Improving operational land surface model canopyevapotranspiration in Africa using a direct remote sensing approach

Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET), a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET), driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at NationalWeather Service Land Surface Model (GNOAH) to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.

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Main Authors: Marshall, K., Tu, Kevin P., Funk, C., Michaelsen, J., Williams, P., Williams, Christopher, Ardö, Junas, Boucher, M., Cappelaere, Bernard, De Grandcourt, Agnès, Nickless, A., Nouvellon, Yann, Scholes, Robert J., Kutsch, Werner L.
Format: article biblioteca
Language:eng
Published: Copernicus GmbH
Subjects:U10 - Informatique, mathématiques et statistiques, U30 - Méthodes de recherche, F60 - Physiologie et biochimie végétale, P40 - Météorologie et climatologie, télédétection, modèle mathématique, évapotranspiration, transpiration, changement climatique, couverture végétale, écosystème, végétation, échange d'énergie, technique de prévision, http://aims.fao.org/aos/agrovoc/c_6498, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_2741, http://aims.fao.org/aos/agrovoc/c_7871, http://aims.fao.org/aos/agrovoc/c_1666, http://aims.fao.org/aos/agrovoc/c_25409, http://aims.fao.org/aos/agrovoc/c_2482, http://aims.fao.org/aos/agrovoc/c_8176, http://aims.fao.org/aos/agrovoc/c_2568, http://aims.fao.org/aos/agrovoc/c_3041, http://aims.fao.org/aos/agrovoc/c_6734, http://aims.fao.org/aos/agrovoc/c_166,
Online Access:http://agritrop.cirad.fr/568061/
http://agritrop.cirad.fr/568061/1/document_568061.pdf
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spelling dig-cirad-fr-5680612024-12-20T10:32:59Z http://agritrop.cirad.fr/568061/ http://agritrop.cirad.fr/568061/ Improving operational land surface model canopyevapotranspiration in Africa using a direct remote sensing approach. Marshall K., Tu Kevin P., Funk C., Michaelsen J., Williams P., Williams Christopher, Ardö Junas, Boucher M., Cappelaere Bernard, De Grandcourt Agnès, Nickless A., Nouvellon Yann, Scholes Robert J., Kutsch Werner L.. 2013. Hydrology and Earth System Sciences, 17 : 1079-1091.https://doi.org/10.5194/hess-17-1079-2013 <https://doi.org/10.5194/hess-17-1079-2013> Improving operational land surface model canopyevapotranspiration in Africa using a direct remote sensing approach Marshall, K. Tu, Kevin P. Funk, C. Michaelsen, J. Williams, P. Williams, Christopher Ardö, Junas Boucher, M. Cappelaere, Bernard De Grandcourt, Agnès Nickless, A. Nouvellon, Yann Scholes, Robert J. Kutsch, Werner L. eng 2013 Copernicus GmbH Hydrology and Earth System Sciences U10 - Informatique, mathématiques et statistiques U30 - Méthodes de recherche F60 - Physiologie et biochimie végétale P40 - Météorologie et climatologie télédétection modèle mathématique évapotranspiration transpiration changement climatique couverture végétale écosystème végétation échange d'énergie technique de prévision http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_2741 http://aims.fao.org/aos/agrovoc/c_7871 http://aims.fao.org/aos/agrovoc/c_1666 http://aims.fao.org/aos/agrovoc/c_25409 http://aims.fao.org/aos/agrovoc/c_2482 http://aims.fao.org/aos/agrovoc/c_8176 http://aims.fao.org/aos/agrovoc/c_2568 http://aims.fao.org/aos/agrovoc/c_3041 Sahel Afrique au sud du Sahara http://aims.fao.org/aos/agrovoc/c_6734 http://aims.fao.org/aos/agrovoc/c_166 Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET), a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET), driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at NationalWeather Service Land Surface Model (GNOAH) to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/568061/1/document_568061.pdf application/pdf Cirad license info:eu-repo/semantics/openAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.5194/hess-17-1079-2013 10.5194/hess-17-1079-2013 info:eu-repo/semantics/altIdentifier/doi/10.5194/hess-17-1079-2013 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.5194/hess-17-1079-2013
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic U10 - Informatique, mathématiques et statistiques
U30 - Méthodes de recherche
F60 - Physiologie et biochimie végétale
P40 - Météorologie et climatologie
télédétection
modèle mathématique
évapotranspiration
transpiration
changement climatique
couverture végétale
écosystème
végétation
échange d'énergie
technique de prévision
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_2741
http://aims.fao.org/aos/agrovoc/c_7871
http://aims.fao.org/aos/agrovoc/c_1666
http://aims.fao.org/aos/agrovoc/c_25409
http://aims.fao.org/aos/agrovoc/c_2482
http://aims.fao.org/aos/agrovoc/c_8176
http://aims.fao.org/aos/agrovoc/c_2568
http://aims.fao.org/aos/agrovoc/c_3041
http://aims.fao.org/aos/agrovoc/c_6734
http://aims.fao.org/aos/agrovoc/c_166
U10 - Informatique, mathématiques et statistiques
U30 - Méthodes de recherche
F60 - Physiologie et biochimie végétale
P40 - Météorologie et climatologie
télédétection
modèle mathématique
évapotranspiration
transpiration
changement climatique
couverture végétale
écosystème
végétation
échange d'énergie
technique de prévision
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_2741
http://aims.fao.org/aos/agrovoc/c_7871
http://aims.fao.org/aos/agrovoc/c_1666
http://aims.fao.org/aos/agrovoc/c_25409
http://aims.fao.org/aos/agrovoc/c_2482
http://aims.fao.org/aos/agrovoc/c_8176
http://aims.fao.org/aos/agrovoc/c_2568
http://aims.fao.org/aos/agrovoc/c_3041
http://aims.fao.org/aos/agrovoc/c_6734
http://aims.fao.org/aos/agrovoc/c_166
spellingShingle U10 - Informatique, mathématiques et statistiques
U30 - Méthodes de recherche
F60 - Physiologie et biochimie végétale
P40 - Météorologie et climatologie
télédétection
modèle mathématique
évapotranspiration
transpiration
changement climatique
couverture végétale
écosystème
végétation
échange d'énergie
technique de prévision
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_2741
http://aims.fao.org/aos/agrovoc/c_7871
http://aims.fao.org/aos/agrovoc/c_1666
http://aims.fao.org/aos/agrovoc/c_25409
http://aims.fao.org/aos/agrovoc/c_2482
http://aims.fao.org/aos/agrovoc/c_8176
http://aims.fao.org/aos/agrovoc/c_2568
http://aims.fao.org/aos/agrovoc/c_3041
http://aims.fao.org/aos/agrovoc/c_6734
http://aims.fao.org/aos/agrovoc/c_166
U10 - Informatique, mathématiques et statistiques
U30 - Méthodes de recherche
F60 - Physiologie et biochimie végétale
P40 - Météorologie et climatologie
télédétection
modèle mathématique
évapotranspiration
transpiration
changement climatique
couverture végétale
écosystème
végétation
échange d'énergie
technique de prévision
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_2741
http://aims.fao.org/aos/agrovoc/c_7871
http://aims.fao.org/aos/agrovoc/c_1666
http://aims.fao.org/aos/agrovoc/c_25409
http://aims.fao.org/aos/agrovoc/c_2482
http://aims.fao.org/aos/agrovoc/c_8176
http://aims.fao.org/aos/agrovoc/c_2568
http://aims.fao.org/aos/agrovoc/c_3041
http://aims.fao.org/aos/agrovoc/c_6734
http://aims.fao.org/aos/agrovoc/c_166
Marshall, K.
Tu, Kevin P.
Funk, C.
Michaelsen, J.
Williams, P.
Williams, Christopher
Ardö, Junas
Boucher, M.
Cappelaere, Bernard
De Grandcourt, Agnès
Nickless, A.
Nouvellon, Yann
Scholes, Robert J.
Kutsch, Werner L.
Improving operational land surface model canopyevapotranspiration in Africa using a direct remote sensing approach
description Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET), a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET), driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at NationalWeather Service Land Surface Model (GNOAH) to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.
format article
topic_facet U10 - Informatique, mathématiques et statistiques
U30 - Méthodes de recherche
F60 - Physiologie et biochimie végétale
P40 - Météorologie et climatologie
télédétection
modèle mathématique
évapotranspiration
transpiration
changement climatique
couverture végétale
écosystème
végétation
échange d'énergie
technique de prévision
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_2741
http://aims.fao.org/aos/agrovoc/c_7871
http://aims.fao.org/aos/agrovoc/c_1666
http://aims.fao.org/aos/agrovoc/c_25409
http://aims.fao.org/aos/agrovoc/c_2482
http://aims.fao.org/aos/agrovoc/c_8176
http://aims.fao.org/aos/agrovoc/c_2568
http://aims.fao.org/aos/agrovoc/c_3041
http://aims.fao.org/aos/agrovoc/c_6734
http://aims.fao.org/aos/agrovoc/c_166
author Marshall, K.
Tu, Kevin P.
Funk, C.
Michaelsen, J.
Williams, P.
Williams, Christopher
Ardö, Junas
Boucher, M.
Cappelaere, Bernard
De Grandcourt, Agnès
Nickless, A.
Nouvellon, Yann
Scholes, Robert J.
Kutsch, Werner L.
author_facet Marshall, K.
Tu, Kevin P.
Funk, C.
Michaelsen, J.
Williams, P.
Williams, Christopher
Ardö, Junas
Boucher, M.
Cappelaere, Bernard
De Grandcourt, Agnès
Nickless, A.
Nouvellon, Yann
Scholes, Robert J.
Kutsch, Werner L.
author_sort Marshall, K.
title Improving operational land surface model canopyevapotranspiration in Africa using a direct remote sensing approach
title_short Improving operational land surface model canopyevapotranspiration in Africa using a direct remote sensing approach
title_full Improving operational land surface model canopyevapotranspiration in Africa using a direct remote sensing approach
title_fullStr Improving operational land surface model canopyevapotranspiration in Africa using a direct remote sensing approach
title_full_unstemmed Improving operational land surface model canopyevapotranspiration in Africa using a direct remote sensing approach
title_sort improving operational land surface model canopyevapotranspiration in africa using a direct remote sensing approach
publisher Copernicus GmbH
url http://agritrop.cirad.fr/568061/
http://agritrop.cirad.fr/568061/1/document_568061.pdf
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