Abstract
Recent climatic disasters have shown the vulnerability of transportation infrastructures against natural hazards. To understand the risk of coastal hazards on urban travel activities, this study presents an activity-based modeling approach to evaluate the impacts of storm surge on the transportation network under sea-level rise in Miami-Dade County, FL. A Markov-Chain Monte Carlo (MCMC) based algorithm is applied to generate population attributes and travel diaries in the model simulation. Flooding scenarios in 2045 are developed based on different adaptation standards under the 100-year storm surge and population projections are from the land-use conflict identification strategy (LUCIS) model. Our analysis indicates that about 29.3% of the transportation infrastructure, including areas of the US No. 1 highway, roadways in the south and southwest of the county, and bridges connecting Miami Beach area, will be damaged under the storm surge when a low-level adaptation standard is chosen. However, the high-level adaptation standard will reduce the vulnerable infrastructures to 12.4%. Furthermore, the total increased travel time of the low-level adaptation standard could be as high as twice of that in the high-level adaptation standard during peak morning hours. Our model results also reveal that the average increased travel time due to future storm surge damage ranges between 14.2 and 62.8 min per trip.
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Acknowledgements
We acknowledge the support from Florida Department of Transportation (FDOT). We also acknowledge the support from the National Science Foundation [Award #1832693: CRISP 2.0 Type 2: Collaborative Research: Organizing Decentralized Resilience in Critical Interdependent-infrastructure Systems and Processes (ORDER-CRISP)]. Contents of this study are solely the responsibility of the authors and do not necessarily represent the official views of the National Science Foundation or FDOT.
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YH designed the study, conducted literature search and review, developed and calibrated the MATSim model and conducted scenario analysis. CC conducted the LUCIS model simulation and visualization. YH and CC wrote the manuscript. Z-RP and PM reviewed and revised the manuscript. All authors read and approve the manuscript.
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Han, Y., Chen, C., Peng, ZR. et al. Evaluating impacts of coastal flooding on the transportation system using an activity-based travel demand model: a case study in Miami-Dade County, FL. Transportation 49, 163–184 (2022). https://doi.org/10.1007/s11116-021-10172-w
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DOI: https://doi.org/10.1007/s11116-021-10172-w