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Reliable precipitation data in the Himalayas are essential for the study of the water resources, the evolution of glaciers, and the present and future climate. Although several types of precipitation datasets are available for the Himalayan region, all of them have limitations, which hamper the quantification of the precipitation fluxes at high elevations. This study compares different types of precipitation datasets issued from (i) in situ data, (ii) satellite-based data [TRMM, Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS)], and (iii) a reanalysis product [High Asia Refined analysis (HAR)] for a small headwater catchment at high elevations (Upper Dudh Koshi, Nepal) and assesses the impact of the precipitation uncertainty on the result of the modeling of the glacio-hydrological system. During the analyzed period from 2010 to 2015, large differences between the precipitation datasets occur regarding annual amounts (ranging from 410 to 1190 mm yr−1) as well as in seasonal and diurnal cycles. The simulations with the glacio-hydrological model Distributed Hydrological Soil Vegetation Model–Glaciers Dynamics Model (DHSVM-GDM) show that the choice of a given precipitation dataset greatly impacts the simulated snow cover dynamics and glacier mass balances as well as the annual, seasonal, and diurnal streamflows. Due to the uncertainty in the precipitation, the simulated contribution of the ice melt to the annual outflow also remains uncertain and simulated fractions range from 29% to 76% for the 2012–13 glaciological year.

Evaluation of Gridded and In Situ Precipitation Datasets on Modeled Glacio-Hydrologic Response of a Small Glacierized Himalayan Catchment