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Mortality during Hurricane Sandy: the effects of waterfront flood protection on Staten Island, New York

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Abstract

Hard defenses, such as levees or land berms, are often considered the most effective approach to reduce flood risk. This study reveals a potential increase in mortality when hard protections cannot defend a location against low-probability, extreme flood events. Staten Island, New York, suffered devastating damage from Hurricane Sandy, including 23 fatalities, of which 18 occurred in the neighborhoods along the island’s eastern shore. This study demonstrates that the elevated berm along the eastern shore may have contributed to the concentration of fatalities in the area by increasing the speed at which seawater rose, causing some people to be trapped in places where they could not escape rising waters. The study uses a hydrodynamic model to simulate Hurricane Sandy flood conditions, providing water depth, rise rate, and velocity. Statistical analyses show that water rise rate influences mortality, while other flood characteristics and several demographic and socioeconomic factors do not. A model experiment that qualitatively examines flood conditions in the presence of a lower discontinuous berm that historically existed at the location in Midland Beach finds that the increased height and continuity of the berm increased probability of mortality by worsening the water rise rate during Sandy by about 50%. The potential increase in mortality needs to be taken into account when designing coastal protections. If a protection strategy does not prevent low-probability, extreme floods, then there is a trade-off between protection against more frequent floods and increased risk of mortality during extreme floods.

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Notes

  1. Tsuchiya and Kawata (1981) and Boyd et al. (2005) research on the relationship between water characteristics and mortalities. Water rise rate was found to have effect on flood mortality in the 1953 flood event in the Netherlands (Jonkman et al. 2008). Other studies investigate human instability in floodwater flows (Abt et al. 1989; Lind and Hartford 2000; Ramsbottom et al. 2004; Milanesi et al. 2016). The studies were based on experiments that simulate an outdoor environment, in which people were standing in flowing water facing a flood.

  2. 5 The focus on blocks that contain residences excludes parks and natural, wetland areas. The flooded parts of the East and South Shores are mainly residential, with businesses located on blocks that also contain residences. No deaths occurred in the parks or natural areas.

  3. 6 The high proportion of the resolved units with zero mortality reduces the applicability of linear regression. Instead of studying specific values of mortality or mortality fraction, logistic regression evaluates which factors influence a variable’s relationship with probability of mortality by building a binary dataset where zeros represent no death and ones represent at least one death in a given spatial unit (e.g. grid cell, census block).

  4. The neighborhood of Midland Beach, the area behind the berm where most of the fatalities were concentrated, has the same or higher percentage of white residents as neighboring neighborhoods (see for example https://statisticalatlas.com/neighborhood/New-York/New-York/).

References

  • Abt SR, Wittier RJ, Taylor A, Love DJ (1989) Human stability in a high flood hazard zone 1. JAWRA J Am Water Resour As 25:881–890

    Article  Google Scholar 

  • Aerts JCJH, Lin N, Botzen W et al (2013) Low-probability flood risk modeling for New York City. Risk Anal 33:772–788. https://doi.org/10.1111/risa.12008

    Article  Google Scholar 

  • Bilskie MV, Hagen SC, Alizad K et al (2016) Dynamic simulation and numerical analysis of hurricane storm surge under sea level rise with geomorphologic changes along the northern Gulf of Mexico. Earth’s Future 4:177–193. https://doi.org/10.1002/2015EF000347

    Article  Google Scholar 

  • Blake ES, Kimberlain TB, Berg R, et al (2013) Tropical Cyclone Report: Hurricane Sandy (AL182012), 22–29 October 2012. National Hurricane Center, NOAA

  • Blumberg A, Georgas N, Yin L et al (2015) Street scale modeling of storm surge inundation along the New Jersey Hudson River waterfront. J Atmos Ocean Technol. https://doi.org/10.1175/JTECH-D-14-00213.1

    Article  Google Scholar 

  • Boyd E, Levitan M, Van Heerden I (2005) Further specification of the dose–response relationship for flood fatality estimation. In: Paper presented at The US‐Bangladesh workshop on innovation in windstorm/storm surge mitigation construction. National Science Foundation and Ministry of Disaster & Relief, Government of Bangladesh, Dhaka, Bangladesh, pp 19–21

    Google Scholar 

  • Brandon CM, Woodruff JD, Donnelly JP, Sullivan RM (2014) How unique was Hurricane Sandy? Sedimentary reconstructions of extreme flooding from New York Harbor. Scientific reports 4

  • Brandon CM, Woodruff JD, Orton PM, Donnelly JP (2016) Evidence for elevated coastal vulnerability following large-scale historical oyster bed harvesting. Earth Surf Proc Land 41:1136–1143. https://doi.org/10.1002/esp.3931

    Article  Google Scholar 

  • Bunya S, Dietrich JC, Westerink JJ et al (2010) A high-resolution coupled riverine flow, tide, wind, wind wave, and storm surge model for Southern Louisiana and Mississippi. Part I: model development and validation. Mon Weather Rev 138:345

    Article  Google Scholar 

  • Clark GE, Moser SC, Ratick SJ et al (1998) Assessing the vulnerability of coastal communities to extreme storms: the case of Revere, MA., USA. Mitig Adapt Strat Glob Change 3:59–82

    Article  Google Scholar 

  • Cox AT, Greenwood JA, Cardone VJ, Swail VR (1995) An interactive objective kinematic analysis system. In: Fourth international workshop on wave hindcasting and forecasting. pp 109–118

  • Cutter SL, Boruff BJ, Shirley WL (2003) Social vulnerability to environmental hazards. Soc Sci Q 84:242–261

    Article  Google Scholar 

  • De Bruijn KM, Klijn F (2009) Risky places in the Netherlands: a first approximation for floods. J Flood Risk Manag 2:58–67

    Article  Google Scholar 

  • Dietrich JC, Dawson CN, Proft JM et al (2013) Real-time forecasting and visualization of hurricane waves and storm surge using SWAN + ADCIRC and FigureGen. Comput Chall Geosci 156:49–70. https://doi.org/10.1007/978-1-4614-7434-0_3

    Article  Google Scholar 

  • Federal Emergency Management Agency (FEMA) (2014) Region IIStorm surge project—development of wind and pressure forcingin tropical and extra-tropical storms. FEMA, Washington

    Google Scholar 

  • FEMA (2014) Region II coastal storm surge study: overview. Federal Emergency Management Agency, Washington

    Google Scholar 

  • Flamm HA (1957) Seaside Boulevard construction project. In: Historic Richmond Town. https://statenisland.pastperfectonline.com/photo/592A160F-169E−4110-B38E−628518191083. Accessed 8 Aug 2018

  • Gouldby B, Sayers P, Mulet-Marti J, et al (2008) A methodology for regional-scale flood risk assessment. In: Proceedings of the institution of civil engineers-water management. Thomas Telford Ltd, pp 169–182

  • Gurumurthy P, Orton PM, Talke SA, Georgas N, Booth JF (2019) Mechanics and historical evolution of sea level blowouts in New York Harbor. J Mar Sci Eng 7(5):160. https://doi.org/10.3390/jmse7050160

    Article  Google Scholar 

  • Haki ZG, Akyürek Z, Düzgün Ş (2003) Assessment of social vulnerability using geographic information systems: Pendik, Istanbul case study. METU, Ankara

    Google Scholar 

  • Hassler FR (1844) Map of New-York Bay and Harbor and the environs. United States Coast Survey, Washington, DC

    Google Scholar 

  • Hoffmann R, Muttarak R (2017) Learn from the past, prepare for the future: impacts of education and experience on disaster preparedness in the Philippines and Thailand. World Dev 96:32–51

    Article  Google Scholar 

  • Horton R, Little C, Gornitz V et al (2015) New York City panel on climate change 2015 report chapter 2: sea level rise and coastal storms. Ann N Y Acad Sci 1336:36–44

    Article  Google Scholar 

  • Irish JL, Sleath A, Cialone MA et al (2014) Simulations of Hurricane Katrina (2005) under sea level and climate conditions for 1900. Clim Change 122:635–649

    Article  Google Scholar 

  • Jonkman SN (2003) Loss of life caused by floods: an overview of mortality statistics for worldwide floods. Delft Cluster report DC1-233-6

  • Jonkman SN (2007) Loss of life estimation in flood risk assessment; theory and applications. Ph.D. Thesis, Delft University

  • Jonkman SN, Penning-Rowsell E (2008) Human instability in flood flows 1. JAWRA J Am Water Resour As 44:1208–1218

    Article  Google Scholar 

  • Jonkman SN, Vrijling JK (2008) Loss of life due to floods. J Flood Risk Manag 1:43–56. https://doi.org/10.1111/j.1753-318X.2008.00006.x

    Article  Google Scholar 

  • Jonkman SN, Vrijling JK, Vrouwenvelder ACWM (2008) Methods for the estimation of loss of life due to floods: a literature review and a proposal for a new method. Nat Haz 46(3):353–389

    Article  Google Scholar 

  • Jonkman SN, Maaskant B, Boyd E, Levitan ML (2009) Loss of life caused by the flooding of New Orleans after Hurricane Katrina: analysis of the relationship between flood characteristics and mortality. Risk Anal 29:676–698. https://doi.org/10.1111/j.1539-6924.2008.01190.x

    Article  Google Scholar 

  • Karvonen RA, Hepojoki A, Huhta HK, Louhio A (2000) The use of physical models in dam-break analysis. RESCDAM Final Report Helsinki University of Technology, Helsinki, Finland

  • Keller J (2012) Mapping Hurricane Sandy’s deadly toll. https://archive.nytimes.com/www.nytimes.com/interactive/2012/11/17/nyregion/hurricane-sandy-map.html. Accessed 8 Aug 2018

  • Kress ME, Benimoff AI, Fritz WJ et al (2016) Modeling and simulation of storm surge on Staten Island to understand inundation mitigation strategies. J Coast Res. https://doi.org/10.2112/SI76-013

    Article  Google Scholar 

  • Lind N, Hartford D (2000) Probability of human instability in a flooding: a hydrodynamic model. In: Proceedings of ICASP. pp 1151–1156

  • Lorie M, Stedge J, Firlie B et al (2018) Informing policy choices with regional estimates of flood risk across the United States. World Environ Water Resour Congress. https://doi.org/10.1061/9780784481400.016

    Article  Google Scholar 

  • Luettich RA, Westerink JJ, Scheffner NW, US Army Corps of Engineers CERC (1992) ADCIRC: An advanced three-dimensional circulation model for shelves, coasts, and estuaries. Report 1. Theory and Methodology of ADCIRC-2DDI and ADCIRC-3DL

  • Milanesi L, Pilotti M, Bacchi B (2016) Using web-based observations to identify thresholds of a person’s stability in a flow. Water Resour Res 52:7793–7805

    Article  Google Scholar 

  • Mishra S, Suar D (2007) Do lessons people learn determine disaster cognition and preparedness? Psychol Dev Soc 19:143–159

    Google Scholar 

  • Murphy PK, Wilkinson IAG, Soter AO et al (2009) Examining the effects of classroom discussion on students’ comprehension of text: a meta-analysis. J Educ Psychol 101:740–764. https://doi.org/10.1037/a0015576

    Article  Google Scholar 

  • National Research Council (2014) Reducing coastal risks on the east and gulf coasts. The National Academies Press, Washington

    Google Scholar 

  • NOAA Sea Level Trends. In: NOAA Tides and currents. https://tidesandcurrents.noaa.gov/sltrends/sltrends.html. Accessed 21 Aug 2018

  • Orton P, Vinogradov S, Georgas N et al (2015) New York city panel on climate change 2015 report chapter 4: dynamic coastal flood modeling. Ann N Y Acad Sci 1336:56–66

    Article  Google Scholar 

  • Orton PM, Hall TM, Talke S et al (2016) A validated tropical-extratropical flood hazard assessment for New York Harbor. J Geophys Res. https://doi.org/10.1002/2016JC011679

    Article  Google Scholar 

  • Pablopic (2012) Hurricane Sandy, after the storm, Midland Beach, Staten Island, NYC. https://www.youtube.com/watch?v=wPV2eak1WH0. Accessed 8 Aug 2018

  • Padli J, Habibullah MS (2009) Natural disaster death and socio-economic factors in selected Asian countries: a panel analysis. Asian Soc Sci 5:65

    Article  Google Scholar 

  • Ramsbottom D, Wade S, Bain V et al (2004) R&D outputs: flood risks to people. Phase 2. FD2321/IR2. Department for the Environment, Food and Rural Affairs/Environment Agency, London

    Google Scholar 

  • Resio DT, Irish J, Cialone M (2009) A surge response function approach to coastal hazard assessment—part 1: basic concepts. Nat Hazards 51:163–182

    Article  Google Scholar 

  • Schuerman M (2013) Deadly topography: the Staten Island Neighborhood Where 11 Died During Sandy | WNYC | New York Public Radio, Podcasts, Live Streaming Radio, News. In: WNYC. https://www.wnyc.org/story/271288-tricked-topography-how-staten-island-neighborhood-became-so-dangerous-during-sandy/. Accessed 7 Aug 2018

  • Schuerman M (2015) A great wall of Staten Island to Ward Off Hurricanes. In: WNYC. https://www.wnyc.org/story/army-corps-proposes-great-wall-staten-island-ward-hurricanes/. Accessed 8 Aug 2018

  • Taflanidis AA, Kennedy AB, Westerink JJ et al (2013) Rapid assessment of wave and surge risk during landfalling hurricanes: probabilistic approach. J Waterway Port Coast Ocean Eng 139:171–182. https://doi.org/10.1061/(ASCE)WW.1943-5460.0000178

    Article  Google Scholar 

  • Taylor A (2012) Hurricane Sandy: Staten Island Survivors—the Atlantic. https://www.theatlantic.com/photo/2012/11/hurricane-sandy-staten-island-survivors/100410/. Accessed 7 Aug 2018

  • Tobin GA (1995) The levee love affair: a stormy relationship? 1. JAWRA J Am Water Resour As 31:359–367

    Article  Google Scholar 

  • Tsuchiya Y, Kawata Y (1981) Risk to life, warning systems, and protective construction against past storm surges in Osaka Bay. J Nat Disaster Sci 3(1):33–56

    Google Scholar 

  • Van Verseveld HCW, Van Dongeren AR, Plant NG et al (2015) Modelling multi-hazard hurricane damages on an urbanized coast with a Bayesian Network approach. Coast Eng 103:1–14

    Article  Google Scholar 

  • Westerink JJ, Luettich RA, Feyen JC et al (2008) A basin-to channel-scale unstructured grid hurricane storm surge model applied to southern Louisiana. Mon Weather Rev 136:833–864

    Article  Google Scholar 

  • Yates J (2017) Hurricane Sandy’s victims: 24 Staten Islanders lost forever. In: SILIVE. https://www.silive.com/news/2017/10/hurricane_sandys_victims.html. Accessed 8 Aug 2018

  • Zachry BC, Booth WJ, Rhome JR, Sharon TM (2015) A national view of storm surge risk and inundation. Weather Clim Soc 7:109–117

    Article  Google Scholar 

  • Zhong H, van Overloop P-J, van Gelder P, Rijcken T (2012) Influence of a storm surge barrier’s operation on the flood frequency in the rhine delta area. Water 4:474–493

    Article  Google Scholar 

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Acknowledgements

We thank Hugh Roberts and Zachary Cobell (ARCADIS U.S., Inc., Highlands Ranch, CO) who provided their ADCIRC model grid and helped inform our model settings for the study.

Funding

This research was funded by the National Oceanic and Atmospheric Administration’s Climate Program Office (Agreement NA15OAR4310147). Modeling was made possible by a grant of computer time from the City University of New York High Performance Computing Center under NSF Grants CNS-0855217, CNS-0958379 and ACI-1126113.

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Authors and Affiliations

  1. Department Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, Castle Point on Hudson, Hoboken, NJ, 07030, USA

    Fanglin Zhang, Philip M. Orton, Sarath Chandra K. Jagupilla & Roham Bakhtyar

  2. Center for Climate Systems Research, Columbia University, 2880 Broadway, New York, NY, 10025, USA

    Malgosia Madajewicz

  3. Office of Water Prediction - Analysis and Prediction Division, NOAA National Water Center, Tuscaloosa, AL, USA

    Roham Bakhtyar

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  1. Fanglin Zhang
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Correspondence to Fanglin Zhang.

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Appendix

Appendix

See Tables 6, 7 and 8.

Table 7 Results of simple logistic regression of four age categories
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Table 8 Results of two-sample T test of four age categories
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Zhang, F., Orton, P.M., Madajewicz, M. et al. Mortality during Hurricane Sandy: the effects of waterfront flood protection on Staten Island, New York. Nat Hazards 103, 57–85 (2020). https://doi.org/10.1007/s11069-020-03959-0

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