Simulating storm surge waves for structural vulnerability estimation and flood hazard mapping

Wave action during storm surge is a common cause of building damage and therefore a critical consideration when estimating structural vulnerability and mapping flood risk. Traditional depth-damage curves, however, relate building vulnerability solely to inundation depth and therefore neglect an important damage mechanism. Similarly, flood mapping studies typically emphasize expected inundation rather than wave conditions. In this study, we consider the impact of wave effects on vulnerability estimation and flood mapping using a pair of hydrodynamic models (ADCIRC + SWAN and BOUSS1D) to simulate inland storm surge flooding. The models are used to simulate flooding in a heavily impacted coastal community (Ortley Beach, New Jersey) during Hurricane Sandy (2012) and to estimate inland hazard parameters characterizing inundation, wave and velocity effects. To quantify structural vulnerability, fragility curves are developed by statistically relating the simulated hazard parameters to surveyed building damage. The results indicate that dynamic hazard characteristics such as significant wave height are the dominant predictors of severe structural damage. The flood simulation is also used to map the variation of surge and wave effects in the community. Comparing this analysis to flood zones delineated by the Federal Emergency Management Agency in the community’s Flood Insurance Rate Map reveals severe wave action and building damage in a significant portion of the community deemed least exposed to flood impact. It is suspected that this misrepresentation of risk resulted from overconfidence in the performance of the community’s frontal dune under severe surge and wave actions.

[1]  R. Kopp,et al.  Hurricane Sandy’s flood frequency increasing from year 1800 to 2100 , 2016, Proceedings of the National Academy of Sciences.

[2]  C. Wayne Wright,et al.  EAARL-B coastal topography: eastern New Jersey, Hurricane Sandy, 2012: first surface , 2014 .

[3]  K. Emanuel,et al.  Evaluating Flood Resilience Strategies for Coastal Megacities , 2014, Science.

[4]  Ning Lin,et al.  Component-Based Vulnerability Analysis for Residential Structures Subjected to Storm Surge Impact from Hurricane Sandy , 2016 .

[5]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[6]  Marcel Zijlema,et al.  Modeling hurricane waves and storm surge using integrally-coupled, scalable computations , 2011 .

[7]  R. Nicholls,et al.  Future flood losses in major coastal cities , 2013 .

[8]  J. M. Shepherd,et al.  A climatological assessment of Greenland blocking conditions associated with the track of Hurricane Sandy and historical North Atlantic hurricanes , 2015 .

[9]  C. Blain,et al.  ADCIRC: An Advanced Three-Dimensional Circulation Model for Shelves, Coasts, and Estuaries. Report 2. User's Manual for ADCIRC-2DDI , 1994 .

[10]  G. Forristall.  On the statistical distribution of wave heights in a storm , 1978 .

[11]  Mark Crowell,et al.  Improving FEMA's Coastal Risk Assessment through the National Flood Insurance Program: An Historical Overview , 2007 .

[12]  Ning Lin,et al.  Grey swan tropical cyclones , 2015 .

[13]  Alexandros A. Taflanidis,et al.  Tropical cyclone inundation potential on the Hawaiian Islands of Oahu and Kauai , 2012 .

[14]  Alejandro Sánchez,et al.  Wave transformation over reefs: evaluation of one-dimensional numerical models , 2009 .

[15]  Norman W. Scheffner,et al.  ADCIRC: An Advanced Three-Dimensional Circulation Model for Shelves, Coasts, and Estuaries. Report 1. Theory and Methodology of ADCIRC-2DDI and ADCIRC-3DL. , 1992 .

[16]  A. Agresti.  Analysis of Ordinal Categorical Data: Agresti/Analysis , 2010 .

[17]  Elizabeth K. Judge,et al.  Vulnerability indicators for coastal dunes , 2003 .

[18]  Raydonal Ospina,et al.  Inflated beta distributions , 2007, 0705.0700.

[19]  Stephanie E. Chang,et al.  HAZUS-MH Flood Loss Estimation Methodology. II. Damage and Loss Assessment , 2006 .

[20]  C. Tebaldi,et al.  Probabilistic 21st and 22nd century sea‐level projections at a global network of tide‐gauge sites , 2014 .

[21]  John A. Knaff,et al.  Evaluation of Advanced Microwave Sounding Unit Tropical-Cyclone Intensity and Size Estimation Algorithms , 2004 .

[22]  A. Agresti.  Wiley Series in Probability and Statistics , 2002 .

[23]  Clint Dawson,et al.  Performance of the Unstructured-Mesh, SWAN+ADCIRC Model in Computing Hurricane Waves and Surge , 2011, Journal of Scientific Computing.

[24]  G. Holland.  An Analytic Model of the Wind and Pressure Profiles in Hurricanes , 1980 .

[25]  N. Booij,et al.  A third-generation wave model for coastal regions-1 , 1999 .

[26]  Fumihiko Imamura,et al.  Developing tsunami fragility curves based on the satellite remote sensing and the numerical modeling of the 2004 Indian Ocean tsunami in Thailand , 2011 .

[27]  Ning Lin,et al.  Impact of performance interdependencies on structural vulnerability: A systems perspective of storm surge risk to coastal residential communities , 2017, Reliab. Eng. Syst. Saf..

[28]  B. Merz,et al.  Flood Risk Mapping At The Local Scale: Concepts and Challenges , 2007 .

[29]  A. Kennedy,et al.  Hurricane Damage Classification Methodology and Fragility Functions Derived from Hurricane Sandy’s Effects in Coastal New Jersey , 2017 .

[30]  Leslie E. Papke,et al.  Econometric Methods for Fractional Response Variables with an Application to 401(K) Plan Participation Rates , 1993 .

[31]  J. Westerink,et al.  Rapid Assessment of Wave and Surge Risk during Landfalling Hurricanes: Probabilistic Approach , 2013 .

[32]  José M. R. Murteira,et al.  Alternative Estimating and Testing Empirical Strategies for Fractional Regression Models , 2011 .

[33]  Wei Du,et al.  CoreLogic Storm Surge Report , 2013 .

[34]  G. M. Barnes,et al.  Marine Flooding on the Coast of Kaua'i during Hurricane Iniki: Hindcasting Inundation Components and Delineating Washover , 1995 .

[35]  Siyuan Xian,et al.  Storm surge damage to residential areas: a quantitative analysis for Hurricane Sandy in comparison with FEMA flood map , 2015, Natural Hazards.

[36]  Kerry A. Emanuel,et al.  Hurricanes and Global Warming: Results from Downscaling IPCC AR4 Simulations , 2008 .

[37]  T. Barnett,et al.  Measurements of wind-wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP) , 1973 .

[38]  N. Lin,et al.  Coupled modeling of storm surge and coastal inundation: A case study in New York City during Hurricane Sandy , 2016 .

[39]  Francis K C Hui,et al.  The arcsine is asinine: the analysis of proportions in ecology. , 2011, Ecology.

[40]  Esmeralda A. Ramalho,et al.  Fractional regression models for second stage DEA efficiency analyses , 2010 .

[41]  K. Emanuel,et al.  Physically based assessment of hurricane surge threat under climate change , 2012 .

[42]  B. McCallum,et al.  Monitoring storm tide and flooding from Hurricane Sandy along the Atlantic coast of the United States, October 2012 , 2013 .

[43]  T. Walton,et al.  Criteria for Evaluating Coastal Flood-Protection Structures , 1989 .

[44]  Ning Lin,et al.  A Model for the Complete Radial Structure of the Tropical Cyclone Wind Field. Part I: Comparison with Observed Structure* , 2015 .

[45]  Andrew B. Kennedy,et al.  Collapse Limit State Fragilities of Wood-Framed Residences from Storm Surge and Waves during Hurricane Ike , 2014 .

[46]  J. Beven,et al.  Tropical Cyclone Report Hurricane Sandy , 2013 .

[47]  J. Halverson,et al.  Hurricane Sandy: The Science and Impacts of a Superstorm , 2013 .

[48]  Ning Lin,et al.  On hurricane parametric wind and applications in storm surge modeling , 2012 .