Identification and Quantification of Uncertainties in a Hydrodynamic River Model Using Expert Opinions

Identification and Quantification of Uncertainties in a Hydrodynamic River Model Using Expert Opinions

0.00 Avg rating0 Votes
Article ID: iaor20111995
Volume: 25
Issue: 2
Start Page Number: 601
End Page Number: 622
Publication Date: Jan 2011
Journal: Water Resources Management
Authors: , , ,
Keywords: uncertainty, floods
Abstract:

Hydrodynamic river models are applied to design and evaluate measures for purposes such as safety against flooding. The modelling of river processes involves numerous uncertainties, resulting in uncertain model outcomes. Knowledge of the type and magnitude of uncertainties is crucial for a meaningful interpretation of the model results and the usefulness of results in decision making processes. The aim of this study is to identify the sources of uncertainty that contribute most to the uncertainties in the model outcomes and quantify their contribution to the uncertainty in the model outcomes. Experts have been selected based on an objective Pedigree analysis. The selected experts are asked to quantify the most important uncertainties for two situations: (1) the computation of design water levels and (2) the computation of the hydraulic effect of a change in the river bed. For the computation of the design water level, the uncertainties are dominated by the sources that do not change between the calibration and the prediction. The experts state that the upstream discharge and the empirical roughness equation for the main channel have the largest influence on the uncertainty in the modeled water levels. For effect studies, the floodplain bathymetry, weir formulation and discretization of floodplain topography contribute most to the uncertainties in model outcomes. Finally, the contribution of the uncertainties to the model outcomes show that the uncertainties have a significant effect on the predicted water levels, especially under design conditions.

Reviews

Required fields are marked *. Your email address will not be published.