Low‐Probability Flood Risk Modeling for New York City. Issue 5 (5th February 2013)

• Record Type: Journal Article
• Authors: Aerts, Jeroen C. J. H.; Lin, Ning; Botzen, Wouter; Emanuel, Kerry; de Moel, Hans
• Is Part Of: Risk analysis. Volume 33:Issue 5(2013)
• Page Start: 772
• Page End: 788
• Publication Date: 2013-02-05
• Subjects: Catastrophe model -- flood risk -- hurricane -- New York City -- uncertainty; Technology -- Risk assessment -- Periodicals; 658.403
• DOI: 10.1111/risa.12008
• Languages: English
• ISSNs: 0272-4332

Abstract

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.