A flow-based commodity-independent port capacity model for resilience assessment of intermodal freight networks subjected to coastal hazards
Anibal Tafur and
Jamie E. Padgett
Reliability Engineering and System Safety, 2024, vol. 250, issue C
Abstract:
Seaports, critical economic hubs in coastal regions, face escalating vulnerability to natural disasters, particularly storms, exacerbated by climate change. Despite their economic importance, there remains a noticeable gap in methods for adequately characterizing their operational state post-storm impact in terms of flow capacity, crucial for resilience modeling of coastal intermodal networks. This characterization presents significant challenges due to the operational complexity of multi-commodity port sites, intensified by the absence of computationally efficient capacity models. This study introduces a flow-based port capacity model that integrates probabilistic estimates of post-disaster availability in structural and handling components, accommodating uncertainty propagation through low complexity, and offering adaptability to various terminal and commodity types. A case study conducted on the maritime-rail-road intermodal network in Mobile, Alabama, subjected to five storm scenarios, demonstrates the model’s applicability and value as a tool in the broader context of intermodal resilience. The analysis revealed significant variations in resilience indicators among different terminal types, as well as a greater impact of disruptions in port capacities compared to inland corridors. These results underscore the proposed model’s capability to provide crucial quantitative insights into post-disaster port functionality that might otherwise be overlooked, ultimately contributing to the development of more robust strategies for ensuring the continuity of critical supply chains and mitigating economic impacts on coastal communities amidst climate-related hazards.
Keywords: Resilience; Seaports; Freight transportation; Port capacity; Storm hazards (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:250:y:2024:i:c:s0951832024003521
DOI: 10.1016/j.ress.2024.110280
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