Microcystis population vertical distribution influence factor analysis method

Abstract

The embodiment of the invention provides a method for analyzing influence factors of vertical distribution of a microcystis group. The method comprises the following steps: constructing a Lagrange particle model for simulating vertical distribution of the microcystis group; any parameter is selected from the hydrodynamic parameters and / or the self-migration parameters to serve as a target parameter; keeping parameter values corresponding to parameters except the target parameter as fixed values, and determining a plurality of parameter values for the target parameter; respectively inputting parameter values corresponding to parameters except the target parameters and different parameter values corresponding to the target parameters into a hydrodynamic model, a self-migration model and a Lagrange particle model, and determining vertical distribution of microcystis groups under different parameter values; and determining 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. And a control variable method is adopted to identify the contribution degree of each factor, so that understanding of a water bloom outbreak mechanism is facilitated.

Description

Technical Field

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

[0002] Microcystis is a globally widespread species of cyanobacteria that causes algal blooms. It is also the main component of the most common cyanobacteria blooms in eutrophic water bodies in my country. It is a photoautotrophic prokaryotic organism. Microcystis usually exists in single cells and colonies in environmental water bodies. There are many cylindrical pseudocavities in Microcystis cells, which can provide buoyancy for them. Microcystis cells also contain ballasts such as proteins, sugars, nucleic acids, and glycolipids, all of which have a density greater than water. During the day, algal cells carry out photosynthesis, which increases the content of ballast. The buoyancy provided by the pseudocavities is not enough to offset the accumulation of ballast, and the algal cells will sink; when the light intensity decreases, respiration is greater than photosynthesis, consuming sugar substances in the cells, reducing the cell density, and causing the algal cells to float, so there is a saying that "sinks during the day and floats at night."

[0003] In eutrophic water bodies, the vertical distribution of Microcystis colonies is the key to water blooms, and there are many factors that affect the vertical distribution of Microcystis colonies, including the characteristics of the Microcystis colonies themselves and external environmental factors. Clarifying the impact of characteristic factors on the vertical distribution of Microcystis colonies will help understand the mechanism of water blooms, thereby providing a decision-making basis for water bloom prevention and control. Existing methods can only simulate the distribution of Microcystis colonies, but cannot reflect the degree of influence of characteristic factors on the distribution of Microcystis colonies. Summary of the invention

[0004] The embodiment of the present invention provides a method for analyzing factors affecting the vertical distribution of a Microcystis population, so as to solve the problem that it is difficult to determine the factors affecting the vertical distribution of a Microcystis population.

[0005] The embodiment of the present invention discloses a method for analyzing factors affecting the vertical distribution of a Microcystis population, comprising:

[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 a self-migration model; the Lagrangian particle model is associated with a hydrodynamic parameter, a colony size parameter, and an underwater light intensity parameter;

[0007] Select any parameter from the hydrodynamic parameter, the group size parameter, and the underwater light intensity parameter as the target parameter;

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

[0009] Inputting parameter values ​​corresponding to parameters other than the target parameter and 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;

[0010] Based on the vertical distribution of the Microcystis population under the different parameter values, the influence of the target parameter on the vertical distribution of the Microcystis population is determined.

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

[0012]

[0013] Wherein, g is the acceleration due to gravity, t is the time, u is the water 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;

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

[0015]

[0016] Where k is the turbulent kinetic energy, ε is the dissipation rate of 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 turbulent kinetic energy, C1, C2 and C μ is an empirical constant.

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

[0018]

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

[0020] Wherein, 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:

[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 of gravity, D is the diameter of the Microcystis colony, ρ col is the population density of Microcystis, ρ w is the water density, μ is the water viscosity coefficient, and φ is the shape coefficient of the Microcystis colony.

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

[0030]

[0031] in,

[0032]

[0033] Among them, I z is the light intensity function at different water depths, I c To compensate for the 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 cell density change rate considering the delayed effect, ρ col is the population density of Microcystis, ρ muc is the density of Microcystis mucus, n cell is the cell volume fraction, n gas is the volume fraction of pseudo-voids, and a, b, c, and d are constants.

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

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

[0036] Optionally, the cell density change rate considering the delayed effect is expressed as:

[0037]

[0038] in,

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

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

[0041]

[0042] Among them, I s is the light intensity on the water surface, I m is the maximum light intensity on the water surface in one day, D L The duration of sunshine.

[0043] Optionally, the attenuation of the light intensity along the water depth direction follows the Lambert-Beer law. When simulating the change in the concentration of Microcystis for several consecutive days, combined with 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] 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 along the z direction in 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.

[0048] The embodiment of the present invention further provides a device for analyzing factors affecting the vertical distribution of a Microcystis colony, comprising:

[0049] A model building module is used to build a Lagrangian particle model for simulating the vertical distribution of the Microcystis colony; 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;

[0050] A target parameter selection module is used to select any parameter from the hydrodynamic parameters and / or the self-migration parameters as a target parameter;

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

[0052] A distribution analysis module, for inputting parameter values ​​corresponding to parameters other than the target parameter and 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;

[0053] The impact determination module is used to determine the impact 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] The embodiment of the present invention further discloses an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0055] The memory is used to store computer programs;

[0056] The processor is used to implement the method described in the embodiment of the present invention when executing the program stored in the memory.

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

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

[0059] Through the method for analyzing factors affecting the vertical distribution of the Microcystis population provided by the embodiment 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 a hydrodynamic parameter and a self-migration parameter; any parameter is selected from the hydrodynamic parameter and / or the self-migration parameter as a target parameter; the parameter value corresponding to the parameter other than the target parameter is kept as a fixed value, and multiple parameter values ​​are determined for the target parameter; the parameter value corresponding to the parameter 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 the Microcystis population under different parameter values; based on the vertical distribution of the Microcystis population under the different parameter values, the influence of the target parameter on the vertical distribution of the Microcystis population is determined. Therefore, based on the mathematical model of the vertical distribution of the Microcystis population, the embodiment of the present invention adopts the control variable method to analyze the influence of hydrodynamics and self-migration of Microcystis on the vertical concentration distribution of the Microcystis population. It can better reflect the distribution of Microcystis groups along the water depth direction, and greatly reduces the amount of calculation compared with two-dimensional and three-dimensional mathematical models. The single variable method is used to analyze the influence of different factors on the vertical distribution of Microcystis groups, which can identify the contribution of each factor and help understand the mechanism of water bloom outbreaks. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a flowchart of the steps of a method for analyzing factors affecting the vertical distribution of a Microcystis population provided in an embodiment 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 an embodiment of the present invention;

[0062] Figure 3 Schematic diagram of vertical concentration distribution of Microcystis colonies of different sizes under weak hydrodynamic conditions provided in an embodiment of the present invention;

[0063] Figure 4 Schematic diagram of vertical concentration distribution of Microcystis colony under different extinction coefficient conditions provided in the embodiments of the present invention;

[0064] Figure 5 It is a structural block diagram of a device for analyzing factors affecting vertical distribution of a Microcystis colony provided in an embodiment of the present invention;

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

[0066] Figure 7 is a schematic diagram of a computer-readable medium provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0067] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0068] Reference Figure 1 , shows a flowchart of the steps of a method for analyzing factors affecting the vertical distribution of a Microcystis population provided in an embodiment of the present invention, which may specifically include the following steps:

[0069] Step 101, constructing a Lagrangian particle model for simulating the vertical distribution of a Microcystis colony; the Lagrangian particle model is associated with a hydrodynamic model and a self-migration model; the Lagrangian particle model is associated with a hydrodynamic parameter, a colony size parameter, and an underwater light intensity parameter;

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

[0071] Among them, hydrodynamic models can be used to simulate and predict fluid dynamics behaviors in water bodies, including the speed, direction, eddies, turbulence, etc. For example, turbulence can promote the mixing and diffusion of Microcystis, and hydrodynamic models can simulate the effects 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, we can know how Microcystis itself changes in the vertical direction.

[0073] The Lagrangian particle model can comprehensively obtain the vertical distribution of the Microcystis population based on the analysis results of the hydrodynamic model and its own migration model, thereby understanding the distribution changes of the Microcystis population in the vertical direction.

[0074] In order to calculate the vertical distribution of the Microcystis colony, the Lagrangian particle model can be associated with a hydrodynamic parameter, a colony size parameter, and an underwater light intensity parameter. The hydrodynamic parameter, the colony size parameter, and the underwater light intensity parameter can be at least one parameter in the hydrodynamic model and the self-migration model that needs to be used in the calculation and analysis process. Since the calculation process of the Lagrangian particle model is associated with the hydrodynamic model and the self-migration model, the changes in the hydrodynamic parameter, the colony size parameter, and the underwater light intensity parameter can affect the output of the Lagrangian particle model.

[0075] Step 102, selecting any parameter from the hydrodynamic parameters and / or the self-migration parameters as a target parameter;

[0076] In an embodiment of the present invention, in order to better analyze the vertical distribution of the Microcystis population, a control variable method can be used to control the Lagrangian particle model, the hydrodynamic model associated with the Lagrangian particle model, and the self-migration model to change in a single dimension, so that the influence of different factors on the vertical distribution of the Microcystis population can be analyzed separately, and the contribution of each factor can be identified, which is helpful to understand the mechanism of water bloom outbreaks.

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

[0078] Step 103, maintaining parameter values ​​corresponding to parameters other than the target parameter as fixed values, and determining multiple parameter values ​​for the target parameter;

[0079] Afterwards, the corresponding parameter values ​​of other parameters other than the target parameter can be kept unchanged, that is, kept as fixed values, and multiple parameter values ​​can be determined for the target parameter. Thus, a single variable control method can be adopted to observe the changes in the vertical distribution of the Microcystis population through different parameter values ​​for the target parameter, so as to know the influence of the target parameter on the vertical distribution of the Microcystis population.

[0080] Step 104, inputting parameter values ​​corresponding to parameters other than the target parameter and 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;

[0081] In the specific implementation, the parameter values ​​of the parameters other than the target parameters input into the hydrodynamic model, the self-migration model, and the Lagrangian particle model are kept unchanged, while the target parameters are input into the hydrodynamic model, the self-migration model, and the Lagrangian particle model using different parameter values, so that the vertical distribution of the Microcystis population under different parameter values ​​for the target parameters can be obtained.

[0082] Step 104: determining the influence of the target parameter on the vertical distribution of the Microcystis population based on the vertical distribution of the Microcystis population under the different parameter values.

[0083] When the vertical distribution of the Microcystis population under different parameter values ​​corresponding to the target parameter is analyzed, the influence of the target parameter on the vertical distribution of the Microcystis population can be obtained according to the change of the vertical distribution of the Microcystis population following the target parameter.

[0084] Specifically, the hydrodynamic parameters can affect the vertical distribution of the Microcystis colony by affecting the dominant factors of the vertical distribution of the Microcystis colony. Specifically, in a weak hydrodynamic environment, the migration of the Microcystis colony itself plays a dominant role in the vertical concentration distribution, and it is easy to float to the water surface and bloom. Under strong hydrodynamic conditions, the migration ability of the Microcystis colony itself cannot overcome the entrainment of the water flow. At this time, the hydrodynamics plays a dominant role in the vertical concentration distribution of the Microcystis colony, and the vertical concentration distribution tends to be uniform, and it is not easy to bloom.

[0085] The self-migration parameter can affect the vertical distribution of the Microcystis colony by affecting the self-migration ability of the Microcystis colony. Specifically, under weak hydrodynamic conditions, the larger the size of the Microcystis colony, the stronger the self-migration ability, the more Microcystis colonies that can reach the optimal water depth, and the more concentrated the vertical distribution; the smaller the size of the Microcystis colony, the weaker the self-migration ability, the more easily it is affected by water mixing, and the more uniform the vertical concentration distribution.

[0086] Through the method for analyzing factors affecting the vertical distribution of the Microcystis population provided by the embodiment 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 a hydrodynamic parameter and a self-migration parameter; any parameter is selected from the hydrodynamic parameter and / or the self-migration parameter as a target parameter; the parameter value corresponding to the parameter other than the target parameter is kept as a fixed value, and multiple parameter values ​​are determined for the target parameter; the parameter value corresponding to the parameter 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 the Microcystis population under different parameter values; based on the vertical distribution of the Microcystis population under the different parameter values, the influence of the target parameter on the vertical distribution of the Microcystis population is determined. Therefore, based on the mathematical model of the vertical distribution of the Microcystis population, the embodiment of the present invention adopts the control variable method to analyze the influence of hydrodynamics and self-migration of Microcystis on the vertical concentration distribution of the Microcystis population. It can better reflect the distribution of Microcystis groups along the water depth direction, and greatly reduces the amount of calculation compared with two-dimensional and three-dimensional mathematical models. The single variable method is used to analyze the influence of different factors on the vertical distribution of Microcystis groups, which can identify the contribution of each factor and help understand the mechanism of water bloom outbreaks.

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

[0088]

[0089] Where g is the acceleration due to gravity, in m / s 2, t is time, unit is s, u is water velocity, unit is m / s, ζ is water level, unit is m, ν is water viscosity coefficient, unit is m 2 / s, λ is the turbulent diffusion coefficient, unit is m 2 / s, x is the lateral position of Microcystis in the preset three-dimensional coordinate system, the unit is m, y is the longitudinal position of Microcystis in the preset three-dimensional coordinate system, the unit is 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, the unit is m.

[0090] The position of the Microcystis can be represented by a preset three-dimensional coordinate system, in which the x-axis represents the lateral direction parallel to the water surface, the y-axis represents the longitudinal direction parallel to the water surface, and the z-axis represents the depth direction perpendicular to the water surface.

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

[0092] Assuming that the water flow is incompressible and ignoring the source and sink terms, the k-ε equation is:

[0093]

[0094] Where k is the turbulent kinetic energy, in m 2 / s 2 , ε is the dissipation rate of turbulent kinetic energy, unit is m 2 / s 3 , σ k is the Prandtl number corresponding to the turbulent kinetic energy, σ ε is the Prandtl number corresponding to the dissipation rate of turbulent kinetic energy. The Prandtl number represents the dimensionless number of the mutual influence of energy and momentum transfer processes in the fluid. C1, C2 and C μ is an empirical constant.

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

[0096]

[0097] ρ a is the air density, U 10 is the wind speed at 10m above the ground, C D is the wind stress drag coefficient;

[0098] Wherein, the wind stress drag coefficient is determined in the following manner:

[0099]

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

[0101]

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

[0103]

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

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

[0106]

[0107] Among them, I s is the light intensity on the water surface, I m The maximum light intensity on the water surface in one day, the unit of light intensity is μmolphotonsm -2 s -1 , D L is the sunshine duration in seconds, and t is the time in seconds.

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

[0109] I z =I s e -K×z

[0110] Among them, I z is the light intensity function at water depth z, and the unit of light intensity is μmolphotonsm -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 the concentration change of Microcystis for several consecutive days is simulated, combined with the periodic change of light intensity on the water surface and the exponential decay of light intensity underwater, the light intensity function at different water depths is adjusted as follows:

[0112]

[0113] Here, mod represents the modulus operator.

[0114] In the specific implementation, considering that the cell density change has a delayed effect, the cell density change rate is:

[0115]

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

[0117]

[0118] is the rate of change of cell density considering the delayed effect, in kg m -3 s -1 ;, is the cell density change rate without considering the delayed effect, in kg m -3 s -1 , τr is the reaction time, in seconds, I c To compensate for light intensity, the unit of light intensity is μmolphotonsm -2 s -1 ρ i is the cell density at the previous time step. The unit is kg m -3 , a, b, c, d are constants.

[0119] Cell density cell and population density ρ col The relationship between them is:

[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-void volume fraction, ρ muc Represents the density of mucus in kgm -3 It should be noted that the cell volume fraction n cell , pseudo-void volume fraction n gas , mucus density ρ mucThere is no specific restriction on the value of , which is determined based on actual application requirements.

[0122] Therefore, the density change model is:

[0123]

[0124] By integrating the above formulas, we can get the density change model:

[0125]

[0126] Among them, I z is the light intensity function at water depth z, I c To compensate for light intensity, I0 is the light intensity when the cell density reaches the maximum value, and the unit of light intensity is μmolphotonsm -2 s -1 ρ cell is the cell density, in kg m -3 ; is the rate of change of cell density considering the delayed effect, in kg m -3 s -1 ρ col is the density of Microcystis population, in kg m -3 ρ muc is the density of Microcystis mucus, in kg m -3 ;n cell is the cell volume fraction, n gas is the volume fraction of pseudo-voids, and a, b, c, and d are constants.

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

[0128]

[0129] Where w is the vertical migration rate of Microcystis itself, in ms -1 ; g is the acceleration due to gravity, in ms -1 , D is the diameter of the Microcystis colony, in m; ρ col is the density of Microcystis population, in kg m -3 , ρ w is the water density, in kg m -3 , μ is the viscosity coefficient of water, unit is m 2 s -1 , φ is the shape coefficient of Microcystis colony.

[0130] In one embodiment of the present invention, it is assumed that the density of the environmental water body remains constant along the water depth direction, the water body contains sufficient nutrients, and the temperature is suitable. The reproduction and death of the Microcystis colony are not considered, and the density change of the Microcystis colony is only affected by light. The vertical migration of the Microcystis colony includes self-floating / sinking, self-diffusion, and water flow entrainment.

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

[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 along the z direction in 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.

[0134] As a specific example of the present invention, the influence of hydrodynamic force, group size and underwater light intensity on the vertical concentration distribution of Microcystis group can be analyzed one by one by the control variable method. For the hydrodynamic model, the self-migration model, and other parameters in the Lagrangian particle model that are not related to the hydrodynamic force, group 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 hydrodynamics on the vertical concentration distribution of Microcystis colonies can be analyzed.

[0139] In order to clarify the influence of hydrodynamics on the vertical concentration distribution of Microcystis colonies, numerical simulations were performed with different hydrodynamic parameters. The hydrodynamic parameters can include wind speed, which can be set to 0.2m / s, 1m / s, 3m / s and 7m / s, covering the cases of weak to strong hydrodynamics. The colony size was uniformly set to 400μm, and the extinction coefficient was set to 1.5. Substituting the model parameters into the hydrodynamic model, self-migration model, and Lagrangian particle model, we can obtain Figure 2 The vertical concentration distribution of Microcystis colonies under different wind speed conditions is shown in the figure. Figure 2 (a) is 0.2m / s, Figure 2 (b) is 1m / s, Figure 2 (c) is 3m / s, Figure 2 The horizontal axis is time (t), the unit is hour (h), and the vertical axis is water depth (depth), the unit is meter (m).

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

[0141] The simulation results explain that algal blooms usually occur in weak hydrodynamic environments, when the migration of the Microcystis colony itself plays a dominant role in the vertical concentration distribution, and it is easy to float to the water surface and bloom. Under strong hydrodynamic conditions, the migration ability of the Microcystis colony itself cannot overcome the entrainment of the water flow. At this time, hydrodynamics plays a dominant role in the vertical concentration distribution of the Microcystis colony, and the vertical concentration distribution tends to be uniform, making it difficult for algal blooms to occur.

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

[0143] In order to clarify the effect of population size on the vertical concentration distribution of Microcystis, the population size parameter can include the population size, which can simulate the selection of 50μm, 200μm, 400μm and 800μm Microcystis populations, covering the sizes of small, medium and large populations in the size distribution function. The wind speed is uniformly taken as 0.2m / 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 get Figure 3 Vertical concentration distribution of Microcystis colonies of different sizes under weak hydrodynamic conditions. Figure 3 (a) is 50 μm, Figure 3 (b) is 200 μm, Figure 3 (c) is 400 μm, Figure 3 The horizontal axis is time (t), the unit is hour (h), and the vertical axis is water depth (depth), the unit is meter (m).

[0144] It can be seen that the vertical concentration of the 50μm group is close to uniform distribution at any time, and the 200μm, 400μm, and 800μm Microcystis groups are mainly concentrated about 2m underwater, among which the 800μm group is the most concentrated and has the largest concentration peak.

[0145] Under weak hydrodynamic conditions, the larger the size of the Microcystis colony, the stronger its migration ability, the more Microcystis colonies that can reach the optimal water depth, and the more concentrated the vertical distribution; the smaller the size of the Microcystis colony, the weaker its migration ability, the more easily it is affected by water mixing, and the more uniform the vertical concentration distribution. It can be seen that the colony size determines the vertical migration ability of Microcystis, thereby affecting the vertical concentration distribution.

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

[0147] The extinction coefficient directly affects the underwater light intensity and the photosynthesis of the Microcystis colony, and thus affects the density of the Microcystis colony and the vertical concentration distribution. In order to clarify the effect of underwater light intensity on the vertical concentration distribution of the Microcystis colony, the underwater light intensity parameters can be set to include the extinction coefficient, where the extinction coefficient can include the extinction coefficient K = 1.0, 1.5, 2.0 and 3.0, the wind speed is uniformly taken as 0.2m / s, and the colony size is uniformly taken as 400μm. Substituting the model parameters into the hydrodynamic model, the self-migration model, and the Lagrangian particle model, we can get Figure 4 Vertical concentration distribution of Microcystis colonies under different extinction coefficients. Figure 4 (a) is K = 1.0, Figure 4 (b) is K = 1.5, Figure 4 (c) is K = 2.0, Figure 4 (d) is K = 3.0. The horizontal axis is time (t), the unit is hour (h), and the vertical axis is water depth (depth), the unit is 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 3.0-3.5 m underwater. When the extinction coefficient K = 1.5, the position of the maximum concentration moves up to 2.0-2.5 m underwater. When the extinction coefficient K = 2.0, the position of the maximum concentration continues to move up to 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, located at 0.7-1.0 m underwater.

[0149] Underwater light intensity changes the position of the maximum concentration of Microcystis by affecting its population density. The larger the extinction coefficient, the weaker the underwater light intensity, the less ballast produced by photosynthesis of the Microcystis population, the lower the density, the Microcystis population as a whole migrates upward, and the maximum concentration position is closer to the water surface.

[0150] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders 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 required by the embodiments of the present invention.

[0151] Reference Figure 5 , shows a structural block diagram of a device for analyzing factors affecting vertical distribution of a Microcystis colony provided in an embodiment of the present invention, which may specifically include the following modules:

[0152] The model building module 501 is used to build a Lagrangian particle model for simulating the vertical distribution of the Microcystis colony; 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;

[0153] A target parameter selection module 502 is used to select any parameter from the hydrodynamic parameters and / or the self-migration parameters as a target parameter;

[0154] A parameter value determination module 503, used 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] The distribution analysis module 504 is used to input parameter values ​​corresponding to parameters other than the target parameter and 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;

[0156] The impact determination module 505 is used to determine the impact 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.

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

[0158]

[0159] Wherein, g is the acceleration due to gravity, t is the time, u is the water 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;

[0160] The hydrodynamic model is solved based on the k-ε equation, which is:

[0161]

[0162] Where k is the turbulent kinetic energy, ε is the dissipation rate of 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 turbulent kinetic energy, C1, C2 and C μ is an empirical constant.

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

[0164]

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

[0166] Wherein, 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] Where w is the vertical migration rate of Microcystis itself, g is the acceleration of gravity, D is the diameter of the Microcystis colony, ρ col is the population density of Microcystis, ρ w is the water density, μ is the water viscosity coefficient, and φ is the shape coefficient of the Microcystis colony.

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

[0176]

[0177] in,

[0178]

[0179] Among them, I z is the light intensity function at different water depths, I c To compensate for the 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 Microcystis, is the cell density change rate considering the delayed effect, ρ col is the population density of Microcystis, ρ muc is the density of Microcystis mucus, n cell is the cell volume fraction, n gas is the volume fraction of pseudo-voids, and a, b, c, and d are constants.

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

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

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

[0183]

[0184] in,

[0185] is the cell density change rate without considering the delayed 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 at 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 in one day, D L The duration of sunshine.

[0189] Optionally, the attenuation of the light intensity along the water depth direction follows the Lambert-Beer law. When simulating the change in the concentration of Microcystis for several consecutive days, combined with 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:

[0190]

[0191] Optionally, the Lagrangian particle model is:

[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 along the z direction in 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.

[0194] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0195] In addition, an embodiment of the present invention further provides an electronic device, such as Figure 6 As shown, it includes a processor 601, a communication interface 602, a memory 603 and a communication bus 604, wherein the processor 601, the communication interface 602, and the memory 603 communicate with each other through the communication bus 604.

[0196] Memory 603, used for storing computer programs;

[0197] The processor 601 is used to execute the program stored in the memory 603 to implement the following steps:

[0198] Constructing a Lagrangian particle model for simulating the vertical distribution of Microcystis colonies; the Lagrangian particle model is associated with a hydrodynamic model and a self-migration model; the Lagrangian particle model is associated with a hydrodynamic parameter, a colony size parameter, and an underwater light intensity parameter;

[0199] Select any parameter from the hydrodynamic parameter, the group size parameter, and the underwater light intensity parameter as the target parameter;

[0200] Maintaining parameter values ​​corresponding to parameters other than the target parameter as fixed values, and determining multiple parameter values ​​for the target parameter;

[0201] Inputting parameter values ​​corresponding to parameters other than the target parameter and 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;

[0202] Based on the vertical distribution of the Microcystis population under the different parameter values, the influence of the target parameter on the vertical distribution of the Microcystis population is determined.

[0203] The communication bus mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one 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 a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0206] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can 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 gates or transistor logic devices, discrete hardware components.

[0207] like Figure 7 As shown, in another embodiment provided by the present invention, a computer-readable storage medium 701 is also provided, and the computer-readable storage medium stores instructions. When the computer-readable storage medium is run on a computer, the computer executes the method for analyzing factors affecting the vertical distribution of the Microcystis population described in the above embodiment.

[0208] In another embodiment provided by the present invention, a computer program product comprising instructions is also provided, which, when executed on a computer, enables the computer to execute the method for analyzing factors affecting the vertical distribution of a Microcystis population 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 by 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 process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., 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 available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk SolidStateDisk (SSD)), etc.

[0210] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are 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 explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0211] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. 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 partial description of the method embodiment.

[0212] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A method for analyzing factors affecting the vertical distribution of Microcystis populations, characterized in that: include: Constructing a Lagrangian particle model for simulating the vertical distribution of Microcystis colonies; the Lagrangian particle model is associated with a hydrodynamic model and a self-migration model; the Lagrangian particle model is associated with a hydrodynamic parameter, a colony size parameter, and an underwater light intensity parameter; Select any parameter from the hydrodynamic parameter, the group size parameter, and the underwater light intensity parameter as the target parameter; Maintaining parameter values ​​corresponding to parameters other than the target parameter as fixed values, and determining multiple parameter values ​​for the target parameter; Inputting parameter values ​​corresponding to parameters other than the target parameter and 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 the different parameter values, the influence of the target parameter on the vertical distribution of the Microcystis population is determined.

2. The method according to claim 1, characterized in that The hydrodynamic model is: Wherein, g is the acceleration due to gravity, t is the time, u is the water 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; The hydrodynamic model is solved based on the k-ε equation, which is: Where k is the turbulent kinetic energy, ε is the dissipation rate of 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 turbulent kinetic energy, C1, C2 and C μ is an empirical constant.

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 10m above the ground, C D is the wind stress drag coefficient; The wind stress drag coefficient is determined in the following manner:

4. The method according to claim 2, characterized in that: 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, characterized in that: The self-migration parameters include: the self-migration model is: Where w is the vertical migration rate of Microcystis itself, g is the acceleration of gravity, D is the diameter of the Microcystis colony, ρ col is the population density of Microcystis, ρ w is the water density, μ is the water viscosity coefficient, and φ is the shape coefficient of the Microcystis colony.

6. The method according to claim 5, characterized in that The density of the Microcystis colony is determined based on a density variation model, and the density variation model is: in, Among them, I z is the light intensity function at different water depths, I c To compensate for the 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 cell density change rate considering the delayed effect, ρ col is the population density of Microcystis, ρ muc is the density of Microcystis mucus, n cell is the cell volume fraction, n gas is the volume fraction of pseudo-voids, and a, b, c, and d are constants.

7. The method according to claim 6, characterized in that The relationship between the Microcystis population density, the Microcystis cell density and the Microcystis population density is: r col =ρ cell n cell (1-n gas )+r muc (1-n cell )。 8. The method according to claim 6 or 7, characterized in that: The cell density change rate considering the delayed effect is expressed as: in, is the cell density change rate without considering the delayed effect, ρ i is the cell density at the previous time step, and a, b, c, and d are constants.

9. The method according to claim 6, characterized in that: The light intensity on the water surface is expressed as: Among them, I s is the light intensity on the water surface, I m is the maximum light intensity on the water surface in one day, D L The duration of sunshine.

10. The method according to claim 9, 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 many consecutive days, combined with 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 expressed as:

11. The method according to claim 1, characterized in that: The Lagrangian particle model is: 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 along the z direction in 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.

12. A device for analyzing factors affecting the vertical distribution of Microcystis colonies, characterized in that: include: A model building module is used to build a Lagrangian particle model for simulating the vertical distribution of the Microcystis colony; 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; A target parameter selection module is used to select any parameter from the hydrodynamic parameters and / or the self-migration parameters as a target parameter; a parameter value determination module, used to keep parameter values ​​corresponding to parameters other than the target parameter as fixed values, and to determine multiple parameter values ​​for the target parameter; A distribution analysis module, for inputting parameter values ​​corresponding to parameters other than the target parameter and 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; The impact determination module is used to determine the impact 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.

13. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; The memory is used to store computer programs; The processor is used to implement the method according to any one of claims 1 to 11 when executing the program stored in the memory.

14. A computer-readable medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform the method according to any one of claims 1 to 11.

15. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 11 are implemented.

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