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Incorporating Suds Maintenance Costing In A Decision Support Tool For Sustainable And Energy Efficient Urban Stormwater Management

Congress: 2015
Author(s): Neil Berwick (Dundee, UK), Adrian Morales Torres
Polytechnic University of Valencia1

Keyword(s): Sub-theme 10: Management of water resources,
AbstractIntroduction
Decision Support Systems (DSS) and Decision Support Tools (DSTs) can be used to assist users in making complex decisions. DSTs can simplify the decision making process and provide a transparent and unbiased comparison of multiple options for drainage design. DSTs can improve both the efficiency with which users reach a decision as well as improving the effectiveness of that decision (Ellis et al., 2011).

The EU MED Project E²STORMED has developed a DST for use by municipalities within the Mediterranean region to assess the effectiveness of stormwater management techniques for both new and retrofit developments. The E²STORMED DST includes the comparison of energy efficiency, financial cost, and environmental criteria of urban stormwater techniques. The results of applying this tool allow more sustainable, informed and objective stormwater management (Escuder-Bueno et al., 2013).

This E²STORMED project has investigated the challenges of determining accurate and realistic maintenance costs of sustainable drainage systems (SuDS) for use within decision support tools. The appropriateness of existing cost data sets for SuDS maintenance available within the public realm has been investigated, including sample size, geographic variances in rates, relative age of datasets, and equipment type. The findings of the research have been used to make recommendations for the further refinement of the E2²STORMED decision support tool.

Methods
The E²STORMED Project aims to provide a process by which municipalities can compare the benefits and efficiencies of different SuDS options. The development of the tool has involved the review of existing DSTs, and analysis of their benefits and limitations. The availability and quality of guidance for SuDS maintenance regimes, and existing cost data sets has been investigated.

Results and Discussion
A range of Decision Support Tools (DSTs) exist within the public domain; these aim to assist decision makers in selecting the most appropriate sustainable drainage system (SuDS) for a given catchment. DSTs can be designed for use by technical or non-technical users and the range of input data and output information varies. Parameters which can be assessed vary by tool but include construction and operation costs, environmental benefits, social acceptability and energy efficiencies. DSTs can be simple processes, such as flow charts, for example the SUDS for Roads selection tool (Pittner & Allerton, 2009) which uses a matrix scoring system to shortlist possible SuDS options. Complex DSTs use computer software and allow comparison of more complex scenarios and commonly incorporate multiple criteria analysis (MCA) to compare different options. MCA techniques can be used to identify a single preferred plan, to rank options, as short-listing tools to select options for more detailed assessment, or to differentiate acceptable and unacceptable plans.

Complex DSTs require input of greater volumes and types of data; however the outputs can include a comparison of a broad range of criteria, both tangible and intangible. One tangible output that many of the current and emerging tools seek to provide guidance on is infrastructure cost; both for land acquisition and construction phase, and the operational phase. Whilst tangible and non-tangible comparisons are made to assess viability of options, the key selection criterion is often financial; if the financial viability of an option is unrealistic then the other benefits are inconsequential.

The availability of accurate and realistic datasets for stormwater infrastructure is problematic, specifically for the operation and maintenance of SuDS. There is considerable variance between recommendations for the range of maintenance activities, and their appropriate frequency in existing guidance. This is predominantly due to SuDS being a new technology, and the type of maintenance activity required. Within the public domain there exists guidance for the maintenance activities required for SuDS (including Woods-Ballard et al., 2007 and SFPUC, 2009), and cost datasets for SuDS maintenance (including Royal HaskoningDHV, 2012, Lampe et al., 2007, and SCOTS & SUDS Working Party, 2010). However these are not comprehensive and there remain issues when this information is applied within the optioneering process across local, national and international boundaries.

Conclusion
The use of detailed versus simple maintenance costings provides both benefits and limitations. Simple costings permit rapid development of support tools however the detail and accuracy of the cost data is limited; this type of data can be used to provide quick comparisons of options which provide a shortlist of preferable options which can then be further investigated. Detailed maintenance costings provide more accurate cost comparisons of maintenance activity however there are limitations with this approach which include access to detailed, relevant and recent maintenance information and costs. The most problematic area of maintenance costing has been identified as corrective maintenance (where repair, rehabilitation or refurbishment is required).

The appropriateness of current guidance for maintenance activity type and frequency is not comprehensive, particularly across Europe where different climates dictate different regimes. The drivers for maintenance vary by country and in some cases regions, which makes development of a single support tool for use across the Mediterranean region difficult. Further research into maintenance regimes, cost data and external factors is required to make further refinements to the E²STORMED decision support tool.

Acknowledgements
The E²STORMED project (Reference: 1C-MED12-14) described in this paper is being funded by the MED Programme of the European Union. Authors would also like to express their gratitude to the E²STORMED project partners for their help and willingness to collaborate in this work. 1. Ellis, J. B., Lundy, L., & Revitt, D. M. (2011). An Integrated Decision Support Approach to the Selection of Sustainable Urban Drainage Systems (SUDS). In SWITCH Conference: The Future of Urban Water; Solutions for Liveable and Resilient Cities. [online]. Available from: http://www.switchtraining.eu/fileadmin/template/projects/switch_training/files/Resources/Ellis_2011_Integrated_Decision_Support_Approach_for_SUDS.pdf
2. Escuder-Bueno, I., Andrés-Doménech, I., Perales-Momparler, S, Morales-Torres, A. (2014). E²STORMED Decision Support Tool. Guidelines. Universitat Politècnica de València.
3. Lampe, L. et al. (2007). Post-Project Monitoring of BMP's/SUDS to Determine Performance and Whole-Life Costs (Phase 2). WERF Report 01-CTS-21Ta. London: IWA Publishing.
4. Pittner, C., & Allerton, G. (2009). SUDS for Roads. [online]. Available from: http://scots.sharepoint.apptix.net/roads/General%20Publications/Forms/AllItems.aspx
5. Royal HaskoningDHV (2012). Costs and Benefits of Sustainable Drainage Systems. [online]. Available from: http://www.theccc.org.uk/publication/climate-change-is-the-uk-preparing-for-flooding-and-water-scarcity-3rd-progress-report-2012/
6. San Francisco Public Utilities Commission (SFPUC) (2009). San Francisco Stormwater Design Guidelines. San Francisco, CA (2009).
7. SCOTS & SUDS Working Party (2010). SUDS for Roads Whole Life Cost and Whole Life Carbon Toolkit. [online]. Available from: http://www.scotsnet.org.uk/best-practice.php
8. Woods-Ballard, B., et al. (2007). The SUDS manual (C697). The SUDS manual (C697). London: CIRIA.

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