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A household-level flood evacuation decision model in Quezon City, Philippines

Abstract

Evacuation is one of the important preparedness measures in disaster management. It requires careful modeling and planning to minimize chaos and confusion during evacuation operations. The choice of decision-makers, whether to evacuate or stay in the area threatened by hazard, is an important aspect of evacuation travel behavior research. This is considered an essential input for evacuation modeling and planning. This study investigates the effects of various factors determining evacuation decision. A discrete choice model is proposed using the data collected through a face-to-face post-event survey from flood-affected households in Quezon City, Philippines. The model allows a choice among three alternatives of full, partial, and no evacuation. Results show that evacuation decision is determined by a combination of household characteristics and capacity-related factors (gender, educational level, presence of children, and number of years living in the residence, house ownership, number of house floor levels, type of house material), as well as hazard-related factors (distance from source of flood, level of flood damage, and source of warning). Findings in the study provide insights that can be considered by policy-makers in preparing for future evacuations. Appropriate programs can be designed to encourage full evacuation compliance of households that live nearest to the flood source and those living in houses with two or more floor levels who are more likely not to evacuate. Households with children can also be educated for full evacuation compliance since these households have higher probability to partially evacuate.

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References

  • Abarquez I, Murshed D (2004) Community based disaster risk management: field practitioners’ handbook. Asian Disaster Preparedness Center, Thailand

    Google Scholar 

  • Abdelgawad H, Abdulhai B (2010a) Towards a complete evacuation demand and supply modeling and management process. In: Proceedings of the 12th world conference on transportation studies, Lisbon, Portugal

  • Abdelgawad H, Abdulhai B (2010b) Managing large-scale multimodal emergency evacuations. J Transp Saf Secur 2:122–151

    Article  Google Scholar 

  • Akbarzadeh M, Wilmot C (2015) Time-dependent route choice in hurricane evacuation. Nat Hazards Rev. doi:10.1061/(ASCE)NH.1527-6996.0000159

    Google Scholar 

  • Baker EJ (1979) Predicting response to hurricane warnings: a reanalysis of data from four studies. Mass Emerg 4(1):9–24

    Google Scholar 

  • Baker EJ (1991) Evacuation behavior in hurricanes. Int J Mass Emerg Disasters 9(2):287–310

    Google Scholar 

  • Ben-Akiva M, Lerman S (1985) Discrete choice analysis. MIT Press, Cambridge

    Google Scholar 

  • Bourque LB, Russell LA (1994) Experiences during and responses to the Loma Prieta earthquake. Sacramento, CA

    Google Scholar 

  • Bourque LB, Reeder LG, Cherlin A, Raven BH, Walton DM (1971) The unpredictable disaster in a Metropolis: public response to the Los Angeles earthquake of February, 1971. UCLA Survey Research Center, Washington, DC

    Google Scholar 

  • Brommer DM, Senkbeil JC (2010) Pre-landfall evacuee perception of the meteorological hazards associated with Hurricane Gustav. Nat Hazards 55(2):353–369. doi:10.1007/s11069-010-9532-7

    Article  Google Scholar 

  • Cahyanto I, Pennington-Gray L, Thapa B, Srinivasan S, Villegas J, Matyas C, Kiousis S (2014) An empirical evaluation of the determinants of tourist’s hurricane evacuation decision making. J Destin Mark Manag 2(4):253–265. doi:10.1016/j.jdmm.2013.10.003

    Google Scholar 

  • Campion B, Venzke J (2013) Rainfall variability, floods and adaptations of the urban poor to flooding in Kumasi, Ghana. Nat Hazards 65(3):1895–1911

    Article  Google Scholar 

  • Carnegie J, Deka D (2010) Using hypothetical disaster scenarios to predict evacuation behavioral response. In: Proceedings of the 89th annual meeting of the transportation research board, Washington, DC, 10–14 Jan 2010

  • Charnkol T, Tanaboriboon Y (2006) Tsunami evacuation behavior analysis-one step of transportation disaster response. IATSS Res 30(2):83–96

    Article  Google Scholar 

  • Charnkol T, Hanaoka S, Tanaboriboon Y (2007) Emergency trip destination of evacuation as shelter analysis for tsunami disaster. J East Asia Soc Transp Stud 7:853–868. doi:10.11175/easts.7.853

    Google Scholar 

  • Chen C, Zhang G, Tarefder R, Ma J, Wei H (2015) A multinomial logit model-Bayesian network hybrid approach for driver injury severity analyses in rear-end crashes. Accid Anal Prev 80:76–88

    Article  Google Scholar 

  • Cheng G, Wilmot CG, Baker EJ (2008) A destination choice model for hurricane evacuation. In: The 87th transportation research board annual meeting, Washington, DC

  • Cuellar L, Kubicek D, Hengartner N, Hansson A (2009) Emergency relocation: population response model to disasters. In: Proceedings of the IEEE conference on technologies for homeland security, Boston, MA

  • Cutter S, Barnes K (1982) Evacuation behavior and three mile Island. Disasters 6(2):116–124

    Article  Google Scholar 

  • Dash N (2002) Decision-making under extreme uncertainty: rethinking hazard-related perceptions and action. ProQuest ETD Collection for Florida International University. Paper AAI3057593. http://search.proquest.com/docview/276296719 (abstract only)

  • Dash N, Gladwin H (2007) Evacuation decision making and behavioral responses: individual and household. Nat Hazards Rev 8:69–77

    Article  Google Scholar 

  • Der-Martirosian C, Strine T, Atia M, Chu K, Mitchell MN, Dobalian A (2014) General household emergency preparedness: a comparison between veterans and nonveterans. Prehosp Disaster Med 29(2):134–140. doi:10.1017/S1049023X1400020X

    Article  Google Scholar 

  • Dow K, Cutter SL (2000) Public orders and personal opinions: household strategies for hurricane risk assessment. Environ Hazards 2:143–155

    Article  Google Scholar 

  • Dow K, Cutter SL (2002) Emerging hurricane evacuation issues: hurricane Floyd and South Carolina. Nat Hazards Rev 3(1):12–18

    Article  Google Scholar 

  • Durage SW, Kattan L, Wirasinghe SC, Ruwanpura JY (2014) Evacuation behaviour of households and drivers during a tornado. Nat Hazards 71(3):1495–1517. doi:10.1007/s11069-013-0958-6

    Article  Google Scholar 

  • Fedeski M, Gwilliam J (2007) Urban sustainability in the presence of flood and geo-logical hazards: the development of a GIS-based vulnerability and risk assessment methodology. Landsc Urban Plan 83(1):50–61

    Article  Google Scholar 

  • Fischer HW, Stine GF, Stoker BL, Trowbridge ML, Drain EM (1995) Evacuation behaviour: why do some evacuate, while others do not? A case study of the Ephrata, Pennsylvania (USA) evacuation. Disaster Prev Manag 4(4):30–36

    Article  Google Scholar 

  • Fu H, Wilmot G (2004) Sequential logit dynamic travel demand model for hurricane evacuation. Transp Res Board 1882:19–26

    Article  Google Scholar 

  • Fujiwara A, Zhang J (2005) Development of car tourists’ scheduling model for 1-day tour. Transp Res Rec 1921:100–111

    Article  Google Scholar 

  • Gladwin H, Peacock WG (1997) Warning and evacuation: a night for hard houses. In: Peacock WG, Morrow BH, Gladwin H (eds) Hurricane Andrew: ethnicity, gender, and the sociology of disasters. International Hurricane Center, Miami, pp 52–72

    Google Scholar 

  • Hasan S, Ukkusuri S, Gladwin H, Murray-Tuite P (2011) Behavioral model to understand household-level hurricane evacuation decision making. J Transp Eng 137(5):341–348

    Article  Google Scholar 

  • Hasan S, Mesa-Arango R, Ukkusuri S, Murray-Tuite P (2012) Transferability of hurricane evacuation choice model: joint model estimation combining multiple data sources. J Transp Eng 138(5):548–556

    Article  Google Scholar 

  • Hasan S, Mesa-Arango R, Ukkusuri S (2013) A random-parameter hazard-based model to understand household evacuation timing behavior. Transp Res Part C 27:108–116

    Article  Google Scholar 

  • Hensher D, Rose J, Greene W (2005) Applied choice analysis: a primer. Cambridge University Press, UK

    Book  Google Scholar 

  • Horney JA, MacDonald PDM, Van Willigen M, Berke PR, Kaufman JS (2010) Individual actual or perceived property flood risk: Did it predict evacuation from Hurricane Isabel in North Carolina, 2003? Risk Anal 30(3):501–511. doi:10.1111/j.1539-6924.2009.01341.x

    Article  Google Scholar 

  • Hosmer DW, Lemeshow S (eds) (2000) Applied logistic regression, 2nd edn. Wiley, New York

    Google Scholar 

  • Houts PS, Lindell MK, Weittu T, Cleary PD, Tokuhata G, Flynn CB (1984) The protective action decision model applied to evacuation during the three mile Island crisis. Int J Mass Emerg Disasters 2(1):27–39

    Google Scholar 

  • Hsu Y, Peeta S (2013) An aggregate approach to model evacuee behavior for no-notice evacuation operation. Transportation 40(3):671–696

    Article  Google Scholar 

  • Huibregtse L, Bliemer M, Hoogendoorn S (2010) Analysis of near-optimal evacuation instructions. Procedia Eng 3:189–203

    Article  Google Scholar 

  • Kim J, Oh S (2014) Confidence, knowledge, and compliance with emergency evacuation. J Risk Res 18(1):1–16. doi:10.1080/13669877.2014.880728

    Article  Google Scholar 

  • Kolen B, Helsloot I (2014) Decision-making and evacuation planning for flood risk management in the Netherlands. Disasters 38(3):610–635. doi:10.1111/disa.12059

    Article  Google Scholar 

  • Kwak C, Matthews AC (2002) Multinomial logistic regression. Nurs Res 51(6):404–410

    Article  Google Scholar 

  • Lewis MA, Noguchi E (2009) Logistic regression to describe how the relationship between social connection and self-rated health varies by gender. J Appl Quant Methods 4(2):166–174

    Google Scholar 

  • Lim H Jr, Lim MB, Piantanakulchai M (2013a) A review of recent studies on flood evacuation planning. J East Asia Soc Transp Stud 10:147–162

    Google Scholar 

  • Lim MB, Lim H Jr, Piantanakulchai M (2013b) Factors of evacuation decision and its implication to transportation planning. J East Asia Soc Transp Stud 10:163–177

    Google Scholar 

  • Lim H Jr, Lim MB, Piantanakulchai M (2015a) Household flood evacuation route choice model at sub-district level. In: Proceedings of the 11th Eastern Asia society for transportation studies conference. Cebu, Philippines, 11–14 Sept 2015

  • Lim H Jr, Lim MB, Piantanakulchai M (2015b) Modeling route choice behavior of evacuees in highly urbanized area: a case study of Bagong Silangan, Quezon City, Philippines. In: Proceedings of the 3rd international conference on evacuation modeling and management, Tainan, Taiwan, 1–3 June 2015

  • Lim MB, Lim H Jr, Piantanakulchai M, Uy FA (2015c) Flood evacuation decision modeling for high risk urban area in the Philippines. In: Proceedings of the 3rd international conference on evacuation modeling and management, Tainan, Taiwan, 1–3 June 2015

  • Lindell MK (2013) Disaster studies. Curr Sociol 61(5–6):797–825. doi:10.1177/0011392113484456

    Article  Google Scholar 

  • Lindell MK, Hwang SN (2008) Households’ perceived personal risk and responses in a multihazard environment. Risk Anal 28(2):539–556

    Article  Google Scholar 

  • Lindell M, Lu J, Prater C (2005) Household decision making and evacuation in response to hurricane Lili. Nat Hazards Rev 6(4):171–179. doi:10.1061/(ASCE)1527-6988(2005)6:4(171)

    Article  Google Scholar 

  • Liu S, Murray-Tuite P, Schweitzer L (2012) Analysis of child pick-up during daily routines and for daytime no-notice evacuations. Transp Res Part A 46:48–67

    Google Scholar 

  • Liu S, Murray-Tuite P, Schweitzer L (2014) Uniting multi-adult households during emergency evacuation planning. Disasters 38(3):587–609

    Article  Google Scholar 

  • Lumbroso D, Stone K, Vinet F (2011) An assessment of flood emergency plans in England and Wales, France and the Netherlands. Nat Hazards 58:341–363

    Article  Google Scholar 

  • Luo Y, Shaw R, Lin H, Joerin J (2014) Assessing response behaviour of debris-flows affected communities in Kaohsiung, Taiwan. Nat Hazards 74(3):1429–1448. doi:10.1007/s11069-014-1258-5

    Article  Google Scholar 

  • Mesa-Arango R, Hasan S, Ukkusuri S, Murray-Tuite P (2013) Household-level model for hurricane evacuation destination type choice using Hurricane Ivan data. Nat Hazards Rev 14(1):11–20. doi:10.1061/(ASCE)NH.1527-6996.0000083

    Article  Google Scholar 

  • Mileti DS, Bandy R, Bourque LB, Johnson A, Kano M, Peek L, Sutton J, Wood M (2006) Annotated bibliography for public risk communication on warnings for public protective actions response and public education. http://www.colorado.edu/hazards/publications/informer/infrmr2/pubhazbibann.pdf

  • Morrow BH, Gladwin H (2005) Hurricane Ivan behavioral analysis, 2004 hurricane assessments, Federal Emergency Management Agency and U.S. Army Corps of Engineers, Washington, DC

  • Murray-Tuite P, Wolshon B (2013) Evacuation transportation modeling: an overview of research, development, and practice. Transp Res Part C Emerg Technol 27:25–45

    Article  Google Scholar 

  • NDRRMC (2013) Updates on effects of southwest monsoon enhanced by tropical storm “Maring” Sitrep No. 17. Quezon City Philippines. http://ndrrmc.gov.ph. Accessed 20 Aug 2013

  • Ng M, Behr J, Diaz R (2014) Unraveling the evacuation behavior of the medically fragile population: findings from hurricane Irene. Transp Res Part A Policy Pract 64:122–134. doi:10.1016/j.tra.2014.03.015

    Article  Google Scholar 

  • Pel A, Hoogendoorn S, Bliemer M (2010) Evacuation modelling including traveler information and compliance behavior. Procedia Eng 3:101–111

    Article  Google Scholar 

  • Pel A, Bliemer M, Hoogendoorn S (2012) A review on travel behaviour modelling in dynamic traffic simulation models for evacuations. Transportation 39:97–123

    Article  Google Scholar 

  • Perry RW (1979) Evacuation decision-making in natural disasters. Mass Emerg 4(1):25–38

    Google Scholar 

  • Provost F, Domingos P (2001) Well-trained PETS: improving probability estimation trees. CeDER working paper IS-00-04, New York

  • Pryanishnikov I, Zigova K (2003) Multinomial logit models for the Austrian labor market. Austrian J Stat 32(4):267–282

    Google Scholar 

  • Quezon City Government City Planning and Development Office (2013) Actual and projected population by district and by barangay 2010–2020

  • Quezon City Government, Earthquakes and Megacities Initiative (2013) Disaster risk reduction and management plan 2014–2020. Building a disaster resilient Quezon City project

  • Riad JK, Norris FH, Ruback RB (1999) Predicting evacuation in two major disasters: risk perception, social influence, and access to resources. J Appl Soc Psychol 29(5):918–934. doi:10.1111/j.1559-1816.1999.tb00132.x

    Article  Google Scholar 

  • Sadri AM, Ukkusuri SV, Murray-Tuite P, Gladwin H (2014a) Analysis of hurricane evacuee mode choice behavior. Transp Res Part C Emerg Technol 48:37–46. doi:10.1016/j.trc.2014.08.008

    Article  Google Scholar 

  • Sadri AM, Ukkusuri SV, Murray-Tuite P, Gladwin H (2014b) How to evacuate: model for understanding the routing strategies during Hurricane evacuation. J Transp Eng 140(1):61–69

    Article  Google Scholar 

  • Scott DM, Kanaroglou PS (2002) An activity-episode generation model that captures interactions between household heads: development and empirical analysis. Transp Res Part B Methodol 36(10):875–896. doi:10.1016/S0191-2615(01)00039-X

    Article  Google Scholar 

  • Shiwakoti N, Liu Z, Hopkins T, Young W (2013) An overview on multimodal emergency evacuation in an urban network. In: Proceedings of the Australasian transport research forum, Brisbane, Australia

  • Siebeneck L, Cova T (2012) Spatial and temporal variation in evacuee risk perception throughout the evacuation and return-entry process. Risk Anal 32(9):1468–1480

    Article  Google Scholar 

  • Sorensen J, Vogt B (2006) Interactive emergency evacuation guidebook. Chemical Stockpile Emergency Preparedness Program. Department of Homeland Security, Washington, DC

    Google Scholar 

  • Sorensen JH, Vogt BM, Mileti DS (1987) Evacuation: an assessment of planning and research Oak Ridge National Laboratory, report prepared for the Federal Emergency Management Agency Washington DC

  • SSDD (2013) Report on affected and evacuated families during flood in August 2013. Unpublished report

  • Steyeberg E, Borsboom G, van Houwelingen H, Eijkemans M, Habbema D (2004) Validation and updating of predictive logistic regression models: a study on sample size and shrinkage. Stat Med 12:2567–2586

    Article  Google Scholar 

  • Stopher P, Rose J, Alsnih R (2004) Dynamic travel demand for emergency evacuation: the case of bushfires. Working Paper, Institute of Transport Studies

  • Tay R, Barua U, Kattan L (2009) Factors contributing to hit-and-run in fatal crashes. Accid Anal Prev 41:227–233

    Article  Google Scholar 

  • Taylor M, Freeman S (2010) A review of planning and operational models used for emergency evacuation situations in Australia. Procedia Eng 3:3–14

    Article  Google Scholar 

  • Taylor JG, Gillette SC, Hodgson RW, Downing JL, Burns MR, Chavez DJ, Hogan JT (2007) Informing the network: improving communication with interface communities during wildland fire. Human Ecol Rev 14(2):198–211

    Google Scholar 

  • Train K (ed) (2009) Discrete choice methods with simulation, 2nd edn. Cambridge University Press, New York

    Google Scholar 

  • UNOCHA (2013) Philippine southwest monsoon flooding situation report no. 4. http://reliefweb.int/sites/reliefweb.int/files/resources/OCHAPhilippinesSouthwestMonsoonSitrepNo.4.28August2013.pdf. Accessed 20 October 2013

  • Wallace JW, Poole C, Horney JA (2014) The association between actual and perceived flood risk and evacuation from Hurricane Irene, Beaufort County, North Carolina. J Flood Risk Manag. doi:10.1111/jfr3.12115

  • Whitehead J, Edwards B, Van Willigen M, Maiolo J, Wilson K, Smith K (2000) Heading for higher ground: factors affecting real and hypothetical hurricane evacuation behavior. Environ Hazards 2(4):133–142

    Article  Google Scholar 

  • Wilmot CG, Mei B (2004) Comparison of alternative trip generation models for Hurricane evacuation. Nat Hazards Rev 5(4):170–178

    Article  Google Scholar 

  • Yin W, Murray-Tuite P, Ukkusuri S, Gladwin H (2014) An agent-based modeling system for travel demand simulation for hurricane evacuation. Transp Res Part C 42:44–59

    Article  Google Scholar 

  • Zaghdoudi T (2013) Bank failure prediction with logistic regression. Int J Econ Financ Issues 3(2):537–543

    Google Scholar 

  • Zhang J, Kuwano M, Lee B, Fujiwara A (2009) Modeling household discrete choice behavior incorporating heterogeneous group decision-making mechanisms. Transp Res Part B Methodol 43(2):230–250. doi:10.1016/j.trb.2008.05.002

    Article  Google Scholar 

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Acknowledgments

This research was funded in part through the scholarship given by Sirindhorn International Institute of Technology (SIIT), Thammasat University, Thailand. The accuracy of the information written in this paper is the sole responsibility of the authors and does not in any way represent the ideas of SIIT. The authors are grateful to all the officials of Quezon City Government who assisted in facilitating the data collection and providing the secondary data and other pertinent information.

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Correspondence to Ma. Bernadeth B. Lim.

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Lim, M.B.B., Lim, H.R., Piantanakulchai, M. et al. A household-level flood evacuation decision model in Quezon City, Philippines. Nat Hazards 80, 1539–1561 (2016). https://doi.org/10.1007/s11069-015-2038-6

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Keywords

  • Flood
  • Evacuation decision
  • Travel behavior
  • Evacuation modeling
  • Discrete choice