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. Improving operational land surface model canopyevapotranspiration in Africa using a direct remote sensing approach. Hydrology and Earth System Sciences, 17 : 1079-1091.

https://doi.org/10.5194/hess-17-1079-2013

Article de revue ; Article de revue à facteur d'impact Revue en libre accès total

Prévisualisation

Version publiée - Anglais
Utilisation soumise à autorisation de l'auteur ou du Cirad.
document_568061.pdf
Télécharger (1MB) | Prévisualisation

Quartile : Q1, Sujet : WATER RESOURCES / Quartile : Q1, Sujet : GEOSCIENCES, MULTIDISCIPLINARY

Résumé : 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.

Mots-clés Agrovoc : télédétection, modèle mathématique, évapotranspiration, transpiration, changement climatique, couverture végétale, écosystème, végétation, échange d'énergie, technique de prévision

Mots-clés géographiques Agrovoc : Sahel, Afrique au sud du Sahara

Classification Agris : U10 - Informatique, mathématiques et statistiques
U30 - Méthodes de recherche
F60 - Physiologie et biochimie végétale
P40 - Météorologie et climatologie

Champ stratégique Cirad : Axe 6 (2005-2013) - Agriculture, environnement, nature et sociétés

Auteurs et affiliations