E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||9|
|Published online||20 October 2016|
Methodology to assess coastal infrastructure resilience to climate change
1 HR Wallingford, Howbery Business Park. Crowmarsh Gifford, Wallingford, Oxfordshire, OX10 8BA, United Kingdom
2 CH2M Hill, Burderop Park, Swindon, SN4 0QD, United Kingdom
3 Network Rail, Western House, 1 Holbrook Way, Swindon, Wiltshire, SN1 1BD, United Kingdom
a Corresponding author: email@example.com
The section of railway which runs along the coastline of south Devon in United Kingdom, from Exeter to Newton Abbot, is one of the most photographed sections of railway in the world. It was opened in 1846 with embankments and seawalls protecting and supporting the railway, providing the route of an atmospheric railway. Despite regular maintenance however, there has been a history of storm damage, one of the most severe occurring in February 2014. This resulted in the collapse of the line, interruption of all rail traffic into and out of the far South- West of the United Kingdom (affecting parts of Devon and the whole of Cornwall) and significant damage to the region’s economy.
In order to improve the resilience of the line, several options have been considered to evaluate and reduce climate change impacts to the railway. This paper describes the methodological approach developed to evaluate the risks of flooding for a range of scenarios in the estuary and open coast reaches of the line. Components to derive the present day and future climate change coastal conditions including some possible adaptation measures are also presented together with the results of the hindcasting analysis to assess the performance of the modelling system. An overview of the modelling results obtained to support the development of a long-term Resilience Strategy for asset management is also discussed.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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