Using integrated multivariate statistics to assess the hydrochemistry of surface water quality, lake Taihu basin, China

We investigated the hydrochemical setting of Lake Taihu (eastern China) to determine how different land use types influence the variability of surface water chemistry in different water sources to the lake. Major water types within the watershed range from caclium-magnesium bicaxrbonate water, typical of relatively pristine water, highly ocntaminated water characterized by more sulfate, sodium, chloride and nutrients. Principal components analysis produced three principal components that explained 78% of the variance in the water quality and reflect three major types of water chemistry. Agricultural land use is associated with greater concentrations of nutrients; urban areas with high concentrations of sodium, chloride, sulfate, fluoride and potassium; and natural weathering with calcium, magnesium and bicarbonate. Discriminant analysis and hierarchical cluster analysis produce complementary and similar results. Broadly speaking, future remediation to reduce nutrient loadings to the lake or industrial contamination can now be focused on specific land use practices, which are readily identifiable by using statistics in conjunction with GIS.