Uncertainty quantification of floodplain friction in hydrodynamic models

Uncertainty quantification of floodplain friction in hydrodynamic models

This study proposes a framework to estimate the uncertainty of hydrodynamic models on floodplains. The traditional floodplain resistance formula of Pasche (1984) (based on Lindner, 1982) used for river modelling as well as the approaches of Baptist et al. (2007), Järvelä (2004), and Battiato and Rub...

Full description

Saved in:
Bibliographic Details
Published in:Hydrology and earth system sciences Vol. 23; no. 8; pp. 3373 - 3385
Main Authors: Dalledonne, Guilherme Luiz, Kopmann, Rebekka, Brudy-Zippelius, Thomas
Format: Journal Article
Language:English
Published: Katlenburg-Lindau Copernicus GmbH 15-08-2019
Copernicus Publications
Subjects:
Approximation
Computer simulation
Floodplains
Flow velocity
Formulae
Friction
Hydrodynamic models
Hydrodynamics
Mathematical models
Metamodels
Monte Carlo methods
Monte Carlo simulation
Parameters
Permeability
Plant cover
Rivers
Statistical methods
Steady flow
Two dimensional models
Uncertainty
Variance analysis
Velocity
Water levels
United States
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This study proposes a framework to estimate the uncertainty of hydrodynamic models on floodplains. The traditional floodplain resistance formula of Pasche (1984) (based on Lindner, 1982) used for river modelling as well as the approaches of Baptist et al. (2007), Järvelä (2004), and Battiato and Rubol (2014) was considered for carrying out an uncertainty quantification (UQ). The analysis was performed by means of three different methods: traditional Monte Carlo (MC), first-order second-moment (FOSM) and metamodelling. Using a two-dimensional hydrodynamic model, a 10 km reach of the River Rhine was simulated. The model was calibrated with water level measurements under steady flow conditions and then the analysis was carried out based on flow velocity results. The compared floodplain friction formulae produced qualitatively similar results, in which uncertainties in flow velocity were most significant on the floodplains. Among the tested resistance formulae the approach from Järvelä (2004) presented on average the smallest prediction intervals, i.e. the smallest variance. It is important to keep in mind that UQ results are not only dependent on the defined input parameter deviations, but also on the number of parameters considered in the analysis. In that sense, the approach from Battiato and Rubol (2014) is still attractive for it reduces the current analysis to a single parameter, the canopy permeability. The three UQ methods compared gave similar results, which means that FOSM is the less expensive one. Nevertheless it should be used with caution as it is a first-order method (linear approximation). In studies involving dominant non-linear processes, one is advised to carry out further comparisons.
ISSN:1607-7938
1027-5606
1607-7938
DOI:10.5194/hess-23-3373-2019