Methods for Preserving Duration–Intensity Correlation on Synthetically Generated Water-Demand Pulses
Publication: Journal of Water Resources Planning and Management
Volume 142, Issue 2
Abstract
This paper proposes the application of three different methods for preserving the correlation between duration and intensity of synthetically generated water-demand pulses. The first two methods, that is, the Iman and Conover method and the Gaussian copula, respectively, are derived from known statistical approaches, although they had never been applied to the context of demand-pulse generation. The third is a novel methodology developed in this work and is a variation in the Gaussian copula approach. Poisson models fitted with the methods are applied to reproduce the measured pulses in one household, with parameters being obtained with the method of moments. Comparisons are made with another method previously proposed in the scientific literature, showing that the three methods have similar effectiveness and are applicable under more general conditions.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors thank Professor S.G. Buchberger for providing the data demand for the Milford households. This study was carried out as part of the ongoing projects: (1) iWIDGET (Grant Agreement No 318272), which is funded by the European Commission within the 7th Framework Programme, (2) the PRIN 2012 project Tools and procedures for an advanced and sustainable management of water distribution systems, no 20127PKJ4X, funded by MIUR, and (3) under the framework of Terra&Acqua Tech Laboratory, Axis I activity 1.1 of the POR FESR 2007–2013, project funded by the Emilia-Romagna Regional Council (Italy).
References
Alcocer-Yamanaka, V. H., Tzatchkov, V., and Buchberger, S. G. (2006). “Instantaneous water demand parameter estimation from coarse meter readings.” Proc., Water Distribution Systems Analysis Symp., ASCE, Reston, VA, 1–14.
Alcocer-Yamanaka, V. H., and Tzatchkov, V. G. (2012). “Modeling of drinking water distribution networks using stochastic demand.” Water Resour. Manage., 26(7), 1779–1792.
Alvisi, S., Ansaloni, N., and Franchini, M. (2014). “Generation of synthetic water demand time series at different temporal and spatial aggregation levels.” Urban Water J., 11(4), 297–310.
Alvisi, S., Franchini, M., and Marinelli, A. (2003). “A stochastic model for representing drinking water demand at residential level.” Water Resour. Manage., 17(3), 197–222.
Blokker, E. J. M., Vreeburg, J. H. G., and van Dijk, J. C. (2010). “Simulating residential water demand with a stochastic end-use model.” J. Water Resour. Plann. Manage., 19–26.
Buchberger, S. G., Carter, J. T., Lee, Y. H., and Schade, T. G. (2003). “Random demands, travel times and water quality in dead-ends, prepared for American water works association research foundation.”, American Water Works Association Research Foundation, Denver, CO, 470.
Buchberger, S. G., and Wells, G. J. (1996). “Intensity, duration and frequency of residential water demands.” J. Water Resour. Plann. Manage., 11–19.
Buchberger, S. G., and Wu, L. (1995). “Model for instantaneous residential water demands.” J. Hydraul. Eng., 232–246.
Creaco, E., Farmani, R., Kapelan, Z., Vamvakeridou-Lyroudia, L., and Savic, D. (2015). “Considering the mutual dependence of pulse duration and intensity in models for generating residential water demand.” J. Water Resour. Plann. Manage., 04015031.
Garcıa, V. J., Garcıa-Bartual, R., Cabrera, E., Arregui, F., and Garcıa-Serra, J. (2004). “Stochastic model to evaluate residential water demands.” J. Water Resour. Plann. Manage., 386–394.
Guercio, R., Magini, R., and Pallavicini, I. (2001). “Instantaneous residential water demand as stochastic point process.” Water resources management, C. A. Brebbia, P. Anagnostopoulos, K. L. Katsifarakis, and A. H.-D. Chengeds, WIT Press, Southampton, UK, 129–138.
Hall, A. R. (2004). “Generalized method of moments.” Advanced texts in econometrics, Oxford University Press, Oxford.
Iman, R. L., and Conover, W. J. (1982). “A distribution-free approach to inducing rank correlation among input variables.” Commun. Stat., 11(3), 311–334.
Johnson, R. A., and Bhattacharyya, G. K. (1992). Statistics: Principles and methods, 2nd Ed., Wiley, Hoboken, NJ.
Nelsen, R. B. (1999). An introduction to copulas, Springer, New York.
Press, W. H., Flannery, B. P., Teukolsky, S. A., and Vetterling, W. T. (1990). Numerical recipes: The art of scientific computing, Cambridge University Press, New York.
Walski, M., Chase, D., Savic, D., Grayman, W., Beckwith, S., and Koelle, E. (2003). Advanced water distribution modelling and management, Haestad Press, Waterbury, CT.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 142 • Issue 2 • February 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Jun 15, 2015
Accepted: Sep 1, 2015
Published online: Oct 15, 2015
Published in print: Feb 1, 2016
Discussion open until: Mar 15, 2016
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.