ABSTRACT Future streamflow projections are vital for the formulation of effective water resource management strategies and policies for the water‐dependent sectors. Reliable streamflow projections are critical for efficient water resources planning to facilitate better mitigation measures for extreme hydrological hazards such as floods and droughts. Cascading uncertainties in climate and hydrological models due to incorporation of different parametrization, boundary conditions, hydrological processes, model structures, erroneous data and so forth, adds complexity in the adaptation planning. Hence, testing of more than one climate and hydrological models becomes critical. The research provides improved projections of future streamflow, essential for water resource management in various basins throughout the Indian subcontinent. Best‐performing hydrological model and general circulation model (GCM) were identified for 128 river basins of India. Further, impact of climate change on future streamflow were assessed under altered climatic regimes represented by SSP2‐4.5 and SSP5‐8.5 scenarios. Uncertainty in the flow regimes were examined using four hydrological models—MILC, GR4J, HYMOD and HBV along with 12 GCMs and their ensemble mean. Furthermore, 13 hydrological indicators representing flow regime characteristics were used to analyse the changes in the future streamflow. MILC was found to be the best‐performing model for 43.71% of the basins, followed by GR4J, HBV and HYMOD, for 22.52%, 19.87% and 13.90% of the basins, respectively. Among all the analysed GCMs, BCC‐CSM2‐MR, TaiESM1, CMCC‐ESM2, NorESM2‐MM and NESM‐3 were found to be five top performing models. The future hydrological indicators projected an increase in the high flow frequency and duration, highlighting greater flood risks, whereas uncertainty existed for the low flow events, with some basins experiencing prolonged dry spells, whereas others faced shorter and intermittent droughts. Most basins are projected to have an increase in the runoff ratio and zero‐flow events with a decrease in the baseflow index and delay in the half‐flow date.
Sharma et al. (2026) studied this question.