Application of remote sensing-based two-source energy balance model for mapping field surface fluxes with composite and component surface temperatures

Abstract Operational application of a remote sensing-based two source energy balance model (TSEB) to estimate evaportranspiration ( ET ) and the components evaporation ( E ), transpiration ( T ) at a range of space and time scales is very useful for managing water resources in arid and semiarid watersheds. The TSEB model uses composite land surface temperature as input and applies a simplified Priestley–Taylor formulation to partition this temperature into soil and vegetation component temperatures and then computes subsequent component energy fluxes. The remote sensing-based TSEB model using component temperatures of the soil and canopy has not been adequately evaluated due to a dearth of reliable observations. In this study, soil and vegetation component temperatures partitioned from visible and near infrared and thermal remote sensing data supplied by advanced scanning thermal emission and reflection radiometer (ASTER) are applied as model inputs (TSEB CT ) to assess and refine the subsequent component energy fluxes estimation in TSEB scheme under heterogeneous land surface conditions in an advective environment. The model outputs including sensible heat flux ( H ), latent heat flux ( LE ), component LE from soil and canopy from the TSEB CT and original model (TSEB PT ) are compared with ground measurements from eddy covariance (EC) and larger aperture scintillometers (LAS) technique, and stable isotopic method. Both model versions yield errors of about 10% with LE observations. However, the TSEB CT model output of H and LE are in closer agreement with the observations and is found to be generally more robust in component flux estimation compared to the TSEB PT using the ASTER data in this heterogeneous advective environment. Thus given accurate soil and canopy temperatures, TSEB CT may provide more reliable estimates of plant water use and values of water use efficiency at large scales for water resource management in arid and semiarid landscapes.

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