Surface energy balance model

Presented at the fifth international conference on irrigation and drainage, Irrigation and drainage for food, energy and the environment on November 3-6, 2009 in Salt Lake City, Utah.Includes bibliographical references.Remote sensing algorithms are currently being used to estimate regional surface energy fluxes [e.g., latent heat flux (LE) 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 estimating 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 (i.e., soil water sensors, lysimeters, weather station data, etc.), 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 study focuses on the use of the energy balance-based model "Remote Sensing of ET" (ReSET) that uses an enhanced procedure to deal with the spatial and temporal variability of ET. ET was estimated for several years of data for the Arkansas River Basin, South Platte, and Palo Verde Irrigation District along with one day ET estimates for the Southern High Plains. Comparisons between the Remote Sensing ET values and ET values from more conventional ET methods [e.g., 2005 ASCE-EWRI Standardized Reference Evapotranspiration (Penman-Monteith) Equation] also are presented