Using Empirical Data to Quantify Port Resilience: Hurricane Matthew and the Southeastern Seaboard

Abstract

The economic significance of the U.S. Marine Transportation System (MTS) generates a need to understand the resilience of the MTS. Resilience is defined herein as a system’s ability maintain a given critical function through preparing, resisting, recovering, and adapting to a disturbance. Past studies quantifying MTS resilience provided conceptual frameworks for measurement; however, detailed and accurate field data throughout each phase of a resilience challenge are extremely difficult to obtain. In addition, port-system resilience analysis techniques must be widely applicable and reproducible. This case study examined the impact of Hurricane Matthew (October 216) on three ports in the southeastern United States: Charleston, Savannah, and Jacksonville. The study used automatic identification system vessel-position data to calculate two port performance metrics: cumulative dwell time (CDT) and net vessel count (NVC). These metrics were analyzed to quantify system behavior during five stages of the storm: prestorm, prepare, resist, recover, and poststorm. Bayesian changepoint analysis was used to identify the abrupt variations in system performance over time, most notably the transition from recovery to poststorm stages.