Evaluation of OSEB and SEBAL models for energy balance of a crop area in a humid subtropical climate

ABSTRACT This study evaluated the adequacy of the One-Source Energy Balance (OSEB) and Surface Energy Balance Algorithm for Land (SEBAL) models to estimate evapotranspiration in grain growing areas with humid subtropical climate in Rio Grande do Sul, southern Brazil. The dataset was obtained from a...

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Bibliographic Details
Main Authors: Juliano Schirmbeck, Denise Cybis Fontana, Débora Regina Roberti
Format: Article
Language:English
Published: Instituto Agronômico de Campinas 2018-11-01
Series:Bragantia
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052018005013101&lng=en&tlng=en
Description
Summary:ABSTRACT This study evaluated the adequacy of the One-Source Energy Balance (OSEB) and Surface Energy Balance Algorithm for Land (SEBAL) models to estimate evapotranspiration in grain growing areas with humid subtropical climate in Rio Grande do Sul, southern Brazil. The dataset was obtained from a micrometeorological station (Eddy Covariance) and MODIS (Moderate Resolution Imaging Spectroradiometer) products during 84 observation days between 2009 and 2011. The OSEB and SEBAL models were used to estimate the partition of net radiation (Rn) into the components latent heat flux (LE), sensible heat flux (H), and ground heat flux (G) estimated from the MODIS images while the experimental data measured in situ were used to compare the results. Analyses indicated that the Energy Balance (EB) components were estimated from the MODIS images satisfactorily despite the spatial resolution limitations. Furthermore, the SEBAL model estimated the EB components satisfactorily only for summer crops. There are uncertainties associated with determining the hot and cold pixels due to the region humid subtropical climate and the spatial resolution of the sensor used in the other periods. The OSEB model has the lowest errors and the most adequate partitioning of the EB components throughout the year, and therefore, it is the most suitable for the climatic conditions of Rio Grande do Sul.
ISSN:1678-4499