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Lookup NU author(s): Dr Maria Pregnolato, Dr Alistair FordORCiD, Professor Sean Wilkinson, Professor Richard DawsonORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2017 Transport networks underpin economic activity by enabling the movement of goods and people. During extreme weather events transport infrastructure can be directly or indirectly damaged, posing a threat to human safety, and causing significant disruption and associated economic and social impacts. Flooding, especially as a result of intense precipitation, is the predominant cause of weather-related disruption to the transport sector. Existing approaches to assess the disruptive impact of flooding on road transport fail to capture the interactions between floodwater and the transport system, typically assuming a road is fully operational or fully blocked, which is not supported by observations. In this paper we develop a relationship between depth of standing water and vehicle speed. The function that describes this relationship has been constructed by fitting a curve to video analysis supplemented by a range of quantitative data that has be extracted from existing studies and other safety literature. The proposed relationship is a good fit to the observed data, with an R-squared of 0.95. The significance of this work is that it is simple to incorporate our function into existing transport models to produce better estimates of flood induced delays and we demonstrate this with an example from the 28th June 2012 flood in Newcastle upon Tyne, UK.
Author(s): Pregnolato M, Ford A, Wilkinson SM, Dawson RJ
Publication type: Article
Publication status: Published
Journal: Transportation Research Part D: Transport and Environment
Year: 2017
Volume: 55
Pages: 67-81
Print publication date: 01/08/2017
Online publication date: 23/06/2017
Acceptance date: 02/04/2016
Date deposited: 13/07/2017
ISSN (print): 1361-9209
ISSN (electronic): 1879-2340
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.trd.2017.06.020
DOI: 10.1016/j.trd.2017.06.020
Data Access Statement: http://dx.doi.org/10.17634/121736-4
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