Impact of the timing of a SAR image acquisition on the calibration of a flood inundation model

Sacha Gobeyn, Alexandra Van Wesemael*, Jeffrey Neal, Hans Lievens, Katrien Van Eerdenbrugh, Niels De Vleeschouwer, Guy Schumann, Giuliano Di Baldassarre, Bernard De Baets, Paul Bates, Niko E C Verhoest

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

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Synthetic 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 modelled 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.

Original languageEnglish
Pages (from-to)126-138
Number of pages13
JournalAdvances in Water Resources
Early online date10 Dec 2016
Publication statusPublished - 1 Feb 2017


  • Calibration
  • Flood inundation
  • Hydraulic modelling
  • Remote sensing


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