A Community Resilience Approach To Assessing Transportation Risk in Disasters

Abstract eng:
This paper addresses the need for new measures and models of infrastructure performance that can facilitate the strengthening of community resilience to disasters. While many infrastructure measures and models focus on performance in terms of disaster-induced damage, from the perspective of populations and cities that would be affected, there is a need for analysis of service loss and of approaches to rapidly restore service in an emergency. Focusing on transportation, this paper notes limitations of current performance measures, proposes a systems analytic framework that addresses community resilience, and demonstrates how the framework can be applied to analyze and model transportation disruption in earthquakes and other disasters. The approach is demonstrated for a case study of south coastal British Columbia, Canada, with particular attention to the role of maritime transportation in the distribution of one essential commodity, gasoline fuel. Coastal communities in this region are extremely reliant on maritime transportation for delivery of essential goods such as fuel, and because of the shift towards just-in-time production systems, have very little storage or warehousing capacity. Expert interviews, stakeholder workshops, satellite-based tracking of ships, and network analyses are used to characterize the transportation system and assess risk and resilience. Two approaches to system analysis are implemented: one emphasizing network topology, and the other focusing on network functionality. This enables a comparison of the strengths and limitations of these two major methodological approaches. In the case study demonstration, the topological approach is able to capture, with relatively low data requirements, the relative vulnerability of communities situated in different parts of the network. Resilience-enhancing strategies that are related to network topology, such as adding network links as a response in emergencies, can be readily assessed. The topological approach is limited, however, in its ability to address detailed damage and operational issues related to emergency response actions that are key to resilience analysis. In the second approach, a functional model is developed that emphasizes flows in the network. This enables a more realistic representation of system operations, thereby facilitating more specific understanding of how transportation damage can lead to disruption of fuel flows and impacts to communities. The functional model can be readily integrated with hazard and facility damage models. The approach is particularly advantageous in being able to capture time-dependent variables such as reserve volumes and supply deliveries, which are crucial types of information for assessing how different decision options (e.g., seismic retrofit of port facilities, increasing storage capacity, adding shipping routes) could enhance community resilience. Data requirements are very high, however, and pose an important limitation to this approach.

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