Optimal locations of monitoring stations in water distribution systems under multiple demand patterns: a flaw of demand coverage method and modification

Abstract

A flaw of demand coverage method in solving optimal monitoring stations problem under multiple demand patterns was identified in this paper. In the demand coverage method, the demand coverage of each set of monitoring stations is calculated by accumulating their demand coverage under each demand pattern, and the impact of temporal distribution between different time periods or demand patterns is ignored. This could lead to miscalculation of the optimal locations of the monitoring stations. To overcome this flaw, this paper presents a Demand Coverage Index (DCI) based method. The optimization considers extended period unsteady hydraulics due to the change of nodal demands with time. The method is cast in a genetic algorithm framework for integration with Environmental Protection Agency Net (EPANET) and is demonstrated through example applications. Results show that the set of optimal locations of monitoring stations obtained using the DCI method can represent the water quality of water distribution systems under multiple demand patterns better than the one obtained using previous methods.

Keywords

demand coverage / monitoring / optimization / water distribution network / water quality

References

[1] Clark R M, Sivaganesan M. Predicting chlorine residuals in drinking water: second order model. Journal of Water Resources Planning and Management, 2002, 128(2): 152–161

[2] Murray R, Uber J, Janke R. Model for estimating acute health impacts from consumption of contaminated drinking water. Journal of Water Resources Planning and Management, 2006, 132(4): 293–299

[3] Burrows W D, Renner S E. Biological warfare agents as threats to potable water. Environmental Health Perspectives, 1999, 107(12): 975–984

[4] Ministry of Housing and Urban-Rural Development, China. Regulation on Drinking Water Quality, 2006 (in Chinese)

[5] Ostfeld A, Salomons E. Securing water distribution systems using online contamination monitoring. Journal of Water Resources Planning and Management, 2005, 131(5): 402–405

[6] Cozzolino L, Mucherino C, Pianese D, Pirozzi F. Positioning, within water distribution networks, of monitoring stations aiming at an early detection of intentional contamination. Civil Engineering and Environmental Systems, 2006, 23(3): 161–174

[7] Preis A, Ostfeld A. Genetic algorithm for contaminant source characterization using imperfect sensors. Civil Engineering and Environmental Systems, 2008, 25(1): 29–39

[8] Lee B H, Deininger R A. Optimal locations of monitoring stations in water distributions system. Journal of Environmental Engineering-ASCE, 1992, 118(1): 4–16

[9] Boulos P, Altman T. Explicit calculation of water quality parameters in pipe distribution systems. Civil Engineering Systems, 1993, 10(3): 187–206

[10] Kumar A, Kansal M L, Arora G. Identification of monitoring stations in water distribution system. Journal of Environmental Engineering–ASCE, 1997, 123(8): 746–752

[11] Al-Zahrani M A, Moied K. Locating optimum water quality monitoring stations in water distribution system, in Bridging the Gap: Meeting the World’s Water and Environmental Resources Challenges. In: Proceedings of the ASCE annual conference on Water Resources Planning and Management. Virginia: Reston, 2001

[12] Tryby M E, Uber J G. Representative water quality sampling in water distribution systems, in Bridging the Gap: Meeting the World’s Water and Environmental Resources Challenges. In Proceedings of the ASCE annual conference on Water Resources Planning and Management, Virginia: Reston, 2001

[13] Harmant P, Nace A, Kiene L, Fotoohi F. Optimal supervision of drinking water distribution network, in 99—preparing for the 21st Century. In Proceedings of the ASCE annual conference on Water Resources Planning and Management. Virginia: Reston, 1999

[14] Woo H M, Yoon J H, Choi D Y. Optimal monitoring sites based on water quality and quantity in water distribution systems, in Bridging the Gap: Meeting the World’s Water and Environmental Resources Challenges. In: Proceedings of the ASCE annual conference on Water Resources Planning and Management, Virginia: Reston, 2001

[15] Environmental Protection Agency, EPANET 2.0 User Manual, 2000

[16] Goldberg D E. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley: New York, 1989

[17] Gupta I, Gupta A, Khanna A. Genetic algorithm for optimization of water distribution systems. Environmental Modelling & Software, 1999, 14(5): 437–446

[18] Mallick K A, Ahmed I, Tickle K S, Lansey K E. Determining pipe groupings for water distribution networks. Journal of Water Resources Planning and Management, 2002, 128(2): 130–139

[19] Preis A, Ostfeld A. Multiobjective contaminant sensor network design for water distribution systems. Journal of Water Resources Planning and Management, 2008, 134(4): 366–377

[20] Liu S, Butler D, Brazier R, Heathwaite L, Khu S T. Using genetic algorithms to calibrate a water quality model. Science of the Total Environment, 2007, 374(2-3): 260–272