Analysis method for influencing factors of vertical distribution of Microcystis colonies

Abstract

An embodiment of the present invention provides a method for analyzing influencing factors of the vertical distribution of Microcystis colonies. By constructing a Lagrangian particle model to simulate the vertical distribution of Microcystis colonies; selecting any one parameter from hydrodynamic parameters and / or self-migration parameters as the target parameter; keeping the parameter values corresponding to the parameters other than the target parameter as fixed values, and determining multiple parameter values for the target parameter; inputting the parameter values corresponding to the parameters other than the target parameter and the different parameter values corresponding to the target parameter into the hydrodynamic model, the self-migration model, and the Lagrangian particle model respectively to determine the vertical distribution of Microcystis colonies under different parameter values; based on the vertical distribution of Microcystis colonies under different parameter values, determining the influence of the target parameter on the vertical distribution of Microcystis colonies. Using the method of controlling variables to identify the contribution degree of each factor is helpful to understand the mechanism of algal bloom outbreak.

Description

Technical Field

[0001] The present invention relates to the technical field of water ecological environment, and particularly relates to a method for analyzing influencing factors of the vertical distribution of Microcystis colonies, an apparatus for analyzing influencing factors of the vertical distribution of Microcystis colonies, an electronic device, and a computer-readable medium. Background Art

[0002] Microcystis is a globally widespread cyanobacteria species causing algal blooms, and is also the main component of the most common cyanobacterial blooms in eutrophic waters in China. It is a photoautotrophic prokaryote. In environmental waters, Microcystis usually exists in two forms: single cells and colonies. There are many cylindrical pseudovacuoles in Microcystis cells, which can provide buoyancy for them. Microcystis cells also contain heavy substances such as proteins, carbohydrates, nucleic acids, and glycolipids, and their densities are all greater than that of water. During the day, algal cells carry out photosynthesis, increasing the content of heavy substances. The buoyancy provided by pseudovacuoles is not enough to offset the accumulation of heavy substances, and the algal cells will sink; when the light intensity decreases, respiration is greater than photosynthesis, consuming the carbohydrate substances in the cells, reducing the cell density, and thus causing the algal cells to float. Therefore, there is a saying of "sinking during the day and floating at night".

[0003] In eutrophic waters, the vertical distribution of Microcystis colonies is the key to algal bloom outbreaks. There are many factors affecting the vertical distribution of Microcystis colonies, including the characteristics of Microcystis colonies themselves and external environmental factors. Understanding the influence of characteristic factors on the vertical distribution of Microcystis colonies helps to understand the mechanism of algal bloom outbreaks, and thus provides a decision-making basis for algal bloom prevention and control. Existing methods can only simulate the distribution of Microcystis colonies and cannot reflect the degree of influence of characteristic factors on the distribution of Microcystis colonies. Summary of the Invention

[0004] Embodiments of the present invention provide a method for analyzing influencing factors of the vertical distribution of Microcystis colonies to solve the problem of difficultly determining the elements affecting the vertical distribution of Microcystis colonies.

[0005] Embodiments of the present invention disclose a method for analyzing influencing factors of the vertical distribution of Microcystis colonies, including:

[0006] Constructing a Lagrangian particle model for simulating the vertical distribution of Microcystis colonies; the Lagrangian particle model is associated with a hydrodynamic model and its own migration model; the Lagrangian particle model is associated with hydrodynamic parameters, colony size parameters, and underwater light intensity parameters;

[0007] Selecting any one of the hydrodynamic parameters, colony size parameters, and underwater light intensity parameters as a target parameter;

[0008] Keeping the parameter values corresponding to the parameters other than the target parameter as fixed values, and determining multiple parameter values for the target parameter;

[0009] Input the parameter values corresponding to the parameters other than the target parameter and the different parameter values corresponding to the target parameter into the hydrodynamic model, the self-migration model, and the Lagrangian particle model respectively to determine the vertical distribution of Microcystis populations under different parameter values;

[0010] Based on the vertical distribution of Microcystis populations under different parameter values, determine the influence of the target parameter on the vertical distribution of Microcystis populations.

[0011] Optionally, the hydrodynamic parameter is the turbulent diffusion coefficient; the hydrodynamic model is:

[0012]

[0013] where g is the acceleration due to gravity, t is time, u is the water flow velocity, ζ is the water level, ν is the kinematic viscosity of water, λ is the turbulent diffusion coefficient, x is the lateral position of Microcystis in the preset three-dimensional coordinate system, y is the longitudinal position of Microcystis in the preset three-dimensional coordinate system, and z is the depth position of Microcystis in the preset three-dimensional coordinate system, which is equal to the water depth position of Microcystis;

[0014] where the hydrodynamic model is solved based on the k-ε equation, and the k-ε equation is:

[0015]

[0016] where k is the turbulent kinetic energy, ε is the dissipation rate of the turbulent kinetic energy, σ k is the Prandtl number corresponding to the turbulent kinetic energy, σ ε is the Prandtl number corresponding to the dissipation rate of the turbulent kinetic energy, C1, C2, and C μ are empirical constants.

[0017] Optionally, the upper boundary condition of the hydrodynamic model is given by the wind stress and is expressed as:

[0018]

[0019] ρ a is the air density, U 10 is the wind speed at 10 m above the ground, C D is the wind stress drag coefficient;

[0020] where the wind stress drag coefficient is determined in the following manner:

[0021]

[0022] Optionally, the upper and lower boundary conditions of the turbulent kinetic energy are:

[0023]

[0024] The upper and lower boundary conditions of the dissipation rate of the turbulent kinetic energy are as follows:

[0025]

[0026] Optionally, the self-migration parameter is the vertical migration rate of Microcystis itself, and the self-migration model is:

[0027]

[0028] where w is the vertical migration rate of Microcystis itself, g is the acceleration due to gravity, D is the diameter of the Microcystis colony, ρ col is the density of the Microcystis colony, ρ w is the density of the water body, μ is the kinematic viscosity of the water body, and φ is the shape coefficient of the Microcystis colony.

[0029] Optionally, the density of the Microcystis colony is determined based on a density change model, and the density change model is:

[0030]

[0031] where

[0032]

[0033] where I z is the light intensity function at different water depths, I c is the compensation light intensity, I0 is the light intensity when the cell density reaches the maximum value, τ r is the reaction time, ρ cell is the cell density of the Microcystis, is the change rate of the cell density considering the time-delay effect, ρ col is the density of the Microcystis colony, ρ muc is the density of the Microcystis mucus, n cell is the cell volume fraction, n gas is the pseudo-vacuole volume fraction, and a, b, c, and d are constants.

[0034] Optionally, the relationship between the density of the Microcystis colony, the cell density of the Microcystis, and the density of the Microcystis colony is:

[0035] ρ col = ρ cell n cell (1 - n gas ) + ρ muc (1 - n cell ).

[0036] Optionally, the change rate of the cell density considering the time-delay effect is expressed as:

[0037]

[0038] Among them,

[0039] is the change rate of cell density without considering the delay effect, and ρ i is the cell density at the previous time step, and a, b, c, and d are constants.

[0040] Optionally, the light intensity on the water surface is expressed as:

[0041]

[0042] Among them, I s is the light intensity on the water surface, and I m is the maximum light intensity on the water surface within a day, and D L is the sunshine duration.

[0043] Optionally, the attenuation of the light intensity along the water depth direction follows the Lambert-Beer law. When simulating the change of Microcystis aeruginosa concentration for multiple consecutive days, considering the periodic change of the light intensity on the water surface and the exponential attenuation of the light intensity underwater, the light intensity function at different water depths is expressed as:

[0044]

[0045] Optionally, the Lagrangian particle model is:

[0046]

[0047] Among them, z(i,t) represents the position of the i-th Microcystis aeruginosa population at time t, Δt represents the time step, λ' represents the gradient of the turbulent diffusion coefficient in the z direction of the preset three-dimensional coordinate system, and R n is a random variable extracted from the standard normal distribution function, and w is the vertical migration rate of Microcystis aeruginosa itself.

[0048] An embodiment of the present invention further provides an analysis device for influencing factors of the vertical distribution of Microcystis aeruginosa populations, including:

[0049] A model construction module, configured to construct a Lagrangian particle model for simulating the vertical distribution of Microcystis aeruginosa populations; the Lagrangian particle model is associated with a hydrodynamic model and its own migration model; the Lagrangian particle model is associated with hydrodynamic parameters and its own migration parameters;

[0050] A target parameter selection module, configured to select any parameter from the hydrodynamic parameters and / or its own migration parameters as the target parameter;

[0051] A parameter value determination module, configured to keep the parameter values corresponding to the parameters other than the target parameter as fixed values, and determine multiple parameter values for the target parameter;

[0052] A distribution analysis module, configured to input the parameter values corresponding to the parameters other than the target parameter and the different parameter values corresponding to the target parameter into the hydrodynamic model, the self-migration model, and the Lagrangian particle model respectively, and determine the vertical distribution of the Microcystis population under different parameter values;

[0053] An influence determination module, configured to determine the influence of the target parameter on the vertical distribution of the Microcystis population based on the vertical distribution of the Microcystis population under different parameter values.

[0054] An embodiment of the present invention also discloses an electronic device, including a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus;

[0055] The memory is used to store a computer program;

[0056] When the processor is used to execute the program stored on the memory, it implements the method as described in the embodiment of the present invention.

[0057] An embodiment of the present invention also discloses one or more computer-readable media, on which instructions are stored. When executed by one or more processors, the instructions cause the processors to execute the method as described in the embodiment of the present invention.

[0058] The embodiments of the present invention have the following advantages:

[0059] Through the method for analyzing influencing factors of the vertical distribution of Microcystis colonies provided by the embodiments of the present invention, a Lagrangian particle model for simulating the vertical distribution of Microcystis colonies is constructed; the Lagrangian particle model is associated with a hydrodynamic model and its own migration model; the Lagrangian particle model is associated with hydrodynamic parameters and its own migration parameters; any one of the parameters in the hydrodynamic parameters and / or its own migration parameters is selected as the target parameter; the parameter values corresponding to the parameters other than the target parameter are kept as fixed values, and multiple parameter values are determined for the target parameter; the parameter values corresponding to the parameters other than the target parameter and the different parameter values corresponding to the target parameter are respectively input into the hydrodynamic model, the self-migration model, and the Lagrangian particle model to determine the vertical distribution of Microcystis colonies under different parameter values; based on the vertical distribution of Microcystis colonies under different parameter values, the influence of the target parameter on the vertical distribution of Microcystis colonies is determined. Thus, the embodiments of the present invention analyze the influence of hydrodynamic force and the self-migration of Microcystis on the vertical concentration distribution of Microcystis colonies by using the control variable method based on the mathematical model of the vertical distribution of Microcystis colonies. It can better reflect the distribution of Microcystis colonies along the water depth direction, and greatly reduces the calculation amount compared with two-dimensional and three-dimensional mathematical models; using the single variable method to analyze the influence of different factors on the vertical distribution of Microcystis colonies can identify the contribution degree of each factor, which helps to understand the mechanism of algal bloom outbreak. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 is a flowchart of the steps of a method for analyzing influencing factors of the vertical distribution of Microcystis colonies provided in the embodiments of the present invention;

[0061] Figure 2 is a schematic diagram of the vertical concentration distribution of Microcystis colonies under different wind speed conditions provided in the embodiments of the present invention;

[0062] Figure 3 is a schematic diagram of the vertical concentration distribution of Microcystis colonies of different sizes under weak hydrodynamic conditions provided in the embodiments of the present invention;

[0063] Figure 4 is a schematic diagram of the vertical concentration distribution of Microcystis colonies under different extinction coefficient conditions provided in the embodiments of the present invention;

[0064] Figure 5 is a structural block diagram of an apparatus for analyzing influencing factors of the vertical distribution of Microcystis colonies provided in the embodiments of the present invention;

[0065] Figure 6 is a block diagram of an electronic device provided in the embodiments of the present invention;

[0066] Figure 7 is a schematic diagram of a computer-readable medium provided in the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0067] To make the above objects, features and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0068] Refer to Figure 1 , which shows a step flowchart of a method for analyzing the influencing factors of the vertical distribution of Microcystis colonies provided in an embodiment of the present invention, and specifically may include the following steps:

[0069] Step 101, construct a Lagrangian particle model for simulating the vertical distribution of Microcystis colonies; the Lagrangian particle model is associated with a hydrodynamic model and its own migration model; the Lagrangian particle model is associated with hydrodynamic parameters, colony size parameters, and underwater light intensity parameters;

[0070] In a specific implementation, in order to analyze the influence degree of different factors on the distribution of Microcystis colonies, a Lagrangian particle model for simulating the vertical distribution of Microcystis colonies can be constructed first. The parameters used in this model can be associated with a hydrodynamic model and its own migration model.

[0071] Among them, the hydrodynamic model can be used to simulate and predict the hydrodynamic behavior in the water body, including the velocity, direction, eddy current, turbulence, etc. of the water flow. For example, turbulence can promote the mixing and diffusion of Microcystis, and the hydrodynamic model can simulate the influence of turbulence on the distribution of Microcystis.

[0072] The self-migration model can be used to analyze the vertical migration rate of Microcystis itself, so that based on the self-migration model, it can be known how Microcystis itself changes in the vertical direction.

[0073] The Lagrangian particle model can comprehensively obtain the vertical distribution of Microcystis colonies based on the analysis results of the hydrodynamic model and its own migration model, so as to know the distribution change of Microcystis colonies in the vertical direction.

[0074] Among them, in order to calculate the vertical distribution of Microcystis colonies, the Lagrangian particle model can be associated with hydrodynamic parameters, colony size parameters, and underwater light intensity parameters. The hydrodynamic parameters, colony size parameters, and underwater light intensity parameters can be parameters required in at least one of the hydrodynamic model and its own migration model during the calculation and analysis process. Since the calculation process of the Lagrangian particle model is associated with the hydrodynamic model and its own migration model, thus, the changes in the hydrodynamic parameters, colony size parameters, and underwater light intensity parameters can affect the output of the Lagrangian particle model.

[0075] Step 102, select any one of the hydrodynamic parameters and / or self-migration parameters as the target parameter;

[0076] In the embodiments of the present invention, in order to better analyze the vertical distribution of Microcystis colonies, a method of controlling variables can be adopted to control the Lagrangian particle model, as well as the hydrodynamic model and the self-migration model associated with the Lagrangian particle model to vary in a single dimension. Thus, the effects of different factors on the vertical distribution of Microcystis colonies can be analyzed separately, the contribution degrees of various factors can be identified, which helps to understand the mechanism of algal bloom outbreak.

[0077] Generally speaking, the vertical distribution of Microcystis colonies may be related to hydrodynamics and the vertical migration rate of Microcystis itself. In order to analyze different factors separately, any one of the hydrodynamic parameters, colony size parameters, and underwater light intensity parameters can be selected as the target parameter, which serves as the dimension to be analyzed currently.

[0078] Step 103: Keep the parameter values corresponding to the parameters other than the target parameter as fixed values, and determine multiple parameter values for the target parameter.

[0079] After that, it is possible to keep the parameter values corresponding to the other parameters except the target parameter unchanged, that is, keep them as fixed values, and determine multiple parameter values for the target parameter. Thus, a single-variable control method can be adopted. For the target parameter, the changes in the vertical distribution of Microcystis colonies are observed through different parameter values, so as to know the influence of the target parameter on the vertical distribution of Microcystis colonies.

[0080] Step 104: Input the parameter values corresponding to the parameters other than the target parameter and the different parameter values corresponding to the target parameter into the hydrodynamic model, the self-migration model, and the Lagrangian particle model respectively, and determine the vertical distribution of Microcystis colonies under different parameter values.

[0081] In specific implementation, keep the parameter values of the parameters other than the target parameter input into the hydrodynamic model, the self-migration model, and the Lagrangian particle model unchanged, while the target parameter is input into the hydrodynamic model, the self-migration model, and the Lagrangian particle model respectively with different parameter values. Thus, it can be known that for the target parameter, the vertical distribution of Microcystis colonies under different parameter values.

[0082] Step 104: Based on the vertical distribution of Microcystis colonies under different parameter values, determine the influence of the target parameter on the vertical distribution of Microcystis colonies.

[0083] In the case of analyzing the vertical distribution of Microcystis colonies under different parameter values corresponding to the target parameter, that is, according to the change of the vertical distribution of Microcystis colonies following the target parameter, the influence of the target parameter on the vertical distribution of Microcystis colonies can be known.

[0084] Specifically, the hydrodynamic parameters can affect the vertical distribution of the Microcystis population by influencing the dominant factors of the vertical distribution of the Microcystis population. Specifically, in a weak hydrodynamic environment, the self-migration of the Microcystis population plays a dominant role in the vertical concentration distribution, and it is easy to float to the water surface and cause algal blooms. Under strong hydrodynamic conditions, the self-migration ability of the Microcystis population cannot overcome the entrainment of the water flow. At this time, the hydrodynamic force plays a dominant role in the vertical concentration distribution of the Microcystis population, and the vertical concentration distribution tends to be uniform, and it is not easy to cause algal blooms.

[0085] The self-migration parameters can affect the vertical distribution of the Microcystis population by influencing the self-migration ability of the Microcystis population. Specifically, under weak hydrodynamic conditions, the larger the size of the Microcystis population, the stronger the self-migration ability, and the more Microcystis populations can reach the optimal water depth, and the more concentrated the vertical distribution is; the smaller the size of the Microcystis population, the weaker the self-migration ability, and the more easily affected by the mixing of the water flow, and the more uniform the vertical concentration distribution is.

[0086] Through the method for analyzing the influencing factors of the vertical distribution of the Microcystis population provided by the embodiments of the present invention, a Lagrangian particle model for simulating the vertical distribution of the Microcystis population is constructed; the Lagrangian particle model is associated with a hydrodynamic model and a self-migration model; the Lagrangian particle model is associated with hydrodynamic parameters and self-migration parameters; any one of the hydrodynamic parameters and / or self-migration parameters is selected as the target parameter; keeping the parameter values corresponding to the parameters other than the target parameter as fixed values, and determining multiple parameter values for the target parameter; inputting the parameter values corresponding to the parameters other than the target parameter and the different parameter values corresponding to the target parameter into the hydrodynamic model, the self-migration model, and the Lagrangian particle model respectively to determine the vertical distribution of the Microcystis population under different parameter values; based on the vertical distribution of the Microcystis population under different parameter values, determining the influence of the target parameter on the vertical distribution of the Microcystis population. Thus, the embodiments of the present invention are based on the mathematical model of the vertical distribution of the Microcystis population, and use the method of controlling variables to analyze the influence of hydrodynamic force and the self-migration of Microcystis on the vertical concentration distribution of the Microcystis population. It can better reflect the distribution of the Microcystis population along the water depth direction, and greatly reduces the calculation amount compared with two-dimensional and three-dimensional mathematical models; using the method of single variable to analyze the influence of different factors on the vertical distribution of the Microcystis population can identify the contribution degree of each factor, which is helpful to understand the mechanism of algal bloom outbreak.

[0087] In an embodiment of the present invention, the hydrodynamic model can be expressed as:

[0088]

[0089] where g is the acceleration due to gravity, and the unit is m / s 2, where \(t\) is time in seconds (\(s\)), \(u\) is the water flow velocity in meters per second (\(m / s\)), \(\zeta\) is the water level in meters (\(m\)), \(\nu\) is the kinematic viscosity of water in square meters per second (\(m^2 / s\)), and \(\lambda\) is the turbulent diffusion coefficient in meters per second (\(m / s\)). 2 / s, \(x\) is the lateral position of Microcystis in a preset three-dimensional coordinate system in meters (\(m\)), \(y\) is the longitudinal position of Microcystis in the preset three-dimensional coordinate system in meters (\(m\)), and \(z\) is the depth position of Microcystis in the preset three-dimensional coordinate system, which is equal to the water depth position of Microcystis, in meters (\(m\)). 2 / s, \(x\) is the lateral position of Microcystis in a preset three-dimensional coordinate system in meters (\(m\)), \(y\) is the longitudinal position of Microcystis in the preset three-dimensional coordinate system in meters (\(m\)), and \(z\) is the depth position of Microcystis in the preset three-dimensional coordinate system, which is equal to the water depth position of Microcystis, in meters (\(m\)).

[0090] Among them, the position of Microcystis can be represented by a preset three-dimensional coordinate system. In this three-dimensional coordinate system, the \(x\)-axis can be used to represent the lateral direction parallel to the water surface, the \(y\)-axis can be used to represent the longitudinal direction parallel to the water surface, and the \(z\)-axis can be used to represent the depth direction perpendicular to the water surface.

[0091] Furthermore, since there are three variables, namely the water flow velocity \(u\), the kinematic viscosity of water \(\nu\), and the turbulent diffusion coefficient \(\lambda\) in the hydrodynamic model, the hydrodynamic model cannot be directly solved. Therefore, it can be further solved based on the k-ε equation.

[0092] Among them, assuming that the water flow is incompressible and the source-sink term is not considered, the k-ε equation is:

[0093]

[0094] Among them, \(k\) is the turbulent kinetic energy in square meters per second (\(m^2 / s\)), 2 / s 2 , \(\varepsilon\) is the dissipation rate of the turbulent kinetic energy in cubic meters per second (\(m^3 / s\)), 2 / s 3 , \(\sigma\) k is the Prandtl number corresponding to the turbulent kinetic energy, \(\sigma\) ε is the Prandtl number corresponding to the dissipation rate of the turbulent kinetic energy. The Prandtl number represents a dimensionless number that reflects the mutual influence of the energy and momentum transfer processes in a fluid. \(C_1\), \(C_2\), and \(C\) μ are empirical constants.

[0095] Specifically, the upper boundary condition of the hydrodynamic model is given by the wind stress and expressed as:

[0096]

[0097] \(\rho\) a is the air density, \(U\) 10 is the wind speed at a height of 10 m above the ground, and \(C\) D is the wind stress drag coefficient;

[0098] Among them, the wind stress drag coefficient is determined in the following way:

[0099]

[0100] Specifically, the upper and lower boundary conditions of the turbulent kinetic energy at z = 0 and z = h are as follows:

[0101]

[0102] The upper and lower boundary conditions of the dissipation rate of the turbulent kinetic energy at z = 0 and z = h are as follows:

[0103]

[0104] Thus, through the analysis of the hydrodynamic model, the expression of the turbulent diffusion coefficient λ can be obtained in the vertical direction when the water depth where the Microcystis is located is z, so as to further analyze the vertical distribution of the Microcystis population.

[0105] In an embodiment of the present invention, generally speaking, the change of the light intensity on the water surface at different times of a day is a sine function determined by the maximum light intensity at noon and the photoperiod, which can be expressed as:

[0106]

[0107] where I s is the light intensity on the water surface, I m is the maximum light intensity on the water surface within a day, and the unit of light intensity is μmol photons m -2 s -1 , D L is the sunshine duration, the unit is s, and t is the time, the unit is s.

[0108] Furthermore, the attenuation of the light intensity along the water depth follows the Lambert-Beer law:

[0109] I z = I s e -K×z

[0110] where I z is the light intensity function at the water depth z, and the unit of light intensity is μmol photons m -2 s -1 ; K is the extinction coefficient of the water body, the unit is 1 / m; z is the water depth where the Microcystis is located, the unit is m;

[0111] If simulating the change of the Microcystis concentration for consecutive days, combining the periodic change of the light intensity on the water surface and the exponential attenuation of the underwater light intensity, the light intensity function at different water depths is adjusted as follows:

[0112]

[0113] where mod represents the modulo operator.

[0114] In specific implementation, considering the time-delay effect of the change in cell density, the cell density change rate is as follows:

[0115]

[0116] Among them, the Microcystis colony consists of two parts: single cells and extracellular polysaccharides. The density of extracellular polysaccharides is generally constant. Assuming that the cell volume fraction and pseudo-vacuole volume fraction in the Microcystis colony remain unchanged, the change in the density of the Microcystis colony is determined by the change in the density of single cells. Light is the decisive factor affecting the change in the cell density of Microcystis, mainly including two forms: the carbohydrates synthesized by photosynthesis during the day increase the cell density, and the consumption of carbohydrates at night decreases the cell density. By setting different light conditions, the change in the carbohydrate content in Microcystis is measured.

[0117]

[0118] is the cell density change rate considering the time-delay effect, with the unit of kg m -3 s -1 ; is the cell density change rate without considering the time-delay effect, with the unit of kg m -3 s -1 , τr is the reaction time, with the unit of s, I c is the compensation light intensity, and the unit of light intensity is μmol photons m -2 s -1 ; ρ i is the cell density at the previous time step. The unit is kg m -3 , and a, b, c, and d are constants.

[0119] The cell density ρ cell and the population density ρ col are related as follows:

[0120] ρ col = ρ cell n cell (1 - n gas ) + ρ muc (1 - n cell )

[0121] Among them, n cell represents the cell volume fraction, n gas represents the pseudo-vacuole volume fraction, and ρ muc represents the mucus density, with the unit of kg m -3 . It should be noted that the cell volume fraction n cell , the pseudo-vacuole volume fraction n gas , and the mucus density ρ mucThe value of is not specifically restricted here and is determined according to actual application requirements.

[0122] Therefore, the density change model is:

[0123]

[0124] Integrating the above formula, the density change model can be obtained as:

[0125]

[0126] Among them, I z is the light intensity function at water depth z, I c is the compensation light intensity, I0 is the light intensity when the cell density reaches the maximum value, and the unit of light intensity is μmol photons m -2 s -1 ; ρ cell is the cell density, and the unit is kg m -3 ; is the cell density change rate considering the time-delay effect, and the unit is kg m -3 s -1 ; ρ col is the Microcystis colony density, and the unit is kg m -3 ; ρ muc is the Microcystis mucus density, and the unit is kg m -3 ; n cell is the cell volume fraction, n gas is the pseudo-vacuole volume fraction, and a, b, c, d are constants.

[0127] In an embodiment of the present invention, the self-migration model can be Stokes formula, which can be expressed as:

[0128]

[0129] Among them, w is the vertical self-migration rate of Microcystis, and the unit is m s -1 ; g is the acceleration of gravity, and the unit is m s -1 , D is the diameter of the Microcystis colony, and the unit is m; ρ col is the Microcystis colony density, and the unit is kg m -3 , ρ w is the water body density, and the unit is kg m -3 , μ is the water body viscosity coefficient, and the unit is m 2 s -1 , φ is the Microcystis colony shape coefficient.

[0130] In an embodiment of the present invention, it is assumed that the density of the ambient water body is constant along the water depth direction, the nutrient salts in the water body are sufficient, and the temperature is appropriate. Without considering the reproduction and death of Microcystis colonies, the change in the density of Microcystis colonies is only affected by light. The vertical migration of Microcystis colonies includes self-floating / sinking, self-diffusion, and the entrainment effect of water flow.

[0131] In this case, the Lagrangian particle model is as follows:

[0132]

[0133] where z(i,t) represents the position of the i-th Microcystis colony at time t, Δt represents the time step, λ' represents the gradient of the turbulent diffusion coefficient in the z direction of the preset three-dimensional coordinate system, R n is a random variable extracted from the standard normal distribution function, and w is the vertical migration rate of Microcystis itself.

[0134] As a specific example of the present invention, the effects of hydrodynamic force, colony size, and underwater light intensity on the vertical concentration distribution of Microcystis colonies can be analyzed one by one through the control variable method. For other parameters in the hydrodynamic model, self-migration model, and Lagrangian particle model that are irrelevant to hydrodynamic force, colony size, and underwater light intensity, fixed values can be assigned in advance, as shown in Table 1.

[0135] Table 1 Model parameter values

[0136]

[0137]

[0138] First, the effect of hydrodynamic force on the vertical concentration distribution of Microcystis colonies can be analyzed.

[0139] To clarify the effect of hydrodynamic force on the vertical concentration distribution of Microcystis colonies, numerical simulations are set for calculation conditions with different hydrodynamic parameters. Among them, the hydrodynamic parameters can include wind speed, which can be set to include 0.2 m / s, 1 m / s, 3 m / s, and 7 m / s, covering the cases from weak hydrodynamic force to strong hydrodynamic force. The colony size is uniformly taken as 400 μm, and the extinction coefficient is taken as 1.5. Substituting the model parameters into the hydrodynamic model, self-migration model, and Lagrangian particle model, the Figure 2 vertical concentration distribution of Microcystis colonies under different wind speed conditions as shown can be obtained. Among them, Figure 2 (a) is 0.2 m / s, Figure 2 (b) is 1 m / s, Figure 2 (c) is 3 m / s, Figure 2 (d) is 7 m / s. The horizontal axis is time (t), with the unit of hour (h), and the vertical axis is water depth (depth), with the unit of meter (m).

[0140] It can be seen that when the wind speed is low (0.2 m / s, 1 m / s), the vertical concentration distribution of Microcystis colonies is relatively concentrated, and the maximum concentration is located at about 2 m below the water surface. Field measured data also shows that the maximum concentration usually occurs below the water surface rather than at the water surface. The vertical concentration distribution of Microcystis colonies at a wind speed of 3 m / s is similar to that at wind speeds of 0.2 m / s and 1 m / s, except that the peak value of the maximum concentration decreases and the vertical distribution is more dispersed. Under the condition of a wind speed of 7 m / s, the water body is violently turbulent and the vertical concentration distribution of Microcystis colonies is uniform.

[0141] The simulation results explain that algal blooms usually occur in a weak hydrodynamic environment. At this time, the self-migration of Microcystis colonies plays a dominant role in the vertical concentration distribution and is prone to floating to the water surface to cause algal blooms. Under strong hydrodynamic conditions, the self-migration ability of Microcystis colonies cannot overcome the entrainment of the water flow. At this time, the hydrodynamic force plays a dominant role in the vertical concentration distribution of Microcystis colonies, and the vertical concentration distribution tends to be uniform, making it not easy to cause algal blooms.

[0142] Secondly, the influence of colony size on the vertical concentration distribution of Microcystis can be analyzed.

[0143] To clarify the influence of colony size on the vertical concentration distribution of Microcystis, the colony size parameter can include the colony size. Microcystis colonies with sizes of 50 μm, 200 μm, 400 μm, and 800 μm can be simulated and selected, covering the sizes of small, medium, and large colonies in the size distribution function. The wind speed is uniformly taken as 0.2 m / s, and the extinction coefficient is uniformly taken as 1.5. Substituting the model parameters into the hydrodynamic model, self-migration model, and Lagrangian particle model, we can obtain Figure 3 the vertical concentration distribution of Microcystis colonies of different sizes under weak hydrodynamic conditions. Among them, Figure 3 in (a) is 50 μm, Figure 3 in (b) is 200 μm, Figure 3 in (c) is 400 μm, Figure 3 in (d) is 800 μm. The horizontal axis is time (t), with the unit of hour (h), and the vertical axis is water depth (depth), with the unit of meter (m).

[0144] It can be seen that the vertical concentration of the 50-μm colonies is nearly uniformly distributed at any time. The Microcystis colonies of 200 μm, 400 μm, and 800 μm are mainly concentrated at about 2 m below the water surface. Among them, the 800-μm colonies have the most concentrated distribution and the largest concentration peak.

[0145] Under weak hydrodynamic conditions, the larger the size of Microcystis colonies, the stronger their self-migration ability. More Microcystis colonies can reach the optimal water depth, and the vertical distribution is more concentrated. The smaller the size of Microcystis colonies, the weaker their self-migration ability, and they are more easily affected by water flow mixing, resulting in a more uniform vertical concentration distribution. Thus, it can be seen that the colony size determines the vertical migration ability of Microcystis, thereby affecting the vertical concentration distribution.

[0146] Furthermore, the influence of underwater light intensity on the vertical concentration distribution of Microcystis colonies can be analyzed.

[0147] The extinction coefficient directly affects the underwater light intensity and the photosynthesis of Microcystis colonies, and further affects the density and vertical concentration distribution of Microcystis colonies. To clarify the influence of underwater light intensity on the vertical concentration distribution of Microcystis colonies, underwater light intensity parameters including the extinction coefficient can be set. The extinction coefficient can include extinction coefficients K = 1.0, 1.5, 2.0, and 3.0. The wind speed is uniformly taken as 0.2 m / s, and the colony size is uniformly taken as 400 μm. Substituting the model parameters into the hydrodynamic model, self-migration model, and Lagrangian particle model, we can obtain Figure 4 the vertical concentration distribution of Microcystis colonies under different extinction coefficient conditions. Among them, Figure 4 (a) is for K = 1.0, Figure 4 (b) is for K = 1.5, Figure 4 (c) is for K = 2.0, Figure 4 (d) is for K = 3.0. The horizontal axis is time (t), with the unit of hour (h), and the vertical axis is water depth (depth), with the unit of meter (m).

[0148] It can be seen from the simulation results that when the extinction coefficient K = 1.0, the position of the maximum concentration is at 3.0 - 3.5 m underwater. When the extinction coefficient K = 1.5, the position of the maximum concentration moves upward, to 2.0 - 2.5 m underwater. When the extinction coefficient K = 2.0, the position of the maximum concentration continues to move upward, located at 1.5 - 1.8 m underwater. When the extinction coefficient K = 3.0, the position of the maximum concentration is closest to the water surface, at 0.7 - 1.0 m underwater.

[0149] The underwater light intensity changes the position of the maximum concentration by affecting the density of Microcystis colonies. The larger the extinction coefficient, the weaker the underwater light intensity, the fewer ballast substances produced by the photosynthesis of Microcystis colonies, the lower the density, the overall upward migration of Microcystis colonies, and the closer the position of the maximum concentration is to the water surface.

[0150] It should be noted that for the method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should be aware that the embodiments of the present invention are not limited by the described action sequences, because according to the embodiments of the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential for the embodiments of the present invention.

[0151] Referring to Figure 5 , a structural block diagram of an apparatus for analyzing influencing factors of the vertical distribution of Microcystis colonies provided in an embodiment of the present invention is shown, which may specifically include the following modules:

[0152] A model construction module 501, configured to construct a Lagrangian particle model for simulating the vertical distribution of Microcystis colonies; the Lagrangian particle model is associated with a hydrodynamic model and its own migration model; the Lagrangian particle model is associated with hydrodynamic parameters and its own migration parameters;

[0153] A target parameter selection module 502, configured to select any one parameter from the hydrodynamic parameters and / or its own migration parameters as a target parameter;

[0154] A parameter value determination module 503, configured to keep the parameter values corresponding to the parameters other than the target parameter as fixed values, and determine multiple parameter values for the target parameter;

[0155] A distribution analysis module 504, configured to input the parameter values corresponding to the parameters other than the target parameter and the different parameter values corresponding to the target parameter into the hydrodynamic model, the self-migration model, and the Lagrangian particle model respectively, and determine the vertical distribution of Microcystis colonies under different parameter values;

[0156] An influence determination module 505, configured to determine the influence of the target parameter on the vertical distribution of Microcystis colonies based on the vertical distribution of Microcystis colonies under different parameter values.

[0157] Optionally, the hydrodynamic parameter is a turbulent diffusion coefficient; the hydrodynamic model is:

[0158]

[0159] where g is the acceleration due to gravity, t is time, u is the water flow velocity, ζ is the water level, ν is the kinematic viscosity of water, λ is the turbulent diffusion coefficient, x is the lateral position of Microcystis in a preset three-dimensional coordinate system, y is the longitudinal position of Microcystis in the preset three-dimensional coordinate system, and z is the depth position of Microcystis in the preset three-dimensional coordinate system, which is equal to the water depth position of Microcystis;

[0160] Among them, the hydrodynamic model is solved based on the k-ε equation, and the k-ε equation is as follows:

[0161]

[0162] Among them, k is the turbulent kinetic energy, ε is the dissipation rate of the turbulent kinetic energy, and σ k is the Prandtl number corresponding to the turbulent kinetic energy, and σ ε is the Prandtl number corresponding to the dissipation rate of the turbulent kinetic energy, and C1, C2, and C μ are empirical constants.

[0163] Optionally, the upper boundary condition of the hydrodynamic model is given by the wind stress and is expressed as:

[0164]

[0165] ρ a is the air density, U 10 is the wind speed at 10 m above the ground, and C D is the wind stress drag coefficient;

[0166] Among them, the wind stress drag coefficient is determined in the following manner:

[0167]

[0168] Optionally, the upper and lower boundary conditions of the turbulent kinetic energy are:

[0169]

[0170] The upper and lower boundary conditions of the dissipation rate of the turbulent kinetic energy are:

[0171]

[0172] Optionally, the self-migration parameter is the vertical migration rate of Microcystis itself, and the self-migration model is:

[0173]

[0174] Among them, w is the vertical migration rate of Microcystis itself, g is the acceleration due to gravity, D is the diameter of the Microcystis colony, ρ col is the density of the Microcystis colony, ρ w is the water density, μ is the water viscosity, and φ is the shape factor of the Microcystis colony.

[0175] Optionally, the density of the Microcystis colony is determined based on the density change model, and the density change model is:

[0176]

[0177] Among them,

[0178]

[0179] Among them, I z is the light intensity function at different water depths, I c is the compensation light intensity, I0 is the light intensity when the cell density reaches the maximum value, τr is the reaction time, ρ cell is the cell density of the said Microcystis, is the change rate of cell density considering the delay effect, ρ col is the population density of Microcystis, ρ muc is the mucus density of Microcystis, n cell is the cell volume fraction, n gas is the pseudo-vacuole volume fraction, and a, b, c, and d are constants.

[0180] Optionally, the relationship between the population density of the said Microcystis, the cell density of the said Microcystis, and the population density of the said Microcystis is:

[0181] ρ col = ρ cell n cell (1 - n gas ) + ρ muc (1 - n cell ).

[0182] Optionally, the change rate of cell density considering the delay effect is expressed as:

[0183]

[0184] Among them,

[0185] is the change rate of cell density without considering the delay effect, ρ i is the cell density at the previous time step, and a, b, c, and d are constants.

[0186] Optionally, the light intensity on the water surface is expressed as:

[0187]

[0188] Among them, I s is the light intensity on the water surface, I m is the maximum light intensity on the water surface within a day, D L is the sunshine duration.

[0189] Optionally, the attenuation of the light intensity along the water depth direction follows the Lambert-Beer law. When simulating the change of Microcystis concentration for consecutive days, considering the periodic change of the light intensity on the water surface and the exponential decay of the underwater light intensity, the light intensity function at different water depths is expressed as:

[0190]

[0191] Optionally, the Lagrangian particle model is as follows:

[0192]

[0193] where z(i,t) represents the position of the i-th Microcystis colony at time t, Δt represents the time step, λ' represents the gradient of the turbulent diffusion coefficient in the z direction of the preset three-dimensional coordinate system, R n is a random variable extracted from the standard normal distribution function, and w is the vertical migration rate of Microcystis itself.

[0194] For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple. For related parts, refer to the partial description of the method embodiment.

[0195] In addition, the embodiment of the present invention also provides an electronic device, as Figure 6 shown, including a processor 601, a communication interface 602, a memory 603, and a communication bus 604. Among them, the processor 601, the communication interface 602, and the memory 603 complete mutual communication through the communication bus 604.

[0196] The memory 603 is used to store a computer program;

[0197] When the processor 601 is used to execute the program stored in the memory 603, the following steps are implemented:

[0198] Construct a Lagrangian particle model for simulating the vertical distribution of Microcystis colonies; the Lagrangian particle model is associated with a hydrodynamic model and its own migration model; the Lagrangian particle model is associated with hydrodynamic parameters, colony size parameters, and underwater light intensity parameters;

[0199] Select any one of the hydrodynamic parameters, colony size parameters, and underwater light intensity parameters as the target parameter;

[0200] Keep the parameter values corresponding to the parameters other than the target parameter as fixed values, and determine multiple parameter values for the target parameter;

[0201] Input the parameter values corresponding to the parameters other than the target parameter and the different parameter values corresponding to the target parameter into the hydrodynamic model, its own migration model, and the Lagrangian particle model respectively, and determine the vertical distribution of Microcystis colonies under different parameter values;

[0202] Based on the vertical distribution of Microcystis colonies under different parameter values, determine the influence of the target parameter on the vertical distribution of Microcystis colonies.

[0203] The communication bus mentioned in the above terminal may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, only a thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0204] The communication interface is used for communication between the above terminal and other devices.

[0205] The memory may include a Random Access Memory (RAM), or may also include a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor.

[0206] The above-mentioned processor may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0207] As Figure 7 shown, in another embodiment provided by the present invention, there is also provided a computer-readable storage medium 701. Instructions are stored in this computer-readable storage medium. When it runs on a computer, it causes the computer to execute the method for analyzing the influencing factors of the vertical distribution of Microcystis colonies described in the above embodiment.

[0208] In another embodiment provided by the present invention, there is also provided a computer program product containing instructions. When it runs on a computer, it causes the computer to execute the method for analyzing the influencing factors of the vertical distribution of Microcystis colonies described in the above embodiment.

[0209] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)).

[0210] It should be noted that in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including", or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article, or device including a series of elements includes not only those elements, but also other elements not expressly listed, or elements inherent to such process, method, article, or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article, or device including the element.

[0211] Each embodiment in this specification is described in a related manner. The same or similar parts between the embodiments can be referred to each other, and the differences between each embodiment and other embodiments are emphasized. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiment.

[0212] The above are only the preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are all included within the protection scope of the present invention.

Claims

1. A method for analyzing the influencing factors of the vertical distribution of Microcystis colonies, characterized in that, Including: Constructing a Lagrangian particle model for simulating the vertical distribution of Microcystis colonies; the Lagrangian particle model is associated with a hydrodynamic model and its own migration model; the Lagrangian particle model is associated with hydrodynamic parameters, colony size parameters, and underwater light intensity parameters; Selecting any one of the hydrodynamic parameters, colony size parameters, and underwater light intensity parameters as the target parameter; Keeping the parameter values corresponding to the parameters other than the target parameter as fixed values, and determining multiple parameter values for the target parameter; Inputting the parameter values corresponding to the parameters other than the target parameter and the different parameter values corresponding to the target parameter into the hydrodynamic model, the self-migration model, and the Lagrangian particle model respectively to determine the vertical distribution of Microcystis colonies under different parameter values; Based on the vertical distribution of Microcystis colonies under different parameter values, determining the influence of the target parameter on the vertical distribution of Microcystis colonies; Among them, the hydrodynamic model is: Among them, g is the acceleration due to gravity, t is time, u is the water flow velocity, ζ is the water level, ν is the viscosity coefficient of water, λ is the turbulent diffusion coefficient, x is the lateral position of Microcystis in the preset three-dimensional coordinate system, y is the longitudinal position of Microcystis in the preset three-dimensional coordinate system, and z is the depth position of Microcystis in the preset three-dimensional coordinate system, which is equal to the water depth position of Microcystis; Among them, the self-migration model is: Among them, w is the vertical migration rate of Microcystis itself, g is the acceleration due to gravity, D is the diameter of the Microcystis colony, ρ col is the density of the Microcystis colony, ρ w is the density of the water body, μ is the viscosity coefficient of the water body, and φ is the shape coefficient of the Microcystis colony.

2. The method according to claim 1, wherein The hydrodynamic model is solved based on the k-ε equation, and the k-ε equation is: where k is the turbulent kinetic energy, ε is the dissipation rate of the turbulent kinetic energy, and σ k is the Prandtl number corresponding to the turbulent kinetic energy, and σ ε is the Prandtl number corresponding to the dissipation rate of the turbulent kinetic energy, and C1, C2, and C μ are empirical constants.

3. The method according to claim 2, characterized in that, The upper boundary condition of the hydrodynamic model is given by wind stress and is expressed as: ρ a is the air density, U 10 is the wind speed at 10 m altitude, C D is the wind stress drag coefficient; Among them, the wind stress drag coefficient is determined in the following way:

4. The method according to claim 2, wherein The upper and lower boundary conditions of the turbulent kinetic energy are: The upper and lower boundary conditions of the dissipation rate of the turbulent kinetic energy are:

5. The method according to claim 1, wherein The Microcystis colony density is determined based on the density change model, and the density change model is: Among them, where, I z is the light intensity function at different water depths, I c is the compensation light intensity, I0 is the light intensity when the cell density reaches the maximum value, τ r is the reaction time, ρ cell is the cell density of the Microcystis, is the change rate of cell density considering the time-delay effect, ρcol is the Microcystis colony density, ρmuc is the Microcystis mucus density, n cell is the cell volume fraction, n gas is the pseudo-vacuole volume fraction, and a, b, c, and d are constants.

6. The method according to claim 5, wherein The relationship between the Microcystis colony density and the cell density of Microcystis and the Microcystis colony density is: ρ col = ρ cell n cell (1 - n gas ) + ρ muc (1 - n cell )。 7. The method according to claim 5 or 6, characterized in that The cell density change rate considering the time-delay effect is expressed as: Among them, is the cell density change rate without considering the delay effect, ρi is the cell density at the previous time step, and a, b, c, and d are constants.

8. The method according to claim 5, wherein The light intensity on the water surface is expressed as: Among them, I s is the light intensity on the water surface, and I m is the maximum light intensity on the water surface within a day, and D L is the sunshine duration.

9. The method according to claim 8, characterized in that, The attenuation of the light intensity along the water depth direction follows the Lambert-Beer law. When simulating the change of Microcystis concentration for multiple consecutive days, considering the periodic change of the light intensity on the water surface and the exponential decay of the underwater light intensity, the light intensity function at different water depths is expressed as:

10. The method according to claim 1, characterized in that, The Lagrangian particle model is: Among them, \(z(i,t)\) represents the position of the \(i\)-th Microcystis colony at time \(t\), \(\Delta t\) represents the time step, \(\lambda'\) represents the gradient of the turbulent diffusion coefficient in the \(z\)-direction along the preset three-dimensional coordinate system, and \(R\) n is a random variable extracted from the standard normal distribution function, and \(w\) is the vertical migration rate of Microcystis itself.

11. An analysis device for influencing factors of the vertical distribution of Microcystis colonies, characterized in that, Including: A model construction module for constructing a Lagrangian particle model for simulating the vertical distribution of Microcystis colonies; the Lagrangian particle model is associated with a hydrodynamic model and its own migration model; the Lagrangian particle model is associated with hydrodynamic parameters and self-migration parameters; A target parameter selection module for selecting any one of the hydrodynamic parameters and / or self-migration parameters as the target parameter; A parameter value determination module for keeping the parameter values corresponding to the parameters other than the target parameter as fixed values, and determining multiple parameter values for the target parameter; A distribution analysis module, configured to input the parameter values corresponding to the parameters other than the target parameter and the different parameter values corresponding to the target parameter into the hydrodynamic model, the self-migration model, and the Lagrangian particle model respectively, and determine the vertical distribution of the Microcystis population under different parameter values; An influence determination module, configured to determine the influence of the target parameter on the vertical distribution of the Microcystis population based on the vertical distribution of the Microcystis population under different parameter values; wherein, the hydrodynamic model is: wherein, g is the acceleration due to gravity, t is time, u is the water flow velocity, ζ is the water level, ν is the viscosity coefficient of water, λ is the turbulent diffusion coefficient, x is the lateral position of Microcystis in a preset three-dimensional coordinate system, y is the longitudinal position of Microcystis in the preset three-dimensional coordinate system, and z is the depth position of Microcystis in the preset three-dimensional coordinate system, which is equal to the water depth position of Microcystis; wherein, the self-migration model is: Among them, w is the vertical migration rate of Microcystis itself, g is the acceleration due to gravity, D is the diameter of the Microcystis colony, ρ col is the density of the Microcystis colony, ρ w is the density of the water body, μ is the viscosity coefficient of the water body, and φ is the shape coefficient of the Microcystis colony.

12. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus; The memory is used to store computer programs; When the processor executes the program stored on the memory, it implements the method described in any one of claims 1-10.

13. A computer-readable medium, on which instructions are stored, and when executed by one or more processors, cause the processors to execute the method described in any one of claims 1-10.

14. A computer program product, comprising a computer program / instructions, characterized in that, The steps of the method described in any one of claims 1-10 are implemented when the computer program / instructions are executed by a processor.

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