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Correlations between algae and water quality: factors driving eutrophication in Lake Taihu, China
Li, Y. P.; Tang, C. Y.; Yu, Z. B. & Acharya, K.
Abstract
Rapid population increase and economic
growth in eastern China has lead to the degradation of
many water bodies in the region, such as Lake Taihu,
the third largest freshwater lake in China. Using data
from recent investigations, the correlations between
algae (measured as chlorophyll-α) and water quality
indices in Lake Taihu were described by multivariate
statistical analyses, and the key driving factors for the
lake eutrophication were identified by principal component
analysis. Results revealed strong spatiotemporal
variation in the correlations between algae and water
quality indices, suggesting that the limiting factor for
the dominant algae growth depends on seasonality and
location and it is necessary to reduce both nitrogen and
phosphorus inputs for a long-term eutrophication control
in this hyper-eutrophic system. Water temperature was
another important controlling factor for algal growth in
the lake. Using principal component analysis, nutrient
contaminations from anthropogenic and natural inputs
were identified as the key driving factor for the water
quality problems of the lake. Moreover, five principal
components were extracted and characterized with high
spatial and seasonal variations in Lake Taihu. The key
driving factors were believed to influence spatial variations
including heavily polluted areas located in the
northern and northwestern parts of the lake, where many
manufacturing factories were built and wastewater from
domestic and industrial plants was discharged. Based on
this analysis, attention should be paid to effective land
management, industrial wastewater treatment, and
macrophytic vegetation restoration to reduce the pollutant
loads and improve water quality. Principal component
analysis was found to be a useful and effective
method to reduce the number of analytical parameters
without notably impairing the quality of information in
this study.
Keywords
Cyanobacteria bloom; Large shallow lakes; Nutrient limitation; Principal component analysis
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