Publications des scientifiques de l'IRD

Amri R., Zribi M., Lili-Chabaane Z., Szczypta C., Calvet J. C., Boulet Gilles. (2014). FAO-56 dual model combined with multi-sensor remote sensing for regional evapotranspiration estimations. Remote Sensing, 6 (6), p. 5387-5406. ISSN 2072-4292.

Titre du document
FAO-56 dual model combined with multi-sensor remote sensing for regional evapotranspiration estimations
Année de publication
2014
Type de document
Article référencé dans le Web of Science WOS:000338763300032
Auteurs
Amri R., Zribi M., Lili-Chabaane Z., Szczypta C., Calvet J. C., Boulet Gilles
Source
Remote Sensing, 2014, 6 (6), p. 5387-5406 ISSN 2072-4292
The main goal of this study is to evaluate the potential of the FAO-56 dual technique for the estimation of regional evapotranspiration (ET) and its constituent components (crop transpiration and soil evaporation), for two classes of vegetation (olives trees and cereals) in the semi-arid region of the Kairouan plain in central Tunisia. The proposed approach combines the FAO-56 technique with remote sensing (optical and microwave), not only for vegetation characterization, as proposed in other studies but also for the estimation of soil evaporation, through the use of satellite moisture products. Since it is difficult to use ground flux measurements to validate remotely sensed data at regional scales, comparisons were made with the land surface model ISBA-A-gs which is a physical SVAT (Soil-Vegetation-Atmosphere Transfer) model, an operational tool developed by Meteo-France. It is thus shown that good results can be obtained with this relatively simple approach, based on the FAO-56 technique combined with remote sensing, to retrieve temporal variations of ET. The approach proposed for the daily mapping of evapotranspiration at 1 km resolution is approved in two steps, for the period between 1991 and 2007. In an initial step, the ISBA-A-gs soil moisture outputs are compared with ERS/WSC products. Then, the output of the FAO-56 technique is compared with the output generated by the SVAT ISBA-A-gs model.
Plan de classement
Bioclimatologie [072] ; Télédétection [126]
Description Géographique
TUNISIE
Localisation
Fonds IRD [F B010062378]
Identifiant IRD
fdi:010062378
Contact