Evacuation planning for plausible worst case inundation scenarios in Honolulu, Hawaii

Authors

  • Karl Kim, PhD
  • Pradip Pant, PhD
  • Eric Yamashita, MURP

DOI:

https://doi.org/10.5055/jem.2015.0223

Keywords:

sea level rise, hurricane storm surge, river flooding, travel demand modeling, evacuation, risk reduction, Honolulu

Abstract

Honolulu is susceptible to coastal flooding hazards. Like other coastal cities, Honolulu's long-term economic viability and sustainability depends on how well it can adapt to changes in the natural and built environment. While there is a disagreement over the magnitude and extent of localized impacts associated with climate change, it is widely accepted that by 2100 there will be at least a meter in sea level rise (SLR) and an increase in extreme weather events. Increased exposure and vulnerabilities associated with urbanization and location of human activities in coastal areas warrants serious consideration by planners and policy makers.

This article has three objectives. First, flooding due to the combined effects of SLR and episodic hydrometeorological and geophysical events in Honolulu are investigated and the risks to the community are quantified. Second, the risks and vulnerabilities of critical infrastructure and the surface transportation system are described. Third, using the travel demand software, travel distances and travel times for evacuation from inundated areas are modeled.

Data from three inundation models were used. The first model simulated storm surge from a category 4 hurricane similar to Hurricane Iniki which devastated the island of Kauai in 1992. The second model estimates inundation based on five tsunamis that struck Hawaii. A 1-m increase in sea level was included in both the hurricane storm surge and tsunami flooding models. The third model used in this article generated a 500-year flood event due to riverine flooding. Using a uniform grid cell structure, the three inundation maps were used to assess the worst case flooding scenario. Based on the flood depths, the ruling hazard (hurricane, tsunami, or riverine flooding) for each grid cell was determined. The hazard layer was analyzed with socioeconomic data layers to determine the impact on vulnerable populations, economic activity, and critical infrastructure. The analysis focused both on evacuation needs and the critical elements of the infrastructure system that are needed to ensure effective response and recovery in the advent of flooding.

This study shows that the coastal flooding will seriously affect the economy and employment. Extreme flooding events could affect 38 percent of the freeways, 44 percent of the highways, 69 percent of the arterial roads, and 40 percent of the local streets in the area examined. Approximately 80 percent of the economy and 76 percent of the total employment in the urban core of Honolulu is exposed to flooding. Evacuation modeling, shelter accessibility, and travel time to shelter analyses revealed that there is a significant shortage in sheltering options, as well as increases in travel times and distances as inundation depth increases. The findings are useful for evacuation and shelter planning for extreme coastal events, as well as for climate change adaptation planning in Honolulu. Recommendations for emergency responders as well as those interested in the integration of long-term SLR and low probability, high consequence coastal hazards are included. The study shows how to integrate travel demand modeling across multiple hazards and threats related to evacuating, sheltering, and disaster risk reduction.

Author Biographies

Karl Kim, PhD

National Disaster Preparedness Training Center, University of Hawaii at Manoa, Honolulu, Hawaii.

Pradip Pant, PhD

National Disaster Preparedness Training Center, University of Hawaii at Manoa, Honolulu, Hawaii.

 

Eric Yamashita, MURP

National Disaster Preparedness Training Center, University of Hawaii at Manoa, Honolulu, Hawaii

References

SHELDUS: SHELDUS Products: U.S. Hazard Losses. 2012. Available at http://webra.cas.sc.edu/hvri/docs/Summary_2011.pdf. Accessed July 15, 2013.

Slangen ABA, Katsman CA, van de Wal RSW, et al.: Towards regional projections of twenty-first century sea-level change based on IPCC SRES scenarios. Clim Dyn. 2012; 38(5-6): 1191-1209.

Rignot E, Velicogna I, van den Broeke MR, et al.: Acceleration of the contribution of the Greenland and Antarctic ice sheets to sea level rise. Geophys Res Lett. 2011: 38: 1-5.

Verneer M, Rahmstorf S: Global sea level linked to global temperature. Proc Natl Acad Sci. 2009; 106(51): 21527-21532.

Bamber JL, Aspinall WP: An expert judgement assessment of future sea level rise from the ice sheets. Nat Clim Chang. 2013; 3: 424-427.

Vitousek S, Fletcher CH, Barbee M: A practical approach to mapping extreme wave inundation: Consequences of sea-level rise and coastal erosion. Paper presented at the Proceedings of the Solutions to Coastal Disasters 2008, Oahu, HI, April 13-16, 2008: 85-96.

Cooper HM, Chen Q, Fletcher CH, et al.: Assessing vulnerability due to sea-level rise in Maui, Hawaii using LiDAR remote sensing and GIS. Climate Change 2013; 116: 547-563.

Cooper HM, Fletcher CH, Chen Q, et al.: Sea-level rise vulnerability mapping for adaptation decisions using LiDAR DEMs. Prog Phys Geog. 2013; 37(6): 745-766.

Fletcher C, Rooney J, Barbee M, et al.: Mapping shoreline change using digital orthophotogrammetry on Maui, Hawaii. J Coastal Res, Special Issue. 2003; 38: 106-124.

Kennedy AB, Westerink JJ, Smith JM, et al.: Tropical cyclone inundation potential on the Hawaiian Islands of Oahu and Kauai. Ocean Model. 2012; 52-53(0): 54-68.

Phadke AC, Martino CD, Cheung KF, et al.: Modeling of tropical cyclone winds and waves for emergency management. Ocean Eng. 2003; 30(4): 553-578.

Stopa JE, Cheung KF, Chen YL: Assessment of wave energy resources in Hawaii. Renew Energy. 2011; 36(2): 554-567.

Cheung KF, Phadke AC, Wei Y, et al.: Modeling of storm-induced coastal flooding for emergency management. Ocean Eng. 2003; 30(11): 1353-1386.

Cheung KF, Tang L, Donnelly JP, et al.: Numerical modeling and field evidence of coastal overwash in southern New England from Hurricane Bob and implications for paleotempestology. J Geophys Res. 2007; 112(F3): 2003-2012.

Cheung KF, Bai Y, Yamazaki Y: Surges around the Hawaiian Islands from the 2011 Tohoku Tsunami. J Geophys Res: Oceans. 2013; 118(10): 5703-5719.

Chagué-Goff C, Goff J, Nichol SL, et al.: Multi-proxy evidence for trans-Pacific tsunamis in the Hawai'ian Islands. Mar Geol. 2012; 299-302(0), 77-89.

Day SJ, Watts P, Grilli ST, et al.: Mechanical models of the 1975 Kalapana, Hawaii earthquake and tsunami. Mar Geol. 2005; 215(1-2): 59-92.

Goff J, Dudley WC, deMaintenon MJ, et al.: The largest local tsunami in 20th century Hawaii. Mar Geol. 2006; 226(1-2): 65-79.

Murphy MJ, Businger S: Orographic influences on an Oahu flood. Mon Weather Rev. 2011; 139(7): 2198-2217.

US Army Corps of Engineers: Hydrological and Hydraulics Study: Flood of October 30, 2004. Manoa Stream, Honolulu, Oahu: US Army Corps of Engineers, 2006.

Kim K, Pant P, Yamashita E, et al.: Spatial criticality of transportation risks from sea level rise, storm surge, and tsunami hazards in Honolulu, Hawaii. Paper presented at the 92nd Transportation Research Board Annual Meeting, Washington, DC, 2013.

Pruttipong A, Davidson R, Blanton B, et al.: Long-term regional hurricane hazard analysis for wind and storm surge. Coast Eng. 2011; 58: 499-509.

Roeber V, Cheung KF: Boussinesq-type model for energetic breaking waves in fringing reef environment. Coast Eng. 2012; 70: 1-20.

Stopa JE, Cheung KF, Garcé MA, et al.: Atmospheric Infrasound from nonlinear wave interactions during Hurricanes Felicia and Neki of 2009. J Geophys Res. 2012; 117(C12017).

Yamazaki Y, Cheung KF, Kowalik Z: Depth-integrated, non-hydrostatic model with grid nesting for tsunami generation, propagation, and run-up. Int J Numer Methods Fluids. 2011; 67(12): 2081-2107.

Federal Emergency Management Agency: Hazus. 2012. Available at http://www.fema.gov/protecting-our-communities/hazus. Accessed July 24, 2012.

NOAA: Tides & Currents, Honolulu, HI Station ID:1612340. 2013. Available at http://tidesandcurrents.noaa.gov/data_menu.shtml?unit=0&format=Apply+Change&stn=1612340+Honolulu%2C+HI&type=Datums. Accessed April 22, 2013.

ESRI: ArcGIS 10 [Compuer Program]. Redlands, CA: ESRI, 2010.

SAS Institute: SAS [Compuer Program]. Cary, NC: ESRI, 2010. 30. RM Towill Corporation: Planning for Sustainable Tourism in Hawaii: Economic and Environmental Assessment Modeling Study. Honolulu, HI: The Department of Business, Economic Development, and Tourism, Research and Economic Analysis Division, State of Hawaii. 2005.

Ray S: Car in the Water. 2013. Available at http://www.cfspress.com/carwater.htm. Accessed July 15, 2013.

Published

03/01/2015

How to Cite

Kim, PhD, K., P. Pant, PhD, and E. Yamashita, MURP. “Evacuation Planning for Plausible Worst Case Inundation Scenarios in Honolulu, Hawaii”. Journal of Emergency Management, vol. 13, no. 2, Mar. 2015, pp. 93-108, doi:10.5055/jem.2015.0223.