Lysimetric evaluation of SEBAL using high resolution airborne imagery from BEAREX08 |
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| Institution: | 1. Dipartimento di Neuroscienze, Scienze Riproduttive ed Odontostomatologiche –Università degli Studi di Napoli ‘Federico II’, Via Sergio Pansini, 5-80131, Naples, Italy;2. Dipartimento di Scienze Biomediche Avanzate, Università degli Studi di Napoli ‘Federico II’, Via Sergio Pansini, 5-80131, Naples, Italy;1. University of Goettingen, Faculty of Geoscience and Geography, Goettingen, Germany;2. U.S.D.A. Forest Service, International Programs, c/o CIFOR, World Agroforestry Center, Nairobi, Kenya;3. Federal University of Mato Grosso, Department of Soil and Agricultural Engineering, Cuiabá, Brazil;4. University of Koblenz-Landau, Institute for Environmental Sciences, Geoecology & Physical Geography, Landau, Germany;1. Federal University of Campina Grande, Centre for the Sustainable Development of the Semi - Arid, Sumé, Brazil;2. University of Reading, School of Archaeology, Geography and Environmental Science, Reading, United Kingdom;3. Imperial College London, Faculty of Natural Sciences, Department of Life Sciences, Silwood Park Campus, Ascot, United Kingdom;4. Federal University of Campina Grande, Centre for Natural Resources and Technology, Campina Grande, Brazil;5. University of Gottingen, Institute of Geography, Cartography GIS & Remote Sensing Section, Goettingen, Germany;6. University of Lisbon, School of Agriculture, Forest Research Centre (CEF), Tapada da Ajuda, 1349-017 Lisbon, Portugal |
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| Abstract: | In 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−1 (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. |
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| Keywords: | SEBAL Evapotranspiration Airborne remote sensing Energy balance Excess resistance Aerodynamic roughness parameters |
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