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

S. Alonso Vicario, M. Mazzoleni, S. Bhamidipati, M. Gharesifard, E. Ridolfi, C. Pandolfo, L. Alfonso

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

© 2020 IAHS.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.
Original languageEnglish
Pages (from-to)2359-2375
JournalHydrological Sciences Journal
Volume65
Issue number14
DOIs
Publication statusPublished - 25 Oct 2020
Externally publishedYes

Funding

This work was supported by the Ground Truth 2.0 project - Environmental knowledge discovery of human sensed data [Grant agreement ID: 689744] under the programme H2020-EU.3.5.5. - Developing comprehensive and sustained global environmental observation and information systems (L 347 - 2013-12-11). The authors acknowledge the Regione Umbria and the Consorzio per la Bonifica della Val di Chiana Romana e Val di Paglia for the data provided for this study. The authors acknowledge Erhu Du and an anonymous reviewer whose comments and suggestions helped to improve the paper. Part of this research was supported by the European H2020 Project GroundTruth 2.0 (Grant agreement 689744), by the Swedish Research Council FORMAS, and by the Centre of Natural Hazards and Disaster Science (CNDS) in Sweden. The authors acknowledge the Regione Umbria and the Consorzio per la Bonifica della Val di Chiana Romana e Val di Paglia for the data provided for this study. The authors acknowledge Erhu Du and an anonymous reviewer whose comments and suggestions helped to improve the paper. Part of this research was supported by the European H2020 Project GroundTruth 2.0 (Grant agreement 689744), by the Swedish Research Council FORMAS, and by the Centre of Natural Hazards and Disaster Science (CNDS) in Sweden.

FundersFunder number
Centre of Natural Hazards and Disaster Science
European H2020
H2020 European Research Council689744
Svenska Forskningsrådet Formas
Regione Umbria

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