Water Quality Assessment Using Multivariate Statistical Methods—A Case Study: Melen River System (Turkey)

This study is focused on water quality of Melen River (Turkey) and evaluation of 26 physical and chemical pollution data obtained five monitoring stations during the period 1995–2006. It presents the application of multivariate statistical methods to the data set, namely, principal component and factor analysis (PCA/FA), multiple regression analysis (MRA) and discriminant analysis (DA). The PCA/FA was employed to evaluate the high–low flow periods correlations of water quality parameters, while the principal factor analysis technique was used to extract the parameters that are most important in assessing high–low flow periods variations of river water quality. Latent factors were identified as responsible for data structure explaining 72–97% of the total variance of the each data sets. PCA/FA was supported with multiple regression analysis to determine the most important parameter in each factor. It examines the relation between a single dependent variable and a set of independent variables to best represent the relation in the each factor. Obtained important parameters provided us to determine the major pollution sources in Melen River Basin. So factors are conditionally named soil structure and erosion, domestic, municipal and industrial effluents, agricultural activities (fertilizer, irrigation water and livestock wastes), atmospheric deposition and seasonal effects factors. DA applied the data set to obtain the parameters responsible for temporal and spatial variations. Assessment of high–low flow period changes in surface water quality is an important aspect for evaluating temporal and spatial variations of river pollution. The aim of this study is illustration the usefulness of multivariate statistical analysis for evaluation of complex data sets, in Melen River water quality assessment identification of factors and pollution sources, for effective water quality management determination the spatial and temporal variations in water quality.

[1]  D Kay,et al.  Relationships between microbial water quality and environmental conditions in coastal recreational waters: the Fylde coast, UK. , 2001, Water research.

[2]  Ying Ouyang,et al.  Evaluation of river water quality monitoring stations by principal component analysis. , 2005, Water research.

[3]  William Dixon,et al.  Review of aquatic monitoring program design , 1996 .

[4]  Duran Karakaş,et al.  Source apportionment of trace metals in surface waters of a polluted stream using multivariate statistical analyses. , 2004, Marine pollution bulletin.

[5]  M. Mallin,et al.  EFFECT OF HUMAN DEVELOPMENT ON BACTERIOLOGICAL WATER QUALITY IN COASTAL WATERSHEDS , 2000 .

[6]  L. Sliva,et al.  Buffer zone versus whole catchment approaches to studying land use impact on river water quality. , 2001, Water research.

[7]  B. Amiri,et al.  Modeling the Linkage Between River Water Quality and Landscape Metrics in the Chugoku District of Japan , 2009 .

[8]  Luis Deban,et al.  Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis , 1998 .

[9]  H. Boyacıoğlu,et al.  Water pollution sources assessment by multivariate statistical methods in the Tahtali Basin, Turkey , 2008 .

[10]  Bogusław Buszewski,et al.  Application of chemometrics in river water classification. , 2006, Water research.

[11]  A. Malik,et al.  WATER QUALITY ASSESSMENT AND APPORTIONMENT OF POLLUTION SOURCES OF GOMTI RIVER(INDIA) USING MULTIVARIATE STATISTICAL TECHNIQUES- A CASE STUDY , 2005 .

[12]  Guntis Brumelis,et al.  Use of an artificial model of monitoring data to aid interpretation of principal component analysis , 2000, Environ. Model. Softw..

[13]  V. Simeonov,et al.  Assessment of the surface water quality in Northern Greece. , 2003, Water research.

[14]  Xinhao Wang,et al.  Integrating water-quality management and land-use planning in a watershed context. , 2001, Journal of environmental management.

[15]  N. C. Thanasoulias,et al.  Assessment of River Water Quality in Northwestern Greece , 2005 .

[16]  Chris P Mainston,et al.  Phosphorus in rivers--ecology and management. , 2002, The Science of the total environment.

[17]  Y Ouyang,et al.  Assessment of seasonal variations in surface water quality. , 2006, Water research.

[18]  B. B. Nayak,et al.  Application of factor and cluster analysis for characterization of river and estuarine water systems – A case study: Mahanadi River (India) , 2006 .

[19]  Henry W. Altland,et al.  Regression Analysis: Statistical Modeling of a Response Variable , 1998, Technometrics.

[20]  Philippe Maillard,et al.  A spatial-statistical approach for modeling the effect of non-point source pollution on different water quality parameters in the Velhas river watershed--Brazil. , 2008, Journal of environmental management.

[21]  S. Shrestha,et al.  Assessment of surface water quality using multivariate statistical techniques: A case study of the Fuji river basin, Japan , 2007, Environ. Model. Softw..

[22]  Dinesh Mohan,et al.  Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)--a case study. , 2004, Water research.

[23]  E. Doğan,et al.  Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural network technique. , 2009, Journal of environmental management.

[24]  Kao-Hung Lin,et al.  Application of factor analysis in the assessment of groundwater quality in a blackfoot disease area in Taiwan. , 2003, The Science of the total environment.

[25]  Steven D. Brown,et al.  Handbook of applied multivariate statistics and mathematical modeling , 2000 .

[26]  Seockheon Lee,et al.  Chemometric application in classification and assessment of monitoring locations of an urban river system. , 2007, Analytica chimica acta.