Avinash Yadu*, Anosh Graham and Jyotish Kumar Sahu
Department of Environmental Sciences and NRM, College of Forestry, Sam Higginbottom University of Agriculture, Technology & Sciences Allahabad-211007,Uttar Pradesh, India.
Email:anoshgraham@gmail.com
Received-05.11.2019, Revised-26.11.2019
Abstract: The prediction of Rainfall on monthly and seasonal time scales is not only scientifically Challenging but is also important for planning and devising agricultural strategies. Various research groups attempted to predict rainfall on a seasonal time scales using different techniques. This paper describes the Box-Jenkins time series seasonal ARIMA (Auto Regression Integrated Moving Average) approach for prediction of rainfall on monthly scales. ARIMA model (0, 0, 0) (0, 1, 1) for rainfall was identified the best model to forecast rainfall for next 4years with confidence level of 95 percent by analyzing last 27 year’s data (1990-20016). Previous years data is used to formulate the seasonal ARIMA model and in determination of model parameters. The performance evaluations of the adopted models are carried out on the basis of correlation coefficient (R2) and root mean square error (RMSE). The study conducted at Jagdalpur, Chhattisgarh (India). The results indicate that the ARIMA model provide consistent and satisfactory predictions for rainfall parameters on monthly scale.
Keywords: Rainfall,ARIMA, Correlation Coefficient (R2), Root Mean Square Error (RMSE).
REFERENCES
International Journal of Computer Application (2250-1797) Volume 6-No.2, March- April 2016.
Hirani, Dhawal and Mishra, Nitin A Survey On Rainfall Prediction Techniques
Box GE, Jenkins GM. Time series analysis: Forecasting and control. Rev. ed. San Francisco: Holden-Day; 1976.
Mishra, A.K. and Desai, V.R. (2005). Drought forecasting using stochastic models. Stoch. Environ. Res Ris. Assess.19:326-339.
Time series analysis model to forecast rainfall for Allahabad region Anosh Graham and Ekta Pathak Mishra Journal of Pharmacognosy and Phytochemistry 2017; 6(5): 1418-1421
Box GEP, Jenkins GM. Time series analysis: forecasting and control, Prentince Hall, Inc, 1976, 575.
Nirmala, M. and Sundaram, S.M. (2010). A Seasonal Arima Model for Forecasting monthly rainfall in Tamil Nadu. National. Journal on Advances in Building Sciences and Mechanics. 1(2):43-47.
Etuk EH, Mohamed TM. Time Series Analysis of Monthly Rainfall data for the Gadaref rainfall station, Sudan, by SARIMA Methods. International Journal of Scientific Research in Knowledge. 2014; 2(7):320-327.
Kaushik, I. and Singh, S.M. Seasonal ARIMA model for forecasting of monthly rainfall and temperature.
International Journal of Agriculture Sciences. 2008; 5(8):112-25.
Mohamed, T.M. and Ibrahim, A. (2016). Time Series Analysis of Nyala Rainfall Using ARIMA Method Journal of Engineering and Computer Science (JECS). 17(1):5-11.