Using a Surface Energy Balance Model to Calculate Spatially Distributed Actual Evapotranspiration

Abstract

Remote sensing algorithms are currently being used to estimate regional surface energy fluxes [e.g., latent heat flux or evapotranspiration (ET)]. Many of these surface energy balance models use information derived from satellite imagery such as Landsat, AVHRR, ASTER, and MODIS to estimate ET. The remote sensing approach to estimate ET provides advantages over traditional methods. One of the most important advantages is that it can provide regional estimates of actual ET at low cost. Most conventional methods are based on point measurements (e.g., soil water sensors, lysimeters, and weather station data), limiting their ability to capture the spatial variability of ET. Another advantage of remote sensing/surface energy balance ET models is that they are able to estimate the actual crop ET as a residual of the energy balance without the need of using reference crop ET and tabulated crop coefficients. This paper focuses on the application of the energy balance-based model “Remote Sensing of ET” (ReSET) that uses a procedure to deal with the spatial and temporal variability of ET. The model was used to estimate actual ET for multiple dates in the Arkansas River Basin in Colorado, South Platte River Basin in Colorado, and Palo Verde Irrigation District in California along with a 1-day ET estimate for the Southern High Plains (Texas). Comparisons between ReSET results and ET values from more conventional ET methods [e.g., 2005 ASCE-EWRI Standardized Reference Evapotranspiration (Penman-Monteith) Equation] are also presented.