Besides, lack of fit test and normalized BIC confirms all the models were fitted satisfactorily. Residuals were found white noise at almost all stations. A validation check for each station was performed on residual series. The best SARIMA model was chosen based on the RMSE and normalized BIC criteria. In this study, univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to forecast monthly rainfall for twelve months lead-time for thirty rainfall stations of Bangladesh. Rainfall forecasting could play a significant role in the planning and management of water resource systems also.

Therefore, an early indication of possible rainfall can help to solve several problems related to agriculture, climate change and natural hazards like flood and drought. In Bangladesh, agriculture largely depends on the intensity and variability of rainfall. Rainfall is one of the most important phenomena of the natural system.