Dynamics Analysis And Prediction Method Of Algal Bloom Time Variation System

With the development of economy and society,water eutrophication has become a global problem of water pollution.Algal bloom is a typical manifestation of eutrophication,and is one of the major problems of water pollution in China.The outbreak of water bloom causes the imbalance of water ecosystem,which poses a threat to human health and ecological landscape.Therefore,study on algal bloom formation mechanism and method of forecasting and early warning in depth provides a scientific basis for reducing the harm of algal bloom,and it is of great significance to take effective and timely measures to prevent and control algal bloom.Based on the prediction of algal bloom mechanism modeling and data modeling,this paper combines the two modeling method advantage,and consider the key factors affecting the growth of cyanobacteria,the mechanism model of cyanobacteria and nitrogen nutrient cycling and the mechanism of cyanobacteria and nitrogen and phosphorus nutrient cycling are established.In order to make the model accord with the actual burst behavior,some parameters in the model are set up to be time-varying parameters,which changes the time invariant model into a time-varying system model.According to the actual data collected from Taihu basin,the constant parameters of the model are optimized by the combination of the numerical algorithm and the intelligent evolutionary algorithm,and time-varying parameters are predicted by multivariate time series method.These parameter calibration methods improve the applicability of the model.Then,in order to analyze the mechanism and explain the characteristics of water bloom,bifurcation theory and center manifold theory are used to analyze the model,the bifurcation behavior of the model and conditions of the bloom formation are obtained.Finally,numerical analysis method is used to predict cyanobacteria biomass,and combine the critical point of the mechanism analysis with the disaster point caused by the actual algal bloom to realize the grade warning of water environment.Through the actual data show that the time-varying model proposed in this paper can reflect the nonlinear dynamics characteristics of cyanobacteria,and the prediction accuracy is higher than other methods.The research results of this paper provide a solution for the prediction and early warning of algal bloom,which has practical significance for revealing the law of algae growth,expanding the prediction theory and improving the prediction accuracy of algae.