『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』
1. Introduction
2. Materials and methods
2.1. Study area
2.2. Sampling and analytical methods
2.3. Data treatment
2.3.1. Cluster analysis (CA)
2.3.2. Principal component analysis (PCA)
2.3.3. The fuzzy logic approach
3. Results
3.1. Cluster analysis
3.2. Principal component analysis
3.3. The fuzzy logic approach
4. Discussion
4.1. Temporal characteristics and key factors
4.2. Spatial characteristics and key factors
4.3. Characteristics of CA, PCA and the fuzzy logic approach
5. Conclusion
Acknowledgements
References