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Identification of coastal water quality by statistical analysis methods in Daya Bay, South China Sea |
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| Authors: | Mei-Lin Wu You-Shao Wang Cui-Ci Sun Haili Wang Jian-Ping Yin |
| Institution: | a Key Laboratory of Tropical Marine Environmental Dynamics, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China b Marine Biology Research Station at Daya Bay, Chinese Academy of Sciences, Shenzhen 518121, China c Scripps Institution of Oceanography, University of California, San Diego, CA 92093-0218, USA d College of Chemistry, Shandong University, Jinan 265200, China |
| Abstract: | In this paper, cluster analysis (CA), principal component analysis (PCA) and the fuzzy logic approach were employed to evaluate the trophic status of water quality for 12 monitoring stations in Daya Bay in 2003. CA grouped the four seasons into four groups (winter, spring, summer and autumn) and the sampling sites into two groups (cluster DA: S1, S2, S4-S7, S9 and S12 and cluster DB: S3, S8, S10 and S11). PCA identified the temporal and spatial characteristics of trophic status in Daya Bay. Cluster DB, with higher concentrations of TP and DIN, is located in the western and northern parts of Daya Bay. Cluster DA, with the low Secchi, is located in the southern and eastern parts of Daya Bay. The fuzzy logic approach revealed more information about the temporal and spatial patterns of the trophic status of water quality. Chlorophyll a, TP and Secchi may be major factors for deteriorating water quality. |
| Keywords: | Principal component analysis Fuzzy logic approach Cluster analysis Trophic status Water quality Daya Bay |
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