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Fast-Processing DEM-Based Urban and Rural Inundation Scenarios from Point-Source Flood Volumes

Author

Listed:
  • Kay Khaing Kyaw

    (Department of Civil, Chemical, Environmental and Materials Engineering (DICAM), University of Bologna, 40136 Bologna, Italy)

  • Federica Bonaiuti

    (Department of Civil, Chemical, Environmental and Materials Engineering (DICAM), University of Bologna, 40136 Bologna, Italy
    Autorità di Bacino Distrettuale del Fiume Po, Strada Garibaldi 75, 43121 Parma, Italy)

  • Huimin Wang

    (Department of Civil, Chemical, Environmental and Materials Engineering (DICAM), University of Bologna, 40136 Bologna, Italy)

  • Stefano Bagli

    (GECOsistema Srl, 47923 Rimini, Italy)

  • Paolo Mazzoli

    (GECOsistema Srl, 47923 Rimini, Italy)

  • Pier Paolo Alberoni

    (Arpae-SIMC, Hydro-Meteo-Climate Service of the Regional Agency for Prevention, Environment and Energy (ARPAE), 40122 Bologna, Italy)

  • Simone Persiano

    (Department of Civil, Chemical, Environmental and Materials Engineering (DICAM), University of Bologna, 40136 Bologna, Italy
    Catastrophe Risk Modeling & Mitigation, UnipolSai Assicurazioni S.p.A., Piazza della Costituzione 2/2, 40128 Bologna, Italy)

  • Attilio Castellarin

    (Department of Civil, Chemical, Environmental and Materials Engineering (DICAM), University of Bologna, 40136 Bologna, Italy)

Abstract

Flooding has always been a huge threat to human society. Global climate change coupled with unsustainable regional planning and urban development may cause more frequent inundations and, consequently, higher societal and economic losses. In order to characterize floods and reduce flood risk, flood simulation tools have been developed and widely applied. Hydrodynamic models for inundation simulation are generally sophisticated, yet they normally require massive setup and computational costs. In contrast, simplified conceptual models may be more easily applied and efficient. Based on the Hierarchical Filling-and-Spilling or Puddle-to-Puddle Dynamic Filling-and-Spilling Algorithms (i.e., HFSAs), Safer_RAIN has been developed as a fast-processing DEM-based model for modelling pluvial flooding over large areas. This study assesses Safer_RAIN applicability outside the context for which it was originally developed by looking at two different inundation problems with point-source flooding volumes: (1) rural inundation modelling associated with levee breaching/overtopping; (2) urban flooding caused by drainage systems outflow volumes.

Suggested Citation

  • Kay Khaing Kyaw & Federica Bonaiuti & Huimin Wang & Stefano Bagli & Paolo Mazzoli & Pier Paolo Alberoni & Simone Persiano & Attilio Castellarin, 2024. "Fast-Processing DEM-Based Urban and Rural Inundation Scenarios from Point-Source Flood Volumes," Sustainability, MDPI, vol. 16(2), pages 1-22, January.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:875-:d:1322632
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    References listed on IDEAS

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    1. Julien Ernst & Benjamin Dewals & Sylvain Detrembleur & Pierre Archambeau & Sébastien Erpicum & Michel Pirotton, 2010. "Micro-scale flood risk analysis based on detailed 2D hydraulic modelling and high resolution geographic data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 55(2), pages 181-209, November.
    2. J. Teng & J. Vaze & D. Dutta & S. Marvanek, 2015. "Rapid Inundation Modelling in Large Floodplains Using LiDAR DEM," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2619-2636, June.
    3. Salvatore Manfreda & Caterina Samela & Andrea Gioia & Giuseppe Consoli & Vito Iacobellis & Luciana Giuzio & Andrea Cantisani & Aurelia Sole, 2015. "Flood-prone areas assessment using linear binary classifiers based on flood maps obtained from 1D and 2D hydraulic models," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(2), pages 735-754, November.
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