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Nonlinear Regression Based Analysis on Cyanobacteria Blooms and Water Quality in a Beijing Shallow Lake

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6 Author(s)
Lequan Min ; Sch. of Appl. Sci., Univ. of Sci. & Technol. Beijing, Beijing, China ; Xiaobo Jiang ; Youyan Fu ; Yunhao Yi
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During the last two years, data sets from three groups and twelve sampling points were used to investigate historical changes between the concentration of the cyanobacteria and the concentrations of total nitrogen (TN), total phosphorus (TP), TN/TP, chemical oxygen dawdling (COD), NO3 -, pH, and Chl-a in a shallow temperate zone lake (Guishui Lake, Beijing). The aim of this paper was to evaluate changes of the risk of cyanobacteria blooms, which occurs several times in the lake each year. Observing that high ratios of TN/TP (>20), and low concentration of TP (<0.3 mg/L) may suppress the growth of the cyanobacteria in the lake, we find that three independent thresholds that TN/TP = 11, NO3 - = 3.2 mg/L, and TP = 0.611 mg/L are related to the cyanobacteria blooms in the lake. Based on the data sets, a nonlinear regression formula on the growth of blue algae cells was established via ratio TN/TP, the concentrations of COD, NO3 -, pH, and Chl-a. The calculated results on the number of the cyanobacteria cells via the nonlinear regression formula are well in agreeing with the tested data from the twelve water quality monitoring sites.

Published in:

Computational Intelligence and Security, 2009. CIS '09. International Conference on  (Volume:2 )

Date of Conference:

11-14 Dec. 2009