4.7 Article

Identification of coastal water quality by statistical analysis methods in Daya Bay, South China Sea

期刊

MARINE POLLUTION BULLETIN
卷 60, 期 6, 页码 852-860

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.marpolbul.2010.01.007

关键词

Principal component analysis; Fuzzy logic approach; Cluster analysis; Trophic status; Water quality; Daya Bay

资金

  1. Chinese Academy of Sciences [KSCX2-SW-132, KZCX2-YW-Q0Y-02, SQ200913]
  2. Young People's Innovation Foundation of the South China Sea Institute of Oceanology
  3. Key Laboratory of Global Change and Marine-Atmospheric Chemistry, SOA [GCMAC0906]
  4. South China Sea Institute of Oceanology [LYQ200701]
  5. National 908 project [908-02-04-04]

向作者/读者索取更多资源

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. (C) 2010 Elsevier Ltd. All rights reserved.

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