Open AccessWater Quality Analysis of the Songhua River Basin Using Multivariate Techniques
Author(s) -
Yang Li,
Linyu Xu,
Shun Li
Publication year - 2009
Publication title -
journal of water resource and protection
Language(s) - English
Resource type - Journals
eISSN - 1945-3108
pISSN - 1945-3094
DOI - 10.4236/jwarp.2009.12015
Subject(s) - water quality , environmental science , ammoniacal nitrogen , nitrate , environmental chemistry , wastewater , effluent , biochemical oxygen demand , chemical oxygen demand , principal component analysis , environmental engineering , hydrology (agriculture) , chemistry , ecology , geology , geotechnical engineering , organic chemistry , artificial intelligence , computer science , biology
Multivariate statistical techniques, including cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA), were used to evaluate temporal and spatial variations and to interpret a large and complex water quality data sets collected from the Songhua River Basin. The data sets, which contained 14 parameters, were generated during the 7-year (1998-2004) monitoring program at 14 different sites along the rivers. Three significant sampling locations (less polluted sites, moderately polluted sites and highly polluted sites) were detected by CA method, and five latent factors (organic, inor-ganic, petrochemical, physiochemical, and heavy metals) were identified by PCA and FA methods. The re-sults of DA showed only five parameters (temperature, pH, dissolved oxygen, ammonia nitrogen, and nitrate nitrogen) and eight parameters (temperature, pH, dissolved oxygen, biochemical oxygen demand, ammonia nitrogen, nitrate nitrogen, volatile phenols and total arsenic) were necessarily in temporal and spatial varia-tions analysis, respectively. Furthermore, this study revealed the major causes of water quality deterioration were related to inflow of effluent from domestic and industrial wastewater disposal