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hal.structure.identifierInstitut de Recherche pour le Développement [IRD [Nouvelle-Calédonie]]
dc.contributor.authorDELOGU, Emilie
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorBOULET, Gilles
hal.structure.identifierEnvironnement Méditerranéen et Modélisation des Agro-Hydrosystèmes [EMMAH]
dc.contributor.authorOLIOSO, Albert
hal.structure.identifierEnvironnement Méditerranéen et Modélisation des Agro-Hydrosystèmes [EMMAH]
dc.contributor.authorGARRIGUES, Sébastien
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorBRUT, Aurore
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorTALLEC, Tiphaine
hal.structure.identifierHydrosciences Montpellier [HSM]
dc.contributor.authorDEMARTY, Jérôme
hal.structure.identifierEcologie Systématique et Evolution [ESE]
dc.contributor.authorSOUDANI, Kamel
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLAGOUARDE, Jean-Pierre
dc.date.accessioned2024-04-08T12:04:13Z
dc.date.available2024-04-08T12:04:13Z
dc.date.issued2018-11
dc.identifier.issn2072-4292
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196299
dc.description.abstractEnUsing surface temperature as a signature of the surface energy balance is a way to quantify the spatial distribution of evapotranspiration and water stress. In this work, we used the new dual-source model named Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) based on the Two Sources Energy Balance (TSEB) model rationale which solves the surface energy balance equations for the soil and the canopy. SPARSE can be used (i) to retrieve soil and vegetation stress levels from known surface temperature and (ii) to predict transpiration, soil evaporation, and surface temperature for given stress levels. The main innovative feature of SPARSE is that it allows to bound each retrieved individual flux component (evaporation and transpiration) by its corresponding potential level deduced from running the model in prescribed potential conditions, i.e., a maximum limit if the surface water availability is not limiting. The main objective of the paper is to assess the SPARSE model predictions of water stress and evapotranspiration components for its two proposed versions (the “patch” and “layer” resistances network) over 20 in situ data sets encompassing distinct vegetation and climate. Over a large range of leaf area index values and for contrasting vegetation stress levels, SPARSE showed good retrieval performances of evapotranspiration and sensible heat fluxes. For cereals, the layer version provided better latent heat flux estimates than the patch version while both models showed similar performances for sparse crops and forest ecosystems. The bounded layer version of SPARSE provided the best estimates of latent heat flux over different sites and climates. Broad tendencies of observed and retrieved stress intensities were well reproduced with a reasonable difference obtained for most of the points located within a confidence interval of 0.2. The synchronous dynamics of observed and retrieved estimates underlined that the SPARSE retrieved water stress estimates from Thermal Infra-Red data were relevant tools for stress detection.
dc.language.isoen
dc.publisherMDPI
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subjectevapotranspiration
dc.subjectmodel
dc.subjectpartition
dc.subject.enwater stress
dc.subject.enremote-sensing
dc.title.enEvaluation of the SPARSE Dual-Source Model for Predicting Water Stress and Evapotranspiration from Thermal Infrared Data over Multiple Crops and Climates
dc.typeArticle de revue
dc.identifier.doi10.3390/rs10111806
dc.subject.halSciences de l'environnement
dc.subject.halSciences de l'environnement/Environnement et Société
bordeaux.journalRemote Sensing
bordeaux.volume10
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.issue11
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-01936634
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01936634v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing&rft.date=2018-11&rft.volume=10&rft.issue=11&rft.eissn=2072-4292&rft.issn=2072-4292&rft.au=DELOGU,%20Emilie&BOULET,%20Gilles&OLIOSO,%20Albert&GARRIGUES,%20S%C3%A9bastien&BRUT,%20Aurore&rft.genre=article


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