Assessment of olive transpiration derived from a remote sensing energy balance model compared with sap flow measurements
A remote sensing energy balance (RSEB) algorithm was used to estimate transpiration (TRSEB) from a high density and drip-irrigated olive (Olea europaea L. 'Arbequina') orchard, located in Pencahue Valley, Maule Region of Chile (35°23'S; 71°44'W). Meteorological variables over the orchard such as solar radiation, air temperature, relative humidity, wind speed and canopy temperature from zenith were recorded during the southern hemisphere summer, from January through February 2015. The RSEB model was evaluated using sap flow measurements obtained from compensation heat-pulse sensors. In 30-min intervals, the results showed that RSEB model estimated the olive transpiration with errors of 16%, presenting a root mean square error (RMSE) of 0.2 L h-1 and a mean absolute error (MAE) of 0.1 L h-1. On a daily basis, the RSEB model was able to predict the olive transpiration with RMSE and MAE values of 0.68 and 0.57 mm day-1, respectively. The overall analysis suggested that the model underestimates transpiration with errors of 10% on a daily basis.
Riveros-Burgos, C., Ortega-Farías, S. and Ahumada-Orellana, L. (2018). Assessment of olive transpiration derived from a remote sensing energy balance model compared with sap flow measurements. Acta Hortic. 1222, 189-194
transpiration, olive, compensation heat-pulse