Evaluation of the Parameters of Water Quality with Wavelet Techniques

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), NO3-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-, NO3-N and pH contents were determined for their suitability for irrigation, drinking and other domestic uses.

[1]  Guo H. Huang,et al.  Wavelet-based multiresolution analysis for data cleaning and its application to water quality management systems , 2008, Expert Syst. Appl..

[2]  Kwok-wing Chau,et al.  Assessment of River Water Quality Based on Theory of Variable Fuzzy Sets and Fuzzy Binary Comparison Method , 2014, Water Resources Management.

[3]  Kathleen Dohan,et al.  Identification and characterization of water quality transients using wavelet analysis. I. Wavelet analysis methodology , 1997 .

[4]  D. Swaney,et al.  Application of a Bayesian Watershed Model Linking Multivariate Statistical Analysis to Support Watershed-Scale Nitrogen Management in China , 2014, Water Resources Management.

[5]  Modeling of point and non-point source pollution of nitrate with SWAT in the Jajrood river watershed, Iran. , 2010 .

[6]  Barbara Hubbard,et al.  The World According to Wavelets , 1996 .

[7]  Ahmed El-Shafie,et al.  Water quality prediction model utilizing integrated wavelet-ANFIS model with cross-validation , 2010, Neural Computing and Applications.

[8]  A. E. Greenberg,et al.  Standard methods for the examination of water and wastewater. 14th edition. , 1976 .

[9]  A. E. Greenberg,et al.  Standard methods for the examination of water and wastewater : supplement to the sixteenth edition , 1988 .

[10]  A. H. Siddiqi,et al.  Wavelet Based Computer Simulation of Some Meteorological Parameters: Case Study in Turkey , 2002 .

[11]  Aditi Sharma,et al.  Spatial Data Mining for Drought Monitoring: An Approach Using temporal NDVI and Rainfall Relationship , 2006 .

[12]  A. H. Siddiqi,et al.  TRENDS IN WAVELET APPLICATIONS , 2006 .

[13]  Kulwinder Singh Parmar,et al.  River Water Prediction Modeling Using Neural Networks, Fuzzy and Wavelet Coupled Model , 2014, Water Resources Management.

[14]  Abul Hasan Siddiqi,et al.  Trends in Industrial and Applied Mathematics , 2011 .

[15]  Dong Wang,et al.  Variable Fuzzy Set Theory to Assess Water Quality of the Meiliang Bay in Taihu Lake Basin , 2014, Water Resources Management.

[16]  Abul Hasan Siddiqi,et al.  Wavelet transforms of meteorological parameters and gravity waves , 2005 .

[17]  Peijun Chen,et al.  Prediction of Water-quality Based on Wavelet Transform Using Vector Machine , 2010, 2010 Ninth International Symposium on Distributed Computing and Applications to Business, Engineering and Science.

[18]  Kathleen Dohan,et al.  Identification and characterization of water quality transients using wavelet analysis. II. Application to electronic water quality data , 1997 .

[19]  A. Grossmann,et al.  DECOMPOSITION OF HARDY FUNCTIONS INTO SQUARE INTEGRABLE WAVELETS OF CONSTANT SHAPE , 1984 .

[20]  Shujiang Kang,et al.  Wavelet analysis of hydrological and water quality signals in an agricultural watershed , 2007 .