Drought forecasting using the stochastic model in the Betwa river basin, India

A drought is a severe event that can occur in any part of the world and causes significant damage to the environment and human lives. It is a random phenomenon, and its severity and occurrence are generally studied through stochastic models. The drought information before the occurrence of a drought event is helpful for mitigation measures and strategies. Drought forecasting is necessary for the planning and management of water resources. In this study, the auto-regressive integrated moving average (ARIMA) linear stochastic model is used to forecast drought. This study concerns monitoring the drought in the Betwa river basin, India, based on 44 years of rainfall data from 1970 to 2014. The standardized precipitation index (SPI) is used for the severity estimation of drought events in the Betwa river basin. The most suitable ARIMA model is used to predict the rainfall and compared with the observed rainfall. ARMA (2, 0) is found to the best-suited model for this study among the candidate models (ARMA (p, q)) based on the maximum likelihood estimate and MSE. The drought severities of the estimated rainfall are lie in the range of the observed rainfall severities. It is observed that the present study can be used for a drought preparedness plan to ensure sustainable planning and management of water resources within the river basin.