Extreme climate index estimation and projection in association with enviro-meteorological parameters using random forest-ARIMA hybrid model over the Vidarbha region, India

Abstract

This study aims to estimate and analyse extreme climate indices such as standardised precipitation index (SPI) coupled with enviro-met (air pollutants and meteorological) parameters over the Vidarbha region from 1980 to 2019. Seasonal SPI, also known as the draught index, is derived from rainfall data using the R language. An attempt is made to determine the best combination of enviro-met on SPI using the random forest (RF) models. The study region is divided into four zones to assess the microclimatic impact on the forecast model. Three sets of data combinations, viz., meteorological and air pollution parameters, are applied for SPI prediction using RF. The autoregressive integrated moving average (ARIMA) model is also used for a future scenario projection. It is observed from the projection results that the drought severity is enhancing with time. The drought severity scale from 1980 to 1989 is found to be between - 1 and 1, but the scale increases from 1990 to 2019 (- 3). From 1990 to 2019, SPI's negative (-) scale has become more prominent in all Vidarbha regions. These trends are indicative of drought severity and will have a significant impact on both life and property.