FORECASTING WEEKLY REFERENCE CROP EVAPOTRANSPIRATION SERIES

Evapotranspiration (ET) is an important process in the hydrological cy cle and needs to be accurately quantified for proper irrigation schedu ling and optimal water resources systems operation. The time variant c haracteristics of ET necessitate the need for forecasting ET. In this paper, two techniques, namely a seasonal ARIMA model and Winter's expo nential smoothing model, have been investigated for their applicabilit y for forecasting weekly reference crop ET. A seasonal ARIMA model wit h one autoregressive and one moving average process and with a seasona lity of 52 weeks was found to be an appropriate stochastic model. The ARIMA and Winter's models were compared with a simple ET model to asse ss their performance in forecasting. The forecast errors produced by t hese models were very small and the models would be promisingly of gre at use in real-time irrigation management.