Modelling and prediction of coastal Andhra rainfall using ARIMA and ANN models

Abstract

Precipitation and climate forecasting in the Coastal Andhra are extremely needed for the agriculture and water resource management system. Most challenging factor in this study is nature of rainfall data. Due to drastic climatic conditions, the rainfall becomes nonlinear and dynamic in nature. Conventional statistical models are not enough to predict the actual rainfall trend, which require contemporary computer modelling and simulation techniques for accurate prediction. In this paper, we are using both traditional statistical technique autoregressive integrated moving average (ARIMA) and contemporary AI model Artificial Neural Network (ANN) for prediction of rainfall. In order to evaluate the forecasting efficacy, we used of 117 years of mean annual rainfall data from year 1901 to 2017 of Coastal Andhra (India). The models were trained with 100 years of annual rainfall data. The ARIMA and the ANN methods are used to the data to draw the accuracy. The accuracy of the model was assessed by using remaining 17 years of data. The study explains that ANN model can be used as a significant prediction tool to forecast the rainfall when compare with ARIMA model.