Multi-Mechanism Flood Hazard Assessment: Critical Review of Current Practice and Approaches and Example Use Studies (NUREG/CR-7296)

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Publication Information

Manuscript Completed: February 2022
Date Published: October 2022

Prepared by:
Michelle Bensi, Somayeh Mohammadi
University of Maryland, College Park
College Park, MD 20742

Shih-Chieh Kao, Scott T. DeNeale
Oak Ridge National Laboratory
Oak Ridge, TN 37831-6038

Elena Yegorova, NRC Project Manager

Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington DC 20555-0001

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Flooding of nuclear power plants and other infrastructure can occur because of events involving one or multiple coincident or correlated flood mechanisms. Existing approaches for probabilistic flood hazard assessment (PFHA) focus primarily on the occurrence of a single flood hazard mechanism. However, multi-mechanism flood (MMF) events may result in flooding with severity, duration, characteristics, and extent of impacts that differ from the effects of floods involving a single mechanism. Moreover, the estimated frequency of occurrence of flood severity metrics (e.g., flood elevation or depth) may change (increase) when considering the enhanced impacts of MMF events. Thus, to have a comprehensive estimate of flood hazards for our critical infrastructures, events involving both single and multiple flood mechanisms must be considered.

To extend the state of practice of MMF analysis, this study focuses on the identification of existing research and development of new methods to probabilistically assess hazards associated with MMF events. This research project is funded by the US Nuclear Regulatory Commission PFHA Research Program with an intent to support the development of future guidance on PFHA. This report provides an overview of project research activities focusing on identification of existing approaches for probabilistically assessing MMF events and provides a critique and gap assessment of the current state of practice. It further discusses options for leveraging and extending approaches that show promise (with or without modifications) to support probabilistic assessment of MMF hazards associated with the range of return periods of relevance to nuclear power plants and other critical infrastructure. Two case studies are included to demonstrate the implementation of MMF methods in practice.

Page Last Reviewed/Updated Monday, October 17, 2022