Abstract
Comprehending the impact of climate change on surface runoff is imperative to safeguard against excessive inundation vulnerability and management. This study estimates climate change effects on surface runoff using an ensemble of five climate models and the WetSpass-M model for the baseline period (1986 to 2015), mid-term (2031 to 2060), and long-term (2071 to 2100) periods. The downloaded climate models (CNRM-CM5, GFDL-ESM2M, IPSL-CM5A-MR, MPI-ESM-LR, and NorESM1-M) were downscaled by a dynamic downscaling technique and bias corrected by linear scaling. The model performance statistical indices, such as R2 (0.90 and 0.85), NSE (0.95 and 0.89), and RMSE (4.19 and 9.94), were obtained by comparing the WetSpass-M model and filtered baseflow and direct runoff, respectively. The mean rainfall and temperature are projected to increase compared to the baseline period. The overall average monthly runoff has been rising with 8.70%, 18.22%, 6.53%, and 36.09% for RCP4.5 (MidT4.5) for the mid-term, RCP4.5 (LongT4.5) for the long-term, RCP8.5 (MidT8.5) for the mid-term, and RCP8.5 (LongT8.5) for the long-term, respectively. Seasonally, surface runoff is projected to increase throughout the entire season, except for autumn. Autumn season’s surface runoff is projected to drop by 23.56%, 38.85%, 29.12%, and 43.02% for MidT4.5, LongT4.5, MidT8.5, and LongT8.5, respectively. Annually, surface runoff will increase by 8.3%, 31.20%, 1.80%, and 49.30% for the MidT4.5, LongT4.5, MidT8.5, and LongT8.5, respectively. Moreover, the findings conclusively underscored a dramatically rising surface runoff due to climate change, causing inundation in central and downstream watershed areas. Therefore, this increasing surface runoff will potentially affect daily life and weaken agricultural productivity; thus, reforestation and water conservation measures are required to lessen the adverse effects.