An Assessment of Future Predictions of Rainfall Using GCM Projections in the Western Ghats Region of India

The present study has been taken up to quantify the possible impacts of climate change on the climate variables using the outputs of the global climate model dataset over the Sagar and Kokkarne catchments. The baseline period considered is 30 years (1991-2020), and the daily rainfall dataset is used. The rainfall dataset for the future period is derived from five selected GCMs (Global Circulation Model) datasets under the (Representative Concentration Pathway) RCP 4.5 scenario for the period (2021-2050). The mean, standard deviation, and coefficient of variation of yearly rainfall are determined to check the rainfall variability using statistical analysis. The ensemble rainfall mean values of the five GCMs suggest that the uncertainty in the projected results is reduced by considering the cluster of GCMs. The minimum rainfall for the future period has shown an increasing trend (42.3 % 10.5 %) whereas maximum rainfall has shown decreasing trend (52.44 %, 15.28 %) for Sagar and Kokkarne catchments respectively. The future predicted results show that the percentage change in Ensemble mean annual rainfall for the period 2021-2050 with reference to rainfall data of the baseline period (1991-2020) is depicting an increasing trend of 2.52 % and 4.12 % for Sagar and Kokkarne catchments respectively. Monsoon arrival is earlier in the Kokkarne catchment as compared to the Sagar catchment. The highest positive percentage change in mean annual rainfall of 24.89 %, 10.25 % is projected by MPI-ESM-LR GCM, and the Highest negative percentage change in mean annual rainfall of -28.49 %, -9.19 % is projected by ACCESS1.0 GCM for Sagar and Kokkarne catchments respectively. This analysis will provide useful information for water resources planning engineers, research scientists, and farmers to assess the water availability in the region and create storage if essential.