Rainfall Modeling and Prediction using Neural Networks: A Case Study of Maharashtra

Abstract

In different parts of the globe, accurate rainfall forecasting models are needed to forecast rainfall in real-time during the typhoon season to prevent disasters caused by heavy rainfall in the region. The current study developed a time series based analysis technique to predict precipitation during the monsoon season. As evidenced by the investigations in this study, a data-driven technique has considerable scope for predicting the future variables and patterns from existing data, mainly when applied to complex and challenging natural phenomena such as rainfall. The ANN-based technique has an immense potential to predict rainfall data using lagged time series analysis model. We have investigated rainfall patterns, their variability in Maharashtra state and future rainfall prediction through the present study. The neural network autoregression model put forth is a promising technique for rainfall prediction. The model's performance is evaluated concerning error rate and model fit and exhibits reasonably good performance.