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  • 1. Brandimarte, Luigia
    The seventh facet of uncertainty: wrong assumptions, unknowns and surprises in the dynamics of human–water systems2016Ingår i: Hydrological Sciences Journal, ISSN 0262-6667, E-ISSN 2150-3435, Vol. 61, nr 9, s. 1748-1758Artikel i tidskrift (Refereegranskat)
  • 2. Mazzoleni, M.
    et al.
    Dottori, F.
    Brandimarte, Luigia
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Byggvetenskap, Vattendragsteknik.
    Tekle, S.
    Martina, M. L. V.
    Effects of levee cover strength on flood mapping in the case of levee breach due to overtopping2017Ingår i: Hydrological Sciences Journal, ISSN 0262-6667, E-ISSN 2150-3435, Vol. 62, nr 6, s. 892-910Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The reliability of a levee system is a crucial factor in flood risk management. In this study we present a probabilistic methodology to assess the effects of levee cover strength on levee failure probability, triggering time, flood propagation and consequent impacts on population and assets. A method for determining fragility curves is used in combination with the results of a one-dimensional hydrodynamic model to estimate the conditional probability of levee failure in each river section. Then, a levee breach model is applied to calculate the possible flood hydrographs, and for each breach scenario a two-dimensional hydrodynamic model is used to estimate flood hazard (flood extent and timing, maximum water depths) and flood impacts (economic damage and affected population) in the areas at risk along the river reach. We show an application for levee overtopping and different flood scenarios for a 98 km reach of the lower Po River in Italy. The results show how different design solutions for the levee cover can influence the probability of levee failure and the consequent flood scenarios. In particular, good grass cover strength can significantly delay levee failure and reduce maximum flood depths in the flood-prone areas, thus helping the implementation of flood risk management actions.

  • 3.
    Okoli, Kenechukwu
    et al.
    Uppsala Univ, Dept Earth Sci, Uppsala, Sweden.;Ctr Nat Hazards & Disaster Sci CNDS, Uppsala, Sweden..
    Breinl, Korbinian
    Uppsala Univ, Dept Earth Sci, Uppsala, Sweden.;Ctr Nat Hazards & Disaster Sci CNDS, Uppsala, Sweden..
    Brandimarte, Luigia
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Hållbar utveckling, miljövetenskap och teknik.
    Botto, Anna
    Univ Padua, Dept Civil Environm & Architectural Engn, Padua, Italy..
    Volpi, Elena
    Univ Roma Tre, Dept Sci Ingn Civile, Rome, Italy..
    Di Baldassarre, Giuliano
    Uppsala Univ, Dept Earth Sci, Uppsala, Sweden.;Ctr Nat Hazards & Disaster Sci CNDS, Uppsala, Sweden..
    Model averaging versus model selection: estimating design floods with uncertain river flow data2018Ingår i: Hydrological Sciences Journal, ISSN 0262-6667, E-ISSN 2150-3435, Vol. 63, nr 13-14, s. 1913-1926Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This study compares model averaging and model selection methods to estimate design floods, while accounting for the observation error that is typically associated with annual maximum flow data. Model selection refers to methods where a single distribution function is chosen based on prior knowledge or by means of selection criteria. Model averaging refers to methods where the results of multiple distribution functions are combined. Numerical experiments were carried out by generating synthetic data using the Wakeby distribution function as the parent distribution. For this study, comparisons were made in terms of relative error and root mean square error (RMSE) referring to the 1-in-100 year flood. The experiments show that model averaging and model selection methods lead to similar results, especially when short samples are drawn from a highly asymmetric parent. Also, taking an arithmetic average of all design flood estimates gives estimated variances similar to those obtained with more complex weighted model averaging.

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