E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||8|
|Section||Management and maintenance of infrastructure|
|Published online||20 October 2016|
Asset Management Planning – providing the evidence to support robust and risk-based investment decisions
1 Environment Agency, Kingsmeadow House, Kingsmeadow Road, Reading, RG1 8DQ, UK
2 CH2M, Burderop Park, Swindon, SN4 0QD, UK
3 HR Wallingford, Howbery Park, Wallingford, Oxfordshire OX10 8BA UK
4 Royal Haskoning DHV, Rightwell House, Bretton, Peterborough, PE3 8DW UK
a Corresponding author: email@example.com
Over the last decade the UK’s joint Flood and Coastal Erosion Risk Management Research and Development programme has been developing methods to support a move to a risk-based approach to flood defence asset management. Looking to ensure investment is less ‘find and fix’ and made to those assets where the biggest risk reduction can be made for the money available. In addition, providing the capability to articulate the benefits of investing in these assets quantitatively and transparently. This paper describes how the Asset Performance Tools (APT) project  is delivering practical methods, prototype tools and supporting guidance which, together with related initiatives such as the Environment Agency’s Creating Asset Management Capacity (CAMC) strategic programme  and the ‘State of the Nation’ (SoN)  supportive datasets, will enable a risk-based, ‘predict and protect’ approach to asset management. A key advance is the ability to bring in local knowledge to make national generic datasets locally relevant. The paper also highlights existing outputs that can already be used to support a more proactive approach to asset management. It will summarise the ongoing work which will further develop and fine tune performance assessment and investment decision processes within an integrated conceptual framework aligned with ISO55000, deliverable via CAMC and whose concepts can be used by all risk management authorities.
© 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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