Journal of Marine Science and Engineering (Mar 2017)

Application of State of the Art Modeling Techniques to Predict Flooding and Waves for a Coastal Area within a Protected Bay

  • Malcolm L. Spaulding,
  • Annette Grilli,
  • Chris Damon,
  • Grover Fugate,
  • Tatsu Isaji,
  • Lauren Schambach

DOI
https://doi.org/10.3390/jmse5010014
Journal volume & issue
Vol. 5, no. 1
p. 14

Abstract

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Flood Insurance Rate Maps (FIRMs) are developed by the Federal Emergency Management Agency (FEMA) to provide guidance in establishing the risk to structures and infrastructure from storm surge sand associated waves in the coastal zone. The maps are used by state agencies and municipalities to help guide coastal planning and establish the minimum elevation and construction standards for new or substantially improved structures. A summary of the methods used and a comparison with the results of 2013 FIRM mapping are presented for Warwick, Rhode Island (RI), a coastal community located within Narragansett Bay. Because of its location, Warwick is protected from significant coastal erosion and wave attacks, but is subject to surge amplification. Concerns surrounding the FEMA methods used in the 2013 FIRM analysis are put in context with the National Research Council’s (NRC) 2009 review of the FEMA coastal mapping program. New mapping is then performed using state of the art, fully coupled surge and wave modeling, and data analysis methods, to address the NRC concerns. The new maps and methodologies are in compliance with FEMA regulations and guidelines. This new approach makes extensive use of the numerical modeling results from the recent US Army Corp of Engineers, North Atlantic Coast Comprehensive Study (NACCS, 2015). Revised flooding maps are presented and compared to the 2013 FIRM maps, to provide insight into the differences. The new maps highlight the importance of developing better estimates of surge dynamics and the advancement in nearshore mapping of waves in flood inundated areas by the use of state of the art, two-dimensional, wave transformation models.

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