Critical Infrastructure Systems: A Case Study of the Interconnectedness of Risks Posed by Hurricane Sandy for New York City

Citation:

Masahiko Haraguchi and Soojun Kim. 2016. “Critical Infrastructure Systems: A Case Study of the Interconnectedness of Risks Posed by Hurricane Sandy for New York City.” International Journal of Disaster Resilience in the Built Environment, 7, 2, Pp. 133-143. Publisher's Version
Critical Infrastructure Systems: A Case Study of the Interconnectedness of Risks Posed by Hurricane Sandy for New York City

Abstract:

Purpose
This study aims to investigate the impact of Hurricane Sandy from the perspective of interdependence among different sectors of critical infrastructure in New York City and to assess the interconnected nature of risks posed by such a hurricane.

Design/methodology/approach
This study uses indirect damages of each sector to estimate the degree of functional interdependence among the sectors. The study examines the impact of the hurricane on different critical infrastructures by combining hazard maps of actual inundation areas with maps of critical infrastructure. The direct damages of each sector are calculated from the inundation areas in the flood map. The indirect damages are estimated by considering the areas that were not inundated but affected by Sandy through the interconnected infrastructure.

Findings
The electricity sector was the key sector to propagate risks to other sectors. The examination of new initiatives to increase the resilience of critical infrastructures in New York City after Sandy reveals that these initiatives focus primarily on building hard infrastructures to decrease direct damages. They understate the importance of interdependent risk across sectors. Future disaster risk reduction strategies must address interdependent infrastructures to reduce indirect damages.

Originality/value
This paper focuses on estimating the direct and indirect damages caused by Hurricane Sandy in each critical infrastructure sector, using GIS mapping techniques. It also introduces a Bayesian network as a tool to analyze critical infrastructure interdependence.

Last updated on 07/20/2019