Method and apparatus for predicting adhesion time and distance of adhesive fish eggs in vegetated water flows

Abstract

The application discloses a method and device for predicting adsorption time and distance of viscous fish eggs in vegetation water flow, a storage medium and an electronic device. The method comprises the following steps: acquiring hydrodynamic basic parameters of a research river area; calculating a water flow longitudinal velocity and a turbulent diffusion coefficient according to the hydrodynamic basic parameters; determining an adsorption probability of fish eggs; and constructing a random displacement model, inputting the hydrodynamic basic parameters, the water flow longitudinal velocity and the turbulent diffusion coefficient into the random displacement model, and obtaining adsorption time and an adsorption position of the fish eggs. The application can accurately predict the adsorption time and distance of the fish eggs in the vegetation river, which is beneficial to the development of targeted fish egg protection measures in actual engineering.

Description

Technical Field

[0001] This application relates to the field of predicting the adsorption characteristics of sticky fish eggs, and in particular to a method, apparatus, storage medium and electronic equipment for predicting the adsorption time and distance of sticky fish eggs in vegetation-covered water flow. Background Technology

[0002] The movement and transport of fish eggs under hydrodynamic conditions are of significant biological importance, greatly affecting their successful hatching. For example, the transport, suspension, sedimentation, and adsorption of adhesive fish eggs (typically Chinese sturgeon eggs) under hydrodynamic influences, with the adsorption time and location being crucial to egg survival. On one hand, the transport patterns of fish eggs and their adsorption locations in river channels are important aspects of early fish resource research, facilitating the evaluation and optimization of ecological compensation measures to improve fish resources. Therefore, accurate prediction of the transport patterns, adsorption and spawning locations, and adsorption time of adhesive fish eggs under hydrodynamic conditions is urgently needed. On the other hand, common aquatic vegetation in river channels not only significantly alters hydrodynamic conditions but also provides food sources and habitats for important aquatic organisms such as fish. Currently, predicting the spatiotemporal characteristics of fish egg adsorption in vegetated water flows to determine the impact of aquatic vegetation on fish egg adsorption is an important topic in early fish resource research. Therefore, establishing effective mathematical models to predict the adsorption time and distance of fish eggs in aquatic vegetation and water flow can provide technical support for the protection of fish resources and is of great significance for the protection of fish and aquatic ecosystems.

[0003] Currently, research on the drifting process of fish eggs by scholars both domestically and internationally mainly focuses on on-site monitoring and laboratory flume model experiments. Studies on the drifting and adsorption characteristics of fish eggs are still limited to general properties (such as density, diameter, and settling velocity), and mostly focus on the drifting process of fish eggs in the absence of vegetation. There is a lack of effective methods to successfully simulate and predict the drift of sticky fish eggs in vegetated water flows, and research results and technical methods on the adsorption time and distance characteristics of sticky fish eggs in a common habitat of aquatic vegetation are even more scarce. These deficiencies hinder the implementation of targeted protection measures for spawning grounds to improve the survival rate of fish eggs during engineering projects. In particular, the impact of different characteristics of aquatic vegetation (such as vegetation density and submersion degree) on the adsorption of fish eggs remains unknown. There is an urgent need to develop an efficient predictive model and device for the adsorption time and space of fish eggs in vegetated water flows to address the impact of variable river environments on fish egg survival rates. Summary of the Invention

[0004] This application provides a method, apparatus, storage medium, and electronic device for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, which can accurately predict the adsorption time and distance of fish eggs transported in vegetated waterways.

[0005] This application provides a method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, including:

[0006] To obtain the basic hydrodynamic parameters of the river channel area under study;

[0007] Based on the aforementioned hydrodynamic fundamental parameters, calculate the longitudinal flow velocity and turbulent diffusion coefficient;

[0008] Determine the adsorption probability of fish eggs;

[0009] A random displacement model is constructed, and the hydrodynamic basic parameters, the longitudinal flow velocity of the water flow, and the turbulent diffusion coefficient are input into the random displacement model to obtain the adsorption time and adsorption location of the fish eggs.

[0010] Furthermore, in the above-mentioned method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, the basic hydrodynamic parameters include at least the riverbed slope, the depth of river intrusion, the water flow velocity, and the vegetation density.

[0011] Furthermore, in the above-mentioned method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, the step of calculating the longitudinal flow velocity and turbulent diffusion coefficient based on the aforementioned hydrodynamic fundamental parameters includes:

[0012] The cross-sectional average flow velocity of the emergent vegetation and the turbulent diffusion coefficient of the emergent vegetation are calculated based on the riverbed slope and the vegetation density.

[0013] The average cross-sectional velocity and turbulent diffusion coefficient of the submerged vegetation are calculated based on the river intrusion depth, the water flow velocity, and the vegetation density.

[0014] Furthermore, in the above-mentioned method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, the step of calculating the cross-sectional average flow velocity of emergent vegetation flow based on the riverbed slope and the vegetation density includes:

[0015] The cross-sectional average flow velocity of the emergent vegetation water flow is calculated using a first formula, which is:

[0016]

[0017] Where g is the acceleration due to gravity, and s is the riverbed slope. The area density before vegetation cover. This represents the vegetation drag coefficient.

[0018] Furthermore, the above-mentioned method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow includes calculating the turbulent diffusion coefficient of emergent vegetation based on the riverbed slope and the vegetation density, comprising:

[0019] The turbulent diffusion coefficient of the emergent vegetation is calculated using a first formula, which is:

[0020]

[0021] in, The average cross-sectional velocity of the water flow in emergent vegetation. This is an empirical coefficient. The diameter is the vegetation diameter.

[0022] Furthermore, in the above-mentioned method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, the step of calculating the average cross-sectional velocity of the submerged vegetation based on the river intrusion depth, the water flow velocity, and the vegetation density includes:

[0023] for The average flow velocity across the submerged vegetation top area is:

[0024]

[0025] in, The roughness height of the vegetated river channel, The zero-plane displacement height of the rough boundary. Kármán's constant;

[0026] in, , The depth of river intrusion;

[0027] for In the upper vegetation zone, the average flow velocity across the submerged vegetation section is:

[0028]

[0029] in, Represents the water flow velocity at the top of the vegetation. This is an empirical coefficient;

[0030] for Within the vegetated wake zone, the average flow velocity across the submerged vegetation section is:

[0031] .

[0032] Furthermore, the above-mentioned method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow includes calculating the turbulent diffusion coefficient of submerged vegetation based on the river intrusion depth, the water flow velocity, and the vegetation density, comprising:

[0033] for The turbulent diffusion coefficient of the submerged vegetation top area is:

[0034]

[0035] in, Velocity in the top vegetation zone and velocity in the wake zone Speed ​​difference, The thickness of the hybrid layer;

[0036] for In the wake zone within vegetation, the turbulent diffusion coefficient of the submerged vegetation is:

[0037] .

[0038] Furthermore, in the above-mentioned method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, the drift path of the fish eggs is calculated in the random displacement model using the hydrodynamic fundamental parameters, the longitudinal flow velocity, and the turbulent diffusion coefficient. The calculation formula is as follows:

[0039]

[0040]

[0041] in, and These are the water flow direction and the vertical direction, respectively. i and( i +1) indicates the first i Subsequent i +1 iterations, and These represent the longitudinal velocity of the water flow and the settling velocity of the fish egg particles, respectively. R is the time step for iteration, and it is a random number with a mean of 0 and a standard deviation of 1, used to simulate the effect of the randomness of turbulence on the movement of fish egg particles.

[0042] This application also provides a device for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, including:

[0043] The acquisition module is used to acquire basic hydrodynamic parameters of the studied river area;

[0044] The calculation module is used to calculate the longitudinal flow velocity and turbulent diffusion coefficient of the water flow based on the aforementioned hydrodynamic fundamental parameters.

[0045] The determination module is used to determine the adsorption probability of fish eggs;

[0046] The prediction module is used to construct a random displacement model. The hydrodynamic basic parameters, the longitudinal flow velocity of the water flow, and the turbulent diffusion coefficient are input into the random displacement model to obtain the adsorption time and adsorption location of the fish eggs.

[0047] Furthermore, the aforementioned device for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow further includes:

[0048] The fish egg movement area determination module is used to define the transport restriction area for fish eggs. If the fish eggs move beyond the water surface, they will be bounced. If the fish eggs move to the bottom of the riverbed, the module will determine whether the fish eggs will be adsorbed or bounced and transported with the current again based on the adsorption probability.

[0049] The iterative calculation module is used to set the starting position and time of the fish egg drift and repeatedly calculate the spatial position of the fish egg;

[0050] The adsorption judgment module is used to determine whether the near-bottom fish eggs are adsorbed to the bottom of the riverbed based on the adsorption probability. If the fish eggs are adsorbed, they will stop moving; if the fish eggs are not adsorbed, they will continue to move with the current.

[0051] The results display module is used to display the location of fish eggs at a specific time according to the set display time step;

[0052] The control module is used to receive the operator's input of the time to stop the iterative calculation, and the iterative calculation will automatically stop after the specified time;

[0053] The input display module is communicatively connected to the fish egg movement area determination module, the iterative calculation module, the adsorption judgment module, the display module, and the control module, respectively, and is used to receive the hydrodynamic basic parameters of the calculation area input by the operator as input data.

[0054] This application also provides a computer-readable storage medium storing multiple instructions adapted for loading by a processor to execute any of the above-described methods for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow.

[0055] This application also provides an electronic device, including a processor and a memory, wherein the processor is electrically connected to the memory, the memory is used to store instructions and data, and the processor is used in the steps of the above-described method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow.

[0056] This application provides a method, apparatus, storage medium, and electronic equipment for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow. This application calculates the longitudinal flow velocity and turbulent diffusion coefficient of the water flow using hydrodynamic parameters of the river area. Based on the governing equation of random displacement, it calculates and tracks the fish egg transport process, using the fish egg adsorption probability as the criterion for adsorption, predicting the adsorption time and location of the fish eggs. Combined with a random displacement model, it determines the significant altering effect of aquatic vegetation on the transport of sticky fish eggs, accurately predicting the adsorption time and distance of fish eggs in vegetated river channels. This is beneficial for developing targeted fish egg protection measures in practical engineering. For example, based on the hydrodynamic and vegetation characteristics of the spawning ground area, the adsorption location and time of fish eggs can be predicted, allowing for targeted protection measures to improve the survival rate of the fish eggs. Attached Figure Description

[0057] The technical solution and other beneficial effects of this application will become apparent from the following detailed description of specific embodiments in conjunction with the accompanying drawings.

[0058] Figure 1 A flowchart illustrating the method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, as provided in this application embodiment.

[0059] Figure 2 A flowchart for calculating the adsorption time and adsorption location of fish eggs provided in the embodiments of this application.

[0060] Figure 3 This is one of the schematic diagrams of flow field velocity and turbulent diffusion coefficient distribution provided in the embodiments of this application.

[0061] Figure 4 This is the second schematic diagram of the flow field velocity and turbulent diffusion coefficient distribution provided in the embodiments of this application.

[0062] Figure 5 The fish egg adsorption time and adsorption location distribution and normal distribution fitting diagram provided in the embodiments of this application.

[0063] Figure 6 This is a schematic diagram showing the relationship between the fish egg adsorption location and the emergent vegetation density provided in an embodiment of this application.

[0064] Figure 7 This is a schematic diagram illustrating the relationship between fish egg adsorption time and emergent vegetation density, provided in an embodiment of this application.

[0065] Figure 8 This is a schematic diagram of the device for predicting the adsorption time and distance of sticky fish eggs in vegetation-filled water flow, provided in an embodiment of this application.

[0066] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0067] Figure 10 Another structural schematic diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0068] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0069] This application provides a method, apparatus, storage medium, and electronic device for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow. The device for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow provided in this application can be integrated into an electronic device, such as a terminal or server. The terminal can include a tablet computer, laptop computer, personal computer (PC), microprocessor box, or other devices.

[0070] Please see Figure 1 , Figure 1 The flowchart illustrates a method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, as provided in this application embodiment. This method, applied in electronic devices, includes the following steps:

[0071] S1, obtain the basic hydrodynamic parameters of the river area under study.

[0072] Among them, the basic hydrodynamic parameters include riverbed slope, river intrusion depth, water flow velocity, and vegetation density.

[0073] S2, based on the basic hydrodynamic parameters, calculate the longitudinal flow velocity and turbulent diffusion coefficient.

[0074] In one embodiment, step S2 includes the following steps:

[0075] S21. Calculate the cross-sectional average flow velocity of emergent vegetation and the turbulent diffusion coefficient of emergent vegetation based on riverbed slope and vegetation density.

[0076] Specifically, assuming the vegetation is a rigid rod, the average cross-sectional velocity U of the emergent vegetation flow is calculated using the law of conservation of energy in the river channel:

[0077]

[0078] Where g is the acceleration due to gravity, and s is the riverbed slope. It is the area density of vegetation (the water-blocking area of ​​vegetation per unit volume). This represents the vegetation drag coefficient.

[0079] The turbulent diffusion coefficient of emergent vegetation can be calculated using the following formula:

[0080]

[0081] in, The average cross-sectional velocity of the water flow in emergent vegetation. The diameter of the vegetation. For empirical coefficients, empirical coefficients The value of varies depending on the calculated diffusion coefficient. When calculating the vertical diffusion coefficient... =0.2, and for the calculation of the longitudinal (water flow direction) diffusion coefficient, the value of this coefficient is 0.8.

[0082] S22, calculate the cross-sectional average velocity and turbulent diffusion coefficient of the submerged vegetation based on the river intrusion depth, water flow velocity and vegetation density.

[0083] for The average flow velocity across the submerged vegetation top area is:

[0084]

[0085] in, The roughness height of the vegetated river channel, The zero-plane displacement height of the rough boundary represents the center location of momentum infiltration in the vegetated area. For water, the constant is usually 0.40.

[0086] in, , The depth of river intrusion.

[0087] The formula for calculating intrusion depth is:

[0088]

[0089] Roughness height It mainly depends on the effective height. Based on the water flow stratification characteristics of vegetated areas, the roughness height is related to vegetation density and invasion depth. For dense vegetation, i.e. The roughness height can be calculated using the following formula:

[0090]

[0091] for In the upper layer of vegetation, the water flow is affected by fluid gravity and turbulent shear stress, and the average flow velocity of the submerged vegetation section is:

[0092]

[0093] in, This represents the water flow velocity at the top of the vegetation. This value can be calculated using the formula for calculating the average flow velocity across the submerged vegetation cross-section. This is an empirical coefficient. .

[0094] for Within the vegetated wake zone, the flow velocity is approximately constant, with only slight variations near the riverbed bottom. Vegetation drag and fluid gravity are the primary forces at play, while other forces, such as Reynolds stress, are relatively weak and can be ignored. Based on the balance between gravity and drag, the average flow velocity across the submerged vegetation section within the wake zone can be derived as follows:

[0095] .

[0096] exist In the submerged vegetation top area, influenced by the KH unstable eddy, momentum and mass exchange are intense, resulting in a turbulent diffusion coefficient at this location that is the highest along the entire channel depth.

[0097]

[0098] in, Velocity in the top vegetation zone and velocity in the wake zone Speed ​​difference, The thickness of the hybrid layer.

[0099] for In the wake zone within vegetation, the turbulent diffusion coefficient of the submerged vegetation is:

[0100] .

[0101] To simplify the expression for the diffusion coefficient, we retain the key characteristics of the diffusion properties and use an approximation method to describe it. Based on the two formulas above, the maximum values ​​of the wake zone and the top of the vegetation are determined, and the diffusion intensity at the water surface is assumed to be zero. The region between the above three characteristic locations is simplified by approximating a linear expression.

[0102] S3, Determine the adsorption probability of fish eggs. P a .

[0103] Determined adsorption probability P a This parameter represents the probability of an adsorption event when fish eggs move to the bottom of the riverbed. It is closely related to the riverbed sediment, water flow conditions, and characteristics of fish eggs, and can generally be set as a constant.

[0104] S4. Construct a random displacement model by inputting the hydrodynamic basic parameters, the longitudinal flow velocity of the water, and the turbulent diffusion coefficient into the random displacement model to obtain the adsorption time and adsorption location of the fish eggs.

[0105] Among them, the random displacement model belongs to the Lagrange model. Considering two-dimensional vertical calculation, the model can trace and calculate the drift path of each fish egg. The formula for calculating the drift path of the fish egg is:

[0106]

[0107]

[0108] in, and These are the water flow direction and the vertical direction, respectively. i and( i +1) indicates the first i Subsequent i +1 iterations, and These represent the longitudinal velocity of the water flow and the settling velocity of the fish egg particles, respectively. R is the time step for iteration, and it is a random number with a mean of 0 and a standard deviation of 1, used to simulate the effect of the randomness of turbulence on the movement of fish egg particles.

[0109] Since the longitudinal water flow velocity is very high, the longitudinal movement of fish egg particles is dominated by the water flow velocity. Therefore, the governing equation only considers the vertical pulsation of the velocity, i.e., the last term of the above equation, which represents the physical meaning of the vertical pulsation velocity of the water flow affecting the particles within a time step. The vertical displacement caused by the action.

[0110] When the transported viscous fish eggs move to the bottom boundary of the riverbed, there is a certain probability that they will be adsorbed. Based on the adsorption probability, assuming that the adsorbed fish eggs will no longer move, this position and time are the adsorption distance and time of the fish egg particles. Figure 2 A flowchart for calculating the adsorption time and adsorption location of fish eggs is provided in the embodiments of this application, such as... Figure 2 As shown, this process includes:

[0111] (1) Calculate time T based on hydrodynamic parameters, fish egg adsorption probability time step, and other parameters;

[0112] (2) Determine the number of fish eggs n and the spawning location;

[0113] (3) Let i = N+1, calculate the number of n fish eggs (N+1). The position at that moment;

[0114] (4) Count the number of fish eggs n1 where z<0, and generate n1 random numbers R1 uniformly distributed between (0,1);

[0115] (5) When R1≤ P a At this time, the fish eggs are adsorbed, and when R1> P a At that time, the fish eggs react;

[0116] (6) Display the location of fish eggs;

[0117] (7) Count the number of fish eggs that have been adsorbed (Na);

[0118] (8) When t≥T or Na=n, count the adsorption time and location of the fish eggs; otherwise, return to step (3).

[0119] The above steps are illustrated below through a specific embodiment:

[0120] 1. Determine the hydrodynamic conditions of the study area.

[0121] The method provided by this invention is applicable to various computational needs, requiring only the flow field information and fish egg characteristic information of the desired scenario for calculation. Preferably, the calculation is performed in a two-dimensional vertical configuration with a riverbed slope of s=0.01 and a flow rate of 0.053 m³ / s. 3 / s, the fish egg particles are released at the water surface, and the corresponding water depth in the absence of vegetation is calculated to be 0.16 m / s according to the logarithmic distribution formula of open channel velocity. With vegetation, to study the effect of vegetation density on the fish egg adsorption characteristics, five different vegetation densities were set up, namely... =2, 4, 6, 7 and 8 m -1 The water depth and the corresponding average flow velocity across the cross section are calculated based on the flow rate, bottom slope, and resistance of vegetation to the water flow.

[0122] 2. Calculate the longitudinal velocity and turbulent diffusion coefficient of the water flow.

[0123] 2.1 Water flow containing emergent vegetation

[0124] Figure 3 This is one of the schematic diagrams of flow field velocity and turbulent diffusion coefficient distribution provided in the embodiments of this application, such as... Figure 3 As shown, the cross-sectional average flow velocity of emergent vegetation and the turbulent diffusion coefficient of emergent vegetation are calculated based on the riverbed slope and vegetation density.

[0125] 2.2 Water flow including submerged vegetation

[0126] Figure 4 This is the second schematic diagram of the flow field velocity and turbulent diffusion coefficient distribution provided in the embodiments of this application, as shown below. Figure 4As shown, the average cross-sectional velocity and turbulent diffusion coefficient of the submerged vegetation are calculated based on the river intrusion depth, water flow velocity, and vegetation density.

[0127] 3. Selection of Adsorption Probability

[0128] The adsorption probability is generally closely related to the characteristics of the spawning ground substrate, the characteristics of the fish eggs, and hydrodynamic conditions. This parameter has a significant impact on the adsorption location of the fish eggs and usually needs to be determined through experiments or field surveys. In this embodiment, the adsorption probability is set to 1 for calculation, assuming that the fish eggs will be adsorbed when they reach the bottom boundary of the riverbed. Since the settling velocity of the fish eggs is relatively large compared to the turbulent diffusion and shear flow velocity at the bottom of the riverbed, the probability of the fish eggs being adsorbed is extremely high. Therefore, the assumption in this embodiment is reasonable. In practical applications, when the conditions of the study area change, only the corresponding fish egg adsorption probability needs to be input, and the method and device of this invention can be used to directly perform the calculation.

[0129] 4. Statistical analysis of the spatiotemporal characteristics of fish egg adsorption

[0130] After the iterative calculation is completed, the locations and adsorption times of all adsorbed fish eggs are statistically analyzed and fitted with a normal distribution to show the spatiotemporal characteristics of fish egg adsorption. Figure 5 The fish egg adsorption time and adsorption location distribution and normal distribution fitting diagram provided in the embodiments of this application are as follows: Figure 5 The figure shows the calculation of the no-vegetation case and the results of this invention. a v =6 m -1 The adsorption location and adsorption time under the operating conditions.

[0131] Furthermore, this invention also uses the above method to predict the spatiotemporal adsorption of fish eggs based on vegetation density, and the results are as follows: Figure 6 and Figure 7 As shown, Figure 6 This is a schematic diagram illustrating the relationship between the fish egg adsorption location and the emergent vegetation density provided in an embodiment of this application. Figure 7 This diagram illustrates the relationship between fish egg adsorption time and emergent vegetation density, as provided in an embodiment of this application. Figure 6 and Figure 7 This further demonstrates the significant impact of aquatic vegetation on fish egg adsorption, confirming the key role of this invention in practical applications.

[0132] This application calculates the longitudinal flow velocity and turbulent diffusion coefficient of water flow using hydrodynamic parameters of the river channel. Based on the governing equations of random displacement, it calculates and tracks the fish egg transport process, using the fish egg adsorption probability as the criterion for adsorption, predicting the adsorption time and location of fish eggs. Combined with the random displacement model, it determines the significant altering effect of aquatic vegetation on the transport of sticky fish eggs, accurately predicting the adsorption time and distance of fish eggs in vegetated river channels. This is beneficial for developing targeted fish egg protection measures in practical engineering. For example, based on the hydrodynamic and vegetation characteristics of the spawning ground area, the adsorption location and time of fish eggs can be predicted, allowing for targeted protection measures to improve the survival rate of fish eggs.

[0133] Based on the method described in the above embodiments, this embodiment will further describe the adsorption time and distance prediction device for sticky fish eggs in vegetated water flow. The adsorption time and distance prediction device for sticky fish eggs in vegetated water flow can be implemented as an independent entity or integrated into an electronic device. The electronic device can be a terminal, server, or other device. The terminal can include a tablet computer, a laptop computer, a personal computer (PC), a microprocessor box, or other devices.

[0134] Please see Figure 8 , Figure 8 This application provides a specific description of a device for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, which is applied in electronic devices. This device may include:

[0135] The acquisition module is used to acquire basic hydrodynamic parameters of the studied river area;

[0136] The calculation module is used to calculate the longitudinal flow velocity and turbulent diffusion coefficient of the water flow based on the basic hydrodynamic parameters;

[0137] The determination module is used to determine the adsorption probability of fish eggs;

[0138] The prediction module is used to construct a stochastic displacement model. The basic hydrodynamic parameters, longitudinal flow velocity, and turbulent diffusion coefficient are input into the stochastic displacement model to obtain the adsorption time and location of the fish eggs.

[0139] Furthermore, the device for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow also includes:

[0140] The fish egg movement area determination module is used to define the restricted area for fish egg transport. If the fish egg moves above the water surface, it will bounce back. If the fish egg moves to the bottom of the riverbed, the module will determine whether the fish egg will be adsorbed or bounce back and be transported with the current again by using the adsorption probability.

[0141] Specifically, the fish egg movement area determination module uses the flow field space range as the transport restriction area for fish eggs. If the fish eggs move beyond the water surface, they are bounced back. If the fish eggs move to the bottom of the riverbed, the module determines whether the fish eggs will be adsorbed or bounced back and transported with the flow again by using the adsorption probability.

[0142] The iterative calculation module is used to set the starting position and time of the fish egg drift and repeatedly calculate the spatial position of the fish egg.

[0143] Numerous fish eggs are released simultaneously from a designated spawning location. The starting position and time (0) of the fish egg drift are set. Under the influence of hydrodynamic parameters, the fish eggs drift in the flow field. The iteration time step is set, and the spatial position of the fish eggs is calculated iteratively.

[0144] The adsorption judgment module is used to determine whether near-bottom fish eggs are adsorbed to the bottom of the riverbed based on the adsorption probability. If the fish eggs are adsorbed, they will stop moving; if the fish eggs are not adsorbed, they will continue to move with the current.

[0145] The results display module is used to display the location of fish eggs at a specific time according to the set display time step.

[0146] The control module is used to receive the operator's input of the time to stop the iterative calculation, and the iterative calculation will automatically stop after the specified time.

[0147] The input display module is connected to the fish egg movement area determination module, iterative calculation module, adsorption judgment module, display module, and control module, respectively, and is used to receive the hydrodynamic basic parameters of the calculation area input by the operator as input data.

[0148] The operator inputs the time to stop the iterative calculation. The iterative calculation will automatically stop after the specified time. By default, the iteration will automatically stop after all fish eggs have been adsorbed onto the riverbed bottom module. It is connected to the fish egg movement area determination module, iterative calculation module, adsorption judgment module, input display module, and result display module to control their operation.

[0149] The operator inputs data such as water depth, flow rate, bottom slope, vegetation density, fish egg density, and adsorption probability for the calculation area. The parameters input to the display unit are crucial; they dynamically adjust the calculation results from the fish egg movement area determination module, iterative calculation module, adsorption judgment module, result display module, and control module based on control commands. The result display module dynamically displays the calculation results in the form of data and images.

[0150] In specific implementation, the above modules and / or units can be implemented as independent entities, or they can be arbitrarily combined and implemented as the same or several entities. For the specific implementation of the above modules and / or units, please refer to the previous method embodiments. For the specific beneficial effects that can be achieved, please also refer to the beneficial effects in the previous method embodiments, which will not be repeated here.

[0151] In addition, embodiments of this application also provide an electronic device, which may be a computer, tablet computer, or other similar device. Figure 9 As shown, the electronic device 400 includes a processor 401 and a memory 402. The processor 401 and the memory 402 are electrically connected.

[0152] The processor 401 is the control center of the electronic device 400. It connects various parts of the electronic device through various interfaces and lines. By running or loading the application program stored in the memory 402 and calling the data stored in the memory 402, it performs various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole.

[0153] In this embodiment, the processor 401 in the electronic device 400 loads the instructions corresponding to the processes of one or more application programs into the memory 402 according to the following steps, and the processor 401 runs the application programs stored in the memory 402 to realize various functions:

[0154] To obtain the basic hydrodynamic parameters of the river channel area under study;

[0155] Based on the aforementioned hydrodynamic fundamental parameters, calculate the longitudinal flow velocity and turbulent diffusion coefficient;

[0156] Determine the adsorption probability of fish eggs;

[0157] A random displacement model is constructed, and the hydrodynamic basic parameters, the longitudinal flow velocity of the water flow, and the turbulent diffusion coefficient are input into the random displacement model to obtain the adsorption time and adsorption location of the fish eggs.

[0158] This electronic device can implement the steps in any embodiment of the method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow provided in the embodiments of this application. Therefore, it can achieve the beneficial effects that any method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow provided in the embodiments of this invention can achieve. For details, please refer to the previous embodiments, which will not be repeated here.

[0159] Figure 10A specific structural block diagram of an electronic device provided in an embodiment of the present invention is shown. This electronic device can be used to implement the method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow provided in the above embodiments. The electronic device 500 can be a terminal, server, or other device. The terminal can include a tablet computer, laptop computer, personal computer (PC), microprocessor box, or other devices.

[0160] RF circuit 510 is used to receive and transmit electromagnetic waves, converting electromagnetic waves into electrical signals and vice versa, thereby enabling communication with communication networks or other devices. RF circuit 510 may include various existing circuit elements used to perform these functions, such as antennas, radio frequency transceivers, digital signal processors, encryption / decryption chips, subscriber identity modules (SIM cards), memory, etc. RF circuit 510 can communicate with various networks such as the Internet, corporate intranets, and wireless networks, or communicate with other devices via wireless networks. The aforementioned wireless networks may include cellular telephone networks, wireless local area networks (WLANs), or metropolitan area networks (MANs). The aforementioned wireless networks may use various communication standards, protocols, and technologies, including but not limited to Global System for Mobile Communication (GSM), Enhanced Data GSM Environment (EDGE), Wideband Code Division Multiple Access (WCDMA), Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Wireless Fidelity (Wi-Fi) (such as IEEE 802.11a, IEEE 802.11b, IEEE 802.11g, and / or IEEE 802.11n), Voice over Internet Protocol (VoIP), Worldwide Interoperability for Microwave Access (Wi-Max), other protocols for email, instant messaging, and short messages, and any other suitable communication protocols, including those that have not yet been developed.

[0161] The memory 520 can be used to store software programs and modules, such as the program instructions / modules corresponding to those in the above embodiments. The processor 580 executes various functional applications and data processing by running the software programs and modules stored in the memory 520, such as taking pictures with the front-facing camera, processing the captured images, and switching the display colors of the content displayed on the screen. The memory 520 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 520 may further include memory remotely located relative to the processor 580, and these remote memories can be connected to the electronic device 500 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0162] The input unit 530 can be used to receive input numeric or character information, and to generate a keyboard and mouse related to user settings and function control.

[0163] Display unit 540 can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces, which can be composed of graphics, text, icons, video, and any combination thereof. Display unit 540 may include display panel 541, which may optionally be configured in the form of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), or other similar forms.

[0164] Audio circuitry 560, speaker 561, and microphone 562 provide an audio interface between the user and electronic device 500. Audio circuitry 560 converts received audio data into electrical signals and transmits them to speaker 561, where speaker 561 converts them into sound signals for output. Conversely, microphone 562 converts collected sound signals into electrical signals, which are then received by audio circuitry 560, converted back into audio data, and processed by processor 580. The audio data is then transmitted via RF circuitry 510 to, for example, another terminal, or output to memory 520 for further processing. Audio circuitry 560 may also include an earphone jack to facilitate communication between external headphones and electronic device 500.

[0165] Electronic device 500, through transmission module 570 (e.g., Wi-Fi module), can help users receive requests, send information, etc., providing users with wireless broadband internet access. Although transmission module 570 is shown in the figure, it is understood that it is not an essential component of electronic device 500 and can be omitted as needed without changing the essence of the invention.

[0166] The processor 580 is the control center of the electronic device 500. It connects to various parts of the phone via various interfaces and lines, and performs various functions and processes data of the electronic device 500 by running or executing software programs and / or modules stored in the memory 520, and by calling data stored in the memory 520, thereby providing overall monitoring of the electronic device. Optionally, the processor 580 may include one or more processing cores; in some embodiments, the processor 580 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into the processor 580.

[0167] Electronic device 500 also includes a power supply 590 (such as a battery) that supplies power to various components. In some embodiments, the power supply may be logically connected to processor 580 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 590 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0168] Although not shown, the electronic device 500 also includes cameras (such as front-facing cameras and rear-facing cameras), Bluetooth modules, etc., which will not be described in detail here. Specifically, in this embodiment, the display unit of the electronic device is a touch screen display, and the mobile terminal also includes a memory and one or more programs, wherein one or more programs are stored in the memory and configured to be executed by one or more processors. One or more programs contain instructions for performing the following operations:

[0169] To obtain the basic hydrodynamic parameters of the river channel area under study;

[0170] Based on the aforementioned hydrodynamic fundamental parameters, calculate the longitudinal flow velocity and turbulent diffusion coefficient;

[0171] Determine the adsorption probability of fish eggs;

[0172] A random displacement model is constructed, and the hydrodynamic basic parameters, the longitudinal flow velocity of the water flow, and the turbulent diffusion coefficient are input into the random displacement model to obtain the adsorption time and adsorption location of the fish eggs.

[0173] In practice, the above modules can be implemented as independent entities or combined in any way to be implemented as the same or several entities. For the specific implementation of the above modules, please refer to the previous method implementation examples, which will not be repeated here.

[0174] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor. Therefore, embodiments of the present invention provide a storage medium storing multiple instructions that can be loaded by a processor to execute the steps of any embodiment of the method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow provided by the present invention.

[0175] The computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0176] Since the instructions stored in the storage medium can execute the steps in any embodiment of the method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow provided in the embodiments of the present invention, the beneficial effects that the method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow provided in the embodiments of the present invention can achieve can be seen in the previous embodiments, and will not be repeated here.

[0177] The above provides a detailed description of the method, apparatus, storage medium, and electronic device for predicting the adsorption time and distance of sticky fish eggs in vegetation-filled water flow, as provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and its core ideas. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for predicting the adsorption time and distance of sticky fish eggs in vegetation-filled water flow, characterized in that, The method includes: (1) Calculate time T based on hydrodynamic basic parameters and fish egg adsorption probability time step parameters; wherein, the hydrodynamic basic parameters include at least riverbed slope, river intrusion depth, water flow velocity and vegetation density; (2) Determine the number of fish eggs n and the spawning location; (3) Let i = N+1, calculate the number of n fish eggs (N+1). The position at that moment; Based on the fundamental hydrodynamic parameters, calculate the longitudinal flow velocity and turbulent diffusion coefficient, including: The cross-sectional average flow velocity and turbulent diffusion coefficient of emergent vegetation were calculated based on the riverbed slope and vegetation density. Assuming the vegetation is a rigid rod, calculate the cross-sectional average flow velocity U of the emergent vegetation flow using the law of conservation of energy in the river channel: Where g is the acceleration due to gravity, and s is the riverbed slope. It is the area density of vegetation (the water-blocking area of ​​vegetation per unit volume). This is the vegetation drag coefficient; The turbulent diffusion coefficient of emergent vegetation is calculated by the following formula: in, The average cross-sectional velocity of the water flow in emergent vegetation. The diameter of the vegetation. This is an empirical coefficient; Calculate the cross-sectional average velocity and turbulent diffusion coefficient of the submerged vegetation based on the river intrusion depth, water flow velocity, and vegetation density: for The average flow velocity across the submerged vegetation top area is: in, The roughness height of the vegetated river channel, The zero-plane displacement height of the rough boundary represents the center location of momentum infiltration in the vegetated area. Kármán's constant, The friction speed; in, , The depth of river intrusion; The formula for calculating intrusion depth is: For dense vegetation situations, i.e. The roughness height is calculated using the following formula: for In the upper layer of vegetation, the water flow is affected by fluid gravity and turbulent shear stress, and the average flow velocity of the submerged vegetation section is: in, Represents the water flow velocity at the top of the vegetation. The value is calculated using the formula for calculating the average flow velocity across the submerged vegetation cross-section in the top region of the submerged vegetation. This is an empirical coefficient. ; for Within the vegetated wake zone, the average flow velocity across the cross-section submerged by the vegetation is: exist In the submerged vegetation top area, the turbulent diffusion coefficient is the maximum value along the entire river channel depth: in, Velocity in the top vegetation zone and velocity in the wake zone Speed ​​difference, The thickness of the hybrid layer; for In the wake zone within vegetation, the turbulent diffusion coefficient of the submerged vegetation is: Determine the adsorption probability of fish eggs P a ; A random displacement model is constructed, and the hydrodynamic basic parameters, the longitudinal flow velocity of the water flow, and the turbulent diffusion coefficient are input into the random displacement model to obtain the adsorption time and adsorption location of the fish eggs; (4) Count the number of fish eggs n1 where z<0, and generate n1 random numbers R1 uniformly distributed between (0,1); (5) When R1≤ P a At this time, the fish eggs are adsorbed, and when R1> P a At that time, the fish eggs react; (6) Display the location of fish eggs; (7) Count the number of fish eggs that have been adsorbed (Na); (8) When t≥T or Na=n, count the adsorption time and location of the fish eggs; otherwise, return to step (3).

2. The method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow according to claim 1, characterized in that, In the random displacement model, the drift path of the fish eggs is calculated using the basic hydrodynamic parameters, the longitudinal flow velocity, and the turbulence diffusion coefficient. The calculation formula is as follows: in, and These are the direction of water flow and the vertical direction of water flow, respectively. i and( i +1) indicates the first i Subsequent i +1 iterations, and These represent the longitudinal velocity of the water flow and the settling velocity of the fish egg particles, respectively. R is the time step for iteration, and it is a random number with a mean of 0 and a standard deviation of 1, used to simulate the effect of the randomness of turbulence on the movement of fish egg particles.

3. A device for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow, wherein the device is used to implement the method for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow as described in claim 1, characterized in that, include: The acquisition module is used to acquire basic hydrodynamic parameters of the studied river area; The calculation module is used to calculate the longitudinal flow velocity and turbulent diffusion coefficient of the water flow based on the aforementioned hydrodynamic fundamental parameters. The determination module is used to determine the adsorption probability of fish eggs; The prediction module is used to construct a random displacement model. The hydrodynamic basic parameters, the longitudinal flow velocity of the water flow, and the turbulent diffusion coefficient are input into the random displacement model to obtain the adsorption time and adsorption location of the fish eggs.

4. The device for predicting the adsorption time and distance of sticky fish eggs in vegetated water flow according to claim 3, characterized in that, The device further includes: The fish egg movement area determination module is used to define the transport restriction area for fish eggs. If the fish eggs move beyond the water surface, they will be bounced. If the fish eggs move to the bottom of the riverbed, the module will determine whether the fish eggs will be adsorbed or bounced and transported with the current again based on the adsorption probability. The iterative calculation module is used to set the starting position and time of the fish egg drift and repeatedly calculate the spatial position of the fish egg; The adsorption judgment module is used to determine whether the near-bottom fish eggs are adsorbed to the bottom of the riverbed based on the adsorption probability. If the fish eggs are adsorbed, they will stop moving; if the fish eggs are not adsorbed, they will continue to move with the current. The results display module is used to display the location of fish eggs at a specific time according to the set display time step; The control module is used to receive the operator's input of the time to stop the iterative calculation, and the iterative calculation will automatically stop after the specified time; The input display module is communicatively connected to the fish egg movement area determination module, the iterative calculation module, the adsorption judgment module, the display module, and the control module, respectively, and is used to receive the hydrodynamic basic parameters of the calculation area input by the operator as input data.

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