HR: 09:00h
AN: H11G-04 [Abstracts]
TI: The influence of rating curve uncertainty on flood inundation predictions
AU: Pappenberger, F
EM: f.pappenberger@lancaster.ac.uk
AF: Lancaster University, Environmental Sciences, Lancaster, LA1 4YQ
United Kingdom
AU: Matgen, P
EM: matgen@crpgl.lu
AF: Centre de Recherche Public-Gabriel Lippmann, 162a, avenue de la Fa‹encerie, Luxembourg, 1511
Luxembourg
AU: * Beven, K
EM: k.beven@lancaster.ac.uk
AF: Lancaster University, Environmental Sciences, Lancaster, LA1 4YQ
United Kingdom
AU: Henry, J
EM: jb@sertit.u-strasbg.fr
AF: Service R‚gional de Traitement d'Image et de T‚l‚d‚tection (SERTIT), Parc d'Innovation - Bld S‚bastien
Brant BP 10413, ILLKIRCH CEDEX, 67412
France
AU: Pfister, L
AF: Centre de Recherche Public-Gabriel Lippmann, 162a, avenue de la Fa‹encerie, Luxembourg, 1511
Luxembourg
AU: de Fraipont, P
AF: Service R‚gional de Traitement d'Image et de T‚l‚d‚tection (SERTIT), Parc d'Innovation - Bld S‚bastien
Brant BP 10413, ILLKIRCH CEDEX, 67412
France
AB:
The uncertainty of rating curves is well explored and understood in current literature. However, most estimations and methods
are usually accompanied by a warning not to extrapolate the rating curve beyond a certain range. This is very often
impossible for flooding events. Nevertheless, the uncertainty in using these rating curves for flood inundation models is
usually ignored. In this paper we investigate the effect of uncertainty of rating curves on flood inundation predictions. The
rating curve has been interpolated with two different equations, which are commonly used. The first method is based on a
polynomial representation and the second method interpolates data points with the help of the Manning equation. A set of
rating curves which represent the system equally well has been derived via the Generalized Likelihood Uncertainty Estimation
(GLUE) and the Multicomponent Mapping (Mx) methodology. The multiple rating curves have been used as upstream boundary of the
one dimensional unsteady flow routing model HEC-RAS. The manning roughness as well as the model input have been considered
as uncertain and varied within a Monte Carlo framework. The model has been evaluated on inundation information retrieved from
three different remote sensing sources.
DE: 1719 Hydrology
DE: 1812 Drought
DE: 1860 Runoff and streamflow
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting