The present study aimed to evaluate the efficiency of SEBAL algorithm in estimating the energy balance components and evapotranspiration for irrigated soybean areas, near the municipality of Cruz Alta, RS, Brazil, and to analyze the temporal and spatial variation of evapotranspiration from Landsat TM5 image. The Surface Energy Balance Algorithm for Land (SEBAL) was applied to six images distributed throughout the soybean growth season in 2009 and 2010 harvests. The estimates were compared to micrometeorological data retrieved from a station located in the studied area. The most accurate modeled parameter estimatives was net radiation while the one which presented the highest error was soil heat flux. The SEBAL showed potential to map the spatial and temporal evapotranspiration variability, showing sensitivity to different types of land cover and to different crop development stages.
Glycine max L.; remote sensing; SEBAL; water resources
