Assessment of Climate Change Impacts on the Precipitation and Temperature: A Case Study on Krishna River Basin, India

In this study, the statistical downscaling model (SDSM) is employed for downscaling the precipitation (PREC), maximum temperature (T-max), and minimum temperature (T-min) over the Krishna River Basin (KRB). The Canadian Earth System Model, version 2 (CanESM2) General Circulation Model (GCM) outputs were considered as predictor variables. First, the SDSM was calibrated using the data for a 30-year period (1961-1990) and subsequently validated with the data for a 15-year period (1991-2005). Upon perceiving a satisfactory performance, the SDSM was then used for projecting the predictand variables (PREC, T-max, and T-min) for the 21st century considering three representative concentration pathway (RCP) scenarios viz. RCP2.6, RCP4.5, and RCP8.5. The future period was divided into three 30-year time slices named epoch-1 (2011-2040), epoch-2 (2041-2070), and epoch-3 (2071-2100), respectively. The period 1976-2005 was considered as baseline period and all the future results were compared with this data. The results were analysed at various temporal scales, i.e., monthly, seasonal, and annual. The study has reveals that the KRB is going to become wetter during all the seasons. The results are discussed for the worst-case scenario, i.e., RCP8.5 epoch-3. The average annual maximum and minimum temperature is expected to increase. The extreme event analysis is also carried out considering the 90th and 95th percentile values. It is noticed that the extreme (90th and 95th percentiles) are going to increase. There are extreme events that go beyong extreme values. The outcome of this study can be used in flood modeling for the KRB and also for the modeling of future irrigation demands along with the planning of optimal irrigation in the KRB culturable area.