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Metamodeling for Uncertainty Quantification of a Flood Wave Model for Concrete Dam Breaks

Author

Listed:
  • Anna Kalinina

    (Laboratory for Energy System Analysis, Paul Scherrer Institut, 5232 Villigen PSI, Switzerland)

  • Matteo Spada

    (Laboratory for Energy System Analysis, Paul Scherrer Institut, 5232 Villigen PSI, Switzerland)

  • David F. Vetsch

    (Department of Civil, Environmental and Geomatic Engineering, ETH Zurich, Stefano-Franscini-Platz 5, 8093 Zurich, Switzerland)

  • Stefano Marelli

    (Department of Civil, Environmental and Geomatic Engineering, ETH Zurich, Stefano-Franscini-Platz 5, 8093 Zurich, Switzerland)

  • Calvin Whealton

    (Laboratory for Energy System Analysis, Paul Scherrer Institut, 5232 Villigen PSI, Switzerland)

  • Peter Burgherr

    (Laboratory for Energy System Analysis, Paul Scherrer Institut, 5232 Villigen PSI, Switzerland)

  • Bruno Sudret

    (Department of Civil, Environmental and Geomatic Engineering, ETH Zurich, Stefano-Franscini-Platz 5, 8093 Zurich, Switzerland)

Abstract

Uncertainties in instantaneous dam-break floods are difficult to assess with standard methods (e.g., Monte Carlo simulation) because of the lack of historical observations and high computational costs of the numerical models. In this study, polynomial chaos expansion (PCE) was applied to a dam-break flood model reflecting the population of large concrete dams in Switzerland. The flood model was approximated with a metamodel and uncertainty in the inputs was propagated to the flow quantities downstream of the dam. The study demonstrates that the application of metamodeling for uncertainty quantification in dam-break studies allows for reduced computational costs compared to standard methods. Finally, Sobol’ sensitivity indices indicate that reservoir volume, length of the valley, and surface roughness contributed most to the variability of the outputs. The proposed methodology, when applied to similar studies in flood risk assessment, allows for more generalized risk quantification than conventional approaches.

Suggested Citation

  • Anna Kalinina & Matteo Spada & David F. Vetsch & Stefano Marelli & Calvin Whealton & Peter Burgherr & Bruno Sudret, 2020. "Metamodeling for Uncertainty Quantification of a Flood Wave Model for Concrete Dam Breaks," Energies, MDPI, vol. 13(14), pages 1-25, July.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3685-:d:386286
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    References listed on IDEAS

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    1. Zellner, Arnold & Highfield, Richard A., 1988. "Calculation of maximum entropy distributions and approximation of marginalposterior distributions," Journal of Econometrics, Elsevier, vol. 37(2), pages 195-209, February.
    2. Philipp Arbenz, 2013. "Bayesian Copulae Distributions, with Application to Operational Risk Management—Some Comments," Methodology and Computing in Applied Probability, Springer, vol. 15(1), pages 105-108, March.
    3. Sudret, Bruno, 2008. "Global sensitivity analysis using polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 964-979.
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    Cited by:

    1. Amir Abdel Menaem & Rustam Valiev & Vladislav Oboskalov & Taher S. Hassan & Hegazy Rezk & Mohamed N. Ibrahim, 2020. "An Efficient Framework for Adequacy Evaluation through Extraction of Rare Load Curtailment Events in Composite Power Systems," Mathematics, MDPI, vol. 8(11), pages 1-21, November.

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