Abstract
Multivariate statistical methods, such as cluster analysis (CA), discriminant analysis (DA), and factor analysis (FA) were applied to the data on water quality of Lake Taoranting (Beijing), generated during two years (2011-2012), with monitoring at five different sites. The CA grouped the eight months (March to November) into three periods,and classified five sites into two clusters based on water quality characteristics. The DA showed the best results for data reduction and temporal analysis. It calculated six parameters (TEMP,pH,SD,CODMn,TSS and Chl-a) were the major sources of temporal variations in water quality. The FA applied to datasets of two special clusters of the lake calculated three factors for each region, capturing 72.89% and 78.88% of the total variance, respectively. Factors obtained from FA indicate that some parameters such as Chl-a, TSS, TP and NH4 + -N are mainly key factors responsible for water quality. Thus, this study results suggested that multivariate statistical methods is a effective tool for analysis of urban landscape water quality.
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