How vulnerable is a rail transit system to flooding? How much damage will a 1-in-100-year flood inflict on the tunnels and related transit infrastructure? How will this change with future sea level rise? These straightforward questions can be immediately answered at a superficial level: floodwaters pour in from street-level openings and collect in the tunnels, damage to infrastructure assets will be expensive, and flood events will bring increasingly greater damage with sea level rise. These casual and nonspecific answers are readily intuited by engineers, planners, and members of the general public, but are of limited value for key decision makers tasked with planning for current and future coastal flood risk. While a general sense of the magnitude and trends of coastal flood risk can inform high level policy efforts, such general intuition is likely to be insufficient for developing actionable and specific climate adaptation and flood risk reduction strategies.
Ideally, transit agencies and infrastructure managers would be able to predict and quantify the consequences of coastal flood events in advance, and take appropriate mitigation measures, rather than pay the damage costs after a flood event, such as the case of New York City Transit, which experienced $5B in damages during Hurricane Sandy1. While the hard-learned lessons of Sandy have since informed significant investments in climate adaptation and flood risk reduction measures2, learning of these consequences through ex-ante prediction is certainly preferable, particularly given the potential increase in consequences from the recurrence of a similar event under future sea level conditions3.
Yet, little attention has thus far been paid to assessing and quantifying the damages of coastal flood events for transit infrastructure, either in the literature or in engineering practice, despite an emerging recognition of the need for such analysis4. In our recent work, we attempt to provide specific answers to the questions posed above, developing a flood damage cost estimation model for transit infrastructure. Building upon prior flood modeling work, we first develop an event-specific exposure model for a transit system, estimating flood depths across the interconnected network of tunnels based on inflow rates through portals and at-grade openings. We estimate the resulting damage cost to specific infrastructure assets, considering several sources of uncertainty, ultimately enabling the development of a systemwide flood damage cost for a flood event of interest. Considering several flood events of varying severity, we develop estimates of expected annualized losses (EAL) for several future sea levels. Using these estimates, we project how EAL will change over time given uncertainty in future sea levels, based on several projections provided by the IPCC 6th Assessment Report5,6,7,8.
Applying these methods to the Massachusetts Bay Transportation Authority (MBTA) rail transit system, we estimate that coastal flood risk (as measured by EAL) has already more than doubled since 2008 and is expected to more than double again by 2030, if no adaptation measures are undertaken. We found these results to be particularly surprising, given that mean sea level in Boston Harbor has only risen by a few centimeters over the past decade, and is only expected to rise a few more centimeters through the end of the decade5,6,7,8,9. These results underscore the extreme sensitivity of coastal rail transit systems to sea level rise, as a significant portion of their assets are found within present-day floodplains or located below ground, often traversing coastal waterways (e.g., MBTA Blue Line). As sea levels continue to rise, our results suggest that coastal flood risk for the MBTA will continue to accelerate. Further, if no adaptation measures are undertaken, significant portions of the system are likely to be permanently inundated. Even with +0.43 m of SLR (which could be reasonably expected by 2050), we expect the 1-in-2-year flood event (i.e., the highest high tide expected every other year) to produce more flood damage than the 1-in-100-year flood event under 2008 sea level conditions. Though alarming, these results underscore the urgent need for near-term investments in adaptation for high-vulnerability locations, as well as for long-term strategic adaptation planning to ensure sufficient flood risk reduction for the entire system. Though future research is needed, these results and the new analysis framework we present provide meaningful and specific answers to our motivating research questions, enabling the prediction of flood depths, event-specific damages, and future risk for subway systems and rail transit infrastructure.
- Aerts, J. C. J. H., Botzen, W. J. W., de Moel, H., & Bowman, M. (2013). Cost estimates for flood resilience and protection strategies in New York City: Flood management strategies for New York City. Annals of the New York Academy of Sciences, 1294(1), 1–104. https://doi.org/10.1111/nyas.12200
- Metropolitan Transit Authority (MTA). (2019). 2019 Resiliency Report: Update on agency-wide climate resiliency projects. MTA. https://new.mta.info/document/10461
- Strauss, B. H., Orton, P. M., Bittermann, K., Buchanan, M. K., Gilford, D. M., Kopp, R. E., Kulp, S., Massey, C., Moel, H. de, & Vinogradov, S. (2021). Economic damages from Hurricane Sandy attributable to sea level rise caused by anthropogenic climate change. Nature Communications, 12(1), 2720. https://doi.org/10.1038/s41467-021-22838-1
- Martello, M.V. & Whittle, A.J. (2023). Climate-resilient transportation infrastructure in coastal cities. In Torgal, F.P., & Goran-Granvist, C.G. (Eds.) Adapting the Built Environment for Climate Change: Design Principles for Climate Emergencies. Woodhead Publishing (Elsevier). https://doi.org/10.1016/B978-0-323-95336-8.00007-X
- Intergovernmental Panel on Climate Change (IPCC). (2022). Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [H.-O. Pörtner, D.C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck, A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem, B. Rama (eds.)]. Cambridge University Press.
- Fox-Kemper, B., H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, R. E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, A. B. A. Slangen, Y. Yu. (2021). Ocean, Cryosphere and Sea Level Change. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu and B. Zhou (eds.)]. Cambridge University Press. In press.
- Garner, G. G., Hermans, T., Kopp, R. E., Slangen, A. B. A., Edwards, T. L., Levermann, A., Nowicki, S., Palmer, M. D., Smith, C., Fox-Kemper, B., Hewitt, H. T., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S. S., Golledge, N. R., Hemer, M., Krinner, G., Mix, A., Notz, D., … Pearson, B. (2021). IPCC AR6 Sea Level Projections (Version 20210809) [Data set]. Zenodo. https://doi.org/10.5281/ZENODO.5914709
- Garner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, R. E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson. (2021). IPCC AR6 Sea-Level Rise Projections. Version 20210809. PO.DAAC, CA, USA. Dataset accessed [2021-12-02] at https://podaac.jpl.nasa.gov/announcements/2021-08-09-Sea-level-projections-from-the-IPCC-6th-Assessment-Report
9. National Oceanic and Atmospheric Administration. (NOAA). (2023). Boston, MA - Station ID: 8443970. Retrieved from: https://tidesandcurrents.noaa.gov/stationhome.html?id=8443970
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