Toward Digital Twins for Emerging Contaminants in Water Distribution Systems
Publication: World Environmental and Water Resources Congress 2023
ABSTRACT
Emerging contaminants (ECs) are natural or manufactured chemical compounds that are hard to remove through water treatment; hence, they accumulate in the environment. Such contaminants have already been detected in wastewater, aquatic environments, and water distribution systems (WDSs). Consequently, researchers are developing sensors tailored explicitly to new contaminants. By combining those new sensors with real-time simulation models, digital twins are within reach to assess system-wide water quality. In the future, such twins will build the cornerstone for early warning or real-time control systems concerning these new pollutants. However, realistic simulation tools competent enough to create such digital twins are lacking, mainly because of two reasons: (1) hydraulic models are unable to account for the spatiotemporal dynamics of customer demand, and (2) water quality models are not equipped to simulate the fate and transport of ECs. Our work aims to close this gap by proposing a novel way to model water quality that combines realistic water demand models (i.e., by using the stochastic water demand end-use model, pySIMDEUM), hydraulic solvers (i.e., using the object-oriented Python NETwork analysis tool, OOPNET), and water quality solvers (i.e., using EPyT-C). Extending the state-of-the-art for hydraulic and water quality modeling by incorporating the water demand stochasticity and the uncertainties associated with the imperfect understanding of the formation and transmission of ECs in WDSs is expected to advance the digital twins technology for detecting ECs’ formation and evaluating health-related exposure risks in WDSs.
Get full access to this article
View all available purchase options and get full access to this chapter.
REFERENCES
Abhijith, G. R., and Mohan, S. (2020). “Random Walk Particle Tracking embedded Cellular Automata model for predicting temporospatial variations of chlorine in water distribution systems.” Environmental Processes, 7(1), 271–296.
Abhijith, G. R., and Ostfeld, A. (2021a). “Modeling the Response of Nonchlorinated, Chlorinated, and Chloraminated Water Distribution Systems toward Arsenic Contamination.” Journal of Environmental Engineering, 147(10), 04021045.
Abhijith, G. R., and Ostfeld, A. (2021b). “Model-based investigation of the formation, transmission, and health risk of perfluorooctanoic acid, a member of PFASs group, in drinking water distribution systems.” Water Research, Elsevier Ltd, 204(August), 117626.
Abhijith, G. R., and Ostfeld, A. (2021c). “Modeling the Formation and Propagation of 2,4,6-trichloroanisole, a Dominant Taste and Odor Compound, in Water Distribution Systems.” Water, 13(5), 638.
Abhijith, G. R., and Ostfeld, A. (2022a). “Flexible decision-making framework for developing operation protocol for water distribution systems.” Journal of Environmental Management, Elsevier Ltd, 320, 115817.
Abhijith, G. R., and Ostfeld, A. (2022b). “Making Waves : Applying Systems Biology Principles in Water Distribution Systems.” Water Research, Elsevier Ltd, 118527.
Abhijith, G. R., and Ostfeld, A. (2022c). “Examining the Longitudinal Dispersion of Solutes Inside Water Distribution Systems.” Journal of Water Resources Planning and Management, 148(6), 04022022.
Abhijith, G. R., and Ostfeld, A. (2022d). “Contaminant Fate and Transport Modeling in Distribution Systems: EPANET-C.” Water (Switzerland), 14(10), 1665.
Abokifa, A. A. (2018). Developing Multi-Scale Models for Water Quality Management in Drinking Water Distribution Systems. Washington University in St. Louis.
Abokifa, A. A., Yang, Y. J., Lo, C. S., and Biswas, P. (2016a). “Investigating the role of biofilms in trihalomethane formation in water distribution systems with a multicomponent model.” Water Res., Elsevier Ltd, 104, 208–219.
Abokifa, A. A., Yang, Y. J., Lo, C. S., and Biswas, P. (2016b). “Water quality modeling in the dead end sections of drinking water distribution networks.” Water Research, Elsevier Ltd, 89, 107–117.
Aldama, A. A., Tzatchkov, V. G., and Arreguin, F. I. (1998). “The numerical Green’s function technique for boundary value problems in networks.” Transactions on Ecology and the Environment, 26, 121–130.
Alzamora, F. M., Conejos, P., Castro-Gama, M., and Vertommen, I. (2021). Digital Twins - A new paradigm for water supply and distribution networks. Association for Hydro-Environment Engineering, International hydrolink.
Blokker, E. J. M., Vreeburg, J. H. G., Buchberger, S. G., and Van Dijk, J. C. (2008). “Importance of demand modelling in network water quality models: A review.” Drinking Water Engineering and Science, 1(1), 27–38.
Blokker, E. J. M., Vreeburg, J. H. G., and van Dijk, J. C. (2010). “Simulating Residential Water Demand with a Stochastic End-Use Model.” Journal of Water Resources Planning and Management, 136(1), 19–26.
Boyce, S. D., and Hornlg, J. F. (1983). “Reaction Pathways of Trihalomethane Formation from the Halogenation of Dihydroxyaromatic Model Compounds for Humic Acid.” Environmental Science and Technology, 17(4), 202–211.
Central Bureau of Statistics. (2022). “The 2008 Census of Population.” Population Census by Government of Israel, <https://www.cbs.gov.il/en/subjects/Pages/The-2008-Census-of-Population.aspx>(Oct. 6, 2022).
González Perea, R., Camacho Poyato, E., Montesinos, P., and Rodríguez Díaz, J. A. (2019). “Optimisation of water demand forecasting by artificial intelligence with short data sets.” Biosystems Engineering, 177, 59–66.
Khan, S., Naushad, M., Govarthanan, M., Iqbal, J., and Alfadul, S. M. (2022). “Emerging contaminants of high concern for the environment: Current trends and future research.” Environmental Research, Elsevier Inc., 207(December 2021), 112609.
Kudlek, E. (2020). “Transformation of Contaminants of Emerging Concern (CECs) during UV-Catalyzed Processes Assisted by Chlorine.” Catalysts, 10, 1432.
Lei, M., Zhang, L., Lei, J., Zong, L., Li, J., Wu, Z., and Wang, Z. (2015). “Overview of emerging contaminants and associated human health effects.” BioMed Research International, Hindawi Publishing Corporation, 2015, 404796.
Mäki-Arvela, P., Salmi, T., and Paatero, E. (1994). “Kinetics of the Chlorination of Acetic Acid with Chlorine in the Presence of Chlorosulfonic Acid and Thionyl Chloride.” Industrial and Engineering Chemistry Research, 33(9), 2073–2083.
Ohar, Z., Ostfeld, A., Lahav, O., and Birnhack, L. (2015). “Modelling heavy metal contamination events in water distribution systems.” Procedia Engineering, 119(1), 328–336.
Rossman, L. A. (2000). EPANET 2: users manual. Natl. Risk Manag. Res. Lab. US Environ. Prot. Agency, Cincinatti, Washington, DC.
Rossman, L. A., Woo, H., Tryby, M., Shang, F., Janke, R., and Haxton, T. (2020). Epanet 2.2 User ’s Manual. USEPA, Cincinnati, Ohio.
Selak, A., Reberski, J. L., Klobučar, G., and Grčić, I. (2022). “Ecotoxicological aspects related to the occurrence of emerging contaminants in the Dinaric karst aquifer of Jadro and Žrnovnica springs.” Science of the Total Environment, 825.
State of Israel Ministry of Health. (2022). “Growth Charts.” Health Matters, <https://www.health.gov.il/English/Topics/KidsAndMatures/Pages/curves.aspx>(Oct. 6, 2022).
Steffelbauer, D. B., Hillebrand, B., and Blokker, E. J. M. (2022). “pySIMDEUM – An open-source stochastic water demand end-use model in Python.” n the Proceedings of the 2nd International Joint Conference on Water Distribution Systems Analysis & Computing and Control in the Water Industry, Valencia, Spain, 18-22 July 2022, Valencia, Spain.
Steffelbauer, D., and Fuchs-Hanusch, D. (2015). “OOPNET: An object-oriented EPANET in Python.” Procedia Engineering, Elsevier B.V., 119(1), 710–718.
Tzatchkov, V. G., Aldama, A. A., and Arreguin, F. I. (2002). “Advection-Dispersion-Reaction Modeling in Water Distribution Networks.” Journal of Water Resources Planning and Management, 128(5), 334–342.
USEPA. (2010). Comprehensive Disinfectants and Disinfection Byproducts Rules (Stage 1 and Stage 2): Quick Reference Guide Overview of the Rules.
USEPA. (2016). Drinking water health advisory for perfluorooctanoic acid (PFOA). Washington, DC.
USEPA. (2019). “Chapter 3-Ingestion of Water and Other Select Liquids.” Exposure Factors Handbook, Washington, DC, 1–157.
WHO (World Helath Organization). (2017). Guidelines for Drinking-water Quality - Fourth Edition incorporating the First Addendum. (World Helath Organization, ed.), Geneva.
Xiao, F., Hanson, R. A., Golovko, S. A., Golovko, M. Y., and Arnold, W. A. (2018). “PFOA and PFOS Are Generated from Zwitterionic and Cationic Precursor Compounds during Water Disinfection with Chlorine or Ozone.” Environmental Science and Technology Letters, 5(6), 382–388.
Information & Authors
Information
Published In
History
Published online: May 18, 2023
ASCE Technical Topics:
- Business management
- Decision making
- Decision support systems
- Engineering fundamentals
- Environmental engineering
- Hydraulic models
- Models (by type)
- Pollutants
- Practice and Profession
- Simulation models
- Water and water resources
- Water demand
- Water management
- Water quality
- Water supply
- Water supply systems
- Water treatment
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.