Volume No. 3 Issue No.: 2 Page No.: 506-514 Oct-Dec 2008

 

SEASONAL ARIMA MODEL FOR FORECASTING OF MONTHLY RAINFALL AND TEMPERATURE

 

Inderjeet Kaushik1 and Sabita Madhvi Singh*2

1. Department of Civil Engineering, Institute of Technology, B.H.U., Varanasi, (INDIA)
2. Department of Civil Engineering, Haldia Institute of Technology, Haldia, (INDIA)

 

Received on : August 13, 2008

 

ABSTRACT

 

The prediction of temperature and rainfall on a seasonal time scales has been attempted by various research groups using different techniques. The prediction of these parameters on monthly and seasonal time scales is not only scientifically challenging but is also important for planning and devising agricultural strategies. This paper describes the Box-Jenkins time series seasonal ARIMA (Auto Regression Integrated Moving Average) approach for prediction of temperature and rainfall on monthly scales. The Box Jenkins technique is applied to predict temperature and rainfall of next five years by analyzing last twelve years data (1994-2006). 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 Mirzapur, Uttar Pradesh (India). The results indicate that the seasonal ARIMA model provide reliable and satisfactory predictions for rainfall and temperature parameters on monthly scale.

 

Keywords : ARIMA, Meteorology, Rain fall, Hydroelectric power

 

 

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