Incorporating an iterative energy restraint for the Surface Energy Balance System (SEBS)

Webster, E; Ramp, D; Kingsford, RT

Incorporating an iterative energy restraint for the Surface Energy Balance System (SEBS)

Webster, E Ramp, D

Kingsford, RT

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Publication Type:: Journal Article
Citation:: Remote Sensing of Environment, 2017, 198 pp. 267 - 285
Issue Date:: 2017-09-01

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Field	Value	Language
dc.contributor.author	Webster, E	en_US
dc.contributor.author	Ramp, D https://orcid.org/0000-0003-3202-9898	en_US
dc.contributor.author	Kingsford, RT	en_US
dc.date.issued	2017-09-01	en_US
dc.identifier.citation	Remote Sensing of Environment, 2017, 198 pp. 267 - 285	en_US
dc.identifier.issn	0034-4257	en_US
dc.identifier.uri	http://hdl.handle.net/10453/110182
dc.description.abstract	© 2017 Elsevier Inc. The Surface Energy Balance System (SEBS) has proven itself as an effective remotely sensed estimator of actual evapotranspiration (ETa). However, it has several vulnerabilities associated with the partitioning of the available energy (AE) at the land surface. We introduce a two stage energy restraint process into the SEBS algorithm (SEBS-ER) to overcome these vulnerabilities. The first offsets the remotely sensed surface temperature to ensure the surface to air temperature difference reflects AE, while the second stage uses a domain based image search process to identify and adjust the proportions of sensible (H) and latent (λE) heat flux with respect to AE. We effectively implemented SEBS-ER over 61 acquisitions over two Landsat tiles (path 90 row 84 and path 91 row 85) in south-eastern Australia that feature heterogeneous land covers. Across the two areas we showed that the SEBS-ER algorithm has: greater resilience to perturbed errors in surface energy balance algorithm inputs; significantly improved accuracy (p < 0.05) at two eddy covariance flux towers in heavily forested (RMSE 62.3 W m− 2, R2 0.879) and sub-alpine grassland (RMSE 33.2 W m− 2, R2 0.939) land covers; and greater temporal stability across 52 daily actual evapotranspiration (ETa) estimates compared to a temporally stable and independent ETa dataset. The energy restraint within SEBS-ER has reduced exposure to the complex errors and uncertainties within remotely sensed, meteorological, and land type SEBS inputs, providing more reliable and accurate spatially distributed ETa products.	en_US
dc.relation.ispartof	Remote Sensing of Environment	en_US
dc.relation.isbasedon	10.1016/j.rse.2017.06.012	en_US
dc.subject.classification	Geological & Geomatics Engineering	en_US
dc.title	Incorporating an iterative energy restraint for the Surface Energy Balance System (SEBS)	en_US
dc.type	Journal Article
utslib.citation.volume	198	en_US
utslib.for	0406 Physical Geography and Environmental Geoscience	en_US
utslib.for	0909 Geomatic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	198	en_US

Abstract:

© 2017 Elsevier Inc. The Surface Energy Balance System (SEBS) has proven itself as an effective remotely sensed estimator of actual evapotranspiration (ETa). However, it has several vulnerabilities associated with the partitioning of the available energy (AE) at the land surface. We introduce a two stage energy restraint process into the SEBS algorithm (SEBS-ER) to overcome these vulnerabilities. The first offsets the remotely sensed surface temperature to ensure the surface to air temperature difference reflects AE, while the second stage uses a domain based image search process to identify and adjust the proportions of sensible (H) and latent (λE) heat flux with respect to AE. We effectively implemented SEBS-ER over 61 acquisitions over two Landsat tiles (path 90 row 84 and path 91 row 85) in south-eastern Australia that feature heterogeneous land covers. Across the two areas we showed that the SEBS-ER algorithm has: greater resilience to perturbed errors in surface energy balance algorithm inputs; significantly improved accuracy (p < 0.05) at two eddy covariance flux towers in heavily forested (RMSE 62.3 W m− 2, R2 0.879) and sub-alpine grassland (RMSE 33.2 W m− 2, R2 0.939) land covers; and greater temporal stability across 52 daily actual evapotranspiration (ETa) estimates compared to a temporally stable and independent ETa dataset. The energy restraint within SEBS-ER has reduced exposure to the complex errors and uncertainties within remotely sensed, meteorological, and land type SEBS inputs, providing more reliable and accurate spatially distributed ETa products.

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http://hdl.handle.net/10453/110182