Critical infrastructure interdependence in New York City during Hurricane Sandy

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.

Changes in extreme events and the potential impacts on human health

“…For example, Hurricane Sandy flooded large portions of New York City in 2012 and damaged critical electricity infrastructure. The cascading impacts of electricity loss included hospital and subway closures, telecommunication outages, halted pipeline fuel distribution, and food delivery disruption (Haraguchi et al 2016). The total number of excess deaths increased immediately after the event and remained elevated for 2 months (Howland et al 2014).…”

Resilience Assessment of Interdependent Infrastructure Systems: A Case Study Based on Different Response Strategies

“…where 0 t is the time when the disturbance occurs, 1 0  t t is the buffering time B T calculated as the period of the infrastructure malfunctioning, 3 t is the starting time of infrastructure repair, The adaptive capacity of a single layer network is a function of the adaptive capacity of all elements', the network size, structure and operation mechanism (intra-network interdependencies). Each adaptive layer capacity is obtained as the average value of the adaptive capacities of all elements obtained by dynamic integration.…”

“…The electric transmission will not work if its links with information infrastructure are cut off, which refers to node-path dependence and use of Equation (4). All the electric transmissions malfunction if the information control infrastructure malfunctions, which refers to the node-cluster dependence and use of Equation (3). Information control center and Internet service providers are powered by the electric infrastructure located in the same geographic area, which refers to the node-node or node-edge dependencies and use of Equation (1) or (2).…”

“…Based on the system performance and resilience of single layer and multilayer infrastructure networks illustrated in Figures 13-18, RS-HD always leads to better results. RS-HD refers to the restoration strategy giving repair priority to elements of hidden dependent patterns or path dependent patterns, which are represented by Equation (3). This kind of infrastructure dependence is invisible in normal operations, but emerges and becomes obvious under disturbance.…”

Real-Time Chronological Hazard Impact Modeling

“…Hurricanes place critical facilities, such as hospitals, electrical systems, and transportation links, at risk [1]. The potential of ADvanced CIRCulation model (ADCIRC) as a tool to analyze vulnerabilities of specific geographic points has long been recognized [2].…”