Drinking Water Engineering and Science Discussions www.drink-water-eng-sci-discuss.net 1996-9473 1996-9481 3 1 2010 10.5194/dwesd-3-1-2010 http://www.drink-water-eng-sci-discuss.net/3/1/2010/ http://www.drink-water-eng-sci-discuss.net/3/1/2010/dwesd-3-1-2010.html http://www.drink-water-eng-sci-discuss.net/3/1/2010/dwesd-3-1-2010.pdf 1 24 2010-01-04 A bottom-up approach of stochastic demand allocation in water quality modelling E. J. M. Blokker mirjam.blokker@kwrwater.nl J. H. G. Vreeburg H. Beverloo M. Klein Arfman J. C. van Dijk KWR Watercycle Research Institute, 3430 BB Nieuwegein, The Netherlands Delft University of Technology, Department of Civil Engineering and Geosciences, 2600 GA Delft, The Netherlands PWN Water Supply Company North-Holland, 1990 AC, Velserbroek, The Netherlands An "all pipes" hydraulic model of a DMA-sized drinking water distribution system was constructed with two types of demand allocations. One is constructed with the conventional top-down approach, i.e. a demand multiplier pattern from the booster station is allocated to all demand nodes with a correction factor to account for the average water demand on that node. The other is constructed with a bottom-up approach of demand allocation, i.e., each individual home is represented by one demand node with its own stochastic water demand pattern. <br><br> The stochastic water demand patterns are constructed with an end-use model on a per second basis and per individual home. The flow entering the test area was measured and a tracer test with sodium chloride was performed to measure travel times. The two models were evaluated on the predicted sum of demands and travel times, compared with what was measured in the test area. <br><br> The new bottom-up approach performs at least as well as the conventional top-down approach with respect to total demand and travel times, without the need for any flow measurements or calibration measurements. The bottom-up approach leads to a stochastic method of hydraulic modelling and gives insight into the variability of travel times as an added feature beyond the conventional way of modelling. 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, 2008. Blokker, E. J. M. and Beverloo, H.: Travel times distribution network Zandvoort, Measurements boulevard Zandvoort summer 2008, KWR, Nieuwegein, 2009 (in Dutch). Blokker, E. J. M., Vreeburg, J. H. G., and van Dijk, J. C.: Simulating residential water demand with a stochastic end-use model, J. Water Res. Pl.-ASCE, 136(1), 19–26, doi:10.1061/(ASCE)WR.1943-5452.0000002, 2009. http://statline.cbs.nl, last access: June 2008. Powell, J., Clement, J., Brandt, M., R, C., Holt, D., Grayman, W., and LeChevallier, M.: Predictive Models for Water Quality in Distribution Systems, AWWARF, Denver, Colorado, USA, 2004. Rossman, L. A.: EPANET 2 user manual, United States Environmental Protection Agency, Cincinnati, 2000. Skipworth, P. J., Machell, J., and Saul, A. J.: Empirical travel time estimation in a distribution network, Water & Maritime Engineering, 154, 41–49, 2002. Slaats, P. G. G., Rosenthal, L. P. M., Siegers, W. G., van den Boomen, M., Beuken, R. H. S., and Vreeburg, J. H. G.: Processes involved in the generation of discolored water, AWWARF, Denver, Co, USA, 2003. Vreeburg, J. H. G.: Discolouration in drinking water systems: a particular approach, 183~pp., 2007. Vreeburg, J. H. G. and Boxall, J. B.: Discolouration in potable water distribution systems, a review, Water Res., 41, 519–529, 2007.