A Two-source Trapezoid Model for Evapotranspiration (TTME) from satellite imagery

This study develops a Two-source Trapezoid Model for Evapotranspiration (TTME) from satellite imagery by interpreting the remotely sensed fractional vegetation cover (f(c))-radiative surface temperature (T-rad) space and the concept of soil surface moisture availability isopleths superimposed on the space. The theoretical upper boundary condition of TTME is determined by solving for temperatures of the driest bare surface (T-s,T-max) and the driest fully vegetated surface (T-c,T-max) both implicit in radiation budget and energy balance equations. Air temperature (T-a) constitutes the lower boundary of TTME. T-rad of a pixel within the f(c)-T-rad space is decomposed into temperature components (T-c and T-s) by interpolating the slope of the theoretical boundaries and interpreting variation in T-rad with f(c) for each isopiestic line going across the pixel. Vegetation transpiration and soil surface evaporation are then separately parameterized. TTME was applied to the Soil Moisture-Atmosphere Coupling Experiment (SMACEX) site in central Iowa, U.S., on three days in 2002 during the period of rapid growth in corn and soybean when three scenes of Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images and one scene of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image were acquired. Results indicate that TTME is capable of reproducing latent heat flux (LE) with a mean absolute percentage difference (MAPD) of similar to 10%, and a root mean square difference (RMSD) of 45.6 W m(-2) and 63.1 W m(-2) for Landsat TM/ETM+ and ASTER images, respectively. Comparison of TTME with other one-source and two-source models using the same data set suggests that TTME shows comparable accuracy as the Two-Source Energy Balance (TSEB), but requires relatively fewer inputs and obviates the computation of resistance networks in the modeling domain and the overestimation of vegetation transpiration incurred by using the Priestley-Taylor equation. Sensitivity analysis suggests that TTME is most sensitive to T-rad and T-a, but not sensitive to a range of meteorological observations and variables and parameters derived/specified. (c) 2012 Elsevier Inc. All rights reserved.