Abstract
The prediction of potential evapotranspiration (PET) is quite important task for reliable management of irrigation systems. This article is generally based on the models which try to mimic the actual occurrence of the Potential evapotranspiration in the future days for Yadgir district. In this study the potential evapotranspiration was estimated with the help of max and min temperature (o C) data using a Thornthwaite method and the prediction was carried out using the seasonal Autoregressive moving average method (SARIMA). The models were developed based upon autocorrelation function (ACF) and partial autocorrelation function (PACF). Furthermore, the model with the least Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) values were selected. The models selected for different stations were ARIMA(2,0,2) (2,1,0)12, ARIMA(2,0,2)(2,1,0)12, ARIMA (1,0,1)(2,1,0)12, and ARIMA(2,0,2)(2,1,0)12, for Yadgir, Gurmitkal, Shahapur and Shorapur respectively. Furthermore, the results showed that the models developed for Gurmitkaland Shahapur were found to be quite promising compared to the other two stations. All four models were found to be producing better results. The models provided significant potential in improving the decision making in irrigation planning and command area management practices for better management of water resources.
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