonly used index to quantify the impact of water stress [46]. VPD can indicate the impact of water stress on plant photosynthesis from stomatal conductance changes. It can also indicate the impact of soil moisture due to its close relationship with adjacent atmospheric moisture [47]. However, this link is compromised because it includes periods when the atmospheric indicators are independent of the soil moisture. For example, at night, the temperature drops rapidly and the relative humidity (RH) tends to be 100% due to the cooling temperature, while at the same time, the soil moisture stays relatively stable without rapid changes [46]. The strongest link between the atmosphere and the soil moisture is at noon under convective conditions with strong vertical mixing and the influence of surface conditions on the atmosphere [46]. Thus, using the atmospheric indicators during noon, which correspond to the maximum VPD (VPD\({}_{\text{max}}\)) and minimum relative humidities (RH\({}_{\text{min}}\)), is better correlated with the soil moisture conditions than their averages. In light of this, the purpose of this work is to present a new, more accurate water stress model based on the indication of soil moisture content compared with previous studies. The objectives of this paper are as follows: (a) to introduce a new model for measuring water stress that describes the impact of water content as a function of RH\({}_{\text{min}}\) and VPD\({}_{\text{max}}\); (b) to build an alpine vegetation photosynthesis model (AVPM) under the framework of the MOD17 NPP model and introduce the new water stress model to the AVPM; (c) to perform a spatio-temporal analysis of the NPP on the TRH region so that the grassland growth status from 2001 to 2020 can be clearly quantified.