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TitleUncertainty analysis of a two-dimensional hydraulic model
AuthorOubennaceur, K; Chokmani, K; Nastev, M; Tanguy, M; Raymond, S
Source"Water (Switzerland)"; vol. 10, 3, 2018., https://doi.org/10.3390/w10030272
Year2018
Alt SeriesNatural Resources Canada, Contribution Series 20182499
PublisherMDPI AG
Documentserial
Lang.English
Mediapaper; on-line; digital
ProgramRapid Risk Assessment, Public Safety Geoscience
Released2018 03 04
AbstractA reliability approach referred to as the point estimate method (PEM) is presented to assess the uncertainty of a two-dimensional hydraulic model. PEM is a special case of numerical quadrature based on orthogonal polynomials, which evaluates the statistical moments of a performance function involving random variables. When applied to hydraulic problems, the variables are the inputs to the hydraulic model, and the first and second statistical moments refer to the mean and standard deviation of the model's output. In providing approximate estimates of the uncertainty, PEM appears considerably simpler and requires less information and fewer runs than standard Monte Carlo methods. An example of uncertainty assessment is shown for simulated water depths in a 46 km reach of the Richelieu River, Canada. The 2D hydraulic model, H2D2, was used to solve the shallow water equations. Standard deviations around the mean water depths were estimated by considering the uncertainties of three main input variables: flow rate, Manning's coefficient and topography. Results indicate that the mean standard deviation is < 27 cm for the considered flow rates of 759, 824, 936, 1113 m3/s. Higher standard deviations were obtained upstream of the topographic shoal at the municipality of Saint-Jean-sur-Richelieu. The PEM method adds further value to the H2D2 model predictions as it indicates the magnitude and the spatial variation in uncertainties. The effort required to complete an uncertainty analysis using the PEM method is minimal and the resulting insight is meaningful. This knowledge should be incorporated into decision-making in the context of flood risk assessment. © 2018 by the authors.
GEOSCAN ID311092