This paper evaluates the level of inoperability and the resilience of the critical infrastructure networks of the New York Metropolitan Area affected by Hurricane Sandy in October 2012. The region analyzed in the case study includes New York City and some New Jersey counties. The highly concentrated critical infrastructures of this area are vulnerable to the direct impact of catastrophic events, such as hurricanes, as well as to the disruptive cascading effects that are spread through the existing interdependencies. The inoperability Input-Output model, developed by Haimes and Jiang, is selected to numerically define the degree of interconnection among these systems and quantify the effect of an external perturbation on the network's functionality. Based on the model's results, a new indicator called the “inoperability ratio” is introduced to identify some initiatives that policymakers can implement during the restoration process. These actions reduce the inoperability ratio to prevent cascading effects and to speed up the recovery process.
Modeling interdependencies of critical infrastructures after hurricane Sandy / Cimellaro, G. P.; Crupi, P.; Kim, H. U.; Agrawal, A.. - In: INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION. - ISSN 2212-4209. - ELETTRONICO. - 38:(2019), p. 101191. [10.1016/j.ijdrr.2019.101191]
Modeling interdependencies of critical infrastructures after hurricane Sandy
Cimellaro G. P.;Crupi P.;
2019
Abstract
This paper evaluates the level of inoperability and the resilience of the critical infrastructure networks of the New York Metropolitan Area affected by Hurricane Sandy in October 2012. The region analyzed in the case study includes New York City and some New Jersey counties. The highly concentrated critical infrastructures of this area are vulnerable to the direct impact of catastrophic events, such as hurricanes, as well as to the disruptive cascading effects that are spread through the existing interdependencies. The inoperability Input-Output model, developed by Haimes and Jiang, is selected to numerically define the degree of interconnection among these systems and quantify the effect of an external perturbation on the network's functionality. Based on the model's results, a new indicator called the “inoperability ratio” is introduced to identify some initiatives that policymakers can implement during the restoration process. These actions reduce the inoperability ratio to prevent cascading effects and to speed up the recovery process.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2840463