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Predicting normalised monthly patterns of domestic external water demand using rainfall and temperature data
journal contributionposted on 2017-12-06, 00:00 authored by Benjamin TaylorBenjamin Taylor
An Australian national approach is presented to predict monthly patterns of local domestic external water demand from climatic indices of daily rainfall and maximum temperature. The model, which can be rapidly applied to potentially any location in Australia, has been verified by measured monthly external water demand at Adelaide, Bundaberg, Emerald, Fraser Coast, Gold Coast, Mackay, Melbourne, Newcastle, Perth and Toowoomba. The survey data represents demands in periods priorto, during and after the millennium drought of 2001–2005 by discontinuously spanning 25 years from 1985 to 2010. The model avoids local calibration through a national regression of parameters. A demand index is produced that predicts daily proportions of annual demand. Results show that the model is capable of identifying 90% of the spatial and temporal variability in water demand, based on daily index summations by month. This research is useful for reliability estimates of intermittent water supplies, such as rainwater harvesting.
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)
Number of Pages11
PublisherI W A Publishing
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External Author AffiliationsNot affiliated to a Research Institute; University of Southern Queensland;
JournalWater science and technology : water supply.