Drifting roe survival prediction method applied to water flow submerging vegetation

Abstract

The embodiment of the invention discloses a drifting roe survival prediction method applied to vegetation submerging water flow, and relates to the technical field of biological monitoring, and the method comprises the steps: determining a to-be-researched region and a to-be-predicted target, and obtaining a roe parameter change curve, vegetation characteristic parameters and other influence parameters; determining input parameters of a current period, and performing calculation through a drifting roe survival prediction model: calculating the settling velocity of each roe, calculating coordinates based on the settling velocity, further determining roes settling to a riverbed, determining whether the settled roes are resuspended, updating the number of suspended roes, and predicting the survival of the drifting roes. Outputting a fish egg survival prediction result based on the ratio of the suspended fish egg number to the egg laying number; updating the parameters of the next period, and circularly calculating until the drifting time is greater than or equal to the hatching time threshold value. According to the method, systematic analysis is carried out by considering the water flow characteristics, the vegetation characteristics and the biological characteristics of the roes, the movement and survival conditions of the roes can be predicted more accurately, and data support can be provided for ecological protection.

Description

Technical Field

[0001] The present application relates to the field of biological monitoring technology, and in particular to a method for predicting the survival of drifting fish eggs in water flows that submerge vegetation. Background Art

[0002] In aquatic ecosystems, the reproduction and survival of fish are closely related to the drifting environment of their eggs. Drifting fish eggs are suspended, transported and dispersed under hydrodynamic conditions to avoid the risks of death, abortion or predation caused by sinking to the bottom. Therefore, suitable water flow and aquatic ecological environment are crucial to the survival of fish eggs.

[0003] At present, most studies mainly analyze the spatiotemporal variation of fish egg concentration by numerically solving the convection-diffusion equation to reveal its movement law. However, these models often fail to accurately depict the movement trajectory of fish eggs, and fail to fully consider the changes in physical and biological properties caused by the growth and development of fish eggs during drifting. In addition, the abundance of large submerged vegetation in rivers and lakes around the world is gradually increasing. These submerged vegetation provide a complex habitat for fish eggs, which not only affects the drifting path of fish eggs, but also may provide them with shelter and nutrients, thereby affecting their survival and development. Related technologies usually ignore the role of vegetation factors in the drift and sedimentation of fish eggs. Previous studies have shown that when fish eggs drift in the water, they are affected by many factors such as water flow velocity, vegetation density, vegetation submergence, and physical and chemical properties of the water body.

[0004] Therefore, there is currently a lack of a systematic analysis that can comprehensively consider water flow characteristics, vegetation distribution, and the biological characteristics of fish eggs. This will help to more accurately predict the movement and survival of fish eggs. This multi-factor comprehensive study can not only improve the understanding of fish ecology, but also provide an important theoretical basis for water resources management and ecological protection. Summary of the invention

[0005] The embodiment of the present application provides a method for predicting the survival of drifting fish eggs in water flow submerged by vegetation, so as to solve the defects of the above-mentioned related technologies. The embodiment of the present application can simulate different fish eggs and vegetation characteristics to predict the early movement of fish eggs in the water body after fertilization, as well as the suspension and sedimentation behavior of fish eggs under the combined action of vegetation and water flow, and more accurately predict the early survival of drifting fish eggs. The technical solution is as follows: In a first aspect, an embodiment of the present application provides a method for predicting the survival of drifting fish eggs in a water flow that submerges vegetation, comprising: Determine the area to be studied and the target to be predicted, obtain the fish egg parameter change curve of the fish egg type corresponding to the target to be predicted, and obtain the vegetation characteristic parameters and other influencing parameters in the area to be studied; wherein the target to be predicted includes fish eggs corresponding to the spawning quantity; Determine the fish egg parameters of each fish egg in the current cycle, use the fish egg parameters, the vegetation characteristic parameters and the other influencing parameters as input parameters, and input them into a drifting fish egg survival prediction model. The calculation process of the drifting fish egg survival prediction model includes: Calculate the sinking velocity of each fish egg; Calculate the position coordinates of each fish egg based on the sinking speed of each fish egg; Determine the fish eggs that have settled to the riverbed based on the position coordinates of each fish egg, determine whether the fish eggs that have settled to the riverbed are resuspended, and update the number of suspended fish eggs; Outputting a fish egg survival prediction result based on the ratio of the number of the suspended fish eggs to the number of the laid eggs; Update the fish egg parameters of the next cycle, and go to the step of inputting the drifting fish egg survival prediction model until the drifting time is greater than or equal to the hatching time threshold; The fish egg parameters include: fish egg position, fish egg diameter and fish egg density.

[0006] In an optional solution of the first aspect, the calculating the settling velocity of each fish egg comprises: The fluid density is obtained based on the other influencing parameters, the egg diameter and the egg density of each fish egg in the current cycle are obtained, and the settling speed of each fish egg is calculated using the formula: ; ; ; ; in, is the settling velocity of fish eggs, is the acceleration due to gravity, is the drag coefficient of the fish eggs, is the fish egg Reynolds number, is the diameter of the fish eggs, is the egg density; is the density of water, is the kinematic viscosity of water, where and All are functions of water temperature.

[0007] In an optional solution of the first aspect, the position coordinates include horizontal coordinates and vertical coordinates of the fish eggs; The updating of the position coordinates of each fish egg based on the settling speed of each fish egg comprises: Calculate the vertical coordinates of each fish egg, using the formula: ; Calculate the horizontal coordinates of each fish egg and apply the formula: ; in, is the longitudinal velocity of the water body, is the vertical turbulent diffusion coefficient, is a random number selected from a normal distribution with mean 0 and standard deviation 1. is the time step of each cycle, t is the starting time of the current cycle, is the horizontal coordinate of the starting time of the current cycle, is the horizontal coordinate of the end time of the current cycle, is the vertical coordinate of the starting time of the current cycle, is the vertical coordinate of the end time of the current cycle.

[0008] In an optional solution of the first aspect, the longitudinal flow velocity of the water body is a piecewise function related to the vertical coordinate, and a function corresponding to each range is determined based on the range in which the value of the vertical coordinate falls, and the longitudinal flow velocity of the water body is calculated, including: If the value of the vertical coordinate is less than the water body depth and greater than the first depth threshold, it is determined that the fish eggs are located in the upper water flow of the vegetation area, and the longitudinal flow velocity of the water body is calculated using the following formula: ; If the value of the vertical coordinate is less than the first depth threshold and greater than the second depth threshold, it is determined that the fish eggs are located in the exchange zone, and the longitudinal flow velocity of the water body is calculated using the following formula: ; If the value of the vertical coordinate is less than or equal to the second depth threshold, it is determined that the fish eggs are located in the wake area, and the longitudinal flow velocity of the water body is calculated using the following formula: ; The first depth threshold is greater than the second depth threshold, and the first depth threshold is the vegetation height. , the second depth threshold is , is the length of shear vortex penetration into vegetation, , is the water-facing front area of ​​vegetation in a unit volume of water, a is used to characterize vegetation density, is the number of plants per square meter, is the vegetation diameter; is the hydraulic slope, coefficient , roughness height , displacement height , Friction velocity of submerged vegetation , is the longitudinal velocity of the water body in the wake zone, is the Karman constant .

[0009] In an optional solution of the first aspect, after updating the position coordinates of each fish egg based on the settling speed of each fish egg, the method further comprises: When the calculated vertical coordinate is greater than the water depth h, the position of the fish eggs is characterized as being outside the water surface, and the vertical coordinate of the fish eggs is updated using the following formula: ; When the calculated vertical coordinate is less than 0, the position of the fish eggs is characterized as being below the riverbed, and the position of the fish eggs is updated to be settled on the riverbed; in, To update the vertical coordinates obtained by the calculation before, is the vertical coordinate after updating.

[0010] In an optional solution of the first aspect, after updating the position coordinates of each fish egg based on the settling speed of each fish egg, the method further includes: Determine the fish eggs that have settled to the riverbed based on the position coordinates of each fish egg, and determine the fish eggs that have settled to the riverbed and the suspended fish eggs based on the position coordinates of each fish egg; Determine whether the fish eggs that have settled to the riverbed are resuspended, and calculate the rising rate of each fish egg that has settled to the riverbed from the riverbed; For each fish egg that settles to the riverbed, generate a random value randomly drawn from a uniform distribution (0,1); If the random value is less than or equal to the product of the rising rate and the time step, it is determined that the fish eggs that have settled to the riverbed will be resuspended; Update the status of each fish egg and get the updated number of suspended fish eggs.

[0011] In an optional solution of the first aspect, the method further includes: To determine the time step, apply the formula: ; in, is the time step, h is the water depth, is the vertical turbulent diffusion coefficient, z is the ordinate, is the settling velocity of fish eggs.

[0012] In a second aspect, the present application also provides a device for predicting the survival of drifting fish eggs in a water flow that submerges vegetation, comprising: A parameter acquisition unit, used to determine the area to be studied and the target to be predicted, and also used to obtain the fish egg parameter change curve of the fish egg type corresponding to the target to be predicted, and also used to obtain the vegetation characteristic parameters and other influencing parameters in the area to be studied; wherein the target to be predicted includes fish eggs corresponding to the spawning quantity; The parameter acquisition unit is also used to determine the fish egg parameters of each fish egg in the current cycle, and use the fish egg parameters, the vegetation characteristic parameters and the other influencing parameters as input parameters, and input them into the drifting fish egg survival prediction model of the calculation unit. The calculation process of the calculation unit using the drifting fish egg survival prediction model includes: Calculate the sinking velocity of each fish egg; Update the position coordinates of each fish egg based on the sinking speed of each fish egg; Determine the fish eggs that have settled to the riverbed based on the position coordinates of each fish egg, determine whether the fish eggs that have settled to the riverbed are resuspended, and update the number of suspended fish eggs; An analysis unit, configured to output a fish egg survival prediction result based on a ratio of the number of the suspended fish eggs to the number of the laid eggs; The parameter acquisition unit is also used to update the fish egg parameters of the next cycle, and transfer to the step of the drifting fish egg survival prediction model of the input calculation unit until the drifting time is greater than or equal to the hatching time threshold; The fish egg parameters include: fish egg position, fish egg diameter and fish egg density.

[0013] In a third aspect, an embodiment of the present application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method provided in the first aspect of the embodiment of the present application or any one of the implementation methods of the first aspect is implemented.

[0014] In a fourth aspect, the present application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided by the first aspect of the embodiment of the present application or any one of the implementations of the first aspect.

[0015] The beneficial effects brought about by the technical solutions provided by some embodiments of the present application include at least: The present application provides a method for predicting the survival of drifting fish eggs in submerged vegetation water flow. The method is based on the vegetation characteristic parameters and other influencing parameters in the study area containing submerged vegetation and the fish egg parameters of drifting fish eggs. The method also considers the changes in the parameters of the fish eggs and the factors such as resuspension, sinking and abortion of the fish eggs caused by the turbulence of the vegetation water flow. The method simulates the movement trajectory of the drifting fish eggs in the river channel, and constructs a fish egg survival prediction model suitable for different vegetation conditions and fish egg biological characteristics. The method can accurately simulate and predict the number of surviving fish eggs when the hatching time is reached. In addition, the present application also illustrates the influence of vegetation characteristic parameters such as relative submergence of vegetation and vegetation density on the survival score, and provides a prediction model for the dynamic changes of the survival score of fish eggs during vegetation succession.

[0016] The embodiment of the present application comprehensively considers the water flow characteristics, vegetation characteristics and biological characteristics of fish eggs for systematic analysis, which will help to more accurately predict the movement and survival of fish eggs. This multi-factor comprehensive study can not only enhance the understanding of fish ecology, but also provide an important theoretical basis for water resource management and ecological protection.

[0017] In addition, based on the fish egg survival prediction results determined in the embodiments of the present application, early fish resources can be supplemented when the number of surviving fish eggs is less than a certain value. Specifically, the ecological flow required for fish protection can be quantitatively evaluated with the goal of improving the fish egg survival score, and a fish habitat protection and regulation strategy based on hydrodynamic mechanisms can be derived to provide data support for river ecological restoration. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present application or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a flow chart of a method for predicting the survival of drifting fish eggs in a water flow that submerges vegetation provided in an embodiment of the present application; Figure 2 It is a schematic diagram of the survival score distribution of a method for predicting the survival of drifting fish eggs in a water flow that submerges vegetation provided in an embodiment of the present application; Figure 3 It is a schematic diagram of the survival score distribution of a method for predicting the survival of drifting fish eggs in a water flow that submerges vegetation provided in an embodiment of the present application; Figure 4 It is a schematic diagram of the survival score distribution of a method for predicting the survival of drifting fish eggs in a water flow that submerges vegetation provided in an embodiment of the present application; Figure 5 It is a schematic diagram of the survival score distribution of a method for predicting the survival of drifting fish eggs in a water flow that submerges vegetation provided in an embodiment of the present application; Figure 6 It is a structural schematic diagram of a device for predicting the survival of drifting fish eggs applied to a water flow that submerges vegetation, provided in an embodiment of the present application; Figure 7 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0021] The terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device including a series of steps or modules is not limited to the listed steps or modules, but may optionally include steps or modules that are not listed, or may optionally include other steps or modules that are inherent to these processes, methods, products or devices.

[0022] It should be noted that the terms "first\second" involved in the present application are only used to distinguish similar objects, and do not represent a specific order for the objects. It is understandable that "first\second" can be interchanged with a specific order or sequence where permitted. It should be understood that the objects distinguished by "first\second" can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those described or illustrated herein.

[0023] The present application is described in detail below with reference to specific embodiments.

[0024] Next, combine Figure 1 , introduces a method for predicting the survival of drifting fish eggs in water flow that submerges vegetation, provided in an embodiment of the present application. For details, please refer to Figure 1 , Figure 1 A schematic diagram of a method provided in an embodiment of the present application is shown. Figure 1 As shown, the method comprises the following steps: S101, determining a region to be studied and a target to be predicted, obtaining a fish egg parameter variation curve of a fish egg type corresponding to the target to be predicted, and obtaining vegetation characteristic parameters and other influencing parameters in the region to be studied.

[0025] S102, determining the fish egg parameters of each fish egg in the current cycle, and using the fish egg parameters, the vegetation characteristic parameters and the other influencing parameters as input parameters to input into a drifting fish egg survival prediction model.

[0026] The calculation process of the drifting fish egg survival prediction model comprises the following steps: S103, calculating the settling speed of each fish egg.

[0027] S104, calculating the position coordinates of each fish egg based on the settling speed of each fish egg.

[0028] S105, determining the fish eggs that have settled to the riverbed based on the position coordinates of each fish egg, determining whether the fish eggs that have settled to the riverbed are re-suspended, and updating the number of suspended fish eggs.

[0029] S106, outputting a fish egg survival prediction result based on the ratio of the number of the suspended fish eggs to the number of spawned eggs.

[0030] When the fish egg drifting time corresponding to the current cycle does not reach the hatching time threshold of the fish eggs, step S107 is executed: S107, updating the fish egg parameters for the next cycle; Go to the step of inputting the drifting fish egg survival prediction model in S102 until the drifting time is greater than or equal to the hatching time threshold.

[0031] Specifically, in S101, any river section, wetland or other fish spawning grounds of drifting fish eggs can be selected as the area to be studied, and the area to be studied should cover the entire drifting interval from the fish spawning site to before the fish eggs hatch.

[0032] Among them, a certain type of fish can be determined as the research target, the spawning location and corresponding spawning quantity of the research target can be obtained, and the target to be predicted is the sum of the fish eggs corresponding to the spawning quantity. The hatching time can be determined according to the type of fish eggs.

[0033] It can be understood that after spawning, the fish eggs are in the process of growth, and the fish egg parameter change curve of the fish eggs can be determined, the fish egg parameters of the fish eggs, the fish egg diameter and the fish egg density, among which the fish egg density and the fish egg diameter will change with time: ; ; In the formula, , , It is a dimensionless constant. Its specific value is related to the species of fish eggs. For details, please see Table 1.

[0034] In some embodiments, in order to accurately compare the density and settling rate of different types of fish eggs, the calculated fish egg density can be standardized to a specific temperature (generally 22° C.) using the following formula: ; In the formula, is the ambient temperature, is the reference temperature; is the correction factor for temperature adjustment, which can be taken as 0.20646.

[0035] Table 1 Dimensionless constant value table

[0036] In some embodiments, the vegetation characteristic parameters include the height and density of vegetation, etc., and the average value of the height and density of vegetation in the entire area to be studied can be taken; other influencing parameters are external non-biological factors, that is, all environmental factors other than biological influencing factors, such as water body temperature, water body flow, water body width, etc. In general, the average value of the vegetation characteristic parameters of the entire watershed and the average value of each type of parameters in other influencing parameters can be taken.

[0037] Optionally, the distribution of vegetation characteristics and / or other influencing parameters in the area to be studied may be obtained, and the vegetation characteristic related parameters and / or other influencing parameters may be updated in real time according to the fish egg positions during the calculation process of each cycle. This embodiment of the application is not limited to this.

[0038] In some embodiments, in S102, the calculation of the first cycle can be performed with the ovulation site of the fish eggs as the starting point, and the initial parameters of the first cycle can be determined, including the fish egg parameters of each fish egg in the current cycle and the vegetation characteristic parameters and other influencing parameters determined in S101. The initial parameters are used as inputs to the drifting fish egg survival prediction model, and the specific process of the calculation is performed through the drifting fish egg survival prediction model.

[0039] In some embodiments, in S103, the sedimentation velocity of the fish eggs depends on the fluid density, the drifting time, and the diameter of the fish eggs. The fluid density can be obtained based on the other influencing parameters, the drifting time of each fish egg can be obtained according to the current cycle, and the fish egg diameter can be obtained by determining the fish egg parameters in step S102. The iterative equation of the sedimentation velocity of spherical particles in a static fluid can be used to calculate the sedimentation velocity of each fish egg using the formula: ; ; ; ; in, is the settling velocity of fish eggs, is the acceleration due to gravity, is the drag coefficient of the fish eggs, is the fish egg Reynolds number, is the diameter of the fish eggs, is the egg density; is the density of water, is the kinematic viscosity of water, where and All are functions of water temperature.

[0040] In some embodiments, in S104, the position coordinates include the horizontal coordinates and the vertical coordinates of the fish eggs. The horizontal coordinates and the vertical coordinates of the fish eggs can be calculated based on the settling velocity calculated in S103. The horizontal coordinates and the vertical coordinates can be understood as the position change of a single fish egg in a time step corresponding to a cycle. Specifically, the horizontal and vertical displacements of the fish eggs can be simulated by the random displacement module of the drifting fish egg survival prediction model, including: Calculate the vertical coordinates of each fish egg, using the formula: ; Calculate the horizontal coordinates of each fish egg and apply the formula: ; in, is the longitudinal velocity of the water body, is the vertical turbulent diffusion coefficient, is a random number selected from a normal distribution with mean 0 and standard deviation 1. is the time step of each cycle, t is the starting time of the current cycle, is the horizontal coordinate of the starting time of the current cycle, is the horizontal coordinate of the end time of the current cycle, is the vertical coordinate of the starting time of the current cycle, is the vertical coordinate of the end time of the current cycle.

[0041] In the above embodiment, the longitudinal flow velocity of the water body is a piecewise function related to the vertical coordinate, and the function corresponding to each range is determined based on the range in which the value of the vertical coordinate falls, and the longitudinal flow velocity of the water body is calculated, including: If the value of the vertical coordinate is less than the water body depth and greater than the first depth threshold, it is determined that the fish eggs are located in the upper water flow of the vegetation area. The average flow velocity distribution in the upper water flow of the vegetation area follows a logarithmic distribution, and the longitudinal flow velocity of the water body is calculated using the following formula: ,

[0042] If the value of the vertical coordinate is less than the first depth threshold and greater than the second depth threshold, it is determined that the fish eggs are located in the exchange zone, the flow is driven by vegetation resistance and turbulent stress, the speed is exponentially distributed, and the longitudinal flow velocity of the water body is calculated using the following formula: , ; If the value of the vertical coordinate is less than or equal to the second depth threshold, it is determined that the fish eggs are located in the wake area. At this time, the time-averaged flow velocity is approximately uniformly distributed. Since the vegetation resistance is much greater than the riverbed resistance, the momentum equation is usually simplified to the balance between the pressure gradient and the vegetation resistance. The longitudinal flow velocity of the water body is calculated using the following formula: , ; The first depth threshold is greater than the second depth threshold, and the first depth threshold is the vegetation height. , the second depth threshold is , is the length of shear vortex penetration into vegetation, , is the water-facing front area of ​​vegetation in a unit volume of water, a is used to characterize vegetation density, is the number of plants per square meter, is the vegetation diameter; is the hydraulic slope, coefficient , roughness height , displacement height , Friction velocity of submerged vegetation , is the longitudinal velocity of the water body in the wake zone, is the Karman constant.

[0043] In some embodiments, in S104, the turbulent diffusion coefficient of the shear vortex can also be determined according to the different regions where the fish eggs are located in the water body. , including: When the fish eggs are in the wake area, when the vegetation density is high , the turbulent diffusion coefficient of the shear vortex is approximately uniformly distributed: ; When the fish eggs are located in the upper water flow of the vegetation, the transport of the upper water flow is mainly affected by the shear vortex, and the turbulent diffusion coefficient varies with the size of the shear vortex and the speed difference between the vegetation and the average speed of the upper water flow. The turbulence intensity reaches its maximum value at the top of the vegetation, and then gradually decreases from the top of the vegetation to the water surface. For different vegetation densities, the turbulence diffusion coefficient at the top of the vegetation is expressed as: ; in, is the shear vortex length, which is generally approximately equal to the vegetation height. Since the vertical turbulent diffusion coefficient is approximately linearly distributed in the exchange zone and the water flow above the vegetation, after determining the vertical diffusion coefficient in the wake zone and the maximum value at the top of the vegetation, assuming that the vertical turbulent diffusion coefficient at the water surface is zero, the vertical distribution of the vertical turbulent diffusion coefficient can be obtained.

[0044] In some embodiments, the water surface can be used as the upper boundary and the riverbed can be used as the lower boundary. In actual situations, when the fish eggs float, they will not exceed the upper boundary corresponding to the water surface, and when the fish eggs settle, they will not exceed the lower boundary corresponding to the riverbed.

[0045] Thus, the boundary conditions of the upper boundary corresponding to the water surface and the lower boundary corresponding to the riverbed can be set, including: When the calculated vertical coordinate is greater than the water depth h, the position of the fish eggs is characterized as being outside the water surface, and the vertical coordinate of the fish eggs is updated using the following formula: ; When the calculated vertical coordinate is less than 0, the position of the fish eggs is characterized as being below the riverbed, and the position of the fish eggs is updated to be settled on the riverbed; in, To update the vertical coordinates obtained by the calculation before, is the vertical coordinate after updating.

[0046] It can be understood that the position of the fish eggs in the current cycle can be easily updated through the position coordinates of the fish eggs and the position of the fish eggs in the previous cycle. In some embodiments, the ordinate of the water surface may be set to h, and the ordinate of the riverbed may be set to 0, so that it is easy to determine whether the vertical coordinate calculated in S104 needs to be adjusted based on the ordinate.

[0047] Further, after updating the position coordinates of each fish egg based on the settling speed of each fish egg in S104, the method further includes: The fish eggs that have sunk to the riverbed are determined based on the position coordinates of each fish egg, and the fish eggs that have sunk to the riverbed and the suspended fish eggs are determined based on the position coordinates of each fish egg.

[0048] Determine whether the fish eggs that have settled to the riverbed are resuspended, and calculate the rate of rise of each fish egg that has settled to the riverbed from the riverbed .

[0049] For each fish egg that settles to the riverbed, generate a random value drawn from a uniform distribution (0,1) , if the random value is less than or equal to the rise rate and the time step The product of , it is determined that the fish eggs that have settled to the riverbed will be resuspended, otherwise the corresponding fish eggs will remain in the state of settling to the riverbed, that is, deposited on the riverbed.

[0050] Update the status of each fish egg and get the updated number of suspended fish eggs.

[0051] Specifically, the rate of increase The calculation process includes: Particle resuspension and near-bed turbulent energy The turbulent energy of water flow in a vegetated river is partly generated by the bed surface and partly by the vegetation, and the following formula is applied: ; ; ; ; ; ; Among them, the riverbed shear stress ; Friction coefficient of riverbed ; is the average flow velocity of the river; is the average flow rate of the river; For the width of the river; for water depth; is the average velocity in the vegetation area; is the average velocity in the upper layer of vegetation; is the empirical coefficient representing the turbulent stress on the top of vegetation; for rigid vegetation, ; Scale factor ; is the average turbulent length scale; the stem Reynolds number ; Solid volume fraction in vegetation area ; The dimensionless erosion rate of the bed surface can be expressed as follows: ； Among them, the coefficient , ; , is dry bulk density; =, Dimensionless turbulent energy , ; Dimensionless critical turbulence intensity ; Dimensionless critical shear stress , dimensionless fish egg diameter .

[0052] The weight of the fish eggs rising from the bed per unit time is , apply the formula: ; The thickness of the bed eroded per unit time (bed erosion rate) is further calculated: ; The probability of resuspension of deposited particles is determined by the uplift rate of a single particle leaving the bed surface. The uplift rate is calculated using the formula: .

[0053] It should be noted that drifting fish eggs are suspended, transported and scattered under the action of hydrodynamics. If they sink to the riverbed, there is a high probability that they will die, abort or be eaten. Therefore, the survival of the fish eggs is determined based on the ratio of the number of fish eggs remaining suspended in the water to the total number of eggs laid.

[0054] In some embodiments, in S106, the egg survival prediction result can be output according to the ratio of the number of suspended eggs to the spawning number, and in S107, the egg parameters of the next cycle can be updated based on the egg parameter change curve after completing one cycle of calculation.

[0055] It can be understood that in S107, at the end of the previous cycle, the fish egg diameter and fish egg density at the end time of the previous cycle can be determined based on the end time of the previous cycle and the fish egg parameter change curve of the corresponding type, and the fish egg position can be determined based on the position coordinates of each fish egg calculated in the previous cycle. Therefore, the fish egg position, fish egg diameter and fish egg density at the end time of the previous cycle can be used as input parameters for the next cycle, and the drifting fish egg survival prediction model is input in S102 to continue the calculation of the next cycle.

[0056] Specifically, the egg survival prediction result of the corresponding period can be output based on the step S106 in each period, and a chart can be generated with each period as the horizontal coordinate and the ratio of the number of suspended eggs to the number of eggs laid as the vertical coordinate, so as to intuitively display the changes in survival conditions in multiple periods until the egg hatching time threshold; the drift distance can also be used as the horizontal coordinate and the relative submergence as the vertical coordinate, that is, the submergence depth of the eggs in the water body. The position of the eggs in the water body can be determined by the submergence depth of the eggs, thereby reflecting the distribution of the survival conditions of the eggs at different positions during the drifting process. Specifically, the survival score can be determined based on a mapping table of the ratio of the number of suspended eggs to the number of eggs laid and the survival score, such as Figure 2-Figure 3As shown, the survival score of fish eggs changes along the way under different flow conditions. Red indicates that the survival score of fish eggs is higher. From the red area to the blue area, the survival score of fish eggs gradually decreases. The embodiment of the present application does not limit the form of expression of the fish egg survival prediction results.

[0057] In some embodiments, a cross section at a specific drift distance can also be selected to determine the vegetation height. The horizontal axis is the vegetation density a, and the vertical axis is the simulation result diagram. Figure 4-Figure 5 As shown, Figure 4 This example shows that the position where the drift distance is 25m is selected as the cross section. Figure 5 The example uses a drift distance of 50m as the cross section, which reflects the distribution of the survival score of fish eggs at the corresponding cross section affected by vegetation density and vegetation height.

[0058] The following are device embodiments of the present application, which can be used to execute the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

[0059] See next Figure 6 , is a schematic diagram of the structure of a device for predicting the survival of drifting fish eggs applied to submerged vegetation water flow provided by an exemplary embodiment of the present application. The device can be implemented as all or part of a terminal through software, hardware, or a combination of both, and can also be integrated on a server as an independent module. The device for predicting the survival of drifting fish eggs applied to submerged vegetation water flow in the embodiment of the present application can be applied to a terminal or a cloud. The device 60 includes a parameter acquisition unit 601, a calculation unit 602, and an analysis unit 603, wherein: The parameter acquisition unit 601 is used to determine the area to be studied and the target to be predicted, and is also used to obtain the fish egg parameter change curve of the fish egg type corresponding to the target to be predicted, and is also used to obtain the vegetation characteristic parameters and other influencing parameters in the area to be studied; wherein the target to be predicted includes fish eggs corresponding to the number of spawning; The parameter acquisition unit 601 is also used to determine the fish egg parameters of each fish egg in the current cycle, and use the fish egg parameters, the vegetation characteristic parameters and the other influencing parameters as input parameters to input the drifting fish egg survival prediction model of the calculation unit 602. The calculation process of the calculation unit 602 using the drifting fish egg survival prediction model includes: Calculate the sinking velocity of each fish egg; Update the position coordinates of each fish egg based on the sinking speed of each fish egg; Determine the fish eggs that have settled to the riverbed based on the position coordinates of each fish egg, determine whether the fish eggs that have settled to the riverbed are resuspended, and update the number of suspended fish eggs; The analysis unit 603 is used to output a fish egg survival prediction result based on the ratio of the number of the suspended fish eggs to the number of the spawned eggs; The parameter acquisition unit 601 is also used to update the fish egg parameters of the next cycle, and transfer to the step of the drifting fish egg survival prediction model of the input calculation unit 602 until the drifting time is greater than or equal to the hatching time threshold; The fish egg parameters include: fish egg position, fish egg diameter and fish egg density.

[0060] It should be noted that the device 60 provided in the above embodiment only uses the division of the above functional modules as an example when executing the method for predicting the survival of drifting fish eggs applied to submerged vegetation water flow. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the device provided in the above embodiment and the embodiment of the method for predicting the survival of drifting fish eggs applied to submerged vegetation water flow belong to the same concept. The implementation process is detailed in the method embodiment, which will not be repeated here.

[0061] An embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any of the above-mentioned method embodiments when executing the program.

[0062] See also Figure 7 , which is a structural block diagram of an electronic device provided in an embodiment of the present application.

[0063] like Figure 7 As shown, the electronic device 700 includes: a processor 701 and a memory 702 .

[0064] In the embodiment of the present application, the processor 701 is the control center of the computer system, which can be a processor of a physical machine or a processor of a virtual machine. The processor 701 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 701 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array).

[0065] The processor 701 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also called a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state.

[0066] The memory 702 may include one or more computer-readable storage media, which may be non-transitory. The memory 702 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments of the present application, the non-transitory computer-readable storage medium in the memory 702 is used to store at least one instruction, which is used to be executed by the processor 701 to implement the method in the embodiment of the present application.

[0067] In some embodiments, the electronic device 700 further includes: a peripheral device interface 703 and at least one peripheral device 704. The processor 701, the memory 702 and the peripheral device interface 703 can be connected via a bus or a signal line. Each peripheral device 704 can be connected to the peripheral device interface 703 via a bus, a signal line or a circuit board. Specifically, the peripheral device 704 includes: a display screen, a camera and an audio circuit. The peripheral device interface 703 can be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 701 and the memory 702.

[0068] In some embodiments of the present application, the processor 701, the memory 702, and the peripheral device interface 703 are integrated on the same chip or circuit board; in some other embodiments of the present application, any one or two of the processor 701, the memory 702, and the peripheral device interface 703 can be implemented on a separate chip or circuit board. This embodiment of the present application does not specifically limit this.

[0069] The electronic device structure block diagram shown in the embodiment of the present application does not constitute a limitation on the electronic device 700. The electronic device 700 may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0070] The present application also provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of the method of any of the above embodiments are implemented. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a micro drive, and a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic card or an optical card, a nanosystem (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0071] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiment.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for predicting the survival of drifting fish eggs in water flow that submerges vegetation, characterized in that: include: Determine the area to be studied and the target to be predicted, obtain the fish egg parameter change curve of the fish egg type corresponding to the target to be predicted, and obtain the vegetation characteristic parameters and other influencing parameters in the area to be studied; wherein the target to be predicted includes fish eggs corresponding to the spawning quantity; Determine the fish egg parameters of each fish egg in the current cycle, use the fish egg parameters, the vegetation characteristic parameters and the other influencing parameters as input parameters, and input them into a drifting fish egg survival prediction model. The calculation process of the drifting fish egg survival prediction model includes: Calculate the sinking velocity of each fish egg; Calculate the position coordinates of each fish egg based on the sinking speed of each fish egg; Determine the fish eggs that have settled to the riverbed based on the position coordinates of each fish egg, determine whether the fish eggs that have settled to the riverbed are resuspended, and update the number of suspended fish eggs; Outputting a fish egg survival prediction result based on the ratio of the number of the suspended fish eggs to the number of the laid eggs; Update the fish egg parameters of the next cycle, and go to the step of inputting the drifting fish egg survival prediction model until the drifting time is greater than or equal to the hatching time threshold; The fish egg parameters include: fish egg position, fish egg diameter and fish egg density.

2. The method for predicting the survival of drifting fish eggs in water flow submerging vegetation according to claim 1, characterized in that: The calculation of the settling velocity of each fish egg comprises: The fluid density is obtained based on the other influencing parameters, the egg diameter and the egg density of each fish egg in the current cycle are obtained, and the settling speed of each fish egg is calculated using the formula: ； ； ； ； in, is the settling velocity of fish eggs, is the acceleration due to gravity, is the drag coefficient of the fish eggs, is the fish egg Reynolds number, is the diameter of the fish eggs, is the egg density; is the density of water, is the kinematic viscosity of water, where and All are functions of water temperature.

3. The method for predicting the survival of drifting fish eggs in water flow submerging vegetation according to claim 2, characterized in that: The position coordinates include horizontal coordinates and vertical coordinates of the fish eggs; The updating of the position coordinates of each fish egg based on the settling speed of each fish egg comprises: Calculate the vertical coordinates of each fish egg, using the formula: ； Calculate the horizontal coordinates of each fish egg and apply the formula: ； in, is the longitudinal velocity of the water body, is the vertical turbulent diffusion coefficient, is a random number selected from a normal distribution with mean 0 and standard deviation 1. is the time step of each cycle, t is the starting time of the current cycle, is the horizontal coordinate of the starting time of the current cycle, is the horizontal coordinate of the end time of the current cycle, is the vertical coordinate of the starting time of the current cycle, is the vertical coordinate of the end time of the current cycle.

4. A method for predicting the survival of drifting fish eggs in water flow that submerges vegetation according to claim 3, characterized in that: The longitudinal flow velocity of the water body is a piecewise function related to the vertical coordinate, and the function corresponding to each range is determined based on the range in which the value of the vertical coordinate falls, and the longitudinal flow velocity of the water body is calculated, including: If the value of the vertical coordinate is less than the water body depth and greater than the first depth threshold, it is determined that the fish eggs are located in the upper water flow of the vegetation area, and the longitudinal flow velocity of the water body is calculated using the following formula: ； If the value of the vertical coordinate is less than the first depth threshold and greater than the second depth threshold, it is determined that the fish eggs are located in the exchange zone, and the longitudinal flow velocity of the water body is calculated using the following formula: ； If the value of the vertical coordinate is less than or equal to the second depth threshold, it is determined that the fish eggs are located in the wake area, and the longitudinal flow velocity of the water body is calculated using the following formula: ； The coordinate at the water surface is h, where h is the depth of the water body; the coordinate at the riverbed is 0; the first depth threshold is greater than the second depth threshold, where the first depth threshold is the height of the vegetation. , the second depth threshold is , is the length of shear vortex penetration into vegetation, , is the water-facing front area of ​​vegetation in a unit volume of water, a is used to characterize vegetation density, is the number of plants per square meter, is the vegetation diameter; is the hydraulic slope, coefficient , roughness height , displacement height , Frictional velocity of submerged vegetation , is the longitudinal velocity of the water body in the wake zone, is the Karman constant.

5. A method for predicting the survival of drifting fish eggs in water flow that submerges vegetation according to claim 4, characterized in that: After updating the position coordinates of each fish egg based on the settling speed of each fish egg, the method further includes: When the calculated vertical coordinate is greater than the water depth h, the position of the fish eggs is characterized as being outside the water surface, and the vertical coordinate of the fish eggs is updated using the following formula: ； When the calculated vertical coordinate is less than 0, the position of the fish eggs is characterized as being below the riverbed, and the position of the fish eggs is updated to be settled on the riverbed; in, To update the vertical coordinates obtained by the calculation before, is the vertical coordinate after updating.

6. A method for predicting the survival of drifting fish eggs in water flow that submerges vegetation according to claim 5, characterized in that: After updating the position coordinates of each fish egg based on the settling speed of each fish egg, the method further includes: determining the eggs that have sunk to the riverbed and the eggs that are suspended based on the position coordinates of each egg; Determine whether the fish eggs that have settled to the riverbed are resuspended, and calculate the rising rate of each fish egg that has settled to the riverbed from the riverbed; For each fish egg that settles to the riverbed, generate a random value randomly drawn from a uniform distribution (0,1); If the random value is less than or equal to the product of the rising rate and the time step, it is determined that the fish eggs that have settled to the riverbed will be resuspended; Update the status of each fish egg and get the updated number of suspended fish eggs.

7. A method for predicting the survival of drifting fish eggs in water flow that submerges vegetation according to any one of claims 1 to 6, characterized in that: The method further comprises: To determine the time step, apply the formula: ； in, is the time step, h is the water depth, is the vertical turbulent diffusion coefficient, z is the ordinate, is the settling velocity of fish eggs.

8. A device for predicting the survival of drifting fish eggs in water flow that submerges vegetation, characterized in that: include: A parameter acquisition unit, used to determine the area to be studied and the target to be predicted, and also used to obtain the fish egg parameter change curve of the fish egg type corresponding to the target to be predicted, and also used to obtain the vegetation characteristic parameters and other influencing parameters in the area to be studied; wherein the target to be predicted includes fish eggs corresponding to the spawning quantity; The parameter acquisition unit is also used to determine the fish egg parameters of each fish egg in the current cycle, and use the fish egg parameters, the vegetation characteristic parameters and the other influencing parameters as input parameters, and input them into the drifting fish egg survival prediction model of the calculation unit. The calculation process of the calculation unit using the drifting fish egg survival prediction model includes: Calculate the sinking velocity of each fish egg; Calculate the position coordinates of each fish egg based on the sinking speed of each fish egg; Determine the fish eggs that have settled to the riverbed based on the position coordinates of each fish egg, determine whether the fish eggs that have settled to the riverbed are resuspended, and update the number of suspended fish eggs; An analysis unit, configured to output a fish egg survival prediction result based on a ratio of the number of the suspended fish eggs to the number of the laid eggs; The parameter acquisition unit is also used to update the fish egg parameters of the next cycle, and transfer to the step of the drifting fish egg survival prediction model of the input calculation unit until the drifting time is greater than or equal to the hatching time threshold; The fish egg parameters include: fish egg position, fish egg diameter and fish egg density.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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