Seasonal ARIMA model for generation and forecasting evapotranspirtion of Solapur district of Maharashtra - S. D. GORANTIWAR; D. T. MESHRAM; H. K. MITTAL (Journal of Agrometeorology, 2011)
This paper deals with the stochastic modeling of weekly reference crop evapotranspiration in semi-arid climatic condition by using seasonal Auto Regressive Moving Average (ARIMA) model. The weekly values of reference crop evapotranspiration (ETr) estimated by Penman Monteith method for 23 years (1984 to 2006) were used to fit the ARIMA models of different orders. ARIMA models up to 1st order were selected based on autocorrelation function (ACF) and partial autocorrelation function (PACF) of the ETr series. The parameters of the selected models were obtained with the help of maximum likelihood method. The ARIMA models that satisfied the adequacy tests were selected for forecasting. One year ahead forecast (i.e. for 2007) of ETr values were obtained with the help of these selected models. The root mean square error (RMSE) was computed between forecast and actual values of ETr of 2007. The lowest RMSE was obtained for ARIMA (1,1,0) (1,0,1)52 and hence is the best stochastic model for generating and forecasting of weekly ETr values.