Performance Evaluation of CMIP6-GCMs Using Three Spatial Interpolation Methods Over Catchment Area of Koyna Reservoir, India

Abstract

The present study evaluates the performance of general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and spatial interpolation methods over the catchment area of the Koyna reservoir in Maharashtra, India. In this study, daily precipitation data from 15 selected GCMs for the period 1980 to 2014 is downloaded from Copernicus Climate Data Store and interpolated using bilinear, bicubic and inverse distance weighing method at the locations of 8 rain gauge stations in the catchment area of Koyna reservoir. The performance of the selected GCMs and interpolation methods is evaluated using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE) and correlation coefficient (r) as performance indicators. The suitability of the GCMs is determined by comparing the interpolated values at the selected sites with the actual observed daily precipitation data measured and maintained by the Water Resources Department, Government of Maharashtra. For all selected stations, least MAE and RMSE values are obtained using inverse distance weighing method that ranges between 9.21-15.11 mm and 21.97-40.95 mm respectively. The value of correlation coefficient shows slight improvement with inverse distance weighing method with 0.47 as the highest correlation coefficient. The study highlights MIROC-ES2L, CNRM-CM6-1, CNRM-ESM2-1, INM-CM4-8 and EC-Earth3-Veg-LR as the most suitable GCMs and the inverse distance weighting method as the most suitable interpolation method for the study area. The study can be continued with the selected GCMs and interpolation method for predicting future rainfall to develop strategies to mitigate the adverse impacts of floods and droughts in future years.

Keywords

• general circulation models (gcms)
• coupled model intercomparison project
• performance indicators
• spatial interpolation methods