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Early warning of cyanobacteria blooms outbreak based on stoichiometric analysis and catastrophe theory model

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Abstract

Cyanobacteria bloom, mainly caused by chemical factors such as nitrogen and phosphorus, can produce toxic substances in water or even reduce biodiversity. It is urgent to curb the cyanobacteria bloom and early warn their outbreak. This paper proposes a nonlinear mathematical model of cyanobacteria growth based on stoichiometric analysis. Parameters in the cyanobacteria growth nonlinear mathematical model are estimated and optimized by the cuckoo search intelligent algorithm to improve the estimation accuracy. Time of cyanobacteria blooms outbreak is forecasted by bifurcation sets of the nonlinear mathematical model based on cusp catastrophe theory. Certain natural lake monitoring data is processed with the proposed method for illustration. The results show that time of cyanobacteria blooms outbreak is forecasted accurately by the bifurcation sets of the nonlinear model. Hence, cyanobacteria blooms outbreak can be early warned effectively by the proposed method.

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Acknowledgements

The authors acknowledge the National Natural Science Foundation of China (Grant 61703008), the National Natural Science Foundation of China (Grant 61802010). Support Project of High-level Teachers in Beijing Municipal Universities in the Period of 13th Five-year Plan (Grant CIT&TCD201804014). Those supports are gratefully acknowledged.

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Authors and Affiliations

  1. School of Computer and Information Engineering, Beijing Key Laboratory of Big Data, Technology for Food Safety, Beijing Technology and Business University, 11 FuCheng Road, HaiDian District, Beijing, 100048, China

    Li Wang, Junpeng Kang, Jiping Xu, Huiyan Zhang, Xiaoyi Wang, Jiabin Yu, Qian Sun & Zhiyao Zao

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  1. Li Wang
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  2. Junpeng Kang
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  3. Jiping Xu
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  4. Huiyan Zhang
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  5. Xiaoyi Wang
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  7. Qian Sun
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  8. Zhiyao Zao
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Correspondence to Xiaoyi Wang.

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Wang, L., Kang, J., Xu, J. et al. Early warning of cyanobacteria blooms outbreak based on stoichiometric analysis and catastrophe theory model. J Math Chem 58, 906–921 (2020). https://doi.org/10.1007/s10910-019-01052-x

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  • DOI: https://doi.org/10.1007/s10910-019-01052-x

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