Abstract
The montane watersheds are often data-scarce, creating difficulty in modeling the crucial hydrological simulations. A good modeling approach with the least prediction uncertainity is important in predicting the streamflow simulations in such data scarce watersheds. In this study , we applied SWAT model in two high-altitude mountainous watersheds (Liddar-the glaciated and Sandran-non glaciated) of Western Himalayas. Our results indicate that calibration at different sites responds with different simulated streamflow varing spatially from site to site as well as from watershed to watershed. Our analysis suggests that runoff processes, orographic controls, and snow processes are more dominant processes in the glaciated watershed. However groundwater processes are significantly similar in both the watersheds. Temporally, simulated streamflow processes in these watersheds respond with steep rising and falling limbs from May to September but show a flatter recession from October to April. This results from the onset of snowmelt discharge, creating peak spikes during spring and summer flows. This is followed by low flow condition (baseflow) reducing the peak flow from autumn to winter. During the extremely low flow conditions and flood events the model overestimates and underestimates the streamflow respectively. The parameter uncertainty in terms of P_factor and R_factor was relatively lower in the glaciated watershed compared to the non-glaciated watershed. However, this multi-site approach resulted in more realistic parameter values which better represents the spatially influenced hydrological simulations. The results suggest to spatially calibrate and validate the SWAT model in large mountainous watersheds to improve the hydrological simulations.
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