A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas
Instituto de Ciências Humanas e da Informação, Universidade Federal do Rio Grande, Rio Grande, RS CEP 96201-900, Brazil
Departamento de Engenharia Civil e Ambiental, Universidade Federal da Paraíba, João Pessoa, PB CEP 58059-900, Brazil
Instituto de Pesquisas Hidráulicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS CEP 91501-970, Brazil
College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK
Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, SP CEP 05508-900, Brazil
School of Geography and the Environment, Oxford University Centre for the Environment, Oxford OX1 3QY, UK
Author to whom correspondence should be addressed.
Remote Sens. 2012, 4(3), 703-725; https://doi.org/10.3390/rs4030703
Received: 3 February 2012 / Revised: 5 March 2012 / Accepted: 5 March 2012 / Published: 12 March 2012
Evapotranspiration (ET) plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC) measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE) yielded r 2= 0.64 and r2 = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r 2 = 0.76 and r2 = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km2 (r2 = 0.88). Inputs to which the algorithm is most sensitive are vegetation index (NDVI), gradient of temperature (dT) to compute sensible heat flux (H) and net radiation (Rn). It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas.