AN ANALYSIS OF SHIP AVAILABILITY AFTER AN EARTHQUAKE-TSUNAMI: A CASE STUDY IN BRITISH COLUMBIA

Abstract

Maritime logistics play a vital role in supporting emergency relief logistics for communities that are dependent on this transportation mode. By its geographical nature, this concerns specifically island populations. The viability of performing post-disaster operations depends on the availability of infrastructure elements, such as ports, waterways navigation support, and ship availability. During an earthquake event, especially when followed by a tsunami, there is a substantial risk of damage to vessels operating in coastal areas. This research investigates this risk in a Cascadia-type Earthquake event in British Columbia. In particular, a model is proposed to estimate the probability of ships being unavailable to support the humanitarian supply chain operations in the disaster response phase. The study uses spatial analysis tools with vessel movement data from the Automatic Information System. First, their origin and destination ports are determined, and routes and trajectories patterns are extracted from the data. Then, the model investigates the risk of damage to ferries and tugs on points along a specific path. The developed model considers various spatial and attribute components, such as the distance from collapsing structures, tsunami zone, safe depth areas, tsunami arrival time, and other nautical features. The results indicate that many small ferries and some tugs have a substantial probability of being unavailable to support emergency logistics, whereas larger ferries are less affected. Various results, such as the probability of certain parts of the fleet being unavailable, maps of dangerous navigational areas, and routes with reduced transportation capacity, can be used as a resource to support disaster preparedness and mitigation actions. Despite some uncertainties related to exact ship location and tsunami data and some model simplifications, the findings can thus be used to inform regional emergency preparedness decision-making and related risk management.