Abstract
Daily evapotranspiration is a major component in crops water consumption management plans. Consequently, forecasting of daily evapotranspiration is the keystone of any effective water resources management plans in fragile environment similar to the Nile Delta region. The estimation of daily evapotranspiration was carried out using Surface Energy Balance System (SEBS), while the forecasting of the daily evapotranspiration was carried out using Auto Regressive Integrated Moving Average (ARIMA) and its derivative Seasonal ARIMA. Remote sensing data were downloaded from European Space Agency (ESA) and used to estimate daily evapotranspiration values. Remote sensing data collected from August 2005 till December 2009 on a monthly basis for daily evapotranspiration estimation. The application of the most adequate ARIMA (2,1,2) to the evapotranspiration data set failed to sustain the forecasting accuracy over a long period of time. Although, time series analysis of daily evapotranspiration data set showed a seasonality behavior and thus, using seasonal ARIMA [(2,1,2) (1,1,2)6] was the optimum to forecast the daily evapotranspiration over the study area and sustain the forecasting accuracy. A linear regression model was established to test the correlation between the forecasted daily evapotranspiration values using S-ARIMA model and the actual values. The forecasting model indicates an increase of the daily evapotranspiration values with about 1.3 mm per day.