Simulation Of Cyanobacterial Biomass In Taihu Lake Based On Growth Model

With the rapid development of social economy and industrial and agricultural production,the non-point source pollution and point source pollution in Taihu Lake Basin are serious,which makes the water body of Taihu Lake eutrophic,resulting in frequent outbreaks of cyanobacteria in Taihu Lake,seriously affecting the drinking water problems and daily life of the surrounding residents.There are many factors affecting the change of the biomass of cyanobacteria,including not only the biological mechanism of the growth(extinction)of cyanobacteria,but also the dynamic factors of the explosive reproduction of cyanobacteria.At the same time,the dynamic mechanism of lake water is complex and changeable,so it is difficult to accurately simulate and predict the biomass of cyanobacteria.Therefore,the simulation and prediction of cyanobacterial biomass based on dynamic mechanism is an urgent problem to be solved in the process of preventing and controlling water pollution in Taihu Lake,and it is also a hot issue for scholars at home and abroad.In the field of water eutrophication research,numerical simulation method has been widely used.It can simulate the complex hydrodynamic environment and eutrophication of lake water better.However,because the outbreak mechanism of cyanobacteria blooms is complex,the numerical model based on dynamic mechanism is difficult to describe accurately.Meanwhile,for the numerical model in the long-sequence simulation process,it is difficult to acquire quasi-data and calibrate parameters accurately,which results in that the accuracy of model simulation needs to be improved.At the same time,the multivariate statistical model based on observation data is widely used in the simulation and prediction of cyanobacterial biomass,but it has the problems of fewer data points and discontinuous time scales.Therefore,this paper intends to analyze the factors affecting the growth and reproduction of cyanobacteria.A multivariate regression method was used to construct a statistical model of the growth(death)coefficient of cyanobacteria in Taihu Lake,and a model simulation study was carried out in combination with the hydrodynamic model.Based on this,this paper takes Taihu Lake as the research area,constructs the statistical model of cyanobacteria growth(extinction)coefficient,and combines FVCOM model to construct the prediction model of cyanobacteria biomass in Taihu Lake.Combined with the measured data of Taihu Lake buoy station,a case study of the simulation of the coupling model of cyanobacteria in Taihu Lake is carried out.The main research results of this paper are as follows:(1)Establishment of Statistical Model for Growth(Extinction)Coefficient of Cyanobacteria in Taihu LakeBased on the dynamic process of cyanobacteria growth(extinction),the growth(extinction)mechanism under the combined influence of multiple environmental factors was studied,and the factors affecting the growth and reproduction of cyanobacteria were generalized.The statistical model of cyanobacteria growth(extinction)coefficient in Taihu Lake is constructed by multiple regression method,which provides a theoretical basis for the construction of the predictive model.(2)Establishment of Cyanobacteria Biomass Prediction Model in Taihu Lake Based on Growth ModelBased on the FVCOM model,the coupled model is introduced into the statistical model of cyanobacterial growth(death)coefficient constructed in this paper.Considering the complex dynamic mechanism and external conditions,a dynamic model based on the cyanobacteria biomass prediction model of Taihu Lake is constructed.The prediction of biomass prediction reveals the interaction between the growth process of cyanobacteria and external environmental factors.(3)Case Study on Simulation of Cyanobacteria Biomass Model in Taihu LakeBased on the measured data of the buoy monitoring station in Taihu Lake,a dynamic coupling model of cyanobacteria in Taihu Lake is used to simulate the biomass model of cyanobacteria in Taihu Lake.The simulation results and the measured data were analyzed by a case study.The results of error analysis show that the predictive model constructed in this paper can better fit the fluctuation trend of cyanobacteria biomass in Taihu Lake in the short term,and truly reflect the distribution characteristics of cyanobacteria in Taihu Lake on time and space scales.