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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

Postal Subscription Code 80-973

2018 Impact Factor: 3.883

Front Envir Sci Eng    2012, Vol. 6 Issue (2) : 204-212    https://doi.org/10.1007/s11783-011-0364-9
RESEARCH ARTICLE
Optimal locations of monitoring stations in water distribution systems under multiple demand patterns: a flaw of demand coverage method and modification
Shuming LIU1(), Wenjun LIU1, Jinduan CHEN2, Qi WANG3
1. School of Environment, Tsinghua University, Beijing 100084, China; 2. School of Energy, Environmental, Biological and Medical Engineering, University of Cincinnati, Cincinnati, OH 45221-0077, USA; 3. Centre for Water Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, EX4 4QF, UK
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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     
Corresponding Author(s): LIU Shuming,Email:shumingliu@tsinghua.edu.cn   
Issue Date: 01 April 2012
 Cite this article:   
Shuming LIU,Jinduan CHEN,Qi WANG, et al. Optimal locations of monitoring stations in water distribution systems under multiple demand patterns: a flaw of demand coverage method and modification[J]. Front Envir Sci Eng, 2012, 6(2): 204-212.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-011-0364-9
https://academic.hep.com.cn/fese/EN/Y2012/V6/I2/204
Fig.1  The example network 1
monitoringdemand covered under 50% coverage criterion
at nodenode 1node 2node 3node 4node 5node 6node 7total
100000000
200000000
30015000015
400153000045
5001530250070
600000201030
70000001010
Tab.1  Demand coverage matrix for example network under demand pattern 1, unit water
patternsnodes
1234567
1003153,4453,4,5706,730710
6615415,30215,30,25120,103105
2003124,5453,5406,72378
6612425,20120,20215,8385
3003154,5453,535615710
6615325,20115, 202153105
4003204,5503,5406,725710
6620430,20120, 20215,103105
sum0/24(4.7)0/24(4.8)62/15(3)185/5(1)185/7(1.4)93/12(2.4)38/20(4)
Tab.2  Demand coverage matrix for example network 1 under demand patterns 1-4
Fig.2  
GA parametersdescription
chromosomeinteger, size: number of monitoring stations required (1-7 monitoring stations in this paper)
selectorroulette
elitismthe best solution in each generation is preserved in the next generation
crossover rate0.95
mutation rate0.05
number of generations50
number of stall generation20
population size100
Tab.3  GA parameters used
Fig.3  EPANET example network 2
Fig.4  The two demand pattern sets used in this study
patternsnode identifications (IDs)
10182122293233
2065.766.65455.552.578.0753.65
1210171620518
2199.43100.881.88479.5170.881.2
1514201923121
22119147.497.8101177204.397.15
171522214123
23111.9141.1117115166172116.5
23920225221
2486.12132.990.288.3128108.289.73
241192321721
TDC2555232620732049205028672084
ADCR202(1.5)251(1.8)318(2.3)342(2.5)398(2.9)137(1)329(2.4)
DCI1732.81269.6893.1820.8705.72867867.8
Tab.4  Demand coverage matrix for example network 2 under demand pattern set 1
Fig.5  
No. of MSthe DC methodthe DCI method
optimal locationsCR1CR2optimal locationsCR3
1320.35940.3594320.3594
210,320.54810.548110,320.5481
310,30,320.69170.691710,30,320.6917
410,21,30,320.78710.787110,21,30,320.7871
54,10,18,21,300.90890.852010,18,19,21,300.8780
64,10,21,30,32,330.95830.91174,10, 18,19,21,300.9311
74,10,21,30,32,34,360.98170.93894,10, 18,19,21,28,300.9622
Tab.5  Outputs of the DC method and the DCI method for demand pattern set 1
no. of MSthe DC methodthe DCI method
optimal locationsCR1CR2optimal locationsCR2
1320.35940.3176320.3526
210,320.54810.503210,320.5498
310,30,320.69170.657710,30,320.6926
410,21,30,320.78710.733010,18,19,300.7623
54,10,18,21,300.90890.810710,18,19,30,330.8760
64,10,21,30,32,330.95830.86284,10, 18,19,30,330.9236
74,10,21,30,32,34,360.98170.90194,10, 18,19,21,30,330.9546
Tab.6  Outputs of the DC method and the DCI method for demand pattern set 2
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
doi: 10.1061/(ASCE)0733-9496(2002)128:2(152)
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
doi: 10.1061/(ASCE)0733-9496(2006)132:4(293)
3 Burrows W D, Renner S E. Biological warfare agents as threats to potable water. Environmental Health Perspectives , 1999, 107(12): 975–984
doi: 10.1289/ehp.99107975 pmid:10585901
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
doi: 10.1061/(ASCE)0733-9496(2005)131:5(402)
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
doi: 10.1080/10286600600789359
7 Preis A, Ostfeld A. Genetic algorithm for contaminant source characterization using imperfect sensors. Civil Engineering and Environmental Systems , 2008, 25(1): 29–39
doi: 10.1080/10286600701695471
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
doi: 10.1061/(ASCE)0733-9372(1992)118:1(4)
9 Boulos P, Altman T. Explicit calculation of water quality parameters in pipe distribution systems. Civil Engineering Systems , 1993, 10(3): 187–206
doi: 10.1080/02630259308970123
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
doi: 10.1061/(ASCE)0733-9372(1997)123:8(746)
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
doi: 10.1016/S1364-8152(98)00089-9
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
doi: 10.1061/(ASCE)0733-9496(2002)128:2(130)
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
doi: 10.1061/(ASCE)0733-9496(2008)134:4(366)
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
doi: 10.1016/j.scitotenv.2006.12.042 pmid:17276493
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