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Impact of the Timing of a SAR Image Acquisition on the Calibration of a Flood Inundation ModelSynthetic Aperture Radar (SAR) data have proven to be a very useful source of information for the calibration of flood inundation models. Previous studies have focused on assigning uncertainties to SAR images in order to improve flood forecast systems (e.g. Giustarini et al. (2015) and Stephens et al. (2012)). This paper investigates whether the timing of a SAR acquisition of a flood has an important impact on the calibration of a flood inundation model. As no suitable time series of SAR data exists, we generate a sequence of consistent SAR images through the use of a synthetic framework. This framework uses two available ERS-2 SAR images of the study area, one taken during the flood event of interest, the second taken during a dry reference period. The obtained synthetic observations at different points in time during the flood event are used to calibrate the flood inundation model. The results of this study indicate that the uncertainty of the roughness parameters is lower when the model is calibrated with an image taken before rather than during or after the flood peak. The results also show that the error on the modeled extent is much lower when the model is calibrated with a pre-flood peak image than when calibrated with a near-flood peak or a post-flood peak image. It is concluded that the timing of the SAR image acquisition of the flood has a clear impact on the model calibration and consequently on the precision of the predicted flood extent.
Document ID
20170001442
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Gobeyn, Sacha
(Ghent Univ. Belgium)
Van Wesemael, Alexandra
(Ghent Univ. Belgium)
Neal, Jeffrey
(Bristol Univ. United Kingdom)
Lievens, Hans
(Science collaborator)
Van Eerdenbrugh, Katrien
(Ghent Univ. Belgium)
De Vleeschouwer, Niels
(Ghent Univ. Belgium)
Vernieuwe, Hilde
(Ghent Univ. Belgium)
Schumann, Guy J.-P.
(Remote Sensing Solutions, Inc. United States)
Di Baldassarre, Giuliano
(Uppsala Univ. Uppsala, Sweden)
De Baets, Bernard
(Ghent Univ. Belgium)
Bates, Paul D.
(Bristol Univ. United Kingdom)
Verhoest, Niko E. C.
(Ghent Univ. Belgium)
Date Acquired
February 8, 2017
Publication Date
December 10, 2016
Publication Information
Publication: Advances in Water Resources
Publisher: Elsevier
Volume: 100
ISSN: 0309-1708
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN38723
Distribution Limits
Public
Copyright
Other
Keywords
Flood inundation
Hydraulic modeling

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