Investigating the flood evacuation behaviour of older people: A case study of a rural town in Japan

Nakanishi, Hitomi; Black, John; Suenaga, Yoshihiro

doi:10.1016/j.rtbm.2019.100376

Cited by 32 publications

(18 citation statements)

References 26 publications

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“…Another interesting study was conducted by Li et al (2019), which combined a cellular automata model and a ABM system to simulate crowd evacuations in flood disasters, and the model was evaluated by real-participant experiments based on virtual reality (VR) environments. Similar studies on ABM applications in flood evacuation are also found in Higo et al (2017); Lim (2016, 2018); Yamamoto and Takizawa (2019); Nakanishi et al (2019); and Eivazy and Malek (2019).…”

Section: Real-time Flood Emergency Managementsupporting

confidence: 67%

Agent-based modelling and flood risk management: A compendious literature review

Zhuo

Han

2020

Journal of Hydrology

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The use of agent-based modelling (ABM) to tackle flood-related risk challenges is becoming increasingly popular in recent years. This paper reviews the literature at the interface of ABM and flood-related studies in view of understanding the technique's advantages and limitations to flood risk management, based on a set of 61 representative articles. In particular, to understand how this process-based technique can help to link human (also institutional) decisions and behaviour with flood risks through the whole human-flood systems. Overall, the temporal and spatial distributions demonstrate a growing interest in this research area around the world, especially since 2017. Three topic areas are identified, addressing different research challenges in the field: real-time flood emergency management, long-term flood adaptation planning, and flood hydrological modelling. The review has shown that the potential contribution of ABM to future flood risk management lays in its practical application to decision-making in adaptation policy and strategy planning. The review also critically reveals the limitation of ad hoc implementations of decision-making and behaviour in the ABM models that could make the application less realistic in the field. It is recommended that the future development should be guided/influenced by the continuing development and refinement of ABM modelling framework and theoretical foundations, and enhancement of model testing and documenting capabilities. More importantly, active collaborations between disciplines and sectors such as to involve more social and psychological sciences in ABM decision-making 2 modelling should be encouraged; and knowledge sharing will encourage more effective uses of ABM by wider audiences.

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Section: Real-time Flood Emergency Managementsupporting

confidence: 67%

Agent-based modelling and flood risk management: A compendious literature review

Zhuo

Han

2020

Journal of Hydrology

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“…A review by Huang et al ( 2016 ) of actual evacuation studies found that 41% reported a significantly negative correlation between age and evacuation, while the other 59% reported a non-significant correlation. A number of factors can cause a negative relation between age and evacuation, e.g., lack of mobility, pre-existing health conditions, limited social networks, low income, and poor vision and hearing (Cohen and Mulvaney 2005 ; Rosenkoetter et al 2007 ; Smith et al 2009 ; Nakanishi et al 2019 ; Dostal 2015 ). We study whether concerns about the consequences of becoming infected by COVID-19 are an additional barrier to evacuation for older people, who are also more likely to experience adverse health impacts from hurricanes (Jenkins et al 2007 ).…”

Section: Introductionmentioning

confidence: 99%

Individual hurricane evacuation intentions during the COVID-19 pandemic: insights for risk communication and emergency management policies

et al. 2021

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The U.S. 2020 hurricane season was extraordinary because of a record number of named storms coinciding with the COVID-19 pandemic. This study draws lessons on how individual hurricane preparedness is influenced by the additional risk stemming from a pandemic, which turns out to be a combination of perceptions of flood and pandemic risks that have opposite effects on preparedness behavior. We conducted a survey in early June 2020 of 600 respondents in flood-prone areas in Florida to obtain insights into households’ risk perceptions and preparedness for the upcoming hurricane season under COVID-19. The results show that concerns over COVID-19 dominated flood risk perceptions and negatively impacted people’s evacuation intentions. Whereas hotel costs were the main obstacle to evacuating during Hurricane Dorian in 2019 in the same geographic study area, the main evacuation obstacle identified in the 2020 hurricane season is COVID-19. Our statistical analyses investigating the factors influencing evacuation intentions show that older individuals are less likely to evacuate under a voluntary order, because they are more concerned about the consequences of becoming infected by COVID-19. We observe similar findings based on a real-time survey we conducted in Florida with another group of respondents under the threat of Hurricane Eta at the end of the hurricane season in November 2020. We discuss the implications of our findings for risk communication and emergency management policies that aim to improve hurricane preparedness when dealing with additional health risks such as a pandemic, a situation that may be exacerbated under the future climate.

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“…Both studies focused on people who are less able to move quickly during natural hazards. This informs ABM simulation in Japan in particular, where ageing is a serious concern in managing evacuation (Nakanishi, Black, & Suenaga, 2019).…”

Section: A Review Of Research On Abm Models and Its Application To Practicementioning

confidence: 76%

Simulating emergencies with transport outcomes Sim (SETOSim): Application of an agent-based decision support tool to community evacuation planning

Nakanishi

Wise

Suenaga

et al. 2020

International Journal of Disaster Risk Reduction

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In the time since the 2004 Indian Ocean tsunami and Hurricane Katrina in 2005, an increasing number of studies have focused on developing agent-based simulations of citizen evacuation behaviours. The application of simulation to practice (i.e. evacuation planning, community disaster risk reduction strategy), however, is limited. This research aims to explore the effective application of agent-based evacuation simulation to better inform community evacuation planning through a collaborative process. The study developed an evacuation modelling tool focusing on the storm surge and flood evacuation behaviours of residents living in Takamatsu, Japan. The city of Takamatsu borders the Seto Inland Sea, an area where the risks from waterrelated disasters are increasing. The tidal flow of the Seto Inland Sea and storm surge flooding are simulated based on data from the 2004 typhoons, which seriously flooded the study area. An agent-based model exploring the relative vulnerability of residents as a function of location, demographic attributes including age, and previous experience is developed based on a questionnaire survey of residents which gathered information on their stated preference of evacuation. A visualisation of the simulation was shared with residents through workshops held in five neighbourhoods. It was also shared with government officials. The feedback from residents and governments officials on the effective applications to community evacuation planning are discussed and plans for future research are outlined.

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Investigating the flood evacuation behaviour of older people: A case study of a rural town in Japan

Cited by 32 publications

References 26 publications

Agent-based modelling and flood risk management: A compendious literature review

Agent-based modelling and flood risk management: A compendious literature review

Individual hurricane evacuation intentions during the COVID-19 pandemic: insights for risk communication and emergency management policies

Simulating emergencies with transport outcomes Sim (SETOSim): Application of an agent-based decision support tool to community evacuation planning

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