Calibration and validation of a remote sensing algorithm to estimate energy balance components and daily actual evapotranspiration over a drip-irrigated Merlot vineyard

Abstract

A study was carried out to calibrate and validate a remote sensing algorithm (RSA) for estimating instantaneous surface energy balance components and daily actual evapotranspiration (ETa) over a drip-irrigated Merlot vineyard located in the Maule Region of Chile (35° 25′ LS; 71° 32′ LW; 125 m.a.s.l.). ETa was estimated as a function of instantaneous evaporative fraction and average daily net radiation (Rnday) using meteorological variables in combination with reflectance data measured by a hand-held multi-spectral radiometer. The sub-models used to estimate the instantaneous net radiation (Rnins), soil heat flux (G ins), and Rnday were calibrated and validated using measurements of the surface energy balance components, incoming longwave radiation $$(L \downarrow_{\text{ins}})$$ , outgoing longwave radiation $$(L \uparrow_{\text{ins}})$$ , and surface albedo (α). The validations of instantaneous sensible heat flux (H ins), latent heat flux (LEins), and ETa were carried out using turbulent energy fluxes obtained from an eddy correlation (EC) system. For reducing the moderate EC imbalance (about 11 %), turbulent energy fluxes were recalculated using the Bowen ratio method. The validation analysis indicated that the calibrated sub-models of the RSA were able to estimate Rnins, G ins, H ins, and LEins with a root-mean-square error (RMSE), mean absolute error (MAE), and index of agreement (IA) ranging between 16–54, 13–44 W m−2, and 0.72–94, respectively. Also, the RSA was able to estimate ETa with RMSE = 0.38 mm day−1, MAE = 0.32 mm day−1 and IA = 0.96. These results demonstrate the potential use of reflectance and meteorological data to estimate ETa of a drip-irrigated Merlot vineyard.