Statistical Characterization of Hazards and Risk in Coastal Areas

  • Donald T. Resio
  • Mark A. Tumeo
  • Jennifer L. Irish


We examine the foundation for hazard/risk assessment and its application to coastal problems. Historically, emphasis was on specifying expected values of wind waves and storm surges; however, as shown by the recent tsunamis in Southeast Asia in 2004 and in Japan in 2011, there are critical parts of the world where tsunamis represent the dominant threat to coastal communities. Recently, there has been an increased awareness of the combined effects of heavy rainfall and/or river discharge with surge levels and strong winds. This forcing combination played an important role in the flooding in southern Louisiana during Hurricane Isaac in 2012, where water levels exceeded the 500-year return interval levels. Such forcing combinations complicate both the modeling systems required for their simulation and the treatment of the multivariate probabilities that define the relative importance of their impacts.

We begin with a set of consistent hazards and risk definitions, along with comparative definitions from other fields. This should help readers who have focused primarily on traditional coastal hazards and risks understand the broader context of risk assessment and also allow readers with a broader perspective gain insight into the specific nature of coastal hazards and risk. Following this, we introduce the basic concepts used in estimating coastal hazards and risks. We then examine the historical perspective for the evolution of coastal risk assessment, beginning with early deterministic methods and culminating in a recent transition to probabilistic methods. The steady increase in the ability of probabilistic methods to deal with persistent problems such as the lack of data and uncertainty is documented as a part of this transition.


Tropical Cyclone Cumulative Distribution Function Return Period Central Pressure Recurrence Interval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

cumulative distribution function


empirical simulation technique


empirical track method


generalized Pareto distribution


high water mark


joint probability method


maximum possible intensity


optimal sampling


planetary boundary layer


probability density function


probable maximum hurricane


root mean square


Standard Project Hurricane


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Donald T. Resio
    • 1
  • Mark A. Tumeo
    • 2
  • Jennifer L. Irish
    • 3
  1. 1.Dep. Civil EngineeringUniversity of North FloridaJacksonvilleUSA
  2. 2.College of Computing, Engineering & ConstructionUniversity of North FloridaJacksonvilleUSA
  3. 3.Dep. Civil and Environmental EngineeringVirginia TechBlacksburgUSA

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