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Understanding the present water budget in Himalayan Basins is a challenge due to poor in situ coverage, incomplete or unreliable records, and the limitations of coarse resolution gridded data set. In the study, a two-way coupled implementation of the Weather Research and Forecasting (WRF) Model and the WRF-Hydro hydrological modeling extension package (WRF/WRF-Hydro) was employed in its offline configuration, over a 10year simulation period for a mountainous river basin in North India. A triple nest is employed, in which the innermost domain had 3km for atmospheric model grids and 300m for hydrological components. Two microphysical parameterization (MP) schemes are quantitatively evaluated to reveal how differently MP influences orographic-related precipitation and how it impacts hydrological responses. The WRF-Hydro modeling system shows reasonable skill in capturing the spatial and temporal structure of high-resolution precipitation, and the resulting stream flow hydrographs exhibit a good correspondence with observation at monthly timescales, although the model tends to generally underestimate streamflow amounts. The Thompson Scheme fits better to the observations in the study. More importantly, WRF shows that for high-altitude precipitation, a high bias is exhibited in winter precipitation from WRF, which is about double to triple that as estimated from valley-sited rain gauges and remotely sensed precipitation estimates from Tropical Rainfall Measuring Mission and Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation. Given the full annual cycle pattern and amount in high-altitude precipitation and the statistical correspondence in discharge, it is concluded that the WRF-Hydro modeling system shows potential for explicitly predicting potential changes in the atmospheric-hydrology cycle of ungauged or poorly gauged basins.

Plain Language Summary Understanding the present water budget in Himalayan Basins is a challenge due to poor in situ coverage, incomplete or unreliable records, and the limitations of coarse resolution gridded data set. In a Himalayan headwater river basin, the Weather Research and Forecasting (WRF)-Hydro modeling system shows reasonable skill in capturing the precipitation and the resulting stream flow hydrographs exhibit a good correspondence with observation at monthly timescales. More importantly, WRF shows that for high-altitude precipitation, a high bias is exhibited in winter precipitation from WRF, which is about double to triple that as estimated from valley-sited rain gauges and remotely sensed precipitation estimates from both Tropical Rainfall Measuring Mission and Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation. Given the full annual cycle pattern and amount in high-altitude precipitation and the statistical correspondence in discharge, it is concluded that the WRF-Hydro modeling system shows potential for explicitly predicting potential changes in the atmospheric-hydrology cycle of ungauged or poorly gauged basins.