Complementary use of multi-model climate ensemble and Bayesian model averaging for projecting river hydrology in the Himalaya

Considering the sensitivity and importance of water resources in the Himalayan uplands, this study intended to assess the hydrological responses to climate change in the Jhelum basin. Representative concentration pathway (RCP)-based projections from six dynamically downscaled global circulation models (GCMs) were bias-corrected for developing the climatic projections over the twenty-first century. The uncertainty associated with GCM outputs was addressed by using multi-model ensemble projections developed through Bayesian model averaging (BMA) technique. The assessment reveals that compared to the baseline (1980-2010) values, the annual mean maximum temperature in the basin will rise by 0.41-2.31 & DEG;C and 0.63-4.82 & DEG;C, and the mean minimum temperature will increase by 1.39-2.37 & DEG;C and 2.14-4.34 & DEG;C under RCP4.5 and RCP8.5, respectively. While precipitation is expected to decrease by 7.2-4.57% and 4.75-2.47% under RCP4.5 and RCP8.5, correspondingly. BMA ensemble projections were coupled with the Soil and Water Assessment Tool (SWAT) to simulate the future hydrological scenarios of the drainage basin. With the changing climate, the discharge of rivers in the Jhelum basin is expected to witness reductions by about 23-37% for RCP4.5 and 19-46% for RCP8.5. Moreover, the water yield of the basin may also exhibit decreases of 17-25% for RCP4.5 and 18-42% for RCP8.5. The projected scenarios are likely to cause water stress, affect the availability of water for diverse uses, and trigger transboundary water-sharing-related conflicts. The impact of climate change on discharge demands early attention for the formulation of mitigation and adaptive measures at the regional level and beyond.