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

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.