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Dynamic real-time prediction of flood inundation probabilities.

Romanowicz, Renata and Beven, Keith J. (1998) Dynamic real-time prediction of flood inundation probabilities. Hydrological Sciences - Journal des Sciences Hydrologiques, 43 (2). pp. 181-196. ISSN 0262-6667

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Abstract

The Bayesian Generalised Likelihood Uncertainty Estimation (GLUE) methodology, previously used in rainfall-runoff modelling, is applied to the distributed problem of predicting the space and time varying probabilities of inundation of all points on a flood plain. Probability estimates are based on conditioning predictions of Monte Carlo realizations of a distributed quasi-twodimensional flood routing model using known levels at sites along the reach. The methodology can be applied in the flood forecasting context for which the iV-step ahead inundation probability estimates can be updated in real time using telemetered information on water levels. It is also shown that it is possible to condition the Nstep ahead forecasts in real time using the (uncertain) on-line predictions of the downstream water levels at the end of the reach obtained from an adaptive transfer function model calibrated on reach scale inflow and outflow data.

Item Type: Article
Journal or Publication Title: Hydrological Sciences - Journal des Sciences Hydrologiques
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Departments: Faculty of Science and Technology > Lancaster Environment Centre
ID Code: 21864
Deposited By: ep_ss_importer
Deposited On: 10 Feb 2009 14:27
Refereed?: Yes
Published?: Published
Last Modified: 26 Jul 2012 15:52
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/21864

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