Abstract
Climate change has an impact on all of society. This paper will assess the potential impact of rising flood wa-ter on civil transport infrastructure and identify structures which are at risk of disruption or damage based on flood prediction models. Pluvial flood models for Northern Ireland have been developed using LIDAR, digi-tal terrain models and asset data, given the dramatic anthropological changes in recent years these flood mod-els are likely to underestimate the risk. Therefore, by providing a spatial link between flood models and bridge structures within transport networks this study provides a conservative estimation of the risk. Given the de-tailed models have only been developed for urban areas, only the bridges within these geographic regions have been considered. This includes 1513 road bridges and 604 rail bridges. Geographical information systems (GIS) software has been used to provide the data link and the results indicate that approximately 20% of bridges are at risk of disruption according to the Q2 model. This model represents flood risk every 2 years. This finding indicated the urgency in which climate change and flood risk need to be considered in bridge management, maintenance, and planning.
Original language | English |
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Number of pages | 8 |
Publication status | Published - 13 Jun 2023 |
Event | 21st Railway Engineering International Conference 2023 - Royal Society of Edinburgh, 22-26 George Street, EH2 2PQ, Edinburgh, United Kingdom Duration: 13 Jun 2023 → 15 Jun 2023 https://www.railwayengineering.com/ |
Conference
Conference | 21st Railway Engineering International Conference 2023 |
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Country/Territory | United Kingdom |
City | Edinburgh |
Period | 13/06/2023 → 15/06/2023 |
Internet address |
Fingerprint
Dive into the research topics of 'Identifying bridges at risk of closure or damage due to fluvial flooding in urban areas of Northern Ireland'. Together they form a unique fingerprint.Student theses
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Improving the interoperability of bridge related data sets using Geographic Information Systems
Neeson, T. (Author), Lydon, M. (Supervisor), McKinley, J. (Supervisor) & Barry, L. (Supervisor), Jul 2024Student thesis: Masters Thesis › Master of Philosophy
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