Cyanobacterial bloom predicting method based on non-linear kinetic time-series model

Abstract

The invention discloses a cyanobacterial bloom predicting method based on a non-linear kinetic time-series model, which belongs to the water environment predicting field. The method comprises the following steps: using the blue algae growth rate as a time-varying parameter; creating a non-linear kinetic time-series model for the cyanobacteria growth with double nutrient salt cycling; using the combination of the numerical algorithm and the intelligent evolutionary algorithm, optimizing the constant parameters in the non-linear kinetic time-series model for the cyanobacteria growth; through setting the multivariate time-series model to realize the prediction of the time-varying parameter and the cyanobacteria biomass and through using the bifurcation theory and the central manifold theory to make a nonlinear kinetic analysis of the cyanobacteria growth time-varying system, obtaining the outbreak conditions for a cyanobacteria bloom so as to make an early warning of the bloom outbreak. The method proposed by the invention not only determines the conditions for a cyanobacteria bloom outbreak, but also improves the bloom prediction accuracy, providing an effective reference for an environmental protection department and governance decisions for water environment treatment.

Description

technical field [0001] The invention relates to a method for predicting cyanobacteria blooms, belonging to the technical field of water environment prediction, in particular to a method for predicting and early warning of cyanobacteria blooms based on a nonlinear dynamic time series model. Background technique [0002] With the development of economy and society, water eutrophication has become a major global water environment problem. Eutrophication of water body means that under the influence of human activities, a large amount of nutrients such as nitrogen and phosphorus required by organisms enter slow-flowing water bodies such as lakes, rivers, bays, etc., causing algae and other plankton to multiply rapidly and the dissolved oxygen content of water bodies to decrease. , fish and other organisms die in large numbers. Algae bloom is a typical manifestation of eutrophication in water bodies, and it is one of the main problems of water environmental pollution in rivers an...

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Problems solved by technology

[0006] The purpose of the present invention is to solve the problems that the existing cyanobacteria bloom prediction accuracy is not high, ignoring the influence of some influencing factors on the time-varying system of cyanobacteria growth, etc. Based on the measured data such as concentration, water temperature and light, considering the influence of light, water temperature and other factors on the growth of cyanobacteria over time, the growth rate of cyanobacteria is used as a time-varying parameter, and a nonlinear dynamic time series model of cyanobacteria growth with dual nutrient cycle is established , using the combination of numerical algorithm and intelligent evolution algorithm to optimize the constant parameters in the nonlinear dynamic time series model of cyanobacteria growth, and to realize the time-varying parameters and cyanobacteria Prediction of biomass, and use the bifurcation theory and central manifold theory to analyze the nonlinear dynamics of the time-varying system of cyanobacteria growth, obtain the conditions for the outbreak of cyanobacteria blooms, and then realize the early warning of the bloom behavior

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