<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

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

State Key Laboratory of Tropical Oceanography

Oceanological and Hydrobiological Studies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Eleven physicochemical parameters of data collected from 12 stations in Daya Bay in 2003 were analyzed by multivariate statistical analysis. Cluster analysis...

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

Publié en ligne: 06 nov. 2012

Pages: 66 - 76

DOI: https://doi.org/10.2478/s13545-012-0040-0

Mots clés
Daya Bay, water quality, principal component analysis, cluster analysis

© 2012 Faculty of Oceanography and Geography, University of Gdańsk, Poland

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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

Publié en ligne: 06 nov. 2012

Pages: 66 - 76

DOI: https://doi.org/10.2478/s13545-012-0040-0

Mots clésDaya Bay, water quality, principal component analysis, cluster analysis

© 2012 Faculty of Oceanography and Geography, University of Gdańsk, Poland

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Daya Bay, water quality, principal component analysis, cluster analysis