Mountain snowpack is an important water resource in high altitude and latitude regions where terrain is typically complex. However, only limited information has been published on snowmelt pathways in such regions and their de facto contributions to streamflow and soil moisture. To fill this knowledge gap, this study integrated a snowmelt pathway tracking algorithm to the high-resolution physically based Distributed Hydrology Soil Vegetation Model (DHSVM) to track snowmelt movement and to quantify snowmelt contributions during surface hydrologic processes. A simple reservoir operation scheme was also integrated into the model. The modified model was applied to a dammed mesoscale watershed in the northeastern region of the Tibetan Plateau, China, to explore relevant snow and reservoir effects. Results show that both the annual snow contribution to soil moisture (SC-SM) and the snow contribution to streamflow (SC-S) significantly decreased between 1965 and 2019. On a monthly scale, SC-SM amplitudes were highest in the upper soil layer, while peaks in deeper layers lagged behind those in upper layers. Moreover, mean monthly SC-S from all stations revealed bimodal distributions that corresponded to the snowfall season. Finally, reservoir regulation measures only exerted minimal impacts (≤2.0 %) on SC-S. If current climate change rates continue on the same trajectory, mountain snowpack reductions will be the primary cause for decreases in monthly and annual streamflow at the outlet of this basin. To mitigate climate change impacts, better water resource management is needed in this watershed.