Simultaneous Peak Water Demands in Residential Areas

This report was produced for the Urban Water Research Association of Australia, a now discontinued research program.

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Report no. UWRAA 67

September 1993

Synopsis

Water distribution networks must have sufficient capacity to ensure that minimum head requirements at consumer supply offtakes are met during the peak demand period. To achieve this, the design of networks, using computer modelling, requires a clear understanding of the water usage patterns of consumers during this period.

Existing models used by the Water Authority of Western Australia have recognised that the peak water usages by individual consumer services occur at varying times, giving a diversity effect, but have assumed that the distribution of demand at each service can be described statistically as a normal distribution.

The aim of this study was to assess diversity effects during times of peak water use in the Perth summer and involved the recording of instantaneous water use by a sample of 84 Perth households continuously over a period of three months.

The major findings of the study are:

1. During the time of peak water usage (typically at around 6.30 pm on a day with high temperatures and easterly winds) a large proportion of households are still using little or no water.

2. Consequently the traditional models for water demand which assume a normal distribution are particularly inappropriate. There is a need for a skew distribution with an extended upper tail.

3. The Gamma distribution with a shape parameter around 0.2 to 0.3 provides a good model for the observed demand during peaks. The model is best in the upper tail, the region most critical in a description of the diversity effect.

4. No evidence was found for correlation of demand by nearby households. Pressure and long and short services also did not have a measurable effect on peak consumption. However the relatively small sample size (84 households) suggests that this should not be taken as conclusive evidence that correlation can always be ignored.

5. The effect of moving from normal distribution models to Gamma distribution models has a similar effect on the general shape of diversity curves to that of introducing correlation to the normal distribution model. Consequently it is likely that earlier studies which used normal distribution models may have interpreted distribution effects as correlation.

In addition the study developed methodologies for the optimal collection and analysis of instantaneous demand data.

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