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Bayesian estimation of flood inundation probabilities as conditioned on event inundation maps.

Romanowicz, Renata and Beven, Keith J. (2003) Bayesian estimation of flood inundation probabilities as conditioned on event inundation maps. Water Resources Research, 39 (3). p. 1073. ISSN 0043-1397

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Abstract

The generalized likelihood uncertainty estimation (GLUE) methodology is applied to the problem of predicting the spatially distributed, time-varying probabilities of inundation of all points on a floodplain. Advantage is taken of the relative independence of different effective conveyance parameters to minimize the simulations required. Probability estimates are based on conditioning predictions of Monte Carlo realizations of a distributed quasi-two-dimensional flood routing model using maps of maximum inundation and aerial photographs of flooding in the area. The methodology allows posterior distributions of conveyance parameters to be estimated and maps of inundation potential probabilities to be drawn up for flood events of different magnitudes. The results suggest that combining information from different magnitude events should be done with care, as the distributions of effective parameter values may vary with event magnitude. The value of accurate topographic information that is consistent with mapped inundation is also highlighted. The methodology can be used to obtain dynamic probabilities of floodplain inundation in real time forecasting.

Item Type: Article
Journal or Publication Title: Water Resources Research
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Departments: Faculty of Science and Technology > Lancaster Environment Centre
ID Code: 21418
Deposited By: ep_ss_importer
Deposited On: 13 Jan 2009 14:15
Refereed?: Yes
Published?: Published
Last Modified: 26 Jul 2012 15:46
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/21418

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