A method for predicting the drift distance and drift time of early fish resources

Abstract

The present invention provides a method for predicting the drifting distance and time of early-stage fish resources, comprising: step S1: collecting basic data of a study area; based on the collected basic data, selecting a fixed section within the early-stage fish resource drifting channel to conduct an early-stage fish resource survey, obtaining the sampling time, survey section location, and early-stage fish resource samples; constructing a model for predicting the drifting age of early-stage fish resources based on the collected basic data; conducting biological identification on the collected early-stage fish resource samples to obtain the development time of early-stage fish resources; and using the constructed model for predicting the drifting age of early-stage fish resources and the development time of early-stage fish resources to predict the drifting distance and time of early-stage fish resources. The present invention fully considers the dynamic changes in river topography and water flow velocity along the river, resulting in more accurate prediction results and providing scientific support for reservoir ecological regulation.

Description

Technical Field

[0001] The present invention relates to the field of water ecological protection, and in particular to a method for predicting the early drifting distance and drifting time of fish resources. Background Art

[0002] Early-stage fish species that lay drifting eggs lack the ability to swim independently during their early developmental stages. They require sufficiently high current velocities to sustain their development while drifting with the current until they develop the ability to swim independently. However, with the increasing construction of dams and the reduction of reservoir flow velocities, early-stage fish species may sink to the bottom and die prematurely, before they develop the ability to swim independently, leading to fish stock losses. Therefore, it is necessary to accurately predict the drift distance or duration of early-stage fish species under different hydrodynamic conditions to support scientific assessments of the suitability of key habitats such as spawning and feeding grounds.

[0003] Existing prediction methods involve setting up field survey sections within the early resource incubation channel to monitor the flow velocity at a single fixed section during the development phase of the early resource over a specific time period. Based on biological characteristics, the length of time the early resource has developed and the estimated time remaining for development are calculated. The drift distance is then estimated by multiplying the single velocity by the development time. This method calculates drift distance using only the flow velocity at the survey section, failing to account for variations in river topography and flow velocity along the river's course. This results in significant discrepancies between the estimated data and actual results, making it unsuitable for addressing the national river ecological protection needs of the new era. Summary of the Invention

[0004] The purpose of the present invention is to overcome the shortcomings of the background technology and provide a method for predicting the drift distance and drift time of early fish resources.

[0005] To achieve the above object, the present invention provides a method for predicting the early drift distance and drift time of fish resources, comprising the following steps:

[0006] Step S1: Collect basic data of the study area, including hydrological data, underwater topographic data, and water project operation data;

[0007] Step S2: Based on the basic data collected in step S1, a fixed section within the early fish resource drift channel is selected to conduct an early fish resource survey, and the sampling time, survey section location, and early resource samples are obtained;

[0008] Step S3: Based on the basic data collected in step S1, a fish early resource drifting age prediction model is constructed;

[0009] Step S4: conducting biological identification on the early fish resource samples collected in step S2 to obtain the development time of the early fish resource;

[0010] Step S5: using the fish early resource drifting age prediction model constructed in step S3 and the fish early resource development time obtained in step S4 to predict the early resource drifting distance and drifting time.

[0011] Furthermore, the hydrological data includes flow, water level and water temperature; the underwater topography data includes the elevation of the riverbed below the water surface; and the water project operation data includes scheduling regulations, water level in front of the dam and downstream flow.

[0012] Furthermore, step S3 includes: based on the basic data collected in step S1, constructing a hydrodynamic mathematical model of the drifting channel, simulating the water depth and flow velocity distribution of the drifting channel, and then constructing a fish early resource drifting age prediction model, and synchronously inputting the drifting channel water depth and flow velocity simulated by the hydrodynamic mathematical model of the drifting channel into the fish early resource drifting age prediction model for predicting the fish early resource drifting age under changing water flow conditions.

[0013] Furthermore, the hydrodynamic mathematical model of the drift channel is:

[0014]

[0015] Where Q is the flow rate (m 3 / s); A is the cross-sectional area of ​​the flow (m 2 ); x is the longitudinal coordinate (m); t is the time (s); q is the lateral inflow or outflow (m 2 / s); α is the momentum distribution coefficient; g is the acceleration due to gravity (m / s 2 ); h is the water depth (m); C is the coefficient of 1 / 2 / s); R is the hydraulic radius (m);

[0016] The fish early resource drifting age prediction model is:

[0017]

[0018] Where C is the early tracer resource concentration (ind / m 3 ); D is the early resource diffusion coefficient of the tracer (m 2 / s); α is the tracer early bleaching age concentration ((ind·s) / m 3 ); a is the early resource drift age (s).

[0019] Furthermore, step S4 includes:

[0020] Step S41, determining the location of the fish early resource survey section and the development time;

[0021] Step S42: determining the location of the early fish resource survey section and the time required for development;

[0022] Step S43, determining the location of fish spawning grounds and the location of early resource survey sections;

[0023] Among them, the location of the section for early fish resource survey is determined on-site in step S2, the time when early fish resources have developed and the time they still need to develop are determined by professionals through the biological morphology of the early resource samples obtained in step S2, and the location of the fish spawning ground is obtained through early resource survey and data research and analysis.

[0024] Furthermore, step S5 specifically includes:

[0025] Step S51: Based on the location of the early fish resource survey section and the development time data determined in step S41, the early fish resource drifting age prediction model constructed in step S3 is used to predict the achieved drifting distance ΔS0 of the early fish resource and the location of the spawning ground;

[0026] The early drift age of the spawning site location is expressed as:

[0027] a0=a i -t i (6)

[0028] Where a0 is the early drift age of the spawning site (h); a i is the early drift age of resources at the location of the investigation section (h); t i is the development time of early resources (h);

[0029] The location of the spawning ground is the spatial location corresponding to the early resource drifting age a0. At this time, the early fish resources have reached the drifting distance ΔS0, which is expressed as:

[0030] ΔS0=|S i -S0| (7)

[0031] Where ΔS0 is the drift distance of early resources (km); S i is the distance from the survey section to the dam (km); S0 is the distance from the spawning site to the dam (km), corresponding to the spatial distribution of the early resource drifting age a0.

[0032] Step S52: Based on the location of the early fish resource survey section and the data on the remaining development time determined in step S42, the early fish resource drifting age prediction model constructed in step S3 is used to predict the remaining drifting distance ΔS of the early fish resource. i and baiting site locations;

[0033] The early drift age of the resources at the location of the baiting site is expressed as:

[0034] a e =a i +t e (8)

[0035] Where a e is the early drift age of the resources at the location of the foraging site (h); a i is the early drift age of resources at the location of the investigation section (h); t e The time required for early stage resources to develop (h);

[0036] The location of the feeding site is the early resource drift age a e The corresponding spatial position, at this time, the early fish resources still need to drift distance expressed as:

[0037] ΔS i =|S i -S e | (9)

[0038] Where, ΔS i The distance that early resources need to drift (km); S i is the distance between the survey section and the dam (km); S e is the distance from the feeding site to the dam (km), corresponding to the early resource drift age a e The spatial distribution location of

[0039] Step S53: Based on the spawning ground location and the early resource survey location determined in step S43, the fish early resource drifting age prediction model constructed in step S3 is used to predict the fish early resource drifting time;

[0040] t i =a i -a0 (10)

[0041] Where, t i is the early resource drift time of the investigated section (h); a i is the early drifting age of resources at the location of the investigation section (h); a0 is the early drifting age of resources at the location of the spawning ground (h).

[0042] The present invention has the following beneficial effects:

[0043] 1. A method for calculating the drifting age of early fish resources was proposed, which provides a scientific basis for predicting the drifting distance and time of early fish resources.

[0044] 2. This invention predicts the distance and duration of early-stage fish stocks, taking into account the dynamic variations in river topography and water velocity along the river. This method provides more accurate predictions than traditional calculation methods. The greater the spatiotemporal variability in the hydrodynamics of the early-stage fish stock drift path, the more reliable the predictions are compared to traditional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1A flow chart of a method for predicting the early drift distance and drift time of fish resources according to one embodiment of the present invention;

[0046] Figure 2 This is a flow velocity distribution diagram along the early resource drift channel of one embodiment of the present invention. DETAILED DESCRIPTION

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0048] like Figure 1 The embodiment of the present invention provides a method for predicting the early drift distance and drift time of fish resources, comprising the following steps:

[0049] Step S1: Collect basic data for the study area; the basic data includes hydrological data, underwater topographic data, and water project operation data. The hydrological data includes flow, water level, water temperature, etc.; the underwater topographic data includes the elevation of the riverbed below the water surface; and the water project operation data includes scheduling regulations, dam water level, and downstream flow.

[0050] Step S2: Based on the basic data collected in step S1, a fixed section within the drift channel of early fish resources is selected to conduct an early fish resource survey.

[0051] Specifically, surveys should be conducted during the peak fish breeding season, covering both daytime and nighttime. Survey details should include sampling time, survey section location, and early resource samples.

[0052] Step S3: constructing a fish early resource drifting age prediction model;

[0053] Specifically, based on the basic data collected in step S1, a hydrodynamic mathematical model of the drifting channel is constructed to simulate the water depth and flow velocity distribution of the drifting channel, and then a fish early resource drifting age prediction model is constructed. The water depth and flow velocity of the drifting channel simulated by the hydrodynamic mathematical model of the drifting channel are synchronously input into the fish early resource drifting age prediction model. The fish early resource drifting age can be predicted under changing water flow conditions, thereby realizing the coupling of the hydrodynamic mathematical model of the drifting channel and the fish early resource drifting age prediction model, and finally realizing the simulation prediction of the early resource drifting age.

[0054] Furthermore, the hydrodynamic mathematical model of the drift channel can be expressed as:

[0055]

[0056] Where Q is the flow rate (m 3 / s); A is the cross-sectional area of ​​the flow (m 2 ); x is the longitudinal coordinate (m); t is the time (s); q is the lateral inflow or outflow (m 2 / s); α is the momentum distribution coefficient; g is the acceleration due to gravity (m / s 2 ); h is the water depth (m); C is the coefficient of 1 / 2 / s); R is the hydraulic radius (m);

[0057] Furthermore, the early fish resource drifting age prediction model can be expressed as:

[0058]

[0059] Where C is the early tracer resource concentration (ind / m 3 ); D is the early resource diffusion coefficient of the tracer (m 2 / s); α is the tracer early bleaching age concentration ((ind·s) / m 3 ); a is the early resource drift age (s).

[0060] Step S4: identifying the early development time of fish resources;

[0061] Specifically, biological identification is performed on the early fish resource samples collected in step S2, and the development time is identified based on the embryonic development morphology, and the development time required is analyzed. Step S4 specifically includes:

[0062] Step S41, determining the location of the fish early resource survey section and the development time;

[0063] Step S42: determining the location of the early fish resource survey section and the time required for development;

[0064] Step S43: Determine the location of the fish spawning grounds and the location of the early resource survey section.

[0065] Specifically, the location of the section for the early fish resource survey is determined on-site in step S2. The time of development and remaining development of the early fish resource is determined by professionals through biomorphological analysis of the early fish resource samples obtained in step S2. The location of fish spawning grounds can be determined through early resource surveys and data analysis.

[0066] In this example, an early fish resource survey was conducted at a fixed section of a drift channel in a certain reservoir area, and the development time obtained through identification is shown in Table 1.

[0067] Table 1 Fish development timeline

[0068]

[0069]

[0070] Step S5: using the fish early resource drifting age prediction model constructed in step S3 and the fish early resource development time obtained in step S4 to predict the early resource drifting distance and drifting time.

[0071] Specifically, the fish early resource drifting age prediction model constructed in step S3 is used to simulate the distribution pattern of early resource drifting age in the study area under the hydrological and water engineering operation conditions during the early fish resource survey in step S2.

[0072] Step S5 specifically includes:

[0073] Step S51: Based on the early fish resource survey section location and development time data determined in step S41, the early fish resource drifting age prediction model constructed in step S3 is used to predict the achieved drifting distance ΔS0 and spawning ground location of the early fish resource.

[0074] The early drift age of the spawning site location can be expressed as:

[0075] a0=a i -t i (6)

[0076] Where a0 is the early drift age of the spawning site (h); a i is the early drift age of resources at the location of the investigation section (h); t i is the development time of early resources (h);

[0077] The location of the spawning ground is the spatial location corresponding to the early resource drift age a0. At this time, the early fish resources have reached the drift distance ΔS0, which can be expressed as:

[0078] ΔS0=|S i -S0| (7)

[0079] Where ΔS0 is the drift distance of early resources (km); S i is the distance from the survey section to the dam (km); S0 is the distance from the spawning site to the dam (km), corresponding to the spatial distribution of the early resource drifting age a0.

[0080] Step S52: Based on the location of the early fish resource survey section and the data on the remaining development time determined in step S42, the early fish resource drifting age prediction model constructed in step S3 is used to predict the remaining drifting distance ΔS of the early fish resource. i and baiting site locations.

[0081] The early drift age of the baiting site can be expressed as:

[0082] a e =a i +t e (8)

[0083] Where a e is the early drift age of the resources at the location of the foraging site (h); a i is the early drift age of resources at the location of the investigation section (h); t e The time required for early stage resources to develop (h);

[0084] The location of the feeding site is the early resource drift age a e The corresponding spatial position, at this time, the distance that the early fish resources still need to drift can be expressed as:

[0085] ΔS i =|s i -S e | (9)

[0086] Where, ΔS i The distance that early resources need to drift (km); S i is the distance between the survey section and the dam (km); S e is the distance from the feeding site to the dam (km), corresponding to the early resource drift age a e spatial distribution location.

[0087] Step S53: Based on the spawning ground location and early resource survey location determined in step S43, the fish early resource drifting age prediction model constructed in step S3 is used to predict the fish early resource drifting time.

[0088] t i =a i -a0 (10)

[0089] Where, t i is the early resource drift time of the investigated section (h); a i is the early drifting age of resources at the location of the investigation section (h); a0 is the early drifting age of resources at the location of the spawning ground (h).

[0090] Through the above steps, the drift range (including the drift range achieved and the drift range still required) and drift time of early fish resources can be accurately predicted, and the location of fish spawning grounds and feeding grounds of early resources after hatching can be determined.

[0091] This embodiment uses the methods of steps S51 and S52 based on the fish early resource development time data determined in step S4 in Table 1 to predict the fish spawning ground location and feeding ground location, the fish early resource drift distance reached and the required drift distance, as shown in Table 2.

[0092] Table 2 Early resource drift prediction table based on the method of the present invention

[0093]

[0094]

[0095] The locations of fish spawning and feeding grounds, the distances reached and the distances still to be reached for early fish resources obtained using the traditional calculation method based on the average flow velocity of the survey section are shown in Table 3.

[0096] Table 3 Early resource drift prediction based on traditional methods

[0097] Spawning site location / km Location of feeding site / km Achieved drift distance / km Remaining drift distance / km 473 113 34 325 489 100 50 339 467 97 28 342 451 82 12 356 451 58 12 381 526 103 88 336 491 82 53 357

[0098] Traditional methods cannot take into account the temporal and spatial variations of water flow velocity and the drift and diffusion effects of fish, and the predicted values ​​have large deviations. Figure 2 As shown in Figure 2, the survey section is 438.75 km away from the dam. At different times, the flow velocity upstream of the survey section is relatively high, while the flow velocity downstream gradually decreases. The spatial variation of flow velocity leads to significant differences in the predictions of early resource drift distances in Tables 2 and 3.

[0099] As shown in Table 4, compared with the traditional method, the reliability of drift distance prediction achieved by the present invention can be improved by 14%-40%, the reliability of drift distance prediction can be improved by 38%-43%, the reliability of spawning location prediction can be improved by 1-36km, and the reliability of feeding ground location prediction can be improved by 124-164km. The degree of improvement in prediction reliability in different implementation scenarios varies with the degree of hydrodynamic variation in the early resource drift channel.

[0100] Table 4

[0101]

[0102]

[0103] This embodiment proposes a method for calculating the drifting age of early-stage fish stocks, providing a scientific basis for predicting the range and duration of early-stage fish stocks. This method fully accounts for the dynamic changes in river topography and water velocity along the river, resulting in more accurate predictions and reducing prediction errors by up to 43% compared to traditional methods.

[0104] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by technicians in this technical field within the technical scope disclosed in the present invention should be covered by the scope of protection of the present invention.

Claims

1. A method for predicting the early drift range and drift time of fish resources, characterized in that: The following steps are involved: Step S1: Collect basic data of the study area, including hydrological data, underwater topographic data, and water project operation data; Step S2: Based on the basic data collected in step S1, a fixed section within the drift channel of early fish resources is selected to conduct an early fish resource survey, and the sampling time, survey section location, and early resource samples are obtained; Step S3: Based on the basic data collected in step S1, a fish early resource drifting age prediction model is constructed; Step S4: conducting biological identification on the early fish resource samples collected in step S2 to obtain the development time of the early fish resource; Step S5: using the fish early resource drifting age prediction model constructed in step S3 and the fish early resource development time obtained in step S4 to predict the early resource drifting distance and drifting time; Step S3 includes: constructing a drift channel hydrodynamic mathematical model based on the basic data collected in step S1, simulating the water depth and flow velocity distribution of the drift channel, and then constructing a fish early resource drift age prediction model, and synchronously inputting the drift channel water depth and flow velocity simulated by the drift channel hydrodynamic mathematical model into the fish early resource drift age prediction model for predicting the fish early resource drift age under changing water flow conditions; The hydrodynamic mathematical model of the drift channel is: （1）； （2）； Where Q is the flow rate in m 3 / s; A is the cross-sectional area of ​​the flow, in m 2 ; is the vertical coordinate, in m; is the time, in seconds; q is the lateral inflow or outflow, in meters 2 / s; is the momentum distribution coefficient; is the acceleration due to gravity, in m / s 2 ; h is the water depth, in meters; is the Xie Cai coefficient, unit is m 1 / 2 / s; R is the hydraulic radius, in m; The fish early resource drifting age prediction model is: （3）； （4）； （5）； Where, It is the tracer of early resource concentration, ind / m 3 ; is the early resource diffusion coefficient, in m 2 / s; It is the concentration of early-stage resource bleaching age, and its unit is (ind·s) / m 3 ; is the early resource drift age, in seconds.

2. the method for predicting fish early stage resource drifting range and drifting time as claimed in claim 1, is characterized in that, The hydrological data includes flow, water level and water temperature; the underwater topography data includes the riverbed topography elevation below the water surface; and the water project operation data includes scheduling regulations, water level in front of the dam and downstream flow.

3. the method for predicting fish early stage resource drifting range and drifting time as claimed in claim 1, is characterized in that, Step S4 includes: Step S41, determining the location of the fish early resource survey section and the development time; Step S42: determining the location of the early fish resource survey section and the time required for development; Step S43, determining the location of fish spawning grounds and the location of early resource survey sections; Among them, the location of the section for early fish resource survey is determined on-site in step S2, the time when early fish resources have developed and the time they still need to develop are determined by professionals through the biological morphology of the early resource samples obtained in step S2, and the location of the fish spawning ground is obtained through early resource survey and data research and analysis.

4. the method for predicting fish early stage resource drifting range and drifting time as claimed in claim 3, is characterized in that, Step S5 specifically includes: Step S51: Based on the fish early resource survey section location and development time data determined in step S41, the fish early resource drifting age prediction model constructed in step S3 is used to predict the fish early resource has reached the drifting range. and spawning ground locations; The early drift age of the spawning site location is expressed as: （6）； Where, is the early drift age of resources at the spawning site, in h; The early drift age of resources at the location of the investigation section, in h; is the development time of early resources, in hours; The location of the spawning ground is the early drift age of the resource The corresponding spatial position, at this time the early fish resources have reached the drift range Expressed as: （7）； Where, The drift distance of early resources has been achieved, in km; is the distance between the location of the survey section and the dam, in km; is the distance from the spawning site to the dam, in km, corresponding to the early drift age of resources The spatial distribution location of Step S52: Based on the location of the early fish resource survey section and the data on the time required for development determined in step S42, the early fish resource drifting age prediction model constructed in step S3 is used to predict the drifting time required for the early fish resource. and baiting site locations; The early drift age of the resources at the location of the baiting site is expressed as: （8）； Where, is the early drift age of resources at the location of the foraging site, in h; The early drift age of resources at the location of the investigation section, in h; The time required for early resources to develop is in hours; The location of the feeding site is the early drift age of the resource The corresponding spatial position, at this time, the early fish resources still need to drift distance expressed as: （9）； Where, The distance that early stage resources need to drift is in km; is the distance between the location of the survey section and the dam, in km; is the distance from the feeding site to the dam, in km, corresponding to the early drift age of the resource The spatial distribution location of Step S53: Based on the spawning ground location and the early resource survey location determined in step S43, the fish early resource drifting age prediction model constructed in step S3 is used to predict the fish early resource drifting time; （10）； Where, The early resource drift time of the investigated section, in h; is the early resource drift age at the location of the investigation section, in h; is the early resource drift age at the spawning site, in h.

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