Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Aronica, G. T.

Candela, A.

Colli, M.

Lanza, L. G.

English

Hydraulic Engineering Repository

Conference Paper, Published VersionColli, M.; Candela, A.; Aronica, G. T.; Lanza, L. G.Optimal Surface Drainage Inlets Positioning UsingStochastic Pluvial Flooding AnalysisZur Verfügung gestellt in Kooperation mit/Provided in Cooperation with:Kuratorium für Forschung im Küsteningenieurwesen (KFKI)Verfügbar unter/Available at: https://hdl.handle.net/20.500.11970/108593Vorgeschlagene Zitierweise/Suggested citation:Colli, M.; Candela, A.; Aronica, G. T.; Lanza, L. G. (2016): Optimal Surface Drainage InletsPositioning Using Stochastic Pluvial Flooding Analysis. In: Yu, Pao-Shan; Lo, Wie-Cheng(Hg.): ICHE 2016. Proceedings of the 12th International Conference on Hydroscience &Engineering, November 6-10, 2016, Tainan, Taiwan. Tainan: NCKU.Standardnutzungsbedingungen/Terms of Use:Die Dokumente in HENRY stehen unter der Creative Commons Lizenz CC BY 4.0, sofern keine abweichendenNutzungsbedingungen getroffen wurden. Damit ist sowohl die kommerzielle Nutzung als auch das Teilen, dieWeiterbearbeitung und Speicherung erlaubt. Das Verwenden und das Bearbeiten stehen unter der Bedingung derNamensnennung. Im Einzelfall kann eine restriktivere Lizenz gelten; dann gelten abweichend von den obigenNutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte.Documents in HENRY are made available under the Creative Commons License CC BY 4.0, if no other license isapplicable. Under CC BY 4.0 commercial use and sharing, remixing, transforming, and building upon the materialof the work is permitted. In some cases a different, more restrictive license may apply; if applicable the terms ofthe restrictive license will be binding.Verwertungsrechte: Alle Rechte vorbehalten12th International Conference on Hydroscience & Engineering Hydro-Science & Engineering for Environmental Resilience November 6-10, 2016, Tainan, Taiwan.  Optimal Surface Drainage Inlets Positioning Using Stochastic Pluvial Flooding Analysis M.Colli1, A.Candela2, G.T. Aronica3, L.G. Lanza1 1. Department of Civil, Chemical and Environmental Engineering, University of Genova 2. Department of Hydraulic, Environmental, Aerospace and Materials Engineering, University of Palermo 3. Department of Engineering, University of Messina .   ABSTRACT Pluvial flooding occurs because of excess rainfall when surface runoff cannot be fully drained by the artificial network (i.e. surface drainage deficiency) and/or when the drainage systems overflows (i.e. drainage systems failures). Because of surface drainage deficiencies, however, flooding events occur quite frequently as a consequence of rain events of lower intensity than the design one, even in case of proper dimensioning of the drainage system. Inlets are in those cases the critical nodes, and efficient drainage is only ensured when care is taken on their appropriate design and positioning within the drainage area.  In the present work, a methodology is proposed to stochastically assess the optimal positioning of inlets for reducing urban pluvial local flooding and mitigate the consequent flooding hazard. The optimal inlets positions are determined by means of a derivative-free multi-objective trade-off algorithm coupled with a hydrodynamic model (FLURB-2D) describing the propagation of flood waves. A dedicated parameterization of the inlets spatial distribution is addressed with the aim of minimizing a suitable object function and improving the efficiency of the system. The FLURB-2D model (Aronica and Lanza, 2005), originally developed for simulating rainfall excess propagation over initially dry areas, is here implemented on a selected study area in the town of Genoa (Italy). The study area is located in the eastern part of the town centre developed mainly during the thirties and therefore characterized by a regular urban structure (grid plan). Synthetic hyetographs based on both univariate e bivariate statistical analysis with suitable return periods were used as input to the FLURB-2D model.  Simulation results allow highlighting, as expected, that sewer inlets’ position can indeed have a large impact on the occurrence of urban pluvial flooding. In particular, the combined analysis of flood occurrence probability and hazard class maps confirm that topographic effects have the potential to produce local flooding with significant water depths and that inlets’ position conditions may affect the behavior of the urban drainage system as a whole.   Overall, the stochastic approach proposed in this study constitutes a useful tool for dealing with uncertainties in sewer inlet operational conditions and, as compared to deterministic approaches, it allows a more comprehensive assessment of urban pluvial flood hazard, which in turn enables better-informed flood risk assessment and management decisions.    

Optimal Surface Drainage Inlets Positioning Using Stochastic Pluvial Flooding Analysis

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Optimal Surface Drainage Inlets Positioning Using Stochastic Pluvial Flooding Analysis

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