Impact of Satellite and In Situ Data Assimilation on Hydrological Predictions
International audience The assimilation of different satellite and in situ products generally improves the hydrological model predictive skill. Most studies have focused on assimilating a single product at a time with the ensemble size subjectively chosen by the modeller. In this study, we used the...
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Bibliographic Details
Published in: | Remote Sensing |
Main Authors: |
Musuuza, Jude Lubega,
Gustafsson, David,
Pimentel, Rafael,
Crochemore, Louise,
Pechlivanidis, Ilias |
Other Authors: |
Swedish Meteorological and Hydrological Institute (SMHI),
Universidad de Córdoba = University of Córdoba Córdoba,
Swedish Meteorological and Hydrological Institute (SMHI), Hydrology Research, Norrköping,
Hydrosystèmes et Bioprocédés (UR HBAN),
Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF),
Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA),
Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ),
Université Grenoble Alpes (UGA),
RiverLy - Fonctionnement des hydrosystèmes (RiverLy),
Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE),
Institut des Géosciences de l’Environnement (IGE),
Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ) |
Format: | Article in Journal/Newspaper
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Language: | English |
Published: |
HAL CCSD
2020
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Subjects: |
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Online Access: | https://hal.science/hal-04670901
https://hal.science/hal-04670901/document
https://hal.science/hal-04670901/file/remotesensing-12-00811-v2.pdf
https://doi.org/10.3390/rs12050811
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