Assessment of climate change impact on meteorological variables of Indravati River Basin using SDSM and CMIP6 models.

Climate change, one of the most pressing issues of the twenty-first century, threatens the long-term stability and short-term variability of water resources. Variations in precipitation and temperature will influence runoff and water availability, creating significant challenges as demand for potable water increases. This study addresses a critical literature gap by employing the Statistical Downscaling Model (SDSM) to downscale Global Climate Model (GCM) outputs for the Indravati River Basin, India. Maximum temperature (T _max ), minimum temperature (T _min ), and precipitation (PCP) were statistically downscaled, improving the spatial resolution of coarse GCM data. The model established strong predictor-predictand relationships, offering enhanced local-scale climate projections for the basin. This work provides critical insights into regional climate change impacts in a previously underexplored area. The study projected the meteorological variables (T _max , T _min , and PCP) for Chindnar, Jagdalpur, and Pathagudem stations using four GCMs, namely CanESM5, MPI-ESM1-2-HR, EC-Earth3, and NorESM2-LM for the baseline period (1990-2014). The Correlation Coefficient-values (R-values) range from 0.75 to 0.91 for maximum temperature, 0.85 to 0.96 for minimum temperature, and 0.71 to 0.83 for precipitation were achieved using SDSM. The best-performed MPI-ESM1-2-HR model was used to project maximum temperature, minimum temperature, and precipitation for 2024-2054 (2040s) and 2055-2085 (2070s) under SSP4.5 and SSP8.5 scenarios using SDSM. The downscaled results revealed significant shifts in meteorological patterns, highlighting the basin's sensitivity to different socio-economic pathways and future climate conditions. The percentage monthly, seasonal, and annual variations of T _max , T _min , and PCP were analysed based on each scenario and time period to suggest remedial measures for future floods and droughts.
Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Consent for publication: Not applicable. Consent to participate: Not applicable. Ethics approval: Not applicable.
(© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)