Size Matters: Scaling Design Criteria to Service Area Size

Kelvin Meng and Fabian Papa, HydraTek & Associates, ON, Canada, Freddy Baron and Carolyn Truong, York Region, ON, Canada


The Region of York recently undertook a review of the hydraulic loading design criteria applied to the water supply and wastewater collection systems that it operates. The main objective of this work was to reconcile differences between the criteria applied by the Region and that applied by the nine local municipalities within its boundaries, particularly at jurisdictional interfaces where their respective systems connect. Another objective was to develop defensible criteria that can be applied to reduce the scale as well as defer and/or potentially avoid infrastructure investments that would otherwise be required with more conservative criteria. Exploiting the vast quantity of available system performance information, a first principles approach to re-constructing the criteria was adopted and, as the title suggests, the size of the service area in question plays an important role in terms of variability and associated measures for mitigating risks due to uncertainties. Accordingly, wherever possible, the resulting parameters factoring into hydraulic loading estimates are scaled by system size, recognizing that a one-size-fits-all approach is not always appropriate and efficient.

This presentation and paper will review the data analysis undertaken and the resulting development of alternate criteria, the back-testing thereof to confirm its adequacy relative to historically-applied criteria and examples to illustrate relevant implications. Of noteworthy interest is the application of frequency analysis for rainfall-derived inflow and infiltration (RDII) flow rates for more than 250 catchments, rather than relying on the relationship between the frequencies of rainfall event characteristics with RDII frequencies. This is a direct method of assessing level of service and reveals the variability (uncertainty) associated with this parameter and which is also shown to vary with system scale. Finally, the statistical analyses that are foundational to the development of the alternate design criteria afford the opportunity to apply probabilistic methods to support risk assessments of key infrastructure elements, wherever warranted. This will be demonstrated through the application of Monte Carlo Simulation on a sample (real-world) system.

The overall objective of this presentation and paper is to raise awareness of the analysis methodology applied and the results obtained, as well as to promote the use of probabilistically-based risk assessments, all for the purpose of supporting the design and implementation of infrastructure of the right size at the right time so as to maximize the economic efficiency of such investments.

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