The objective of this study was to evaluate the efficiency of SEBAL model in estimating soil surface energy fluxes and daily evapotranspiration for a large area of irrigated rice farms, near the municipality of Paraíso do Sul, RS, Brazil, using data from ASTER sensor. The evaluated variables are important weather and climatic parameters for agrometeorological studies and rationalization of water use. The conventional methodologies for estimating these parameters generally present uncertainties, which increase when concern is in the spatial behavior of such parameters. The Surface Energy Balance Algorithm for Land (SEBAL) was applied in an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scene and the estimates were compared to micrometeorological data retrieved from a station located in the studied area. The most accurate modeled parameter estimatives were sensitive heat and evapotranspiration, and the one which presented the highest error was soil heat flux. The adopted methodology was able to reproduce surface energy fluxes for agrometeorological and crop yield studies.
rice; latent heat; sensitive heat; remote sensing; water use; spatial resolution
