Assessment of seasonal variations in surface water quality.

Assessment of seasonal changes in surface water quality is an important aspect for evaluating temporal variations of river pollution due to natural or anthropogenic inputs of point and non-point sources. In this study, surface water quality data for 16 physical and chemical parameters collected from 22 monitoring stations in a river during the years from 1998 to 2001 were analyzed. The principal component analysis technique was employed to evaluate the seasonal correlations of water quality parameters, while the principal factor analysis technique was used to extract the parameters that are most important in assessing seasonal variations of river water quality. Analysis shows that a parameter that is most important in contributing to water quality variation for one season may not be important for another season except for DOC and electrical conductance, which were always the most important parameters in contributing to water quality variations for all four seasons.

[1]  Damià Barceló,et al.  Multivariate correlation between concentrations of selected herbicides and derivatives in outflows from selected U.S. Midwestern reservoirs , 2000 .

[2]  B. Tabachnick,et al.  Using Multivariate Statistics , 1983 .

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

[4]  J. Shine,et al.  Multivariate statistical examination of spatial and temporal patterns of heavy metal contamination in new bedford harbor marine sediments. , 1995, Environmental science & technology.

[5]  S Gangopadhyay,et al.  Evaluation of ground water monitoring network by principal component analysis. , 2001, Ground water.

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

[7]  Joseph J. Harrington,et al.  Effective dimensionality of environmental indicators: a principal component analysis with bootstrap confidence intervals , 1998 .

[8]  B. Manly.  Multivariate Statistical Methods : A Primer , 1986 .

[9]  Y Ouyang.  APPLICATION OF PRINCIPAL COMPONENT AND FACTOR ANALYSIS TO EVALUATE SURFACE WATER QUALITY MONITORING NETWORK , 2005 .

[10]  G. Underwood,et al.  GRADIENTS OF CHLOROPHYLL A AND WATER CHEMISTRY ALONG AN EUTROPHIC RESERVOIR WITH DETERMINATION OF THE LIMITING NUTRIENT BY IN SITU NUTRIENT ADDITION , 2000 .

[11]  K. Havens.  Phosphorus–Algal Bloom Relationships in Large Lakes of South Florida: Implications for Establishing Nutrient Criteria , 2003 .

[12]  G. Jones,et al.  The seasonal variation of dissolved nutrients, chlorophyll a and suspended sediments at Nelly Bay, Magnetic Island , 2003 .

[13]  E. Manoli,et al.  A Study of Surface Water Quality in Macedonia, Greece: Speciation of Nitrogen and Phosphorus , 2001 .

[14]  T. Marhaba,et al.  Using principal component analysis to monitor spatial and temporal changes in water quality. , 2003, Journal of hazardous materials.

[15]  R. Cattell,et al.  A general plasmode (No. 30-10-5-2) for factor analytic exercises and research. , 1967 .

[16]  L. M. Hodgson,et al.  Relations between color and some limnological characteristics of Florida Lakes , 1984 .

[17]  Hans Wackernagel,et al.  Multivariate Geostatistics: An Introduction with Applications , 1996 .