Multivariate statistical methods for recognition of water quality feature in Meiliang Bay of Taihu Lake - Fan, Liang-Qian; Wu, Zu-Cheng; Zhang, Qing-Yu; Liu, Qi; Yu, Bo (Zhejiang da xue xue bao. Journal of Zhejiang University. Sciences edition. Li xue ban, 2013)
The aim is to identify feature of water quality in Meiliang Bay of Taihu Lake and provide scientific reference for protection, planning, management and water utilization. According to the data of nine monitoring points in Meiliang Bay, the main sources of pollutants were firstly examined based on principal component analysis (PCA); secondly, the sampling points were categorized with cluster analysis (CA) and the spatial similarities and differences between sampling points were identified; at last, the types of pollutants and variations of concentration were analyzed through comparison with the monitoring data of various types of sampling points. The results showed that: the water quality of Meiliang Bay of Taihu Lake is affected by agricultural non-point source, phytoplankton growth, organic suspended matter from external sources, nitrogenous organic pollutant and composition of soil; the nine monitoring points in Meiliangwan Bay can be classified into four categories, namely, the points of river estuary, lak