Spatial sensitivity of surface energy balance algorithms to meteorological data in a heterogeneous environment

Webster, E; Ramp, D; Kingsford, RT

Spatial sensitivity of surface energy balance algorithms to meteorological data in a heterogeneous environment

Webster, E Ramp, D

Kingsford, RT

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Publication Type:: Journal Article
Citation:: Remote Sensing of Environment, 2016, 187 pp. 294 - 319
Issue Date:: 2016-12-15

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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	2016-12-15	en_US
dc.identifier.citation	Remote Sensing of Environment, 2016, 187 pp. 294 - 319	en_US
dc.identifier.issn	0034-4257	en_US
dc.identifier.uri	http://hdl.handle.net/10453/91903
dc.description.abstract	© 2016 Elsevier Inc. Increasing demand for water security requires improved accuracy in water accounting. Quantification of actual evapotranspiration is an essential part of this accounting and is frequently derived from surface energy balance (SEB) models that combine satellite remote sensing and on-ground measurements of meteorological data. However, many of the world's major water supply catchments are highly heterogeneous with land types, vegetation communities, and topography varying spatially. We compared the performance of seven meteorological interpolation methods and three SEB algorithms (the Simplified Surface Energy Balance Index (S-SEBI), the Hybrid Dual-Source Scheme and Trapezoid Framework-Based Evapotranspiration Model (HTEM), and the Surface Energy Balance System (SEBS)), testing their sensitivity to meteorological and remotely sensed inputs in a heterogeneous environment. Under a two dimensional framework, accuracy of interpolation methods varied among SEB meteorological inputs, suggesting that combining methods could improve overall accuracy. SEB algorithms were influenced by the density, type, and variability of meteorological inputs and sensitivity analysis showed that wind speed and air temperature were almost as influential as surface temperature for HTEM and SEBS. SEBS was the most sensitive to meteorological variability caused by choice of interpolation method when analysed globally, while HTEM was the most sensitive to local meteorological variation at flux towers. S-SEBI's simple structure made it the least sensitive to meteorological inputs and interpolation methods. Continued improvement in spatially explicit interpolation methods, combined with increased densities of meteorological stations, will increase accuracy and confidence in remotely sensed SEB fluxes, contributing to improved water accounting in heterogeneous catchments.	en_US
dc.relation.ispartof	Remote Sensing of Environment	en_US
dc.relation.isbasedon	10.1016/j.rse.2016.10.019	en_US
dc.subject.classification	Geological & Geomatics Engineering	en_US
dc.title	Spatial sensitivity of surface energy balance algorithms to meteorological data in a heterogeneous environment	en_US
dc.type	Journal Article
utslib.citation.volume	187	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	closed_access
pubs.publication-status	Published	en_US
pubs.volume	187	en_US

Abstract:

© 2016 Elsevier Inc. Increasing demand for water security requires improved accuracy in water accounting. Quantification of actual evapotranspiration is an essential part of this accounting and is frequently derived from surface energy balance (SEB) models that combine satellite remote sensing and on-ground measurements of meteorological data. However, many of the world's major water supply catchments are highly heterogeneous with land types, vegetation communities, and topography varying spatially. We compared the performance of seven meteorological interpolation methods and three SEB algorithms (the Simplified Surface Energy Balance Index (S-SEBI), the Hybrid Dual-Source Scheme and Trapezoid Framework-Based Evapotranspiration Model (HTEM), and the Surface Energy Balance System (SEBS)), testing their sensitivity to meteorological and remotely sensed inputs in a heterogeneous environment. Under a two dimensional framework, accuracy of interpolation methods varied among SEB meteorological inputs, suggesting that combining methods could improve overall accuracy. SEB algorithms were influenced by the density, type, and variability of meteorological inputs and sensitivity analysis showed that wind speed and air temperature were almost as influential as surface temperature for HTEM and SEBS. SEBS was the most sensitive to meteorological variability caused by choice of interpolation method when analysed globally, while HTEM was the most sensitive to local meteorological variation at flux towers. S-SEBI's simple structure made it the least sensitive to meteorological inputs and interpolation methods. Continued improvement in spatially explicit interpolation methods, combined with increased densities of meteorological stations, will increase accuracy and confidence in remotely sensed SEB fluxes, contributing to improved water accounting in heterogeneous catchments.

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http://hdl.handle.net/10453/91903