Publications des scientifiques de l'IRD

Farhani N., Carreau Julie, Boulet Gilles, Kassouk Z., Mougenot B., Le Page Michel, Chabaane Z.L., Zitouna R. (2020). Scenarios of hydrometeorological variables based on auxiliary data for water stress retrieval in Central Tunisia. In : 2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS) : proceedings. Piscataway : IEEE, 293-296. M2GARSS.Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, TUNIS (TUN), 2020/03/9-11. ISBN 978-1-7281-2191-8.

Titre du document
Scenarios of hydrometeorological variables based on auxiliary data for water stress retrieval in Central Tunisia
Année de publication
2020
Type de document
Article référencé dans le Web of Science WOS:000604612500067
Auteurs
Farhani N., Carreau Julie, Boulet Gilles, Kassouk Z., Mougenot B., Le Page Michel, Chabaane Z.L., Zitouna R.
In
2020 Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS) : proceedings
Source
Piscataway : IEEE, 2020, 293-296 ISBN 978-1-7281-2191-8
Colloque
M2GARSS.Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, TUNIS (TUN), 2020/03/9-11
Characterization of plant water use, generally determined from evapotranspiration, together with water stress, derived from remote sensing data in the thermal infrared domain, are needed to better manage water resources. Evapotranspiration and water stress can be simulated by a dual source energy balance model that combines satellite and in situ hydrometeorological information. Available hydrometeorological observations are often insufficient to account for the spatial and temporal variability of the area of interest. To address this issue, we developed a stochastic weather generator that relies on ERA5 reanalyses and provides spatio-temporal scenarios of multiple hydrometeorological variables. The generator is evaluated and compared with two bias correction methods in terms of their ability to reproduce both observed hydrometeorological variables and simulated evapotranspiration and water stress in central Tunisia. Our analyses show that the stochastic generator offers interesting advantages to perform gap-filling and to extend the hydrometeorological time series in the past.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Bioclimatologie [072] ; Sciences du monde végétal [076] ; Télédétection [126]
Localisation
Fonds IRD [F B010084199]
Identifiant IRD
fdi:010084199
Contact