HR: 10:55h
AN: H12C-03    [Abstracts]
TI: Utility of different data types for calibrating flood inundation models within a GLUE framework
AU: Hunter, N M
EM: neil.hunter@bristol.ac.uk
AF: University of Bristol, School of Geographical Sciences, University Road, Bristol, BS8 1SS United Kingdom
AU: * Bates, P D
EM: Paul.Bates@Bristol.ac.uk
AF: University of Bristol, School of Geographical Sciences, University Road, Bristol, BS8 1SS United Kingdom
AU: Horritt, M S
EM: Matt.Horritt@bristol.ac.uk
AF: University of Bristol, School of Geographical Sciences, University Road, Bristol, BS8 1SS United Kingdom
AB: In this paper we explore the value of different types of data in constraining the predictions of a simple two-dimensional hydraulic model, LISFLOOD-FP, applied to the January 1995 flooding on the River Meuse, The Netherlands. For a 35 km reach of the Meuse between Borgharen and Maaseik a data set has been assembled consisting of Synthetic Aperture Radar and air photo images of inundation extent, downstream stage and discharge hydrographs, two stage hydrographs internal to the model domain and 84 point observations of maximum free surface elevation. The data set thus contains examples of all the types of data that can potentially be used to calibrate flood inundation models. 500 realisations of the model have been conducted with different friction parameterisations and the performance of each realisation has been evaluated against each observed data set. Implementation of the Generalised Likelihood Uncertainty Estimation (GLUE) methodology is then used to determine the value of each data set in constraining the model predictions and to determine the reduction in parameter uncertainty resulting from the updating of generalised likelihoods based on multiple data sources.
DE: 1821 Floods
DE: 1860 Runoff and streamflow
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting