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Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems

Author

Listed:
  • Suchat Tachaudomdach

    (Ph.D. Degree Program in Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Auttawit Upayokin

    (Excellence Center in Infrastructure Technology and Transportation Engineering (ExCITE), Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand
    Department of Civil Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Nopadon Kronprasert

    (Excellence Center in Infrastructure Technology and Transportation Engineering (ExCITE), Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand
    Department of Civil Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Kriangkrai Arunotayanun

    (Excellence Center in Infrastructure Technology and Transportation Engineering (ExCITE), Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand
    Department of Civil Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

Abstract

Amidst sudden and unprecedented increases in the severity and frequency of climate-change-induced natural disasters, building critical infrastructure resilience has become a prominent policy issue globally for reducing disaster risks. Sustainable measures and procedures to strengthen preparedness, response, and recovery of infrastructures are urgently needed, but the standard for measuring such resilient elements has yet to be consensually developed. This study was undertaken with an aim to quantitatively measure transportation infrastructure robustness, a proactive dimension of resilience capacities and capabilities to withstand disasters; in this case, floods. A four-stage analytical framework was empirically implemented: (1) specifying the system and disturbance (i.e., road network and flood risks in Chiang Mai, Thailand), (2) illustrating the system response using the damaged area as a function of floodwater levels and protection measures, (3) determining recovery thresholds based on land use and system functionality, and (4) quantifying robustness through the application of edge- and node-betweenness centrality models. Various quantifiable indicators of transportation robustness can be revealed; not only flood-damaged areas commonly considered in flood-risk management and spatial planning, but also the numbers of affected traffic links, nodes, and cars are highly valuable for transportation planning in achieving sustainable flood-resilient transportation systems.

Suggested Citation

  • Suchat Tachaudomdach & Auttawit Upayokin & Nopadon Kronprasert & Kriangkrai Arunotayanun, 2021. "Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems," Sustainability, MDPI, vol. 13(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3172-:d:516562
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    References listed on IDEAS

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    1. Britta Restemeyer & Johan Woltjer & Margo van den Brink, 2015. "A strategy-based framework for assessing the flood resilience of cities - A Hamburg case study," Planning Theory & Practice, Taylor & Francis Journals, vol. 16(1), pages 45-62, March.
    2. Zhang, X. & Miller-Hooks, E. & Denny, K., 2015. "Assessing the role of network topology in transportation network resilience," Journal of Transport Geography, Elsevier, vol. 46(C), pages 35-45.
    3. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    4. Markolf, Samuel A. & Hoehne, Christopher & Fraser, Andrew & Chester, Mikhail V. & Underwood, B. Shane, 2019. "Transportation resilience to climate change and extreme weather events – Beyond risk and robustness," Transport Policy, Elsevier, vol. 74(C), pages 174-186.
    5. Hiba Baroud & Jose E. Ramirez‐Marquez & Kash Barker & Claudio M. Rocco, 2014. "Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows," Risk Analysis, John Wiley & Sons, vol. 34(7), pages 1317-1335, July.
    6. Steve Bankes, 1993. "Exploratory Modeling for Policy Analysis," Operations Research, INFORMS, vol. 41(3), pages 435-449, June.
    7. Jha, Abhas & Lamond, Jessica & Bloch, Robin & Bhattacharya, Namrata & Lopez, Ana & Papachristodoulou, Nikolaos & Bird, Alan & Proverbs, David & Davies, John & Barker, Robert, 2011. "Five feet high and rising : cities and flooding in the 21st century," Policy Research Working Paper Series 5648, The World Bank.
    8. Jingyi Lin & Yifang Ban, 2013. "Complex Network Topology of Transportation Systems," Transport Reviews, Taylor & Francis Journals, vol. 33(6), pages 658-685, November.
    9. Cats, Oded & Jenelius, Erik, 2015. "Planning for the unexpected: The value of reserve capacity for public transport network robustness," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 47-61.
    10. Sullivan, J.L. & Novak, D.C. & Aultman-Hall, L. & Scott, D.M., 2010. "Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 323-336, June.
    11. Shen, Zuo-Jun Max & Pannala, Jyothsna & Rai, Rohit & Tsoi, Tsz Shing, 2008. "Modeling Transportation Networks During Disruptions and Emergency Evacuations," University of California Transportation Center, Working Papers qt1257t9zn, University of California Transportation Center.
    12. Sybil Derrible, 2012. "Network Centrality of Metro Systems," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-10, July.
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