Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem

© 2020 by the authors.

Detalles Bibliográficos
Autores: Burchard-Levine, Vicente, Nieto, Héctor, Riaño, David, Migliavacca, Mirco, El-Madany, Tarek S., Pérez-Priego, Óscar, Carrara, Arnaud, Martín, M. Pilar
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/205640
Acceso en línea:http://hdl.handle.net/10261/205640
Access Level:acceso abierto
Palabra clave:Two-source energy balance
Semi-arid tree-grass ecosystem
Thermal infrared
Evapotranspiration
Energy fluxes
Seasonality
MODIS
Proximal sensing
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repository_id_str
dc.title.none.fl_str_mv Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem
title Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem
spellingShingle Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem
Burchard-Levine, Vicente
Two-source energy balance
Semi-arid tree-grass ecosystem
Thermal infrared
Evapotranspiration
Energy fluxes
Seasonality
MODIS
Proximal sensing
title_short Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem
title_full Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem
title_fullStr Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem
title_full_unstemmed Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem
title_sort Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem
dc.creator.none.fl_str_mv Burchard-Levine, Vicente
Nieto, Héctor
Riaño, David
Migliavacca, Mirco
El-Madany, Tarek S.
Pérez-Priego, Óscar
Carrara, Arnaud
Martín, M. Pilar
author Burchard-Levine, Vicente
author_facet Burchard-Levine, Vicente
Nieto, Héctor
Riaño, David
Migliavacca, Mirco
El-Madany, Tarek S.
Pérez-Priego, Óscar
Carrara, Arnaud
Martín, M. Pilar
author_role author
author2 Nieto, Héctor
Riaño, David
Migliavacca, Mirco
El-Madany, Tarek S.
Pérez-Priego, Óscar
Carrara, Arnaud
Martín, M. Pilar
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv European Commission
Ministerio de Economía y Competitividad (España)
Ministerio de Ciencia, Innovación y Universidades (España)
Agencia Estatal de Investigación (España)
Generalitat Valenciana
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Two-source energy balance
Semi-arid tree-grass ecosystem
Thermal infrared
Evapotranspiration
Energy fluxes
Seasonality
MODIS
Proximal sensing
topic Two-source energy balance
Semi-arid tree-grass ecosystem
Thermal infrared
Evapotranspiration
Energy fluxes
Seasonality
MODIS
Proximal sensing
description © 2020 by the authors.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/205640
url http://hdl.handle.net/10261/205640
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
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info:eu-repo/grantAgreement/EC/H2020/721995
info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/CGL2015-G9095-R
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/CGL 2017-83538-C3-3-R
CGL 2017-83538-C3-3-R/AEI/10.13039/501100011033
https://doi.org/10.3390/rs12060904
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
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spelling Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass EcosystemBurchard-Levine, VicenteNieto, HéctorRiaño, DavidMigliavacca, MircoEl-Madany, Tarek S.Pérez-Priego, ÓscarCarrara, ArnaudMartín, M. PilarTwo-source energy balanceSemi-arid tree-grass ecosystemThermal infraredEvapotranspirationEnergy fluxesSeasonalityMODISProximal sensing© 2020 by the authors.The thermal-based two-source energy balance (TSEB) model has accurately simulated energy fluxes in a wide range of landscapes with both remote and proximal sensing data. However, tree-grass ecosystems (TGE) have notably complex heterogeneous vegetation mixtures and dynamic phenological characteristics presenting clear challenges to earth observation and modeling methods. Particularly, the TSEB modeling structure assumes a single vegetation source, making it difficult to represent the multiple vegetation layers present in TGEs (i.e., trees and grasses) which have different phenological and structural characteristics. This study evaluates the implementation of TSEB in a TGE located in central Spain and proposes a new strategy to consider the spatial and temporal complexities observed. This was based on sensitivity analyses (SA) conducted on both primary remote sensing inputs (local SA) and model parameters (global SA). The model was subsequently modified considering phenological dynamics in semi-arid TGEs and assuming a dominant vegetation structure and cover (i.e., either grassland or broadleaved trees) for different seasons (TSEB-2S). The adaptation was compared against the default model and evaluated against eddy covariance (EC) flux measurements and lysimeters over the experimental site. TSEB-2S vastly improved over the default TSEB performance decreasing the mean bias and root-mean-square-deviation (RMSD) of latent heat (LE) from 40 and 82 W m−2 to −4 and 59 W m−2, respectively during 2015. TSEB-2S was further validated for two other EC towers and for different years (2015, 2016 and 2017) obtaining similar error statistics with RMSD of LE ranging between 57 and 63 W m−2. The results presented here demonstrate a relatively simple strategy to improve water and energy flux monitoring over a complex and vulnerable landscape, which are often poorly represented through remote sensing models.The research received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 721995. It was also funded by Ministerio de Economía y Competitividad through FLUXPEC CGL2012-34383 and SynerTGE CGL2015-G9095-R (MINECO/FEDER, UE) projects. The research infrastructure at the measurement site in Majadas de Tiétar was partly funded through the Alexander von Humboldt Foundation, ELEMENTAL (CGL 2017-83538-C3-3-R, MINECO-FEDER) and IMAGINA (PROMETEU 2019; Generalitat Valenciana).Peer reviewedMultidisciplinary Digital Publishing InstituteEuropean CommissionMinisterio de Economía y Competitividad (España)Ministerio de Ciencia, Innovación y Universidades (España)Agencia Estatal de Investigación (España)Generalitat ValencianaConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2020202020202020info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/205640reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/H2020/721995info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/CGL2015-G9095-Rinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/CGL 2017-83538-C3-3-RCGL 2017-83538-C3-3-R/AEI/10.13039/501100011033https://doi.org/10.3390/rs12060904Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2056402026-05-22T06:33:51Z
score 15.812429

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