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Lookup NU author(s): Dr Sarah Dunn
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© 2017 Elsevier Ltd. Hydrological infrastructure such as pumps, floodgates (or sluice gates), dams, embankments, and flood barriers are invaluable assets used for controlling water in flood-prone areas such coastal cities. These infrastructure components are often vulnerable to damage or failure due to the impact of floodwaters, thus leaving people and urban property exposed to flood hazards. To minimise the failure of hydrological infrastructure during intense flooding events, it is important to identify the most vulnerable components and to invest scarce resources in reducing their vulnerability. Using the concepts of exposure, susceptibility and resilience, this study proposes a graph-based network approach for measuring the vulnerability of hydrological infrastructure to flood damage in coastal cities. In this graph-based approach, hydrological infrastructures are represented as network nodes and the waterways as edges. The proposed vulnerability assessment approach is applied to measure and rank the vulnerability of floodgates in one of the most exemplary coastal cities - Jakarta, Indonesia. The results show that the proposed solution is both useful in highlighting the most vulnerable infrastructure components and also providing clues as to what actions can be taken to minimise infrastructure vulnerability. More so, the solution was found to be useful in identifying potential locations within the city of Jakarta, where additional infrastructure are required to improve resilience to flooding. This type of information about infrastructure vulnerability and resilience actions is vital to decision-making authorities responsible for planning, flood preparedness and priority-based allocation of resources for the maintenance of flood control infrastructure in coastal cities.
Author(s): Ogie RI, Holderness T, Dunn S, Turpin E
Publication type: Article
Publication status: Published
Journal: Computers, Environment and Urban Systems
Year: 2017
Volume: 68
Pages: 97-109
Print publication date: 01/03/2018
Online publication date: 21/11/2017
Acceptance date: 15/11/2017
Date deposited: 07/02/2018
ISSN (print): 0198-9715
ISSN (electronic): 1873-7587
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.compenvurbsys.2017.11.004
DOI: 10.1016/j.compenvurbsys.2017.11.004
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