Quantification of coastal transportation network resilience to compounding threats from flooding and anthropogenic disturbances: A New York City case study

Abstract

Technological advancements and management adaptations have improved the function of engineered systems in response to threats from coastal flooding. Other natural and anthropogenic disturbances such as pandemics, utility hijacking, infrastructure destruction, and biochemical releases can stress a system beyond acceptable limits or in ways not previously conceived. Such threats can be direct or indirect and often result in large-scale disruption to the critical functions of the system. Traditional risk management approaches, while effective for known and predictable threats, are not adequate preparation for compound disturbances that are often unpredictable and not well defined. Rather, a resilience-based approach is required. Resilience-based approaches acknowledge that multiple disruptions to the system will occur, such as the interaction of impending hurricanes and evacuation complications due to a pandemic, while focusing on the recovery and maintenance of critical functions. The system can be stressed with multiple disturbances to determine its capacity to resist and recover. Analysis of these capacities or subsequent failures can then be used to determine the resilience of the system and provide insight into remedial actions or improvements. A framework combining hydrologic modeling and network science can be used to determine critical weaknesses in transportation infrastructure due to compounding threats. This determination could be used to address pre-disaster staging by identifying areas that are likely to be isolated and to identify the characteristics of a resilient network to incorporate into future designs. To analyze resilience under compounded disturbances, coastal flood modeling is combined with hypothetical vehicle bridge failure in New York City, USA, and connectivity is analyzed through the use of ego networks. Our results show network analysis can be effectively used to identify areas of need to improve whole network resilience and is a valuable tool to quantify the compounding effects of multiple threats.