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Evaluation of the Parameters of Water Quality with Wavelet Techniques

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  • Funda Dökmen
  • Zafer Aslan

Abstract

Generally, wavelets are purposefully crafted to have specific properties that make them useful for signal processing. In recent years, wavelet analysis have commonly been used instead of Fourier analysis. This is a new approach for evaluation of water quality parameters. This study determined water quality parameters and effects on water quality in Gölcük, Turkey. A 13-month data series was compared with results from laboratory analysis by using wavelet model techniques. The study investigated eight surface water sources, located in rural areas (five different villages) in the vicinity of Gölcük. Water samples were obtained during spring and analyzed for contaminants. The samples were analyzed for Cl - (chlorine), NO 3 -N (nitrate) and pH values. Wavelet analysis of extreme events showed the role of seasonal oscillations, and small-, meso- and large-scale effects on some water quality parameters. In addition, the Cl - , NO 3 -N and pH contents were determined for their suitability for irrigation, drinking and other domestic uses. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Funda Dökmen & Zafer Aslan, 2013. "Evaluation of the Parameters of Water Quality with Wavelet Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(14), pages 4977-4988, November.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:14:p:4977-4988
    DOI: 10.1007/s11269-013-0454-5
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    Citations

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    Cited by:

    1. Jian Sha & Zeli Li & Dennis Swaney & Bongghi Hong & Wei Wang & Yuqiu Wang, 2014. "Application of a Bayesian Watershed Model Linking Multivariate Statistical Analysis to Support Watershed-Scale Nitrogen Management in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3681-3695, September.
    2. Wen-chuan Wang & Dong-mei Xu & Kwok-wing Chau & Guan-jun Lei, 2014. "Assessment of River Water Quality Based on Theory of Variable Fuzzy Sets and Fuzzy Binary Comparison Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4183-4200, September.
    3. Kulwinder Parmar & Rashmi Bhardwaj, 2015. "River Water Prediction Modeling Using Neural Networks, Fuzzy and Wavelet Coupled Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(1), pages 17-33, January.
    4. Sajjad Abdollahi & Jalil Raeisi & Mohammadreza Khalilianpour & Farshad Ahmadi & Ozgur Kisi, 2017. "Daily Mean Streamflow Prediction in Perennial and Non-Perennial Rivers Using Four Data Driven Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4855-4874, December.
    5. Jian Sha & Zeli Li & Dennis P. Swaney & Bongghi Hong & Wei Wang & Yuqiu Wang, 2014. "Application of a Bayesian Watershed Model Linking Multivariate Statistical Analysis to Support Watershed-Scale Nitrogen Management in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3681-3695, September.
    6. Yuankun Wang & Dong Sheng & Dong Wang & Huiqun Ma & Jichun Wu & Feng Xu, 2014. "Variable Fuzzy Set Theory to Assess Water Quality of the Meiliang Bay in Taihu Lake Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(3), pages 867-880, February.

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