Evapotranspiration estimates using remote sensing in a tropical forest in Brazil
Abstract:Tropical forests exchange large amounts of water with the atmosphere and play a key role in global hydrological cycles. The Amazon-Cerrado Transitional Forest exhibits little seasonal variation in evapotranspiration (ET) due to its ability to extract water from deep soil profiles and water tables. Seasonal variability of ET over the transitional forest was monitored using an eddy covariance (EC) tower that acquired energy balance flux measurements from about 45 m above the ground surface near Sinop, Mato Grosso, Brazil. The remote sensing based surface Energy Balance Algorithm for Land (SEBAL) model was applied to test its ability to provide estimates of ET that can be used to account for the spatial and temporal variability over such regions. SEBAL-based estimates of ET were compared with EC measurements during the 2006 season using multiple Landsat 5 TM images. Our results indicate that the SEBAL algorithm is capable to reproducing the seasonal variation in ET of the Amazon-Cerrado Transitional Forest and areas surrounding the EC tower.
M.S.B. acknowledges a grant from CAPES (9750/13-4). N.G.M. acknowledges a grant from CAPES (9768/13-0). Partial support was provided by the Remote Sensing Services Laboratory, Department of Civil and Environmental Engineering at Utah State University.