Evaluation of Penman-Monteith Model Based on Sentinel-2 Data for the Estimation of Actual Evapotranspiration in Vineyards - Víctor García-Gutiérrez; Claudio Stöckle; Pilar Macarena Gil; Francisco Javier Meza (Remote Sensing, 2021)
Water scarcity is one of the most important problems of agroecosystems in Mediterranean and semiarid areas, especially for species such as vineyards that largely depend on irrigation. Actual evapotranspiration (ET) is a variable that represents water consumption of a crop, integrating climate and biophysical variables. Actual evapotranspiration models based on remote sensing data from visible bands of Sentinel-2, including Penman-Monteith–Stewart (RS-PMS) and Penman-Monteith–Leuning (RS-PML), were evaluated at different temporal scales in a Cabernet Sauvignon vineyard (Vitis vinifera L.) located in central Chile, and their performance compared with independent ET measurements from an eddy covariance system (EC) and outputs from models based on thermal infrared data from Landsat 7 and Landsat 8, such as Mapping EvapoTranspiration with high Resolution and Internalized Calibration (METRIC) and Priestley–Taylor Two-Source Model (TSEB-PT). The RS-PMS model showed the best goodness of fit for all temporal scales evaluated, especially at instantaneous and daily ET, with root mean squared error (RMSE) of 28.9 Wm−2 and 0.52 mm day−1, respectively, and Willmott agreement index (d1) values of 0.77 at instantaneous scale and 0.7 at daily scale. Additionally, both approaches of RS-PM model were evaluated incorporating a soil evaporation estimation method, one considering the soil water content (fSWC) and the other hand, using the ratio of accumulated precipitation and equivalent evaporation (fZhang), achieving the best fit at instantaneous scale for RS-PMS fSWC method with relative root mean squared error (%RMSE) of 15.2% in comparison to 58.8% of fZhang. Finally, the relevance of the RS-PMS model was highlighted in the assessment and monitoring of vineyard drip irrigation in terms of crop coefficient (Kc) estimation, which is one of the methods commonly used in irrigation planning, yielding a comparable Kc to the one obtained by the EC tower with a bias around 9%.