Water Supply Peaking Factor Stochastics

A method for sizing back-up provisions to match probable water supply failures
L Donaldson
Publication Date (Web): 30 August 2018
DOI: https://doi.org/10.21139/wej.2018.031

In Australia the national water supply design guidelines, Water Supply Code of Australia, recommend that risk assessments are undertaken as part of the process of sizing reservoirs and pump stations, and the determination of system configurations.  The guidelines refer to AS/NZS ISO 31000:2009 Risk Management – Principles and Guidelines which outlines a risk/consequence matrix approach for determining risks, and the most appropriate risk mitigation actions.  

Such matrices can identify the relative need for back-up provisions to cope with identified failure events.  Unfortunately, while water supply failure risks can be well assessed, the consequences are much more difficult to evaluate.  This is primarily because it is usually not possible to know whether the failure event would be most likely to occur during a minimum day, maximum day or some other value demand event.  The size of the back-up provisions therefore cannot be determined with any certainty and it is usual for water supply practitioners to have to make an “educated guess” about the required provisions.
Maximum Day Peaking Factor Exceedance Probability Profiles Figure 1: Maximum Day Peaking Factor Exceedance Probability Profiles
30 Day Peaking Factor Exceedance Probability Profiles Figure 2: 30 Day Peaking Factor Exceedance Probability Profiles
The companion paper, Water Supply Peaking Factor Stochastics, discusses the determination of stochastic based peaking factors from annual daily water supply records.  The availability of stochastic water supply peaking factors allows the sizing of a water supply system to match the demand for an adopted frequency of occurrence, i.e. level of service, in much the same way that a storm water drainage designer might size a drain to match the frequency of a storm event.  

A methodology has been prepared for undertaking risk assessments using the conventional binomial probability approach in conjunction with those stochastic based peaking factors.  Risk assessments can be undertaken using that methodology to quantify the back-up provision needed for a probable failure event while retaining the same level of service adopted for the supply system for normal operational conditions.  

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