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a b s t r a c tIn this study, Surface Energy Balance Algorithm for Land (SEBAL) was evaluated for its ability to derive aerodynamic components and surface energy fluxes from very high resolution airborne remote sensing data acquired during the Bushland Evapotranspiration and Agricultural Remote Sensing Experiment 2008 (BEAREX08) in Texas, USA. Issues related to hot and cold pixel selection and the underlying assumptions of difference between air and surface temperature (dT) being linearly related to the surface temperature were also addressed. Estimated instantaneous evapotranspiration (ET) and other components of the surface energy balance were compared with measured data from four large precision weighing lysimeter fields, two each managed under irrigation and dryland conditions. Instantaneous ET was estimated with overall mean bias error and root mean square error (RMSE) of 0.13 and 0.15 mm h À1 (23.8 and 28.2%) respectively, where relatively large RMSE was contributed by dryland field. Sensitivity analysis of the hot and cold pixel selection indicated that up to 20% of the variability in ET estimates could be attributed to differences in the surface energy balance and roughness properties of the anchor pixels. Adoption of an excess resistance to heat transfer parameter model into SEBAL significantly improved the instantaneous ET estimates.Published by Elsevier Ltd.

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Numerous energy balance (EB) algorithms have been developed to use remote sensing data for mapping evapotranspiration (ET) on a regional basis. Adopting any single or combination of these models for an operational ET remote sensing program requires a thorough evaluation. The Surface Energy Balance System (SEBS) was evaluated for its ability to estimate hourly ET rates of summer tall and short crops grown in the Texas High Plains by using 15 Landsat 5 Thematic Mapper scenes acquired during 2006 to 2009. Performance of SEBS was evaluated by comparing estimated hourly ET values with measured ET data from four large weighing lysimeters, each located at the center of a 4.3 ha field in the USDA‐ARS Conservation and Production Research Laboratory in Bushland, TX. The performance of SEBS in estimating hourly ET was good for crops under both irrigated and dryland conditions. A locally derived, surface albedo‐based soil heat flux (G) model further improved the G estimates. Root mean square error and mean bias error were 0.11 and −0.005 mm h−1, respectively, and the Nash–Sutcliff model efficiency was 0.85 between the measured and calculated hourly ET. Considering the equal or better performance with a minimal amount of ancillary data as compared to with other EB algorithms, SEBS is a promising tool for use in an operational ET remote sensing program in the semiarid Texas High Plains. However, thorough sensitivity and error propagation analyses of input variables to quantify their impact on ET estimations for the major crops in the Texas High Plains under different agroclimatological conditions are needed before adopting the SEBS into operational ET remote sensing programs for irrigation scheduling or other purposes.

The National Oceanic and Atmospheric Administration (NOAA) provides daily reference evapotranspiration (ET ref ) maps for the contiguous United States using climatic data from North American Land Data Assimilation System (NLDAS). This data provides large-scale spatial representation of ET ref , which is essential for regional scale water resources management. Data used in the development of NOAA daily ET ref maps are derived from observations over surfaces that are different from short (grass -ET os ) or tall (alfalfa -ET rs ) reference crops, often in nonagricultural settings, which carries an unknown discrepancy between assumed and actual conditions. In this study, NOAA daily ET os and ET rs maps were evaluated for accuracy, using observed data from the Texas High Plains Evapotranspiration (TXHPET) network. Daily ET os , ET rs and the climatic data (air temperature, wind speed, and solar radiation) used for calculating ET ref were extracted from the NOAA maps for TXHPET locations and compared against ground measurements on reference grass surfaces. NOAA ET ref maps generally overestimated the TXHPET observations (1.4 and 2.2 mm/day ET os and ET rs , respectively), which may be attributed to errors in the NLDAS modeled air temperature and wind speed, to which reference ET ref is most sensitive. Therefore, a bias correction to NLDAS modeled air temperature and wind speed data, or adjustment to the resulting NOAA ET ref , may be needed to improve the accuracy of NOAA ET ref maps.(KEY TERMS: climate; water resources management; Ogallala Aquifer region.)