Evaluation of Penman-Monteith Model Based on Sentinel-2 Data for the Estimation of Actual Evapotranspiration in Vineyards

Abstract

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%.

Evaluation of AquaCrop model of cucumber under greenhouse cultivation

“…These models are expected to improve cultivation management technology, labour management and sales planning. Although models cannot be used instead of experimental investigation, however the main advantage of the crop modelling is time and cost saving (García-Gutiérrez et al, 2021). In this context, various crop growth models have been developed including DSSAT, CropSyst, CROPWAT, FAO, APSIM and EPIC (Jones et al, 2003;Keating et al, 2003;Stockle et al, 2003;Maniruzzaman et al, 2015;Carlson et al, 2016;Jones et al, 2017;Razzaghi et al, 2017;Holzworth et al, 2018;Anar et al, 2019;Xu et al, 2019;Biswal et al, 2021).…”

Leaf Area Index Variations in Ecoregions of Ardabil Province, Iran

“…There are various results in relation to the accuracy assessment of different methods in LAI estimation. The similar reliability, accuracy, and methodology of LP 100 and LAI-2200 PCA as the "world standard" is confirmed by several studies ( [2,33,34,35]. The accuracy of LAI derived from Landsat 7 (ETM+) and Landsat 8 (OLI) was assessed in [36] using the LI-COR LAI-2200 Plant Canopy Analyzer and field data from loblolly pine plantations in the USA.…”

Leaf Area Index Variations in Ecoregions of Ardabil Province, Iran

“…There are various results concerning the accuracy assessment of different methods in LAI estimation. The similar reliability, accuracy, and methodology of LP 100 and LAI-2200 PCA as the "world standard" is confirmed by several studies [2,[32][33][34]. The accuracy of LAI derived from Landsat 7 (ETM+) and Landsat 8 (OLI) was assessed in [35] using the LI-COR LAI-2200 Plant Canopy Analyzer and field data from loblolly pine plantations in the USA.…”