Multivariate Statistical Techniques for the Assessment of Surface Water Quality at the Mid-Black Sea Coast of Turkey

Abstract

The aim of this study was to investigate the seasonal and spatial variations in surface water quality at the mid-Black Sea coast of Turkey. The samples were collected from ten monitoring stations including rivers and sea water during the years from 2007 to 2008. The samples were analyzed for 25 parameters: total carbon, total inorganic carbon, total organic carbon, chromium, cadmium, copper, lead, iron, nickel, manganese, phenol, surfactants, ammonium, nitrite and nitrate-nitrogen, total phosphorus, adsorbable organic halogen, sulfate, hardness, dissolved oxygen, pH, temperature, total dissolved solids, electrical conductivity, and salinity. Multivariate statistical techniques, cluster analysis (CA) and factor analysis/principal component analysis (FA/PCA), were applied to analyze the similarities among the sampling sites to identify the source apportionment of pollution parameters in surface waters. The results indicate that seven factors for river water explained 82.24% of the variance. In seawater, seven factors account for 89.65% of the total variance. Varifactors obtained from factor analysis indicate that the parameters responsible for water quality variations are mainly related to organic pollution (municipal effluents), inorganic pollution (industrial effluents and waste disposal areas), nutrients (agricultural runoff), and dissolved salts (soil leaching and runoff process). © 2010 Springer Science+Business Media B.V.