Print Email Facebook Twitter Large-scale stochastic flood hazard analysis applied to the Po River Title Large-scale stochastic flood hazard analysis applied to the Po River Author Curran, A.N. (TU Delft Hydraulic Structures and Flood Risk; Deltares) de Bruijn, K.M. (Deltares) Domeneghetti, Alessio (University of Bologna) Bianchi, Federica (University of Bologna) Kok, M. (TU Delft Hydraulic Structures and Flood Risk) Vorogushyn, Sergiy (Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences) Castellarin, Attilio (University of Bologna) Date 2020 Abstract Reliable hazard analysis is crucial in the flood risk management of river basins. For the floodplains of large, developed rivers, flood hazard analysis often needs to account for the complex hydrology of multiple tributaries and the potential failure of dikes. Estimating this hazard using deterministic methods ignores two major aspects of large-scale risk analysis: the spatial–temporal variability of extreme events caused by tributaries, and the uncertainty of dike breach development. Innovative stochastic methods are here developed to account for these uncertainties and are applied to the Po River in Italy. The effects of using these stochastic methods are compared against deterministic equivalents, and the methods are combined to demonstrate applications for an overall stochastic hazard analysis. The results show these uncertainties can impact extreme event water levels by more than 2 m at certain channel locations, and also affect inundation and breaching patterns. The combined hazard analysis allows for probability distributions of flood hazard and dike failure to be developed, which can be used to assess future flood risk management measures. Subject CopulaDike breachingFailure probabilitiesFlood riskHazard analysisSystem behaviour To reference this document use: http://resolver.tudelft.nl/uuid:21558431-b014-4945-9649-6d229a28a223 DOI https://doi.org/10.1007/s11069-020-04260-w ISSN 0921-030X Source Natural Hazards, 104 (3), 2027-2049 Part of collection Institutional Repository Document type journal article Rights © 2020 A.N. Curran, K.M. de Bruijn, Alessio Domeneghetti, Federica Bianchi, M. Kok, Sergiy Vorogushyn, Attilio Castellarin Files PDF Curran2020_Article_Large_ ... odHaza.pdf 2.65 MB Close viewer /islandora/object/uuid:21558431-b014-4945-9649-6d229a28a223/datastream/OBJ/view