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

TL;DR

This study employs statistical downscaling with climate model data to project future precipitation and temperature changes in the Krishna River Basin, revealing increased rainfall, temperature rise, and extreme events under various climate scenarios for effective planning.

Contribution

It applies a calibrated statistical downscaling model to project climate variables for the 21st century in the Krishna River Basin using multiple RCP scenarios, providing detailed future climate insights.

Findings

KRB will become wetter across all seasons.

Average temperatures are projected to increase.

Extreme precipitation events are expected to become more frequent.

Abstract

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 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 is calibrated using 30-years (1961-1990) of data and subsequently validated for 15-years (1991-2005). Upon perceiving the satisfactory performance, the SDSM is further used for projecting the predictand variables (PRECP, T max and T min ) for the 21 st century considering three Representative Concentration Pathway (RCP) scenarios viz. RCP2.6, RCP4.5 and RCP8.5. The future period is divided into three 30-year time slices named epoch-1 (2011-2040), epoch-2 (2041-2070) and epoch-3 (2071-2100) respectively. Further, 1976-2005 is considered as baseline period and all the future results are compared with this data. The results were analysed at various temporal scales, i.e., monthly, seasonal and annual. The study 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 90 th and 95 th percentile values. It is noticed that the extreme (90 th and 95 th percentiles) are going to increase. There are events more than extreme values. The outcome of this study can be used in flood modelling for the KRB and also for the modelling of future irrigation demands along with the planning of optimal irrigation in the KRB culturable command area.