Abstract

There is an expectation that many cities in Australia may experience higher temperatures and reduced rainfall in the future. Hence, to support water policy analysis there is a need for predicting water demand and how it changes in response to climate change. This paper describes a methodology to develop a model that explains month-to-month variability in water demand due to climate and weather, on the basis of using statistical methods. To achieve this, we use time series data of historical water use volumes and climate data from relevant weather stations. Applying this model together with hypothetical climate change scenarios, but without community adaptation scenarios, the results indicate that water demand will change moderately and, as may be expected, it is most sensitive to evaporation and temperature, followed by rainfall. With such scenarios, demand is shown to increase by as much as 10–20%, but more realistic climate sequences are required to provide reliable estimates. Given availability of data, this statistical method can be used to support policy analyses in other cities.

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