The Hindu Kush-Himalayan region is an important global freshwater resource. The hydrological regime of the region is vulnerable to climatic variations, especially precipitation and temperature. In our study, we modelled the impact of climate change on the water balance and hydrological regime of the snow dominated Kaligandaki Basin. The Soil and Water Assessment Tool (SWAT) was used for a future projection of changes in the hydrological regime of the Kaligandaki basin based on Representative Concentration Pathways Scenarios (RCP 4.5 and RCP 8.5) of ensemble downscaled Coupled Model Intercomparison Project's (CMIP5) General Circulation Model (GCM) outputs. It is predicted to be a rise in the average annual temperature of over 4°C, and an increase in the average annual precipitation of over 26% by the end of the 21st century under RCP 8.5 scenario. Modeling results show these will lead to significant changes in the basin's water balance and hydrological regime. In particular, a 50% increase in discharge is expected at the outlet of the basin. Snowmelt contribution will largely be affected by climate change, and it is projected to increase by 90% by 2090.Water availability in the basin is not likely to decrease during the 21st century. The study demonstrates that the important water balance components of snowmelt, evapotranspiration, and water yield at higher elevations in the upper and middle sub-basins of the Kaligandaki Basin will be most affected by the increasing temperatures and precipitation.

Estimation of the flow generated in the Brahmaputra river basin is important for establishing an effective flood prediction and warning services as well as for water resources assessment and management. But this is a data scarce region with few and unevenly distributed hydrometeorological stations. Five high-resolution satellite rainfall products (CPC RFE2.0, RFE2.0-Modified, CMORPH, GSMaP, and TRMM 3B42) were evaluated at different spatial and temporal resolutions (daily, dekadal, monthly, and seasonal) with observed rain gauge data from 2004 to 2006 to determine their ability to fill the data gap and suitability for use in hydrological and water resources management applications. Grid-to-grid (G-G) and catchment-to-catchment (C-C) comparisons were performed using the verification methods developed by the International Precipitation Working Group (IPWG). Comparing different products, RFE2.0-Modified, TRMM 3B42, and CMORPH performed best; they all detected heavy, moderate, and low rainfall but still significantly underestimated magnitude of rainfall, particularly in orographically influenced areas. Overall, RFE2.0-Modified performed best showing a high correlation coefficient with observed data and low mean absolute error, root mean square error, and multiple bias and is reasonably good at detecting the occurrence of rainfall. TRMM 3B42 showed the second best performance. The study demonstrates that there is a potential use of satellite rainfall in a data scarce region.