George Paul1, Prasanna Gowda2, P.V. Vara Prasad1, Terry A. Howell2, Scott A. Staggenborg1, Paul Colaizzi2, Robert Aiken3 and Stacy L. Hutchinson4, (1)Agronomy, Kansas State University, Manhattan, KS (2)USDA-ARS, Bushland, TX (3)Kansas State University, Colby, KS (4)Biological and Agricultural Engineering, Kansas State University, Manhattan, KS
Over the past three decades, numerous remote sensing based ET mapping algorithms were developed. These algorithms provided a robust, economical, and efficient tool for ET estimations at field and regional scales. The Two Source Energy Balance Model (TSM), Surface Energy Balance System (SEBS) and Surface Energy Balance Algorithm for Land (SEBAL) covers the majors spectrum of the algorithms available for estimating ET. An intercomparison of these models is important for ascertaining the performances under different conditions and preparing for the next generation operational ET mapping program. This study combines high resolution remote sensing data with field measurements of the agro-meteorological variables and surface energy fluxes acquired during the Bushland Evapotranspiration and Agricultural Remote Sensing Experiment 2007 and 2008 ( BEAREX07, BEAREX08 ) conducted at the USDA-ARS Conservation and Production Research Laboratory (CPRL) in Bushland, Texas. The study offers the several unique set-up for a more stringent evaluation such as (a) simultaneous evaluation of dryland and irrigated conditions using lysimetric data, (b) use of high resolution (1-3 m) airborne images for acquiring ‘pure’ pixels of the lysimeter locations, (c) multiple images acquired from emergence to vegetative growth period from two years and (d) evaluating instantaneous ET (mm h-1) values against lysimeter data provided better representation of algorithm's capabilities.