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| Titel |
Reconstruction of temporal variations of evapotranspiration using instantaneous estimates at the time of satellite overpass |
| VerfasserIn |
E. Delogu, G. Boulet, A. Olioso, B. Coudert, J. Chirouze, E. Ceschia, V. Dantec, O. Marloie, G. Chehbouni, J.-P. Lagouarde |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 16, no. 8 ; Nr. 16, no. 8 (2012-08-27), S.2995-3010 |
| Datensatznummer |
250013442
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| Publikation (Nr.) |
 copernicus.org/hess-16-2995-2012.pdf |
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| Zusammenfassung |
| Evapotranspiration estimates can be derived from remote sensing data and
ancillary, mostly meterorological, information. For this purpose, two types
of methods are classically used: the first type estimates a potential
evapotranspiration rate from vegetation indices, and adjusts this rate
according to water availability derived from either a surface temperature
index or a first guess obtained from a rough estimate of the water budget,
while the second family of methods relies on the link between the surface
temperature and the latent heat flux through the surface energy budget. The
latter provides an instantaneous estimate at the time of satellite overpass.
In order to compute daily evapotranspiration, one needs an extrapolation
algorithm. Since no image is acquired during cloudy conditions, these
methods can only be applied during clear sky days. In order to derive
seasonal evapotranspiration, one needs an interpolation method. Two combined
interpolation/extrapolation methods based on the self preservation of
evaporative fraction and the stress factor are compared to reconstruct
seasonal evapotranspiration from instantaneous measurements acquired in
clear sky conditions. Those measurements are taken from instantaneous latent
heat flux from 11 datasets in Southern France and Morocco. Results show that
both methods have comparable performances with a clear advantage for the
evaporative fraction for datasets with several water stress events. Both
interpolation algorithms tend to underestimate evapotranspiration due to the
energy limiting conditions that prevail during cloudy days. Taking into
account the diurnal variations of the evaporative fraction according to an
empirical relationship derived from a previous study improved the
performance of the extrapolation algorithm and therefore the retrieval of
the seasonal evapotranspiration for all but one datasets. |
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