Hide metadata

dc.date.accessioned2018-03-13T08:28:40Z
dc.date.available2018-03-13T08:28:40Z
dc.date.created2017-12-27T12:34:52Z
dc.date.issued2017
dc.identifier.citationFuentes-Andino, Diana Beven, Keith Halldin, Sven Xu, Chong-Yu Reynolds, Jose Eduardo Di Baldassarre, Giuliano . Reproducing an extreme flood with uncertain post-event information. Hydrology and Earth System Sciences. 2017, 21(7), 3597-3618
dc.identifier.urihttp://hdl.handle.net/10852/60927
dc.description.abstractStudies for the prevention and mitigation of floods require information on discharge and extent of inundation, commonly unavailable or uncertain, especially during extreme events. This study was initiated by the devastating flood in Tegucigalpa, the capital of Honduras, when Hurricane Mitch struck the city. In this study we hypothesized that it is possible to estimate, in a trustworthy way considering large data uncertainties, this extreme 1998 flood discharge and the extent of the inundations that followed from a combination of models and post-event measured data. Post-event data collected in 2000 and 2001 were used to estimate discharge peaks, times of peak, and high-water marks. These data were used in combination with rain data from two gauges to drive and constrain a combination of well-known modelling tools: TOPMODEL, Muskingum–Cunge–Todini routing, and the LISFLOOD-FP hydraulic model. Simulations were performed within the generalized likelihood uncertainty estimation (GLUE) uncertainty-analysis framework. The model combination predicted peak discharge, times of peaks, and more than 90 % of the observed high-water marks within the uncertainty bounds of the evaluation data. This allowed an inundation likelihood map to be produced. Observed high-water marks could not be reproduced at a few locations on the floodplain. Identifications of these locations are useful to improve model set-up, model structure, or post-event data-estimation methods. Rainfall data were of central importance in simulating the times of peak and results would be improved by a better spatial assessment of rainfall, e.g. from radar data or a denser rain-gauge network. Our study demonstrated that it was possible, considering the uncertainty in the post-event data, to reasonably reproduce the extreme Mitch flood in Tegucigalpa in spite of no hydrometric gauging during the event. The method proposed here can be part of a Bayesian framework in which more events can be added into the analysis as they become available.en_US
dc.languageEN
dc.language.isoenen_US
dc.publisherCopernicus
dc.rightsAttribution 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/
dc.titleReproducing an extreme flood with uncertain post-event informationen_US
dc.typeJournal articleen_US
dc.creator.authorFuentes-Andino, Diana
dc.creator.authorBeven, Keith
dc.creator.authorHalldin, Sven
dc.creator.authorXu, Chong-Yu
dc.creator.authorReynolds, Jose Eduardo
dc.creator.authorDi Baldassarre, Giuliano
cristin.unitcode185,15,22,0
cristin.unitnameInstitutt for geofag
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.cristin1532072
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Hydrology and Earth System Sciences&rft.volume=21&rft.spage=3597&rft.date=2017
dc.identifier.jtitleHydrology and Earth System Sciences
dc.identifier.volume21
dc.identifier.issue7
dc.identifier.startpage3597
dc.identifier.endpage3618
dc.identifier.doihttp://dx.doi.org/10.5194/hess-21-3597-2017
dc.identifier.urnURN:NBN:no-63600
dc.type.documentTidsskriftartikkelen_US
dc.type.peerreviewedPeer reviewed
dc.source.issn1027-5606
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/60927/1/hess-21-3597-2017.pdf
dc.type.versionPublishedVersion


Files in this item

Appears in the following Collection

Hide metadata

Attribution 3.0 Unported
This item's license is: Attribution 3.0 Unported