Articles | Volume 28, issue 13
https://doi.org/10.5194/hess-28-2831-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-2831-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Jul 2024
Research article |
| 03 Jul 2024
| 03 Jul 2024
Using the classical model for structured expert judgment to estimate extremes: a case study of discharges in the Meuse River
Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
Pattle Delamore Partners Ltd., Ōtautahi / Christchurch, New Zealand
Oswaldo Morales-Nápoles
Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
Matthijs Kok
Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
HKV consultants, Delft, the Netherlands
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To accurately assess flood risk, it is necessary to evaluate whether a dike will fail. The internal structure and slope conditions of dikes are different from place to place, and it is difficult to survey all of them. Thus, we proposed a method to define the heterogeneity of levees as uncertainty and to calculate the dike failure as probability. Our method can set conditions of dike failure that are closer to reality, and will contribute to improving the accuracy of flood risk assessment.
Elisa Ragno, Markus Hrachowitz, and Oswaldo Morales-Nápoles
Hydrol. Earth Syst. Sci., 26, 1695–1711, https://doi.org/10.5194/hess-26-1695-2022, https://doi.org/10.5194/hess-26-1695-2022, 2022
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Preprint withdrawn
Dominik Paprotny, Oswaldo Morales-Nápoles, and Sebastiaan N. Jonkman
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Short summary
This study proposes a new method for predicting extreme events such as floods on the river Meuse. The current method was shown to be unreliable as it did not predict a recent flood. We developed a model that includes information from experts and combines this with measurements. We found that this approach gives more accurate predictions, particularly for extreme events. The research is important for predictions of extreme flood levels that are necessary for protecting communities against floods.
This study proposes a new method for predicting extreme events such as floods on the river...
