Literature DB >> 23383711

Low-probability flood risk modeling for New York City.

Jeroen C J H Aerts1, Ning Lin, Wouter Botzen, Kerry Emanuel, Hans de Moel.   

Abstract

The devastating impact by Hurricane Sandy (2012) again showed New York City (NYC) is one of the most vulnerable cities to coastal flooding around the globe. The low-lying areas in NYC can be flooded by nor'easter storms and North Atlantic hurricanes. The few studies that have estimated potential flood damage for NYC base their damage estimates on only a single, or a few, possible flood events. The objective of this study is to assess the full distribution of hurricane flood risk in NYC. This is done by calculating potential flood damage with a flood damage model that uses many possible storms and surge heights as input. These storms are representative for the low-probability/high-impact flood hazard faced by the city. Exceedance probability-loss curves are constructed under different assumptions about the severity of flood damage. The estimated flood damage to buildings for NYC is between US$59 and 129 millions/year. The damage caused by a 1/100-year storm surge is within a range of US$2 bn-5 bn, while this is between US$5 bn and 11 bn for a 1/500-year storm surge. An analysis of flood risk in each of the five boroughs of NYC finds that Brooklyn and Queens are the most vulnerable to flooding. This study examines several uncertainties in the various steps of the risk analysis, which resulted in variations in flood damage estimations. These uncertainties include: the interpolation of flood depths; the use of different flood damage curves; and the influence of the spectra of characteristics of the simulated hurricanes.
© 2013 Society for Risk Analysis.

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Year:  2013        PMID: 23383711     DOI: 10.1111/risa.12008

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  8 in total

1.  Increased threat of tropical cyclones and coastal flooding to New York City during the anthropogenic era.

Authors:  Andra J Reed; Michael E Mann; Kerry A Emanuel; Ning Lin; Benjamin P Horton; Andrew C Kemp; Jeffrey P Donnelly
Journal:  Proc Natl Acad Sci U S A       Date:  2015-09-28       Impact factor: 11.205

2.  Model projections of atmospheric steering of Sandy-like superstorms.

Authors:  Elizabeth A Barnes; Lorenzo M Polvani; Adam H Sobel
Journal:  Proc Natl Acad Sci U S A       Date:  2013-09-03       Impact factor: 11.205

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Authors:  Ivan D Haigh; Matthew P Wadey; Shari L Gallop; Heiko Loehr; Robert J Nicholls; Kevin Horsburgh; Jennifer M Brown; Elizabeth Bradshaw
Journal:  Sci Data       Date:  2015-05-12       Impact factor: 6.444

4.  Flood risk assessments at different spatial scales.

Authors:  H de Moel; B Jongman; H Kreibich; B Merz; E Penning-Rowsell; P J Ward
Journal:  Mitig Adapt Strateg Glob Chang       Date:  2015-05-22       Impact factor: 3.583

5.  Spatial Optimization of Future Urban Development with Regards to Climate Risk and Sustainability Objectives.

Authors:  Daniel Caparros-Midwood; Stuart Barr; Richard Dawson
Journal:  Risk Anal       Date:  2017-02-23       Impact factor: 4.000

6.  Adoption of Individual Flood Damage Mitigation Measures in New York City: An Extension of Protection Motivation Theory.

Authors:  W J Wouter Botzen; Howard Kunreuther; Jeffrey Czajkowski; Hans de Moel
Journal:  Risk Anal       Date:  2019-04-25       Impact factor: 4.000

7.  Comparing the cost effectiveness of nature-based and coastal adaptation: A case study from the Gulf Coast of the United States.

Authors:  Borja G Reguero; Michael W Beck; David N Bresch; Juliano Calil; Imen Meliane
Journal:  PLoS One       Date:  2018-04-11       Impact factor: 3.240

8.  Usable Science for Managing the Risks of Sea-Level Rise.

Authors:  Robert E Kopp; Elisabeth A Gilmore; Christopher M Little; Jorge Lorenzo-Trueba; Victoria C Ramenzoni; William V Sweet
Journal:  Earths Future       Date:  2019-12-04       Impact factor: 7.495

  8 in total

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