Energy balance from images in humid climate – SEBAL and METRIC

Abstract

Evapotranspiration is an important phenomenon to agriculture; therefore, this work aims at verifying the suitability of the SEBAL and METRIC models to estimate latent heat flux using remote sensing data from grain cultivation areas in the northwestern subtropical region of Rio Grande do Sul. This region stands out for grain production. The analyzed data set consisted of 84 dates distributed over a 3-year period of areas planted with soy, corn, oats, wheat, and vetch crops. The data estimated from the remote images were compared with the reference measurements acquired in a micrometeorological station using the Eddy Covariance technique. Both models presented satisfactory results. However, the LE estimated by the METRIC model had the lowest error for all 3 types of soil cover analyzed. The best performance of the METRIC model is attributed to the fact that it does not require extreme water condition, i.e. for LE equal to zero, to determine the hot pixel when estimating the sensible heat flux, unlike the SEBAL model.