Abstract

Alpine basins provide the main water resources and sustain socioeconomic development in arid regions. Understating how vegetation and elevation affect the water yield is crucial for sustainable water management of arid regions. However, the scarce observations, heterogeneous hydroclimatic conditions, and oversimplifications of the energy and biogeophysical processes in traditional hydrological models limit the comprehension of hydrological processes associated with water yield over alpine basins. This study combines the fully distributed WRF-Hydro model with the Budyko framework to characterize the water yield of an alpine basin named Xiying River Basin (XRB) located in Northwest China. Results show that WRF-Hydro driven by the remote-sensing-based products was able to reproduce both observed streamflow and evapotranspiration (ET) in the XRB. The ratio of transpiration to ET was considerably underestimated when only calibrating streamflow. Such underestimation can be solved by calibrating parameters related to soil surface resistance and leaf conductance. Additionally, for the dominant vegetation types (i.e., closed shrublands and grasslands) in the XRB, we found that closed shrublands have a lower water yield capacity than grasslands. Closed shrublands have a stronger ET rate, resulting in stronger soil moisture consumption, lower antecedent soil moisture, and higher soil water deficit, causing higher infiltration loss during rainfall events and lower water yield. Moreover, the water yield capacity increases with the increasing elevation, because the precipitation increases while the ET decreases as the elevation rises, and the topographical slope increases, resulting in lower infiltration, lower baseflow index, and higher water yield capacity. Our results also indicate that afforestation should not be encouraged for grasslands and closed shrublands in areas lower than 2800 m and 3200 m, respectively. Overall, this study provides scientific support for vegetation afforestation planning in the alpine regions.

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