Optimal Location Placement of Quality Sensors in Water Distribution Networks by Considering Uncertainty of Parameters

Document Type : Original Article

Authors

1 Department of Hydraulic Engineering and Hydro-Environment, Water Research Institute, Tehran, Iran.

2 Faculty of Engineering,Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran

3 Associate Professor, Faculty of Engineering, Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran.

4 Department of Hydraulic Engineering and Hydro-Environment, Water Research Institute, Tehran, Iran

Abstract

Pollution entrance into water distribution networks can cause irreparable damage to human health. Installing quality sensors in water networks is one of the most effective quality management strategies. In this research, the optimization-simulation approach is used to determine the optimal locations of quality sensors considering the uncertainty of the effective parameters. EPANET software as a simulator and multi-objective genetic and gray wolf algorithms as an optimizer are employed. Two goals including the number of sensors and the maximum possible damage are minimized. To achieve the more realistic answers, the contaminant injection node and injection time are considered indefinitely. Six different scenarios are considered for injection duration time, injection mass rate. Also, ±20% variation for the uncertainty of the demands, and ±6% for the roughness coefficient are applied. Results demonstrate that the optimal location of quality sensors could greatly reduce the damage caused by the entry of pollutants accidentally or intentionally. Only one sensor installation leads to a reduction of the maximum damage in each of the six scenarios by 42.5, 58.5, 53.96, 44.94, 53.53, and 59 percent, respectively. Also, by increasing the number of sensors up to 20, the maximum damage is reduced to 99%. Moreover, optimal locations of the sensors are different based on different scenarios; however, some network nodes were common in different scenarios and had the most repetition of the optimal locations.

Keywords

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References

  1. تابش، م. 1397. مدل‌سازی پیشرفته شبکه‌های توزیع آب. چاپ چهارم. دانشگاه تهران.

     حریف، س.، غ. عزیزیان، م. گیوه‌چی و م. دهقانی درمیان. 1401. تحلیل و ارزیابی ابزارهای مدیریت کیفی در شبکه های های توزیع آب در مقابل ورود آلودگی در شبکه آب شرب شهر زاهدان. نشریه علمی پژوهشی مهندسی آبیاری و آب ایران. دوره 12. شماره 3. ص 453-437

    حریف، س.، غ. عزیزیان، م. گیوه‌چی و م. دهقانی درمیان. 1399. بررسی کارایی جریان رقیق‌ساز، زمان ماند و خروج آب آلوده در مدیریت کیفی شبکۀ توزیع آب پس از وقوع آلودگی (مطالعۀ موردی: شبکۀ آب شرب شهر زاهدان). نشریه اکوهیدرولوژی. دوره 7. شماره 4. ص 1045-1033

    حریف، س.، غ. عزیزیان، م. گیوه‌چی و م. دهقانی درمیان. 1400. جانمایی بهینه سنسورها در شبکه توزیع آب با هدف شناسایی مشخصات منبع آلاینده در حداقل زمان تشخیص. نشریه آبیاری و زهکشی ایران. دوره 15. شماره 2. ص 356-342

     دهقانی درمیان، م.، غ. عزیزیان و س. آ. هاشمی منفرد. 1398.  تحلیل و محاسبه ابزارهای موردنیاز برای حفاظت کیفی آب بمنظور کمینه کردن مخاطرات وارده به محیط‌زیست. نشریه مخاطرات طبیعی. دوره 8. شماره 22. ص 144-123

    هاشمی منفرد، س، آ.، م. دهقانی درمیان، ب. پیرزاده و م. اژدری مقدم. 1395. پیش بینی کیفیت آب در جریان های یک بعدی به کمک تابع انتقال آلودگی جدید و اصلاح معیار همگرایی. مجله پژوهش‌های حفاظت آب و خاک. دوره 23. شماره 2. ص 162-147

    Al-Zahrani, M., and K. Moeid. 2001. Locating optimum water quality monitoring stations in water distribution system. Pages 1-9 in Bridging the Gap: Meeting the World's Water and Environmental Resources Challenges.

    Basupi, I. 2013. Adaptive water distribution system design under future uncertainty.

    Comboul, M., and R. Ghanem. 2013. Value of information in the design of resilient water distribution sensor networks. Journal of Water Resources Planning and Management 139:449-455.

    Corso, P. S., M. H. Kramer, K. A. Blair, D. G. Addiss, J. P. Davis, and A. C. Haddix. 2003. Costs of illness in the 1993 waterborne Cryptosporidium outbreak, Milwaukee, Wisconsin. Emerging infectious diseases 9:426.

     Darmian, M. D., S. A. H. Monfared, G. Azizyan, S. A. Snyder, and J. P. Giesy. 2018. Assessment of tools for protection of quality of water: uncontrollable discharges of pollutants. Ecotoxicology and environmental safety 161:190-197.

    De Winter, C., V. R. Palleti, D. Worm, and R. Kooij. 2019. Optimal placement of imperfect water quality sensors in water distribution networks. Computers & Chemical Engineering 121:200-211.

    Dehghani Darmian, M., F. Khodabandeh, G. Azizyan, J. P. Giesy, and S. A. Hashemi Monfared. 2020. Analysis of assimilation capacity for conservation of water quality: controllable discharges of pollutants. Arabian Journal of Geosciences 13:1-13.

    Hashemi Monfared, S. A., M. Dehghani Darmian, S. A. Snyder, G. Azizyan, B. Pirzadeh, and M. Azhdary Moghaddam. 2017. Water quality planning in rivers: assimilative capacity and dilution flow. Bulletin of environmental contamination and toxicology 99:531-541.

    Hu, C., G. Ren, C. Liu, M. Li, and W. Jie. 2017. A Spark-based genetic algorithm for sensor placement in large scale drinking water distribution systems. Cluster Computing 20:1089-1099.

    Kessler, A., A. Ostfeld, and G. Sinai. 1998. Detecting accidental contaminations in municipal water networks. Journal of Water Resources Planning and Management 124:192-198.

    Khorshidi, M. S., M. R. Nikoo, E. Ebrahimi, and M. Sadegh. 2019. A robust decision support leader-follower framework for design of contamination warning system in water distribution network. Journal of Cleaner Production 214:666-673.

    Lee, B. H., and R. A. Deininger. 1992. Optimal locations of monitoring stations in water distribution system. Journal of Environmental Engineering 118:4-16.

    Mirjalili, S., S. M. Mirjalili, and A. Lewis. 2014. Grey wolf optimizer. Advances in engineering software 69:46-61.

    Muro, C., R. Escobedo, L. Spector, and R. Coppinger. 2011. Wolf-pack (Canis lupus) hunting strategies emerge from simple rules in computational simulations. Behavioural processes 88:192-197.

    Nazempour, R., M. A. S. Monfared, and E. Zio. 2018. A complex network theory approach for optimizing contamination warning sensor location in water distribution networks. International Journal of Disaster Risk Reduction 30:225-234.

    Organization, W.H. 2017.

    1. Ostfeld, A., J. G. Uber, E. Salomons, J. W. Berry, W. E. Hart, C. A. Phillips, J.-P. Watson, G. Dorini, P. Jonkergouw, and Z. Kapelan. 2008. The battle of the water sensor networks (BWSN): A design challenge for engineers and algorithms. Journal of Water Resources Planning and Management 134:556-568.

    Qiu, M., E. Salomons, and A. Ostfeld. 2020. A framework for real-time disinfection plan assembling for a contamination event in water distribution systems. Water research 174:115625.

    Rathi, S., and R. Gupta. 2016. A simple sensor placement approach for regular monitoring and contamination detection in water distribution networks. KSCE Journal of Civil Engineering 20:597-608.

    1. Rossman, L. A. 2000. EPANET 2: user’s manual.

    Salomons, E., and A. Ostfeld. 2016. Slug feed optimal disinfection of water distribution networks following a contamination event. Pages 516-522 in World Environmental and Water Resources Congress 2016.

    Srinivas, N., and K. Deb. 1994. Muiltiobjective optimization using nondominated sorting in genetic algorithms. Evolutionary computation 2:221-248.

    Toolbox, R. P. 2003. Planning for and Responding to Drinking Water Contamination Threats and Incidents. USEPA: Washington, DC, USA.

    UNICEF, WHO. 2009. Diarrhea: Why children are still dying and what can be done. New York/Geneva: UNICEF and WHO, 1995

Irrigation and Water Engineering
Volume 13, Issue 13
August 2023
Pages 211-228

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