Unravelling the influence of human behaviour on reducing casualties during flood evacuation

Floods are the natural hazards that are causing the most deaths worldwide. Flood early warning systems are one of the most cost-efficient methods to reduce death rates, triggering decisions about the evacuation of exposed population. Although previous studies have investigated the effect of human be...

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Bibliographic Details
Published in:Hydrological sciences journal 2020-10, Vol.65 (14), p.2359-2375
Main Authors: Alonso Vicario, S., Mazzoleni, M., Bhamidipati, S., Gharesifard, M., Ridolfi, E., Pandolfo, C., Alfonso, L.
Format: Article
Language:English
Subjects:
agent-based modelling
Behavior
Casualties
Early warning systems
Emergency communications systems
Emergency plans
Emergency preparedness
Evacuation
flood evacuation
flood modelling
Floods
Human behavior
human evacuation behaviour
Hydraulic models
Population studies
socio-hydrology
Traffic models
unsolved problems in hydrology (UPH)
UPH #21
Warning systems
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Summary:Floods are the natural hazards that are causing the most deaths worldwide. Flood early warning systems are one of the most cost-efficient methods to reduce death rates, triggering decisions about the evacuation of exposed population. Although previous studies have investigated the effect of human behaviours on evacuation processes, studies analysing a combination of behaviours, flood onset and warning timing are limited. Our objective is to explore how changes on the aforementioned factors can affect casualties. This is done within a modelling framework that includes an agent-based model, a hydraulic model, and a traffic model, which is implemented for the case study of Orvieto (Italy). The results show that the number of casualties is most impacted by people's behaviour. Besides, we found that a delay of 30 min in releasing the warning can boost the number of casualties up to six times. These results may help managers to propose effective emergency plans.
ISSN:0262-6667
2150-3435
2150-3435
DOI:10.1080/02626667.2020.1810254