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

• Autorzy: Wu M-L. , Wang Y-S. , Sun C-C. , Sun F-L. , Cheng H. , Wang Y-T. , Dong J-D. , Wu J.
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

Daya Bay (DYB); water quality; principal component analysis (PCA); cluster analysis (CA)

• Wydawca: Institute of Oceanography University of Gdańsk
• Czasopismo: Oceanological and Hydrobiological Studies
• Rocznik: 2012
• Tom: Vol. 41, No. 4
• Strony: 66--76
• Opis fizyczny: Bibliogr. 39 poz., rys., wykr.

Twórcy

autor

Wu M-L.

autor

Wang Y-S.

autor

Sun C-C.

autor

Sun F-L.

autor

Cheng H.

autor

Wang Y-T.

autor

Dong J-D.

autor

Wu J.

• State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China,

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