Monsoon-driven Dynamics of water quality by multivariate statistical methods in Daya Bay, South China Sea

Abstract

Abstract Eleven physicochemical parameters of data collected from 12 stations in Daya Bay in 2003 were analyzed by multivariate statistical analysis. Cluster analysis (CA) grouped data from 4 seasons into two groups, the northeast and southwest monsoon periods, representing different natural processes. During the northeast monsoon period, principal component analysis (PCA) and CA group the 12 monitoring sites into Cluster DA1 (S1, S2 and S6) and Cluster DA2 (S3-S5 and S7-S12). During the southwest monsoon period, PCA and CA group the 12 monitoring sites into Cluster WB1 (S1, S2, S7, S9 and S11) and Cluster WB2 (S3-S6, S8, S10, S11 and S12). The spatial heterogeneity within the bay was defined by different hydrodynamic conditions and human activities. These results may be valuable for achieving sustainable use of the coastal ecosystems in Daya Bay.