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| Titel |
Quantification of uncertainty sources in a 2D hydraulic model for the river Rhine using expert opinions |
| VerfasserIn |
J. J. Warmink, H. Van der Klis, M. J. Booij, S. J. M. H. Hulscher |
| Konferenz |
EGU General Assembly 2009
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250026732
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| Zusammenfassung |
| Hydrodynamic river models are applied to design and evaluate measures for purposes such as
safety against flooding. These numerical models are all based on a deterministic approach.
However, the modeling of river processes involves numerous uncertainties, resulting in
uncertain model results. Uncertainty is defined as any deviation from the unachievable ideal
of complete determinism. Uncertainty in models comprises (1) the difference between a
model outcome and a measurement and (2) the possible variation around the computed value
or measurements. Knowledge of the type and magnitude of these uncertainties is crucial for a
meaningful interpretation of the model results. The aim of this study is to identify the sources
of uncertainty that induce the largest uncertainties in the model outcomes and quantify this
uncertainty using expert opinions. In this study, the two-dimensional WAQUA model for
the Dutch river Rhine is used as an example for the quantification of uncertainty
sources.
Sixteen experts have been selected based on a Pedigree matrix with 4 criteria: 1)
experience with code development, 2) experience with WAQUA projects, 3) experience
in years, and 4) number and type of publications about WAQUA. The 16 experts
with the highest Pedigree scores have been invited for an interview. Interviews are
held with 11 of these experts. During the interviews, the experts are asked to list
the most important uncertainty sources for the following two situations: (1) the
computation of design water levels (DWL), based on a design discharge wave and (2)
the computation of the effect of a measure in the river bed, which is done using a
constant discharge as input. To compare the different experts, the experts are asked to
quantify the uncertainty sources on the same level of detail. Finally, the experts
are asked to quantify the effect of the uncertainty sources on the computed water
levels.
The experts stated that the sources of uncertainty are different for the computation of the
DWL and effect studies. In case of effect studies, the experts agreed that the sources of
uncertainty that do not change between the computation with and without a measure
have little influence on the uncertainty in the computed effect. In case of DWL
computations, the uncertainties are dominated by the sources that do not change between the
calibration and the prediction. The experts agreed that the imposed stage-discharge
relation and the roughness predictor for the main channel have a relatively large
uncertainty. Also the data used for calibration are mentioned as an important source
of uncertainty. Next to the large values given for the order of magnitude of the
uncertainty, also a large scatter is shown in the experts’ opinions. Finally, the effect of the
uncertainty sources on the model outcomes showed that the uncertainty sources have a
significant effect on the predicted water levels under design discharge conditions. |
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