Natural Hazards

, Volume 65, Issue 3, pp 1603–1628 | Cite as

Community variations in population exposure to near-field tsunami hazards as a function of pedestrian travel time to safety

  • Nathan J. WoodEmail author
  • Mathew C. Schmidtlein
Original Paper


Efforts to characterize population exposure to near-field tsunami threats typically focus on quantifying the number and type of people in tsunami-hazard zones. To develop and prioritize effective risk-reduction strategies, emergency managers also need information on the potential for successful evacuations and how this evacuation potential varies among communities. To improve efforts to properly characterize and differentiate near-field tsunami threats among multiple communities, we assess community variations in population exposure to tsunamis as a function of pedestrian travel time to safety. We focus our efforts on the multiple coastal communities in Grays Harbor and Pacific Counties (State of Washington, USA), where a substantial resident and visitor population is threatened by near-field tsunamis related to a potential Cascadia subduction zone earthquake. Anisotropic, path distance modeling is conducted to estimate travel times to safety, and results are merged with various population data, including residents, employees, public venues, and dependent-care facilities. Results suggest that there is substantial variability among communities in the number of people that may have insufficient time to evacuate. Successful evacuations may be possible in some communities assuming slow walking speeds, are plausible in others if travel speeds are increased, and are unlikely in another set of communities given the large distances and short time horizon. Emergency managers can use these results to prioritize the location and determine the most appropriate type of tsunami risk-reduction strategies, such as education and training in areas where evacuations are plausible and vertical-evacuation structures in areas where they are not.


Tsunami Evacuation Path distance Modeling Pedestrian Cascadia 



This study was supported by the US Geological Survey (USGS) Geographic Analysis and Monitoring Program. We thank Susan Benjamin, Ronald Kirby, and Mara Tongue of the USGS, John Schelling of the State of Washington Military Department Emergency Management Division, and two anonymous reviewers for their insightful reviews of earlier versions of the article. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the US Government.


  1. Averill J, Mileti D, Peacock R, Kuligowski E, Groner N, Proulx G, Reneke P, Nelson H (2005) Occupant behavior, egress, and emergency communications—federal building and fire safety investigation of the world trade center disaster. National Institute of Standards and Technology National Construction Safety Team Act Report 1–7Google Scholar
  2. Brooks N (2003) Vulnerability, risk and adaptation—a conceptual framework. Tyndall Centre for Climate Change Research Working Paper 38. Available at Accessed 10 August 2012Google Scholar
  3. Cascadia Region Earthquake Workgroup (2005) Cascadia subduction zone earthquakes—a magnitude 9.0 earthquake scenario. Oregon Department of Geology and Mineral Industries, PortlandGoogle Scholar
  4. CloudMade (2011) Available at Accessed 12 Oct 2011
  5. Cutter S (2003) The vulnerability of science and the science of vulnerability. Ann As Am Geogr 93(1):1–12CrossRefGoogle Scholar
  6. Cutter S, Boruff B, Shirley W (2003) Social vulnerability to environmental hazards. Social Sci Q 84(2):242–261CrossRefGoogle Scholar
  7. Dall’Osso F, Cavalletti A, Polo P (2006) Risk assessment and evaluation ArcGIS Toolbox user’s manual, CRATER Coastal Risk Analysis of Tsunamis and Environmental Remediation. Italian Ministry for the Environment and Territory, Rome, Italy and Asian Disaster Preparedness Center, PathumthaniGoogle Scholar
  8. Engstfeld A, Killebrew K, Scott C, Wiser J, Freitag B, El-Anwar O (2010) Tsunami safe haven project—report for Long Beach. Department of Urban Design and Planning, College of Built Environments, University of Washington, WashingtonGoogle Scholar
  9. Franzese O, Sorenson D (2004) Fast deployable system for consequence management—the emergency evacuation component. Proceedings of the ITS Safety and Security conference, Orlando, FL, 13 pGoogle Scholar
  10. Goldfinger C, Nelson C, Morey A, Johnson J, Patton J, Karabanov E, Gutiérrez-Pastor J, Eriksson A, Gràcia E, Dunhill G, Enkin R, Dallimore A, Vallier T (2012) Turbidite event history—methods and implications for Holocene paleoseismicity of the Cascadia subduction zone. U.S. Geological Survey Professional Paper 1661–FGoogle Scholar
  11. Graehl N (2009) Using a GIS to model pedestrian evacuation times for Newport, OR. Unpublished research, Humbolt State University, CaliforniaGoogle Scholar
  12. Grays Harbor County (2011) GIS data download. Available at Accessed 12 Feb 2012
  13. Hewitt K (1997) Regions of risk–a geographical introduction to disasters. Addison Wesley Longman, EssexGoogle Scholar
  14. InfoUSA (2011) Employer database. Available via Accessed 1 Oct 2011
  15. Jonkmann S, Vrijling J, Vrouwenvelder A (2008) Methods for the estimation of loss of life due to floods: a literature review and a proposal for a new method. Nat Hazards 46:353–389CrossRefGoogle Scholar
  16. Knoblauch R, Pietrucha M, Nitzburg M (1995) Field studies of pedestrian walking speed and start-up time. In: Transportation research record, no. 1538, TRB, National Research Council, Washington, DC, pp 27–38Google Scholar
  17. Lander J, Lockridge P (1989) United States tsunamis (including United States possessions) 1690–1988. U.S. Department of Commerce, National Geophysical Data Center, Boulder, Colorado, Publication 41–2Google Scholar
  18. Langlois J, Keyl P, Guralnik J, Foley D, Marottoli R, Wallace R (1997) Characteristics of older pedestrians who have difficulty crossing the street. Am J Pub Health 87:393–397CrossRefGoogle Scholar
  19. (2011) Boston marathon race results 2010, Available at Accessed 8 March 2011
  20. Marrero J, Garcia A, Llinares A, Rodrıguez-Losada J, Ortiz R (2010) The variable scale evacuation model (VSEM)—a new tool for simulating massive evacuation processes during volcanic crises. Nat Hazards Earth Syst Sci 10:747–760CrossRefGoogle Scholar
  21. Mileti D (1999) Disasters by design–a reassessment of natural hazards in the United States: Washington. Joseph Henry Press, DCGoogle Scholar
  22. Mileti D, Sorenson D (1990) Communication of emergency public warnings–a social science perspective and state-of-the-art assessment. Oak Ridge National Laboratory, Oak RidgeCrossRefGoogle Scholar
  23. Miller M, Paton D, Johnston D (1999) Community vulnerability to volcanic hazard consequences. Disaster Prev Manag 8(4):255–260CrossRefGoogle Scholar
  24. Morgan J (1984) A tsunami avoidable susceptibility index. Sci Tsunami Hazards 2(1):3–12Google Scholar
  25. Morrow B (1999) Identifying and mapping community vulnerability. Disasters 23(1):1–18CrossRefGoogle Scholar
  26. National Research Council (1996) Understanding risk—informing decisions in a democratic society. Committee on risk characterization, commission on behavioral and social sciences and education. The National Academies Press, Washington, DCGoogle Scholar
  27. National Research Council (2007) Tools and Methods for Estimating Populations at Risk from Natural Disasters and ComplexHumanitarian Crises. The National Academies Press, Washington, DCGoogle Scholar
  28. National Research Council (2011) Tsunami warning and preparedness: an assessment of the US Tsunami Program and the Nation’s preparedness efforts, Committee on the review of the tsunami warning and forecast system and overview of the nation’s tsunami preparedness. The National Academies Press, Washington, DCGoogle Scholar
  29. National Tsunami Hazard Mitigation Program (2012) About the national tsunami hazard mitigation program. Available at, Accessed 17 Sep 2012
  30. NOAA National Geophysical Data Center/World Data Center (2012) Global historical tsunami database. Available at Accessed 28 Jan 2012
  31. Ohno R, Isagawa T (2012) How do coastal residents behave after a big earthquake—a questionnaire survey after the Great East Japan earthquake at Onjuku, Chiba Prefecture. In: Joint conference proceedings of the 9th international conference on urban earthquake engineering and the 4th Asia conference on earthquake engineering, Tokyo, JapanGoogle Scholar
  32. Pacific County Department of Public Works (2011) Spatial data. Available at Accessed 1 Nov 2011
  33. Papathoma M, Dominey-Howes D, Zong Y, Smith D (2003) Assessing tsunami vulnerability, an example from Herakleio, Crete. Nat Hazards Earth Syst Sci 3(5):377–389CrossRefGoogle Scholar
  34. Paton D, Houghton B, Gregg C, Gill D, Ritchie L, McIvor D, Larin P, Meinhold S, Horan J, Johnston D (2008) Managing tsunami risk in coastal communities—identifying predictors of preparedness. Austr J Emerg Manag 23(1):4–9Google Scholar
  35. Polsky C, Neff R, Yarnal B (2007) Building comparable global change vulnerability assessments–the vulnerability scoping diagram. Glob Environ Change 17:472–485CrossRefGoogle Scholar
  36. Post J, Wegscheider S, Muck M, Zosseder K, Kiefl R, Steinmetz T, Strunz G (2009) Assessment of human immediate response capability related to tsunami threats in Indonesia at a sub-national scale. Nat Hazards Earth Syst Sci 9:1075–1086CrossRefGoogle Scholar
  37. Priest G, Myers III E, Baptista A, Fleuck P, Wang K, Kamphaus R, Peterson C (1997) Cascadia subduction zone tsunamis—hazard mapping at Yaquina Bay, Oregon. Oregon Department of Geology and Mineral Industries Open-File Report O-97-34, 144 pGoogle Scholar
  38. Slovic P (2002) The perception of risk. Earthscan Publications, Ltd, LondonGoogle Scholar
  39. Smit B, Wandel J (2006) Adaptation, adaptive capacity and vulnerability. Glob Environ Change 16:282–292CrossRefGoogle Scholar
  40. Soule R, Goldman R (1972) Terrain coefficients for energy cost prediction. J Appl Physiol 32:706–708Google Scholar
  41. Sumaryono S, Strunz G, Post J, Zosseder K, Ludwig R (2008) Spatial measuring urban vulnerability to tsunami hazards using integrative remote sensing and GIS approaches. In: Proceedings of the international conference on tsunami warning, 12–14 Nov 2008, Bali, IndonesiaGoogle Scholar
  42. Taubenbock H, Post J, Kiefl R, Roth A, Ismail F, Strunz G, Dech S (2008) Risk and vulnerability assessment to tsunami hazard using very high resolution satellite data. In: Carsten J (ed) Remote sensing—new challenges of high resolutionGoogle Scholar
  43. Tierney K, Lindell M, Perry R (2001) Facing the unexpected. Joseph Henry Press, LondonGoogle Scholar
  44. Tobler W (1993) Three presentations on geographical analysis and modeling—non-isotropic geographic modeling. Speculations on the geometry of geography; and global spatial analysis. UCSB. National Center for Geographic Information and Analysis Technical Report 93-1. Available at Accessed 19 July 2010
  45. Turner B, Kasperson R, Matson P, McCarthy J, Corell R, Christensen L, Eckley N, Kasperson J, Luers A, Martello M, Polsky C, Pulsipher A, Schiller A (2003) A framework for vulnerability analysis in sustainability science. Proc Nat Acad Sci 100(14):8074–8079CrossRefGoogle Scholar
  46. United States Census Bureau (2011) American FactFinder. Available at Accessed 1 May 2011
  47. United States Department of Agriculture (2009) Geospatial data gateway. Available at Accessed 1 Feb 2011
  48. United States Department of Transportation (2009) Manual on uniform traffic control devices for streets and highways. Federal Highway AdministrationGoogle Scholar
  49. Walsh T, Caruthers C, Heinitz A, Myers III E, Baptista A, Erdakos G, Kamphaus R (2000) Tsunami hazard map of the southern Washington coast—modeled tsunami inundation from a Cascadia subduction zone earthquake. Washington Department of Natural Resources Division of Geology and Earth Resources Geologic Map GM-49Google Scholar
  50. Washington Division of Geology and Earth Resources (2008) Tsunami inundation zones in Washington State, Version 1.0. Available at Accessed 16 Aug 2010
  51. Washington Military Department Emergency Management Division (2012) Tsunamis. Available at Accessed 17 Sep 2012
  52. Washington Office of Financial Management (2012) Census geographic files. Available at Accessed 12 Feb 2012
  53. WatershedSciences (2010) LIDAR remote sensing data collection. Available at Accessed 7 Aug 2011
  54. Wisner B, Blaikie P, Cannon T, Davis I (2004) At risk–natural hazards, people’s vulnerability and disasters, 2nd edn. Routledge, New YorkGoogle Scholar
  55. Wood N (2011) Understanding risk and resilience to natural hazards. U.S. Geological Survey Fact Sheet 2011-3008Google Scholar
  56. Wood N, Good J (2004) Vulnerability of a port and harbor community to earthquake and tsunami hazards: the use of GIS in community hazard planning. Coast Manag 32(3):243–269CrossRefGoogle Scholar
  57. Wood N, Schmidtlein M (2012) Anisotropic path modeling to assess pedestrian-evacuation potential from Cascadia-related tsunamis in the U.S. Pacific Northwest. Nat Hazards 62(2):275–300CrossRefGoogle Scholar
  58. Wood N, Soulard C (2008) Variations in community exposure to tsunami hazards on the open-ocean and strait of Juan de Fuca coasts of Washington. USGS Scientific Investigations Report 2008-5004Google Scholar
  59. Wood N, Burton C, Cutter S (2010) Community variations in social vulnerability to Cascadia-related tsunamis in the U.S. Pacific Northwest. Nat Hazards 52(2):369–389CrossRefGoogle Scholar
  60. Wood M, Mileti D, Kano M, Kelly M, Regan R, Bourque L (2011) Communicating actionable risk for terrorism and other hazards. Risk Anal 32(4):601–615CrossRefGoogle Scholar
  61. Yeh H, Fiez T, Karon J (2009) A comprehensive tsunami simulator for long beach peninsula phase-1—framework development final report. State of Washington Military Department Emergency Management DivisionGoogle Scholar

Copyright information

© US Government 2012

Authors and Affiliations

  1. 1.Western Geographic Science Center, U.S. Geological SurveyPortlandUSA
  2. 2.Department of GeographySacramento State UniversitySacramentoUSA

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