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Drinking Water Engineering and Science An interactive open-access journal

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Drink. Water Eng. Sci., 1, 27-38, 2008
https://doi.org/10.5194/dwes-1-27-2008
© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
25 Sep 2008
Importance of demand modelling in network water quality models: a review
E. J. M. Blokker1,2, J. H. G. Vreeburg1,2, S. G. Buchberger3, and J. C. van Dijk3 1Kiwa Water Research Groningenhaven 7, 3430 BB Nieuwegein, The Netherlands
2Delft University of Technology, Department of Civil Engineering and Geosciences, P.O. Box 5048, 2600 GA Delft, The Netherlands
3University of Cincinnati, Department of Civil and Environmental Engineering, P.O. Box 210071 Cincinnati, OH 45221-0071, USA
Abstract. Today, there is a growing interest in network water quality modelling. The water quality issues of interest relate to both dissolved and particulate substances. For dissolved substances the main interest is in residual chlorine and (microbiological) contaminant propagation; for particulate substances it is in sediment leading to discolouration. There is a strong influence of flows and velocities on transport, mixing, production and decay of these substances in the network. This imposes a different approach to demand modelling which is reviewed in this article.

For the large diameter lines that comprise the transport portion of a typical municipal pipe system, a skeletonised network model with a top-down approach of demand pattern allocation, a hydraulic time step of 1 h, and a pure advection-reaction water quality model will usually suffice. For the smaller diameter lines that comprise the distribution portion of a municipal pipe system, an all-pipes network model with a bottom-up approach of demand pattern allocation, a hydraulic time step of 1 min or less, and a water quality model that considers dispersion and transients may be needed.

Demand models that provide stochastic residential demands per individual home and on a one-second time scale are available. A stochastic demands based network water quality model needs to be developed and validated with field measurements. Such a model will be probabilistic in nature and will offer a new perspective for assessing water quality in the drinking water distribution system.


Citation: Blokker, E. J. M., Vreeburg, J. H. G., Buchberger, S. G., and van Dijk, J. C.: Importance of demand modelling in network water quality models: a review, Drink. Water Eng. Sci., 1, 27-38, https://doi.org/10.5194/dwes-1-27-2008, 2008.
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