Water Resources

, Volume 46, Issue 1, pp 112–116 | Cite as

Prediction of Water Quality Index by Support Vector Machine: a Case Study in the Sefidrud Basin, Northern Iran

  • Forough Kamyab-Talesh
  • Seyed-Farhad Mousavi
  • Mohammadreza KhaledianEmail author
  • Ozra Yousefi-Falakdehi
  • Mojtaba Norouzi-Masir


The objectives of this study were to predict the water quality index using Support Vector Machine (SVM) model and to identify the most important attributes affecting the variability of the water quality index in the Sefidrud basin which is located in the northern part of Iran. Water samples at each site have been collected monthly from December 2007 to November 2008. At each station, water samples were collected from inside the middle of the river by means of a plastic bucket and were transported to the laboratory. Water quality parameters were measured, calculated and classified according to the standard methods. Prediction of the SVM models in the study area resulted in determination coefficient and root mean square error of 0.87 and 0.061 for the water quality index, respectively. The nitrate was identified as the most important attribute influencing the water quality index. Overall, our results indicated that the SVM models could explain 87% of the total variability in water quality index. Besides, the predictability of water quality index could be improved by other statistical and intelligent models. These predictions help us to improve river management, regarding water quality.


support vector machine modeling water quality index sensitivity coefficient 


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Copyright information

© Pleiades Publishing, Ltd. 2019

Authors and Affiliations

  • Forough Kamyab-Talesh
    • 1
  • Seyed-Farhad Mousavi
    • 2
  • Mohammadreza Khaledian
    • 3
    Email author
  • Ozra Yousefi-Falakdehi
    • 4
  • Mojtaba Norouzi-Masir
    • 5
  1. 1.Water Engineering Department, Isfahan University of TechnologyIsfahanIran
  2. 2.Faculty of Civil Engineering, Semnan UniversitySemnanIran
  3. 3.Water Engineering Department, Faculty of Agricultural Sciences, University of Guilan, and Department of Water Engineering and Environment, Caspian Sea Basin Research CenterRashtIran
  4. 4.Guilan Regional Water CompanyRashtIran
  5. 5.Soil Science Department, Faculty of Agricultural Sciences, Shahid Chamran UniversityAhvazIran

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