Evans, Barry, Lam, Man-Yue ORCID: https://orcid.org/0000-0001-7259-968X, West, Charles, Ahmadian, Reza ORCID: https://orcid.org/0000-0003-2665-4734, Djordjevic, Slobodan, Chen, Albert and Pregnolato, Maria 2024. A combined stability function to quantify flood risks to pedestrians and vehicle occupants. Science of the Total Environment 908 , 168237. 10.1016/j.scitotenv.2023.168237 |
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Abstract
With the increase of the frequency and severity of flooding events, coupled with population growth, the risks posed to people from flooding is ever more apparent. This paper proposes a methodology to examine the risks posed to vehicles' occupants and pedestrians simultaneously in an urban context. Through considering stability functions of a range of vehicle types and pedestrian, a risk assessment profile for a vehicle occupant was derived. Using a historical 1-in-20-year rainfall flood event that took place in the city of Exeter (UK) in 2014, and a synthetic 1 in 100-year rainfall flood event, the potential risks posed to vehicle occupants were analysed. The results showed that for these events the potential risks posed to people travelling by car and caught in flood waters were likely to be more severe if they were to remain within their vehicles than if they were to exit said vehicles. Analysis of the changes in risk over time further revealed that if a vehicle was to become immobilised in flood water, they would only have a short timeframe (~10 min) before the level of risk increases. This is a critical finding, highlighting that remaining inside an immobilised vehicle during flood event and waiting for assistance may increase the level the risk the individual is exposed to, with the results showing the significance of such studies in reducing the risk of flooding to people.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Engineering |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TC Hydraulic engineering. Ocean engineering |
Publisher: | Elsevier |
ISSN: | 0048-9697 |
Funders: | GW4, EU H2020, NERC |
Date of First Compliant Deposit: | 1 December 2023 |
Date of Acceptance: | 29 October 2023 |
Last Modified: | 03 Feb 2024 02:25 |
URI: | https://orca.cardiff.ac.uk/id/eprint/164462 |
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