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Determination of key sensor locations for non-point pollutant sources management in sewer network


As the importance of watershed management has emerged for water systems, non-point pollutant sources have been blamed as the main problem of water pollution. To control non-point pollutant sources, it is necessary to monitor sewers connected to the watershed and to analyze their effects on the sewer network. As the cost to monitor a sewer network depends on the number of sensors installed, the monitoring stations should be decided with proper guide of the installation location rule. In present paper, a new method to select the proper sensor location is proposed by combining monitoring information with data mining techniques. To estimate the amount of pollutants by wash-off and to find the sensor locations in a sewer network, three scenarios are considered based on rainfall intensity, influent concentrations and flow rate. The optimal locations of the sensor were selected based on the proposed method to facilitate the management of non-point pollutant source in sewer network. The presented approach can be extended to a complex sewer network system to design a minimum number of sensors and optimum locations for the sensors.

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  1. 1.

    C. Santhi, R. Srinivasan, J.G. Arnold and J.R. Williams, Env. Model. Soft., 21, 1141 (2006).

    Article  Google Scholar 

  2. 2.

    V. A. Tsihrintzis and R. Hamid, Water Res. Manage., 11, 137 (1997).

    Google Scholar 

  3. 3.

    T.Y. Berger-Wolf, W. E. Hart and J. Saia, Math. Comput. Model., 42(13), 1385 (2005).

    Article  Google Scholar 

  4. 4.

    Y. J. Yang, R. C. Haught and J. A. Goodrich, J. Environ. Manage., 90, 2494 (2009).

    Article  CAS  Google Scholar 

  5. 5.

    A. Aisopou, I. Stoianov and N. J. D. Graham, Water Res., 46, 235 (2012).

    Article  CAS  Google Scholar 

  6. 6.

    M. Kim, J.H. Kim, H. Park, Y. S. Sun, H. Kim, K. Choi and J. Yi, Korean J. Chem. Eng., 24(5), 763 (2007).

    Article  CAS  Google Scholar 

  7. 7.

    G. Choi, J. Lee, J. Yu, D. Ju and J. Park, Korean J. Chem. Eng., 28(5), 1207 (2011).

    Article  CAS  Google Scholar 

  8. 8.

    A. Ostfeld, J.G. Uber, E. Salomons, J.W. Berry, W. E. Hart, C. A. Phillips, J. P. Watson, G. Dorini, P. Jonkergouw, Z. Kapelan, F. Pierro, S. Khu, D. Savic, D. Eliades, M. Polycarpou, S. R. Ghimire, B. D. Barkdoll, R. Gueli, J. J. Huang, E. A. McBean, W. James, A. Krause, J. Leskovec, S. Isovitsch, J. Xu, C. Guestrin, J. VanBriesen, M. Small, P. Fischbeck, A. Preis, M. Propato, O. Piller, G. B. Trachtman, Z.Y. Wu and T. Walski, J. Water Res. Plan. Manage., 134(6), 556 (2008).

    Article  Google Scholar 

  9. 9.

    N. Chang, N. Prapinpongsanone and A. Ernest, Comput. Chem. Eng., 43, 191 (2012).

    Article  CAS  Google Scholar 

  10. 10.

    J. Xu, M. P. Johnson, P. S. Fischbeck, M. J. Small and J. M. Van-Briesen, European J. Oper. Res., 202, 707 (2010).

    Article  Google Scholar 

  11. 11.

    J. U. Jung, Master Thesis, Kangwon University, 55 (2011).

  12. 12.

    G. Mannina and G. Viviani, J. Hydrology, 381(3–4), 248 (2010).

    Article  CAS  Google Scholar 

  13. 13.

    C. R. Jacobson, J. Environ. Manage., 92, 1438 (2011).

    Article  Google Scholar 

  14. 14.

    G. Gambi, M. Maglionico and S. Tondelli, Procedia Eng., 21, 1110 (2011).

    Article  Google Scholar 

  15. 15.

    F. Leisch, Comput. Statist. Data Anal., 51, 526 (2006).

    Article  Google Scholar 

  16. 16.

    P. Pavlidis, Methods, 31, 282 (2003).

    Article  CAS  Google Scholar 

  17. 17.

    D. C. Montgomery, G. C. Runger and N. F. Hubele, Engineering Statistics, 4th Ed. John Wiley & Sons Inc., USA, 162 (2007).

    Google Scholar 

  18. 18.

    C. K. Yoo, S.W. Choi and I.B. Lee, Korean Chem. Eng. Res., 46(2), 233 (2008).

    CAS  Google Scholar 

  19. 19.

    S. J. Hong, C. K. Yoo and C. H. Han, Korean Chem. Eng. Res., 37(3), 445 (1999).

    CAS  Google Scholar 

  20. 20.

    A. Chakraborty and D. Deglon, Comput. Chem. Eng., 32, 382 (2008).

    Article  CAS  Google Scholar 

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Correspondence to ChangKyoo Yoo.

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Kang, O., Lee, S., Wasewar, K. et al. Determination of key sensor locations for non-point pollutant sources management in sewer network. Korean J. Chem. Eng. 30, 20–26 (2013).

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Key words

  • Sewer Network
  • Non-point Pollutant Sources
  • Sensor Location
  • Data Mining