Forecasting Residential Water Demand: Case Study
Publication: Journal of Water Resources Planning and Management
Volume 133, Issue 4
Abstract
A new daily time series model for East Doncaster, Melbourne, Australia, is being evaluated. The model depends on the postulate that total water use is made up of base use and seasonal use, where base use is characterized by the water use during winter months and seasonal use on seasonal, climatic, and persistence components. Using the daily data collected by Yarra Valley Water for East Doncaster water supply distribution zone and the corresponding rainfall and temperature data from the Bureau of Meteorology from 1990 to 2000, the base values were calculated based on the lowest months of water usage in a year and were correlated with the day of the week and temperature and rainfall. Results revealed these three factors to be statistically significant and therefore, base use to be climate dependent. The seasonal water use is modeled by a series of three equations. The separation of the random component from the climatic variable resulted to a better of 86%. The model is further validated using different set of data from 2000 to 2001 yielding a of 86%.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The daily water consumption data were provided by Yarra Valley Water through Stephen Sonnenberg, the then Growth Planning Team Leader of the Service Enhancement Water Section. The daily maximum temperature and rainfall data were obtained from Australian Bureau of Meteorology.
References
Box, G. E. P., and Jenkins, G. M. (1976). Time series analysis: Forecasting and control, Holden-Day, San Francisco.
Bruce, J. P., and Clark, R. H. (1966). Introduction to hydrometeorology, Pergamon, Oxford, U.K.
Campbell, M. J. and Machin, D. (1999). “Medical statistics: A commonsense approach.” The p-value (level of significance), ⟨http://hsc.uwe.ac.uk/dataanalysis/quant_iss_pval.htm⟩ (Jul. 25, 2005).
Devore, J. L. (1990). “Tests of hypotheses based on a single sample.” Probability and statistics for engineering and the sciences, 3rd Ed., Duxbury Press, Wadsworth, Inc., Belmont, Calif., 313–317.
Gato, S., Jayasuriya, N., and Hadgraft, R. (2003). “A simple time series approach to modelling urban water demand.” 28th Int. Hydrology and Water Resources Symp., Institution of Engineers, Australia.
Gato, S., Jayasuriya, N., Roberts, P., and Hadgraft, R. (2004). “Understanding residential water use.” ENVIRO 2004, Sydney, Australia.
Gibbs, K. C. (1978). “Price variable in residential water demand models.” Water Resour. Res., 14(1), 15–18.
Graeser, H. J., Jr. (1958). “Meter records in system planning.” J. Am. Water Works Assoc., 50(11), 1395–1402.
Maidment, D. R., and Miaou, S. P. (1986). “Daily water use in nine cities.” Water Resour. Res., 22(6), 845–851.
Maidment, D. R., Miaou, S. P., and Crawford, M. M. (1985). “Transfer function models of daily urban water use.” Water Resour. Res., 21(4), 425–432.
Miaou, S. P. (1987). “Metropolitan’s daily water use—Analysis and forecasting.” Technical Rep., Metropolitan Water District of Southern California, Los Angeles.
Miaou, S. P. (1990). “A class of time series urban water demand models with nonlinear climatic effects.” Water Resour. Res., 26(2), 169–178.
Water Resources Strategy Committee for the Melbourne Area. (2001). “Discussion starter: Stage 1 in developing a water resources strategy for the greater Melbourne area.” Melbourne, Australia.
Zhou, S. L., McMahon, T. A., Walton, A., and Lewis, J. (2000). “Forecasting daily urban water demand: A case study of Melbourne.” J. Hydrol., 236(3), 153–164.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 133 • Issue 4 • July 2007
Pages: 309 - 319
Copyright
© 2007 ASCE.
History
Received: Dec 9, 2004
Accepted: May 3, 2006
Published online: Jul 1, 2007
Published in print: Jul 2007
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.