Technical Papers
Apr 30, 2024

Determining Critical Cascading Effects of Flooding Events on Transportation Infrastructure Using Data Mining Algorithms

Publication: Journal of Infrastructure Systems
Volume 30, Issue 3

Abstract

Transportation infrastructures and operations can be severely impacted during flood events, leading to significant disruptions to the flow of goods and services. Although numerous studies have evaluated the direct impacts of flood events on the performance of transportation infrastructures, the indirect impacts or cascading effects have been rarely assessed. Hence, this paper examines the cascading effects of floods on transportation infrastructure using data mining algorithms. First, 33 effects of flood events on transportation infrastructure have been identified based on data collected for multiple flood events in New York and New Jersey. Second, association rule mining analysis was implemented to identify the key co-occurrences between flooding and the different events. Third, network analysis was conducted to quantify the co-occurrences or key combinations among the events. Fourth, cluster analysis was used to group or prioritize the cascading effects and co-occurring events into highly connected clusters to identify the most critical ones based on two scenarios: (1) without consideration of co-occurrences (Scenario 1); and (2) with consideration of co-occurrences (Scenario 2). The findings provided insights that while some cascading impacts could be individually critical/frequent (under Scenario 1), other cascading impacts could also result due to a combination of different effects that might not be perceived to be critical on the individual level but rather become critical when combined with other cascading events (under Scenario 2). The outcomes of this paper demonstrate the importance of considering the co-occurrences between the events and cascading effects, rather than analyzing them in isolation. This study adds to the body of knowledge by offering an analytical approach that could be used to identify and prioritize critical cascading effects of flood events on the operations and performance of transportation infrastructures.

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Data Availability Statement

All data generated or analyzed during the study are included in the published paper.

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Journal of Infrastructure Systems
Volume 30Issue 3September 2024

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Received: Oct 3, 2023
Accepted: Feb 17, 2024
Published online: Apr 30, 2024
Published in print: Sep 1, 2024
Discussion open until: Sep 30, 2024

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Assistant Professor of Construction and Civil Infrastructure and Founding Director of the Smart Construction and Intelligent Infrastructure Systems Lab, John A. Reif, Jr. Dept. of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102 (corresponding author). ORCID: https://orcid.org/0000-0003-4626-5656. Email: [email protected]
Mohsen Mohammadi, S.M.ASCE [email protected]
Ph.D. Candidate, John A. Reif, Jr. Dept. of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102. Email: [email protected]
Ghiwa Assaf, S.M.ASCE [email protected]
Ph.D. Candidate, John A. Reif, Jr. Dept. of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102. Email: [email protected]

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