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A Study on the Turbidity Estimation Model Using Data Mining Techniques in the Water Supply System
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 Title & Authors
A Study on the Turbidity Estimation Model Using Data Mining Techniques in the Water Supply System
Park, No-Suk; Kim, Soonho; Lee, Young Joo; Yoon, Sukmin;
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Turbidity is a key indicator to the user that the `Discolored Water` phenomenon known to be caused by corrosion of the pipeline in the water supply system. `Discolored Water` is defined as a state with a turbidity of the degree to which the user visually be able to recognize water. Therefore, this study used data mining techniques in order to estimate turbidity changes in water supply system. Decision tree analysis was applied in data mining techniques to develop estimation models for turbidity changes in the water supply system. The pH and residual chlorine dataset was used as variables of the turbidity estimation model. As a result, the case of applying both variables(pH and residual chlorine) were shown more reasonable estimation results than models only using each variable. However, the estimation model developed in this study were shown to have underestimated predictions for the peak observed values. To overcome this disadvantage, a high-pass filter method was introduced as a pretreatment of estimation model. Modified model using high-pass filter method showed more exactly predictions for the peak observed values as well as improved prediction performance than the conventional model.
Turbidity;Discolored Water;Data Mining Techniques;Decision Tree Analysis;
 Cited by
Hong, J., Mun, H., Yun, H., Yu, C. and Kang, B., "Sensitivity Analysis of Real-time Water Quality Index added Turbidity" Proceedings of the 2015 spring conference of KSWW and KSWQ, pp. 521-522(2015).

Shin, J., Jeong, S. and Hwang, S., "Long-term variation of water turbidity in a Korean river ecosystem (Youngsan River)" Proceedings of the 2005 spring conference of KSWW and KSWQ, pp. 711-714(2005).

Wetzel, R. G., Limnology: Lake and River Ecosystems, 3rd ed., Academic Press, California(2001).

Vreeburg, J. H. G., Discolouration in drinking water systems : the role of particles clarified, IWA Publishing(2010).

REWAB, "Registration system yearly analysis results of Dutch water companies, available through ministry of VROM (Netherlands Ministry of Housing, Spatial Planning and the Environment,"(Eds), Den Haag, The Netherlands

Ellison, D., Investigation of Pipe Cleaning Methods, AWWARF, Denver(2003).

Prince, R., Goulter, I. and Ryan, G., "Relationship Between Velocity Profiles And Turbidity Problems In Distribution Systems," World Water and Environmental Resources Congress, pp. 1-9(2001).

Slaats, N., Rosenthal, L. P. M., Siegers, W. G., Boomen, M. V. d., Beuken, R. H. S. and Vreeburg, J. H. G. Processes involved in the generation of discolored water, American Water Works Association Research Foundation / Kiwa, The Netherlands(2002).

Boxall, J. B., Skipworth, P. J. and Saul, A. J., "Aggressive flushing for discolouration event mitigation in water distribution networks," Water Sci. Technol. Water Supply, 3(1-2), 179-186(2003). crossref(new window)

Clement, J. A., Hayes, M., Kriven, W. M., Sarin, P., Bebee, J., Jim, K., Beckett, M., Snoeyink, V. L., Kirmeyer, G. J. and Pierson, G., Development of red water control strategies, American Water Works Association Research Foundation, Denver(2002).

Kirmeyer, G. J., Friedman, M., Clement, J., Sandvig, A., Noran, P. F., Martel, K. D., Smith, D., LeChevallier, M., Volk, C., Antoun, E., Hiltebrand, D., Dyksen, J. and Cushing, R., Guidance manual for maintaining distribution system water quality, AWWA Research Foundation and American Water Works Association, Denver(2000).

Lee, D., Kwan, B. and Ryu, S., "Filtration Performance Evaluation by Monitoring the Filtered Water Turbidity in Water Treatment Plant," Proceedings of the 2000 autumn conference of KSWW and KSWQ, pp. 115-118(2000).

U.S. EPA, Water Sentinel System Architecture Draft, Version 1.0(2005).

Janke, R., Murray, R. Uber, J. and Taxon, T., "Comparison of Physical Sampling and Real-Time Monitoring Strategies for Designing a Contamination Warning System in a Drinking Water Distribution System," J. Water Resour. Plann. and Manage., 132(4), 310-313(2006). crossref(new window)

U.S. EPAa, Water Security Initiative: System Evaluation of the Cincinnati Contamination Warning System Pilot, U.S EPA Water Security Division(2014).

U.S. EPAb, Water Security Initiative: Evaluation of the Water Quality Monitoring Component of the Cincinnati Contamination Warning System Pilot, U.S EPA Water Security Division(2014).

Park, N. S., Lee, Y., Chae, S. and Yoon, S., "A Study on the Statistical Predictability of Drinking Water Qualities for Contamination Warning System," J. Korean Soc. Water and Wastewater, 29(4), 469-479(2015). crossref(new window)

Park, N. S., Park, S., Kim, S. and Jeong, N., "Establishment of the Refined Model for Prediction of Flocculation/Sedimentation Efficiency Using Model Tree Technique," J. Korean Soc. Water and Wastewater., 20(6), 1-436(2006).