## 3 Results and Discussion  
### Temporal Patterns of Hydrological Indicators  
Volumetric soil water content (VSWC) was affected by precipitation, melting runoff, soil temperature and other hydrological or meteorological factors. The model was able to capture the reasonable magnitude and fluctuation of VSWC during most parts of the growing seasons. Figure 4 reveals that the VSWC was between 0.25-0.45 from day of the year (DOY) 170 to DOY 300 and rapidly responded to daily precipitation at the Arou station. The VSWC reached to field capacity (0.4) around DOY 190 of both years because of the adequate water input from snow melting and rainfall. While experiencing days lacking precipitation (DOY 210-230 of 2013; DOY 190-215 of 2014), the VSWC dropped under the permanent wilting point (0.27). And during this time, ecosystem evapotranspiration \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Parameter Names** & **Unit** & **Conifer** & **Deciduous** & **Grassland** & **W wetland** \\ \hline Canopy clumping index & - & 0.5 & 0.8 & 0.9 & 0.9 \\ Maximum stomatal conductance & m/s & 0.0016 & 0.005 & 0.0055 & 0.005 \\ Root decay rate & & 0.94 & 0.96 & 0.95 & 0.93 \\ Maximum carbovolation rate at 25 \({}^{\circ}\)C & m/mol/m\({}^{2}\)/s & 33 & 60 & 40 & 33 \\ Precipitation interception coefficient & mm/LAI/day & 0.2 & 0.3 & 0.25 & 0.1 \\ Max. leaf N content & \% & 1.6 & 1.8 & 1.6 & 1.2 \\ Ration of g\({}_{\text{s},\text{max}}\) of overstory to understory & - & 1.7 & 0.5 & 1.2 & 1 \\ Optimum temperature for photosynthesis & \({}^{\circ}\)C & 20 & 25 & 20 & 20 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Biophysical parameters of major landscape types in the Upper Heihe watershed. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Soil Hydraulic Parameter** & **Unit** & **Clay** & **Loam** & **Clay Loam** & **Sandy Loam** \\ \hline Field capacity & - & 0.4 & 0.27 & 0.3 & 0.23 \\ Wilting point & - & 0.27 & 0.12 & 0.2 & 0.1 \\ Porosity & \% & 0.457 & 0.463 & 0.464 & 0.453 \\ Max. surface conductance & mm/s & 0.2 & 0.8 & 0.5 & 1 \\ K\({}_{\text{sat},\text{ver}}\) & m/day & 0.11 & 1.8 & 1.2 & 3.2 \\ K\({}_{\text{sat},\text{hor}}\) & m/day & 10 & 2.5 & 1.5 & 3.5 \\ K\({}_{\text{s}}\) decay rate & m\({}^{-1}\) & 0.02 & 0.04 & 0.029 & 0.042 \\ The exponent of the & & & & & \\ Brokes–Corey parameter & - & 11.4 & 5.39 & 5.5 & 4.9 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Hydraulic properties of four main soil types in the Upper Heihe watershed. and lateral water fluxes were the major reasons for soil water losses. There was a dense precipitation after DOY 230 which made the VSWC remain over field capacity. On the other hand, 2013 experienced a prolonged drier autumn that induced a gentle but continuous fall down of VSWC until below the permanent wilting point. While the model overestimated the VSWC during spring and winter when the soil was in a frozen state, it was probably because the model did not take the soil freezing-thawing process into consideration. During the soil frozen period, the permeability would decrease and soil hydraulic characteristics would consequently change. Rather than infiltrated into soil profile, most of the precipitation would drain out as surface overland flow. The lack of these dynamic transformations in the model domain might trigger an unrealistic estimation for soil moisture state. The study area is located in the cold alpine region where the negligence of melting runoff from glaciers and accumulated snowpack might cause the underestimation of soil water especially during spring and early summer. Figure 5 shows the temporal patterns of two years of lateral water fluxes in the Arou site. On account of the lack of validation data, we only compared it with the daily precipitation. The model captured a rapid response of lateral water fluxes to precipitation in spring and early summer. Under a denser precipitation, the lateral water fluxes of 2014 were much higher than that of 2013.