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Strategic storm flood evacuation planning for large coastal cities enables more effective transfer of elderly populations

Nature Water volume 2, pages 274–284 (2024)Cite this article

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Abstract

Emergency responders in coastal cities are anticipated to provide effective evacuation of at-risk populations during the preparedness and response phases of coastal floods due to land-falling storms or cyclones. However, existing contingency plans primarily focus on the evacuation of the general public rather than special arrangement for elderly populations who constitute a large proportion of flood fatalities. Here we present a system-level methodology to elaborate citywide coastal flood evacuation plans for optimal deployment of shelters and effective transfer of elderly people with special needs. We conduct a comparative analysis between Shanghai and New York City, which are both among the most exposed coastal cities to storm-induced flooding but represent two distinct institutional systems of emergency operation. The results show marked disparities in evacuation patterns for elderly residents in the two cities. Storm flood evacuation is more challenging in Shanghai due to insufficient provision of shelter capacity (~230,000). Implementing risk-informed and strategic planning could not only meet the potentially huge demand of vulnerable elderly (~520,000) but also improve the overall efficiency of evacuee transfer by a factor of 3. Our work provides new insights into operational emergency evacuation decisions and informs flood management policy development for major coastal cities globally.

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Fig. 1: Hurricane/flood evacuation zones and emergency shelters in Shanghai and NYC.
Fig. 2: Spatial patterns of O–D pairs for city-wide flood evacuation in Shanghai and NYC.
Fig. 3: Distributions of evacuee transfers and time costs between O–D pairs in the transport systems of Shanghai and NYC.
Fig. 4: Strategic positioning of shelters and the resultant distribution of O–D pairs for strategy 1 and strategy 2 in the City of Shanghai.
Fig. 5: Spatial distribution of evacuee transfers and travel times for large-scale coastal flood evacuation plans with strategy 1 and strategy 2 in Shanghai.
Fig. 6: Theoretical framework of strategic storm flood evacuation planning for effective transfer of elderly population in large coastal cities.

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Data availability

The traffic network data, demographic data, evacuation centre data and evacuation zone map for NYC are freely available from the United States Census Bureau (https://www.census.gov/) and the NYC Open Data Portal (https://opendata.cityofnewyork.us/). The transport network and POI data in Shanghai are obtained from the AMAP Data Portal under licence. Shelter data in Shanghai are derived from the Shanghai municipal civil defence office (https://mfbwz.mfb.sh.gov.cn/mfbwz/mfb/yjbncs/map.html#). The population census data are provided by the Shanghai Statistics Bureau. The topographic data and seawall/floodwall data are collated from Shanghai Municipal Institute of Surveying and Mapping and Shanghai Water Authority, respectively. Certain datasets of Shanghai are available from the authors upon reasonable request and with permission of the parties that provided the data.

Code availability

Data analysis and results representation were produced by using Origin software (https://www.originlab.com) and ESRI ArcGIS (https://www.esri.com). FloodMap modelling software was used with permission from co-author D.Y.

References

  1. Kates, R. W., Colten, C. E., Laska, S. & Leatherman, S. P. Reconstruction of New Orleans after Hurricane Katrina: a research perspective. Proc. Natl Acad. Sci. USA 103, 14653–14660 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Lin, N., Emanuel, K., Oppenheimer, M. & Vanmarcke, E. Physically based assessment of hurricane surge threat under climate change. Nat. Clim. Chang. 2, 462–467 (2012).

    Article  Google Scholar 

  3. Nicholls, R. J. et al. A global analysis of subsidence, relative sea-level change and coastal flood exposure. Nat. Clim. Chang. 11, 338–342 (2021).

    Article  Google Scholar 

  4. Jongman, B., Ward, P. J. & Aerts, J. C. Global exposure to river and coastal flooding: long term trends and changes. Global Environ. Chang. 22, 823–835 (2012).

    Article  Google Scholar 

  5. Aerts, J. C. et al. Evaluating flood resilience strategies for coastal mega-cities. Science 344, 473–475 (2014).

    Article  PubMed  Google Scholar 

  6. Yin, J., Yu, D., Yin, Z., Wang, J. & Xu, S. Modelling the anthropogenic impacts on fluvial flood risks in a coastal mega-city: a scenario-based case study in Shanghai, China. Landsc. Urban Plan. 136, 144–155 (2015).

    Article  Google Scholar 

  7. Kreibich, H. et al. The challenge of unprecedented floods and droughts in risk management. Nature 608, 80–86 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. IPCC. Climate Change 2021: The Physical Science Basis (Cambridge Univ. Press, 2021).

  9. IPCC. Climate Change 2022: Impacts, Adaptation and Vulnerability (Cambridge Univ. Press, 2022).

  10. Hanson, S. et al. A global ranking of port cities with high exposure to climate extremes. Clim. Change 104, 89–111 (2011).

    Article  Google Scholar 

  11. Hallegatte, S., Green, C., Nicholls, R. J. & Corfee-Morlot, J. Future flood losses in major coastal cities. Nat. Clim. Chang. 3, 802–806 (2013).

    Article  Google Scholar 

  12. White, G. F. Human Adjustment to Floods: Department of Geography Research Paper No. 29 (Univ. Chicago, 1945).

  13. Hall, J. W. et al. A methodology for national-scale flood risk assessment. J. Water Maritime Eng. 156, 235–247 (2003).

    Article  Google Scholar 

  14. Rosenzweig, C. & Solecki, W. Hurricane Sandy and adaptation pathways in New York: lessons from a first-responder city. Global Environ. Chang. 28, 395–408 (2014).

    Article  Google Scholar 

  15. Tullos, D. How to achieve better flood-risk governance in the United States. Proc. Natl Acad. Sci. USA 115, 3731–3734 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Logan, T. M., Guikema, S. D. & Bricker, J. D. Hard-adaptive measures can increase vulnerability to storm surge and tsunami hazards over time. Nat. Sustain. 1, 526–530 (2018).

    Article  Google Scholar 

  17. Larson, L. & Plasencia, D. No adverse impact: new direction in floodplain management policy. Nat. Hazards Rev. 2, 157–181 (2001).

    Article  Google Scholar 

  18. Yin, J., Yu, D., Lin, N. & Wilby, R. Evaluating the cascading impacts of sea level rise and coastal flooding on emergency response spatial accessibility in Lower Manhattan, New York City. J. Hydrol. 52, 648–658 (2017).

    Article  Google Scholar 

  19. Urbina, E. & Wolshon, B. National review of hurricane evacuation plans and policies: a comparison and contrast of state practices. Transport. Res. A 37, 257–275 (2003).

    Google Scholar 

  20. Kim, J. & Oh, S. S. Confidence, knowledge, and compliance with emergency evacuation. J. Risk Res. 18, 111–126 (2015).

    Article  Google Scholar 

  21. Feng, K. & Lin, N. Reconstructing and analyzing the traffic flow during evacuation in Hurricane Irma (2017). Transport. Res. D 94, 102788 (2021).

    Article  Google Scholar 

  22. Southworth, F. Regional Evacuation Modeling: A State-of-the-Art Review (Oak Ridge National Laboratory, 1991).

  23. Bayram, V. Optimization models for large scale network evacuation planning and management: a literature review. Surv. Oper. Res. Manag. Sci. 21, 63–84 (2016).

    Google Scholar 

  24. FEMA. Guide for All-Hazard Emergency Operations Planning (Federal Emergency Management Agency, 1996).

  25. FEMA. Design and Construction Guidance for Community Safe Rooms (Federal Emergency Management Agency, 2008).

  26. Sherali, H. D., Carter, T. B. & Hobeika, A. G. A location–allocation model and algorithm for evacuation planning under hurricane/flood conditions. Transport. Res. B 25, 439–452 (1991).

    Article  Google Scholar 

  27. Kalafatas, G. & Peeta, S. Planning for evacuation: insights from an efficient network design model. J. Infrastruct. Syst. 15, 21–30 (2009).

    Article  Google Scholar 

  28. Ng, M. & Lin, D. Y. Sharp probability inequalities for reliable evacuation planning. Transport. Res. C 60, 161–168 (2015).

    Article  Google Scholar 

  29. Lindell, M. K. & Perry, R. W. The protective action decision model: theoretical modifications and additional evidence. Risk Anal. 32, 616–632 (2012).

    Article  PubMed  Google Scholar 

  30. NYC Hurricane Sandy After Action: Report and Recommendations to Mayor Michael R. Bloomberg (NYC Mayor’s Office, 2012).

  31. Coates, L. Flood fatalities in Australia, 1788–1996. Aust. Geogr. 30, 391–408 (1999).

    Article  Google Scholar 

  32. Rappaport, E. N. Loss of life in the United States associated with recent Atlantic tropical cyclones. Bull. Am. Meteorol. Soc. 81, 2065–2073 (2000).

    Article  Google Scholar 

  33. Diakakis, M. & Deligiannakis, G. Flood fatalities in Greece, 1970–2010. J. Flood Risk Manag. 10, 115–123 (2017).

    Article  Google Scholar 

  34. Jonkman, S. N., Maaskant, B., Boyd, E. & Levitan, M. L. Loss of life caused by the flooding of New Orleans after Hurricane Katrina: analysis of the relationship between flood characteristics and mortality. Risk Anal. 29, 676–698 (2009).

    Article  PubMed  Google Scholar 

  35. Yu, D. et al. Disruption of emergency response to vulnerable populations during floods. Nat. Sustain. 3, 728–736 (2020).

    Article  Google Scholar 

  36. Wolshon, B., Urbina, E., Levitan, M. & Wilmot, C. Review of policies and practices for hurricane evacuation. ii: traffic operations, management, and control. Nat. Hazards Rev. 6, 143–161 (2005).

    Article  Google Scholar 

  37. Gori, A., Lin, N., Xi, D. & Emanuel, K. Tropical cyclone climatology change greatly exacerbates US extreme rainfall-surge hazard. Nat. Clim. Chang. 12, 171–178 (2022).

    Article  Google Scholar 

  38. Vousdoukas, M. I. et al. Climatic and socioeconomic controls of future coastal flood risk in Europe. Nat. Clim. Chang. 8, 776–780 (2018).

    Article  Google Scholar 

  39. Becker, M., Karpytchev, M. & Hu, A. Increased exposure of coastal cities to sea-level rise due to internal climate variability. Nat. Clim. Chang. 13, 367–374 (2023).

    Article  Google Scholar 

  40. Rentschler, J., Salhab, M. & Jafino, B. A. Flood exposure and poverty in 188 countries. Nat. Commun. 13, 3527 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Zachry, B. C., Booth, W. J., Rhome, J. R. & Sharon, T. M. A national view of storm surge risk and inundation. Weather Clim. Soc. 7, 109–117 (2015).

    Article  Google Scholar 

  42. Yu, D. & Lane, S. N. Interaction between subgrid-scale resolution, feature representation and grid-scale resolution in flood inundation modelling. Hydrol. Process. 25, 36–53 (2011).

    Article  Google Scholar 

  43. Bates, P. D., Horritt, M. & Fewtrell, T. A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling. J. Hydrol. 387, 33–45 (2010).

    Article  Google Scholar 

  44. Yin, J., Yu, D., Yin, Z., Wang, J. & Xu, S. Modelling the combined impacts of sea-level rise and land subsidence on storm tides induced flooding of the Huangpu River in Shanghai, China. Clim. Change 119, 919–932 (2013).

    Article  Google Scholar 

  45. Yin, J., Lin, N. & Yu, D. Coupled modeling of storm surge and coastal inundation: a case study in New York City during Hurricane Sandy. Water Resour. Res. 52, 8685–8699 (2016).

    Article  Google Scholar 

  46. Yin, J. et al. Flood risks in sinking delta cities: time for a reevaluation? Earth’s Future 8, e2020EF001614 (2020).

    Article  Google Scholar 

  47. Brussee, A. R. et al. Impact of hydraulic model resolution and loss of life model modification on flood fatality risk estimation: case study of the Bommelerwaard, the Netherlands. J. Flood Risk Manag. 14, e12713 (2021).

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (grant no. 42371076), Science and Technology Commission of Shanghai Municipality (grant no. 21230750600), the Engineering and Physical Sciences Research Council of UK (grant no. R034214/1) and Hong Kong Research Grants Council-Early Career Scheme (grant no. 27202419). N.L. has received funding from the National Science Foundation of the United States (grant no. 1652448). D.Y. and R.W. were funded by the UK Natural Environment Research Council (grant no. NE/R009600/1 and NE/S017186/1). J.B. acknowledged financial support from the Netherlands Organization for Scientific Research (NWO) (grant no. ALWSD.2016.007).

Author information

Authors and Affiliations

  1. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, China

    Jie Yin & Yuhan Yang

  2. Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai, China

    Jie Yin

  3. Geography and Environment, Loughborough University, Loughborough, UK

    Dapeng Yu & Robert Wilby

  4. Previsico Ltd, Loughborough, UK

    Dapeng Yu & Mingfu Guan

  5. Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA

    Ning Lin

  6. Institute of Earth Surface Dynamics, University of Lausanne, Lausanne, Switzerland

    Stuart Lane

  7. Research Center for China Administrative Division, East China Normal University, Shanghai, China

    Bindong Sun

  8. Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, USA

    Jeremy Bricker

  9. Department of Hydraulic Engineering, Delft University of Technology, Delft, the Netherlands

    Jeremy Bricker

  10. School of Engineering, University of Birmingham, Birmingham, UK

    Nigel Wright

  11. Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, China

    Lili Yang

  12. Department of Civil Engineering, the University of Hong Kong, Hong Kong, China

    Mingfu Guan

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  1. Jie Yin
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Contributions

J.Y. conceived the study, prepared the dataset, interpreted the result and drafted the manuscript. J.Y. and D.Y. designed the initial emergency evacuation model. R.W., N.L., N.W., S.L., J.B. and M.G. contributed to the further development of the methods and provided guidance on the optimization of shelter deployment. J.Y. and Y.Y. performed flood inundation modelling and network-based geospatial analysis. B.S. and L.Y. assisted in the questionnaire survey. All authors commented on the manuscript and gave final approval for publication.

Corresponding authors

Correspondence to Jie Yin, Dapeng Yu or Mingfu Guan.

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Nature Water thanks Robert Nicholls and the other, anonymous, reviewer for their contribution to the peer review of this work.

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Supplementary Figs. 1–5, Table 1, methods, references and appendix.

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Yin, J., Yang, Y., Yu, D. et al. Strategic storm flood evacuation planning for large coastal cities enables more effective transfer of elderly populations. Nat Water 2, 274–284 (2024). https://doi.org/10.1038/s44221-024-00210-z

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