dbpRisk: Disinfection By-Product Risk Estimation

  • Marios Kyriakou
  • Demetrios G. EliadesEmail author
  • Marios M. Polycarpou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8985)


This work describes a new open-source software platform, the dbpRisk software, for conducting simulation experiments in order to model the formation for disinfection by-product in drinking water distribution networks under various conditions and uncertainties. The goal is to identify the risk-level at each node location, contributing in the enhancement of consumer safety. The use of the dbpRisk software is demonstrated using a real water distribution network model from the Nicosia water transport network.


Disinfection By-Products Simulation Risk evaluation EPANET 



This research work has been partially funded by the European Research Council (ERC) under the project ERC-2011-ADG-291508 “Fault-Adaptive Monitoring and Control of Complex Distributed Dynamical Systems”(FAULT-ADAPTIVE), and by the Cyprus Research Promotion Foundation through the Framework Programme for Research, Technological Development and Innovation 2009–10 (DESMI 2009–2010), co-funded by the Republic of Cyprus and the European Regional Development Fund, under the project “UrbanDBP”.


  1. 1.
    Adin, A., Katzhendler, J., Alkaslassy, D., Rav-Acha, C.: Trihalomethane formation in chlorinated drinking water: a kinetic model. Water Res. 25(7), 797–805 (1991)CrossRefGoogle Scholar
  2. 2.
    Ahn, J.C., Lee, S.W., Choi, K.Y., Koo, J.Y.: Application of EPANET for the determination of chlorine dose and prediction of THMs in a water distribution system. Sustain. Environ. Res. 22(1), 31–38 (2012)Google Scholar
  3. 3.
    Alperovits, E., Shamir, U.: Design of optimal water distribution systems. Water Resour. Res. 13(6), 885–900 (1977)CrossRefGoogle Scholar
  4. 4.
    Amy, G.L., Chadik, P.A., Chowdhury, Z.K.: Developing models for predicting trihalomethane formation potential and kinetics. J. Am. Water Works Assoc. 79(7), 89–97 (1987)Google Scholar
  5. 5.
    Arevalo, J.M.: Modeling free chlorine and chloramine decay in a pilot distribution system. ProQuest (2007)Google Scholar
  6. 6.
    Brown, D.: The management of Trihalomethanes in water supply systems preferred access arrangement. Ph.D. thesis, University of Birmingham (2009)Google Scholar
  7. 7.
    Chowdhury, S., Champagne, P., McLellan, P.J.: Models for predicting disinfection byproduct (DBP) formation in drinking waters: a chronological review. Sci. Total Environ. 407(14), 4189–4206 (2009)CrossRefGoogle Scholar
  8. 8.
    Clark, R.M., Sivaganesan, M.: Predicting chlorine residuals and formation of TTHMs in drinking water. J. Environ. Eng. 124(12), 1203–1210 (1998)CrossRefGoogle Scholar
  9. 9.
    Di Cristo, C., Esposito, G., Leopardi, A.: Modelling trihalomethanes formation in water supply systems. Environ. Technol. 34(1), 61–70 (2013)CrossRefGoogle Scholar
  10. 10.
    Elshorbagy, W.: Kinetics of THM species in finished drinking water. J. Water Resour. Plan. Manage. 126(1), 21–28 (2000)CrossRefGoogle Scholar
  11. 11.
    European Union. European Commission. Directorate-General for the Environment: Water is for Life: How the Water Framework Directive Helps Safeguard Europe’s Resources. Publications Office of the European Union (2010)Google Scholar
  12. 12.
    Geldreich, E.E.: Microbial Quality of Water Supply in Distribution Systems. CRC Press, Boca Raton (1996)Google Scholar
  13. 13.
    Harrington, G.W., Chowdhury, Z.K., Owen, D.M.: Developing a computer model to simulate DBP formation during water treatment. J. Am. Water Works Assoc. 84(11), 78–87 (1992)Google Scholar
  14. 14.
    Hsu, C.H., Jeng, W.L., Chang, R.M., Chien, L.C., Han, B.C.: Estimation of potential lifetime cancer risks for trihalomethanes from consuming chlorinated drinking water in Taiwan. Environ. Res. 85(2), 77–82 (2001)CrossRefGoogle Scholar
  15. 15.
    Hua, G., Yeats, S.: Control of trihalomethanes in wastewater treatment. Fla. Water Resour. J. 4, 6–12 (2010)Google Scholar
  16. 16.
    Jesperson, K.: Safe drinking water act reauthorized. National Drinking Water Clearinghouse (1996)Google Scholar
  17. 17.
    Kavanaugh, M.C., Trussell, A.R., Cromer, J., Trussell, R.R.: An empirical kinetic model of trihalomethane formation: applications to meet the proposed THM standard. J. Am. Water Works Assoc. 72(10), 578–582 (1980)Google Scholar
  18. 18.
    McDonnell, B.E.: Controlling disinfection by-products within a distribution system by implementing bubble aeration within storage tanks. Ph.D. thesis, University of Cincinnati (2012)Google Scholar
  19. 19.
    Nikolaou, A.D., Golfinopoulos, S.K., Arhonditsis, G.B., Kolovoyiannis, V., Lekkas, T.D.: Modeling the formation of chlorination by-products in river waters with different quality. Chemosphere 55(3), 409–420 (2004)CrossRefGoogle Scholar
  20. 20.
    Omar, N.A.J.: The Effects of Pipe Material and Age on the Formation of Disinfection By–Products (DBP) In Nablus Water Network. Ph.D. thesis, National University (2010)Google Scholar
  21. 21.
    Polycarpou, M.M., Uber, J.G., Wang, Z., Shang, F., Brdys, M.: Feedback control of water quality. IEEE Control Syst. 22(3), 68–87 (2002)CrossRefGoogle Scholar
  22. 22.
    Richardson, S.D., Postigo, C.: Drinking water disinfection by-products. In: Emerging Organic Contaminants and Human Health, pp. 93–137. Springer (2012)Google Scholar
  23. 23.
    Rook, J.J.: Formation of haloforms during chlorination of natural waters. Water Treat. Exam. 23, 234–243 (1974)Google Scholar
  24. 24.
    Rossman, L.A.: Epanet 2: users manual. US Environmental Protection Agency, Cincinnati, OH, USA (2000)Google Scholar
  25. 25.
    Sadiq, R., Rodriguez, M.J.: Disinfection by-products (DBPs) in drinking water and predictive models for their occurrence: a review. Sci. Total Environ. 321(1), 21–46 (2004)CrossRefGoogle Scholar
  26. 26.
    Shang, F., Uber, J.G., Rossman, L.: Epanet multi-species extension users manual. National Risk Management Research Laboratory, Office of Research and Development, US Enviromental Protection Agency, Cincinnati, OH 45268 (2007)Google Scholar
  27. 27.
    Speight, V.: Probabilistic Modeling Framework for Assessing Water Quality Sampling Programs. Water Research Foundation (2009)Google Scholar
  28. 28.
    Valenti, C.C.: Modeling Disinfection By-product Formation in Distribution Systems and Consecutive Systems by Hold Studies and Bench Studies with an Investigation of Alternative Disinfection Practices. ProQuest (2008)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Marios Kyriakou
    • 1
  • Demetrios G. Eliades
    • 1
    Email author
  • Marios M. Polycarpou
    • 1
  1. 1.KIOS Research Center for Intelligent Systems and NetworksUniversity of CyprusNicosiaCyprus

Personalised recommendations