Estimating and mapping evapotranspiration in olive groves of semi-arid Tunisia using empirical formulas and satellite remote sensing
Abstract
Accurate estimation of evapotranspiration (ET) is needed to optimize irrigation in semi-arid environments. The present work aims to estimate evapotranspiration using empirical formulas and remote sensing in a commercial olive orchard near Menzel Mhiri in east central Tunisia.
This study compares evapotranspiration with the Mapping Evapotranspiration at high Resolution with Internal Calibration (METRIC) model with estimates from five empirical equations (Penman-Monteith; Blaney-Criddle; Hargreaves temperature; Hargreaves radiation; and Priestley-Taylor). Reference evapotranspiration estimated using these five empirical equations was based on meteorological station measurements in olives at the pilot study site.
Three years of ET estimates based on Landsat-8 satellite images and the METRIC method covering 2017, 2018, and 2019 were downloaded using Google EEFlux. The results obtained by remote sensing showed good ability to characterize seasonal variation in reference (ET0) and actual crop (ETc) evapotranspiration.
Reference evapotranspiration values for olive trees estimated by the METRIC model during the three experimental years accurately represent those estimated with the Penman-Monteith formula. Also, there was very good agreement between results obtained with METRIC and those calculated using the Blaney-Criddle method.
The monthly average of ET0 and ETc values determined during the three experimental years (2017, 2018, and 2019) showed that the METRIC model underestimates irrigation needs by about 15% compared to the Penman-Monteith (PM) approach.