Method for determining river habitat index based on coupling of vorticity and fish energy consumption

Abstract

The application discloses a river habitat index determination method based on vorticity and fish energy consumption coupling, which comprises the following steps: firstly, extracting the geometric characteristics of the river bed, vegetation and reefs, and constructing a physical model of fish habitat; secondly, obtaining three types of vorticity coefficients through experiments and calculations, quantifying and superimposing to obtain the total vorticity; then, combining the fish cruise basic energy consumption and the vorticity correction coefficient to calculate the actual energy consumption, and obtaining the energy consumption and vorticity suitability index through an exponential function; finally, adopting a geometric mean function to construct a comprehensive suitability index, formulating a grading standard, and realizing habitat suitability determination. The method is suitable for river habitat heterogeneity and hydrological dynamic change, can identify suitable habitat and target design repair measures, provides regulation indexes for fish habitat design of water conservancy and waterway engineering, relies on a standardized process and multi-source verification to guarantee the reliability and repeatability of the results, and helps the protection of fish habitat and the recovery of ecological function in the region.

Description

Technical Field

[0001] This invention relates to the field of water conservancy technology, and in particular to a method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption. Background Technology

[0002] Existing methods for assessing fish habitats can be broadly categorized into three types, all of which have significant limitations: Physical habitat models (represented by PHABSIM) assess habitat solely through the superposition of single-factor suitability curves for flow velocity, water depth, and substrate, neglecting the influence of turbulent characteristics, especially eddy currents, on fish behavior; Niche models rely on statistical correlations between species distribution data and environmental factors, making it difficult to explain the intrinsic mechanisms of "habitat structure and fish response"; Hydrodynamic-ecological coupling models focus on macro-habitats, such as the simulation of water temperature and dissolved oxygen, but lack sufficient characterization of micro-habitats directly utilized by fish, such as eddy current scales, and ignore fish's active selection behavior. A common problem with these three approaches is the failure to quantify the causal chain from water flow eddy current characteristics to fish energy consumption and then to habitat selection, making it difficult for assessment results to guide the scientific regulation of micro-habitats in habitat shaping projects. Summary of the Invention

[0003] To achieve the above objectives, one technical solution adopted by the present invention is: a method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption, the method comprising:

[0004] S1. Geometric features of the riverbed sediment, riverbank vegetation, and reef topography are extracted and a physical model of fish habitat is constructed to provide a basic basis for the analysis of this method.

[0005] S2. The riverbed rough vorticity coefficient, vegetation disturbance vorticity coefficient, and topographic flow vorticity coefficient are obtained through flume tests or field tests and theoretical calculations.

[0006] S3. Based on the physical model of fish habitat, the rough vorticity coefficient of the riverbed, the vorticity coefficient of vegetation disturbance and the vorticity coefficient of topographic flow, the rough vorticity of the riverbed, the vorticity of vegetation disturbance and the vorticity of topographic change of the fish habitat physical model are quantitatively calculated.

[0007] S4. Based on the riverbed rough eddy, vegetation disturbance eddy, and topographic abrupt change eddy, the total eddy of the fish habitat physical model is calculated by superposition.

[0008] S5. Based on the actual energy consumption model, calculate the basic energy consumption of fish cruising without vorticity, and obtain the vorticity correction coefficient according to the distribution characteristics of fish utilization of vorticity. Construct a quantitative relationship between vorticity and energy consumption to quantify the actual energy consumption of fish in different vortex environments.

[0009] S6. Based on the actual energy consumption of fish in different vortex environments, the energy consumption suitability index is calculated according to the exponential function.

[0010] S7. Based on the total vorticity, the vorticity suitability index is calculated according to the exponential function.

[0011] S8. Based on the energy consumption suitability index and the eddy current suitability index, a comprehensive habitat suitability index is constructed using a geometric mean function to determine the comprehensive suitability of fish habitats.

[0012] S9. Determine the classification standard of the comprehensive habitat suitability index based on the comprehensive habitat suitability index and the preset threshold range.

[0013] Furthermore, the geometric characteristics of the riverbed sediment include sediment particle size distribution, surface micro-topography, riverbed plan morphology, and longitudinal profile slope.

[0014] The geometric characteristics of the riparian vegetation include the spatial distribution range of the vegetation community, plant height or crown width, vegetation zone width and layering structure, and the geometric morphology of the vegetation root system.

[0015] The geometric features of the reef topography include the spatial location, shape and size of the reefs, the distribution density and topological relationship of the reef group, and the relative elevation of the reefs to the riverbed.

[0016] Furthermore, S2 includes: S201, collecting the hourly average flow velocity, hydraulic radius, water surface gradient, and riverbed roughness height at each measurement point in the flume test with the expected number of collections; calculating and defining the average value of the vorticity component perpendicular to the plane at each measurement point as the theoretical riverbed roughness vorticity; and inversely deriving the formula for calculating the theoretical riverbed roughness vorticity and taking the average value to obtain the riverbed roughness vorticity coefficient for each riverbed type.

[0017] S202. Collect the hourly average flow velocity, vegetation unit area projection ratio, and vegetation canopy height at each measurement point in the flume test with the expected number of collections; calculate and define the average value of the vorticity component perpendicular to the plane at each measurement point as the theoretical vegetation disturbance vorticity; calculate the cross-sectional average flow velocity at each measurement point, and deduce the theoretical vegetation disturbance vorticity calculation formula and take the average value to obtain the vegetation disturbance vorticity coefficient for each vegetation type.

[0018] S203. Collect the hourly average flow velocity and reef diameter at each measurement point in the reef area during the expected number of collections in the flume test; calculate and define the average value of the vorticity component perpendicular to the plane at each measurement point as the theoretical topographic vorticity; calculate the cross-sectional average flow velocity at each measurement point; deduce the formula for calculating the theoretical topographic vorticity and take the average value to obtain the topographic vorticity coefficient for each type of reef.

[0019] Furthermore, S3 includes S301, which quantifies the hydraulic radius, water surface gradient, and riverbed roughness height based on the physical model of fish habitat; calculates the shear velocity generated by the shear flow on the riverbed wall based on the hydraulic radius and water surface gradient; and couples the riverbed roughness eddy coefficient, shear velocity, and eddy covariance characteristic length to obtain the riverbed roughness eddy covariance of the physical model of fish habitat. When the riverbed roughness element causes flow shear, the larger the eddy covariance characteristic length and the steeper the water surface gradient, the stronger the generated riverbed roughness eddy covariance.

[0020] S302. Based on the physical model of fish habitat, the quantified vegetation unit area projection ratio, quantified cross-sectional average flow velocity, vegetation resistance coefficient to water flow, and vegetation canopy height are obtained. Based on the vegetation unit area projection ratio and cross-sectional average flow velocity, the vegetation additional shear velocity is calculated. The vegetation canopy height, vegetation vorticity coefficient, and vegetation additional shear velocity are coupled to obtain the vegetation disturbance vorticity of the physical model of fish habitat. The larger the vegetation unit area projection ratio and the lower the vegetation vorticity characteristic length, the stronger the disturbance to water flow and the larger the vegetation disturbance vorticity generated.

[0021] S303. Based on the physical model of fish habitat, the diameter of the reef, the angle between the water flow and the reef axis, and the average cross-sectional velocity are quantified. Based on the angle between the water flow and the reef axis and the average cross-sectional velocity, the characteristic velocity difference of the water flow around the reef is calculated. The topographic vorticity coefficient, the reef diameter, and the characteristic velocity difference are coupled to obtain the topographic abrupt vorticity of the physical model of fish habitat.

[0022] The higher the average flow velocity across the cross section, the smaller the diameter of the reef, and the closer the angle between the water flow and the reef... The stronger the topographical abrupt eddy current generated by the flow around the object, the more powerful the eddy current becomes.

[0023] Furthermore, S5 includes S501, collecting the average body weight and average cross-sectional flow velocity of a certain type of fish and inputting them into the actual energy consumption basic model to obtain the basic energy consumption of a certain type of fish cruise without eddy current.

[0024] S502. Fish utilization of eddy current exhibits a Gaussian distribution characteristic. Eddy current correction coefficients are calculated. When the eddy current is the same as the suitable eddy current, energy consumption is the lowest. Eddy current that is too low or too high will increase energy consumption. Among them, the suitable eddy current is the eddy current value with the lowest energy consumption and the most frequent activity of fish. It is obtained by a combination of indoor behavioral experiments and field habitat tracking experiments.

[0025] S503. Based on the vortex correction coefficient and the basic energy consumption of a certain type of fish during cruising without vortex, the actual energy consumption of a certain type of fish in different vortex environments is obtained according to the positive linear function.

[0026] Furthermore, in S502, the vorticity corresponding to the lowest energy consumption value is obtained through indoor behavioral experiments and is defined as the suitable indoor vorticity.

[0027] The results were verified through a field habitat tracking experiment. The eddy current range in which fish appeared most frequently was calculated, and the median value of this eddy current range was defined as the suitable eddy current in the wild.

[0028] When the deviation between the suitable indoor vorticity and the suitable outdoor vorticity is less than the preset deviation value, the average of the suitable indoor vorticity and the suitable outdoor vorticity is taken as the suitable vorticity.

[0029] Furthermore, in S6, the energy consumption suitability index is used to reflect the impact of fish's actual energy consumption in different eddy environments on habitat suitability. Higher actual energy consumption by fish in different eddy environments corresponds to lower habitat suitability. The range of the energy consumption suitability index is... ;

[0030] When the actual energy consumption is zero and the energy consumption suitability index is 1, it indicates that the suitability of the habitat is theoretically optimal.

[0031] When the actual energy consumption equals the energy consumption threshold at which fish cannot survive long-term, and the energy suitability index equals This indicates that the habitat is generally suitable.

[0032] When the actual energy consumption exceeds the energy consumption threshold that fish cannot survive in the long term, and the energy consumption suitability index is less than 0.3, it indicates that the habitat is unsuitable.

[0033] Furthermore, in S7, the eddy current suitability index is used to reflect the impact of total eddy current on habitat suitability, and the range of values ​​for the eddy current suitability index is as follows: ;

[0034] When the total vorticity is the optimal vorticity, the vorticity suitability index is equal to 1. The greater the deviation between the total vorticity and the optimal vorticity, the smaller the value of the vorticity suitability index, which is used to reflect the fish's avoidance behavior in extreme vorticity environments.

[0035] Furthermore, in S8, the habitat suitability index is used to comprehensively reflect fish's preference for habitats, and the range of values ​​for the habitat suitability index is [value range missing]. .

[0036] Furthermore, in S9, the comprehensive habitat suitability index grading standard is as follows:

[0037] When the habitat suitability index is greater than the upper limit of the preset range, the habitat is a long-term habitat for fish, with low energy consumption and suitable eddy current, corresponding to the core suitable area.

[0038] When the habitat suitability index is within the preset range, the habitat is a short-term activity area for fish, corresponding to a general suitable area.

[0039] When the habitat suitability index is less than the lower limit of the preset range, the habitat is a fish-avoided area, and the energy consumption is too high or the eddy current is extreme, corresponding to an unsuitable area.

[0040] Compared with existing technologies, this invention has the following advantages: By meticulously extracting the core geometric features of riverbed sediment, riparian vegetation, and reef topography, a high-fidelity physical model of fish habitats is constructed, accurately replicating the physical environment and element relationships of the habitat. This provides a standardized foundation for subsequent analysis, avoiding coupling biases caused by missing or distorted data. Simultaneously, through targeted flume experiments and theoretical derivation, combined with blank control, multi-condition coverage, and repeated verification, three types of vorticity coefficients are systematically obtained, establishing a specific correlation between habitat type and vorticity coefficient. This clarifies the intrinsic mechanism of habitat characteristics and water flow disturbance, providing precise quantitative parameters for coupled analysis.

[0041] By deeply coupling discrete coefficients and continuous models, the three types of vorticity coefficients are transformed into global distributed vorticity data, clarifying the contribution paths of different habitat elements to vorticity. The total vorticity is obtained by vector superposition, integrating the comprehensive disturbance state of water flow, forming a vorticity field characterization logic of component analysis and full-dimensional integration, solving the limitation that a single vorticity cannot fully reflect the disturbance of water flow, and building a core data carrier for subsequent coupled analysis.

[0042] Based on the classical model and Gaussian distribution characteristics, and combined with indoor experiments and field verification, the appropriate eddy current and correction coefficients were determined, and a quantitative relationship between eddy current and fish energy consumption was constructed to accurately quantify the actual energy consumption under different eddy environments. Energy consumption and eddy current were converted into suitability indices to form a two-dimensional evaluation system of physical environment adaptability and biological energy consumption response, which makes up for the shortcomings of traditional evaluation that only focuses on physical parameters and ignores biological needs.

[0043] A comprehensive suitability index is constructed using geometric mean to achieve synergistic evaluation across physical and biological dimensions. Clear grading standards are established, transforming the abstract index into concrete functional zones, coupled with protection priorities and dynamic adjustment mechanisms, directly linking to protection planning and restoration projects. The entire methodology adapts to the heterogeneity of river habitats and dynamic hydrological changes, enabling precise identification of suitable habitats and targeted design of restoration measures. It can provide micro-scale, refined control indicators for the engineering design of fish habitats in water conservancy or waterway projects. Furthermore, standardized processes and multi-source validation ensure the reliability and repeatability of results, contributing to the precise protection and ecological function restoration of river fish habitats. Attached Figure Description

[0044] Figure 1 This is a flowchart illustrating the method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption according to the present invention.

[0045] Figure 2 This is a flowchart of S2.

[0046] Figure 3 This is a flowchart of S3.

[0047] Figure 4 This is a flowchart of S5. Detailed Implementation

[0048] The technical solutions of the river habitat index determination method based on the coupling of eddy current and fish energy consumption provided by the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0049] like Figure 1 As shown, a method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption is presented. This method includes: S1, extracting geometric features of the riverbed sediment, riverbank vegetation, and reef topography, and constructing a physical model of fish habitat to provide a basic basis for the analysis of this method.

[0050] Furthermore, in S1, the geometric characteristics of the riverbed sediment include sediment particle size distribution, surface micro-topography undulation, riverbed plan morphology, and longitudinal profile slope.

[0051] Specifically, sediment particle size distribution refers to the distribution characteristics of different particle sizes in the surface and shallow layers of the riverbed, covering the entire particle size range from clay, silt, and sand to gravel, pebbles, and boulders. The extraction process requires a combination of field sampling and indoor sieving tests to determine the mass or volume fraction of particles in each size range, clarifying key parameters such as dominant particle size, median particle size, and average particle size. Simultaneously, it is necessary to characterize the spatial heterogeneity of particle size distribution, i.e., the differences in particle size distribution at different river sections and cross-sections. This indicator directly determines the surface roughness, thus affecting the average flow velocity distribution and eddy current field structure of the cross-section, and also providing basic conditions for fish spawning substrate selection and juvenile fish shelter.

[0052] Riverbed micro-topographic undulations refer to the minute undulations on the riverbed surface ranging from centimeters to meters, including micro-geomorphic units such as sand waves, sand ridges, scour pits, sedimentary platforms, and riverbed textures. Extraction requires high-precision underwater topographic surveying equipment such as multibeam echo sounders or 3D laser scanners to obtain three-dimensional coordinate data of the riverbed surface. Through topographic interpolation and filtering, the amplitude, frequency, morphological type, and spatial distribution density of the micro-topography are quantified. This indicator directly affects the complexity of local water flow patterns, forming diverse low-velocity zones, backflow zones, and disturbance zones, serving as important micro-habitats for fish to avoid predators, forage, and raise their young.

[0053] Riverbed morphology refers to the planar distribution characteristics of a riverbed, mainly including straight sections, meandering sections, bifurcation sections, sharp bends, and confluence / distribution zones. Core extracted parameters cover the variation range and distribution of river width along its course, bend radius, curvature, number of bifurcation channels in bifurcation sections, the width ratio of each bifurcation channel, and the angle between the bifurcation axes. By combining remote sensing image interpretation with measured river cross-sections, the spatial variation patterns of the planar morphology are accurately depicted. This directly determines the overall evolution direction of water flow, the diversion and confluence patterns, and thus affects the energy distribution and eddy current generation intensity of different river sections.

[0054] Longitudinal profile slope: refers to the slope of the riverbed along the direction of water flow, and is a core indicator reflecting the changes in river gradient, water flow potential energy, and flow velocity along the course. Extraction requires calculation of the average slope and local slope extremes for different river sections based on longitudinal profile measurement data, identifying abrupt changes in slope along the course. Longitudinal profile slope directly dominates the magnitude of water flow velocity and energy gradient, thus affecting the accessibility of fish migration channels, the stability of habitats, and the distribution patterns of prey organisms.

[0055] In S1, the geometric characteristics of the riparian vegetation include the spatial distribution range of the vegetation community, plant height or crown width, vegetation zone width and layering structure, and the geometric morphology of the vegetation root system.

[0056] Specifically, the spatial distribution range of vegetation communities refers to the area of ​​various vegetation communities on the riverbank in plan view. Key extracted parameters include the distribution boundaries, area size, continuous length along the riverbank, intervals between discontinuous distributions, and horizontal distance from the riverbank edge for each type of vegetation community. By combining remote sensing image classification, drone aerial photography, and field surveys, the spatial distribution pattern of vegetation communities is accurately depicted, and the distribution areas of dominant vegetation types are identified. This indicator directly determines the coverage of the ecological buffer function of the riverbank, affecting the obstruction and purification effects of near-shore water flow, and the amount of space resources available for fish to inhabit and reproduce near the shore.

[0057] Plant height or crown width refers to the vertical growth height and horizontal canopy coverage of dominant plants in a vegetation community, and is a core parameter reflecting the growth status and spatial occupancy capacity of vegetation. For tree communities, the crown radius and canopy coverage corresponding to the average tree height, maximum tree height, and diameter at breast height (DBH) need to be extracted; for shrub and herbaceous communities, the average plant height, maximum plant height, and crown width need to be extracted. Data are obtained through a combination of UAV lidar scanning, total station measurements, and field quadrat surveys. This indicator directly affects the light conditions, air humidity, and water flow shading effect in nearshore areas, while also providing habitat for birds, insects, and other prey organisms, indirectly supporting the food resource supply for fish.

[0058] Vegetation zone width and stratification: Vegetation zone width refers to the horizontal extension width of various vegetation communities along the riverbank perpendicular to the direction of water flow. The average width, maximum width, minimum width, and the range of width variation along the riverbank need to be extracted. Stratification refers to the vertical stratification characteristics of the vegetation community, including the number of tree, shrub, herb, and ground cover layers, the vertical height range of each layer, the size of the interlayer gaps, and the coverage percentage of each layer. Data are obtained through field transect surveys and profile measurements. This indicator determines the complexity and stability of the riparian ecological structure, affects the infiltration and retention processes of water flow in the riparian zone, and provides diverse habitats and refuge spaces for fish in different ecological niches.

[0059] The geometric morphology of vegetation roots refers to the growth form and spatial distribution characteristics of riparian vegetation roots in the soil. Key extracted parameters include root distribution depth, horizontal extension range, root diameter, root density, root branching angle and topology, and the way roots integrate with riparian soil and riverbed sediments. Data was obtained through a combination of field root excavation, profile observation, and indoor CT scan modeling. This indicator directly affects the erosion resistance and soil stability of the riparian zone. Furthermore, the porous structure of the roots provides habitat for small benthic organisms, and the tiny pores formed after root decay can serve as hiding places for juvenile fish, further enriching the microhabitat types of the habitat.

[0060] In S1, the geometric features of the reef topography include the spatial location, shape and size of the reefs, the distribution density and topological relationship of the reef group, and the relative elevation of the reefs to the riverbed.

[0061] The spatial location of a reef refers to the precise positioning of a single reef or individual reef within the river channel coordinate system. Key extracted parameters include the reef's planar coordinates, its location within the river channel cross-section, its position relative to the main flow line, and its spatial distance from surrounding key geomorphic units. Data is acquired through a combination of high-precision underwater topographic surveying, multibeam sonar imaging, and on-site marking. This indicator forms the basis for constructing a three-dimensional model of the reef topography, directly determining the range and intensity of the reef's disturbance to local water flow, and consequently influencing the generation location and distribution pattern of the eddy field.

[0062] Morphological dimensions refer to the geometric contours and volume parameters of individual reefs. Key extracted parameters include the reef's length, width, height, cross-sectional shape, surface area, volume, upstream and downstream slopes, and surface roughness. Through underwater 3D scanning and point cloud data processing, the 3D morphology of the reefs is accurately reconstructed, and these parameters are extracted. This directly determines the reef's resistance to water flow and its flow characteristics. Reefs of different morphological dimensions will form different types of flow vortices, thus affecting the dissipation of water energy and the migration path selection of fish.

[0063] The distribution density and topological relationship of reef clusters are discussed. Distribution density refers to the number of reefs per unit river channel area or the total area occupied by reefs, and needs to be statistically analyzed separately for different river sections and water depth ranges. Topological relationship refers to the spatial correlation characteristics between reefs within a reef cluster, including the minimum distance between reefs, their arrangement, the orientation relationship of adjacent reefs, and the overall extension range and morphology of the reef cluster. Data is extracted through point cloud data clustering analysis and spatial topological analysis. This indicator determines the overall disturbance effect of reef clusters on water flow. High-density reef clusters will form a complex multi-body flow environment, generating a high-intensity vortex field. Different topological relationships can lead to the superposition or cancellation of water flow disturbances, further enriching the complexity of the water flow environment.

[0064] The relative elevation of a reef to the riverbed refers to the elevation difference between the top, bottom, and key parts of the reef and the datum level of the riverbed at its location. Key extracted parameters include the reef's exposed height, submersion depth, the depth of the reef's bottom embedded in the riverbed, and the elevation difference between the reef's top and the surrounding riverbed. Data is obtained through underwater elevation measurements and datum level calibration. This indicator directly determines the submersion state of the reef during different hydrological periods, thus affecting the intensity of its disturbance to water flow, and also determining how fish utilize the space around the reef.

[0065] In this embodiment, the method extracts the core geometric features of the riverbed sediment, riverbank vegetation, and reef topography to construct a high-precision physical model of fish habitat. It accurately replicates the key physical environmental parameters of the habitat and the spatial interaction relationships of various elements, providing a standardized and high-fidelity foundation for subsequent eddy field simulation and fish energy consumption calculation. This effectively avoids the coupling analysis bias caused by missing or distorted basic data, and significantly improves the reliability and scientific nature of habitat index determination.

[0066] A refined extraction of the geometric characteristics of three core habitat elements was conducted to clarify the direct impact pathways of each indicator on water flow patterns and fish survival. For example, the particle size distribution of the substrate and the microtopography of the bed determine the eddy field structure, the stratified structure of riparian vegetation provides diverse habitat spaces, and the distribution characteristics of reefs affect the intensity of water flow disturbance and the distribution of fish foraging and resting places. This clearly establishes a bridge between the physical environment and biological responses, providing a clear target for the coupled analysis of eddy current and fish energy consumption.

[0067] The method also includes: S2, obtaining the riverbed rough vorticity coefficient, vegetation disturbance vorticity coefficient, and topographic flow vorticity coefficient through flume tests or field tests and theoretical calculations.

[0068] like Figure 2 As shown, further, S2 includes: S201, firstly, collecting the hourly average flow velocity, hydraulic radius, water surface gradient, and riverbed roughness height at each measurement point in the flume test with the expected number of collections.

[0069] Specifically, the flume test bed layout must strictly replicate the riverbed sediment characteristics extracted in S1. The particle size distribution and laying thickness of the test particles are determined based on the sediment particle size distribution. The bed surface roughness is recreated based on the micro-topographic undulations to ensure the test environment matches the actual habitat's riverbed roughness characteristics, guaranteeing the validity and representativeness of the test data. Simultaneously, multiple test groups with different flow conditions need to be set according to the target river section's flow rate range, covering typical hydrological scenarios such as dry and normal water periods. Each test group corresponds to a preset number of sampling times. Different sediment types can be used at the bottom of the test. River sediment types include: gravel group (particle size distribution...). Simulated rapid flow zone); pebble group (particle size) Simulates the edge of a deep pool); sediment group (medium sand, particle size) (Simulated slow flow zone).

[0070] The layout of measurement points needs to balance spatial uniformity with targeted placement in key areas. Multiple cross-sections should be arranged at equal intervals along the longitudinal direction of the flume. Measurement points should be placed on each cross-section according to different water depth levels, with a focus on increasing the density of measurement points in areas with significant micro-topographic undulations on the waterbed. All measurement points must be accurately located and their distance from the starting end of the flume, their cross-section location, and water depth must be recorded to ensure that subsequent data analysis accurately corresponds to the roughness characteristics of the waterbed. Measurement equipment can include contact-type 3D acoustic Doppler velocimeters or non-contact-type particle image velocimeters.

[0071] Time-averaged velocity refers to the average flow velocity at a given measurement point over a preset observation period, and it is a core parameter reflecting the magnitude of kinetic energy. High-precision velocity measurement equipment such as acoustic Doppler current meters is used for data acquisition. The observation time at each measurement point must be sufficient to fully acquire the flow pulsation signal. The raw pulsating velocity data is processed using the equipment's built-in software to obtain the time-averaged velocity value. Simultaneously, the pulsation intensity of the velocity is recorded, providing supplementary data for quantifying the degree of flow disturbance in subsequent vorticity coefficient calculations. Open channel flow can be simplified to two dimensions, collecting the time-averaged velocity at each point. ,in, For the average velocity of the flow direction, The lateral average velocity.

[0072] The hydraulic radius, or the ratio of the cross-sectional area of ​​a flume to its wetted perimeter, is a key parameter characterizing the geometric properties and resistance distribution of the flow cross-section. Data collection requires first measuring the actual cross-sectional dimensions under each test condition to calculate the cross-sectional area; then measuring the wetted perimeter. The hydraulic radius for each measured cross-section is then accurately calculated using the hydraulic radius calculation formula. If water depths differ at different measurement points within the same cross-section, the average hydraulic radius must be calculated using a depth-weighted approach. Hydraulic radius The calculation formula is:

[0073] ,

[0074] in, The cross-sectional area of ​​the water passage. The wet perimeter of the cross-section.

[0075] The water surface gradient refers to the slope of the elevation change of the water surface along the direction of water flow within a flume, directly reflecting the potential energy gradient and resistance intensity of the water flow. During data collection, a precision level or laser level gauge is used to measure the water surface elevation at multiple fixed observation points along the longitudinal direction of the flume. The spacing between adjacent observation points needs to be reasonably set according to the length of the flume. The water surface gradient of each interval is obtained by calculating the ratio of the elevation difference to the horizontal distance between adjacent observation points, and then the average water surface gradient of the entire flume is obtained. During the measurement process, it is necessary to ensure that the water flow in the flume is in a stable and uniform state to avoid the influence of water flow fluctuations on the accuracy of the water surface elevation measurement. The calculation formula is:

[0076] ,

[0077] in, This is the difference in elevation. This represents the horizontal distance.

[0078] The riverbed roughness height refers to the effective roughness characteristic parameter of the bed surface particles or micro-topographic undulations, directly related to the bottom particle size distribution extracted in S1 and the amplitude of bed surface micro-topographic undulations. During data collection, a 3D laser scanner was used to scan the test bed surface to obtain 3D coordinate data, and the bed roughness height was extracted using topographic data processing software. For particle-layed beds, the equivalent roughness height can be calculated using empirical formulas based on the median particle size determined in S1, ensuring the consistency of this parameter with the actual riverbed roughness characteristics. The mean long axis of large particles is the roughness height of the riverbed sediment. .

[0079] Secondly, the average value of the vorticity component perpendicular to the plane at each measurement point is calculated and defined as the theoretical riverbed rough vorticity.

[0080] Specifically, due to the velocity component perpendicular to the plane Then the vorticity component perpendicular to the plane The calculation formula is:

[0081] ;

[0082] in, Horizontal flow velocity Along the flow direction ( Partial derivatives (direction); For flow direction and velocity Along the lateral direction ( The partial derivative of (direction).

[0083] Finally, the vorticity components at each measurement point are taken. The average value is used as the theoretical riverbed rough vorticity. The value of is obtained by reverse-engineering the theoretical formula for calculating riverbed rough vorticity and taking the average value, thus obtaining the riverbed rough vorticity coefficient for each riverbed substrate type.

[0084] Specifically, the rough eddy current coefficient of the riverbed The calculation formula is:

[0085] ,

[0086] in, It is the acceleration due to gravity. .

[0087] The experiment was repeated multiple times for each riverbed substrate, and the average value was taken as the result for that riverbed substrate. value.

[0088] Based on experience, the typical riverbed sediment of a certain river... The values ​​are shown in Table 1.

[0089] Table 1. Relationship between typical riverbed roughness vorticity coefficient, sediment type, and applicable river section for a certain river.

[0090]

[0091] S202. First, collect the hourly average flow velocity, vegetation unit area projection ratio, and vegetation canopy height at each measurement point in the flume test with the expected number of collections.

[0092] Specifically, based on the typical riverbank vegetation types determined in S1, simulation models of corresponding plants or similar alternative vegetation were selected, and vegetation test areas were set up in the flume according to the vegetation strip width, stratification structure, and spatial distribution density extracted in S1. A separate test group was set up for each vegetation type, along with a blank control group without vegetation, to eliminate interference from other factors such as flume boundaries on water flow disturbance. Each test group required at least three repeated data collections to ensure data reliability and statistical significance.

[0093] Multiple measurement sections were longitudinally arranged in the vegetation test area and upstream and downstream control areas, including the vegetation front edge, the middle of the vegetation area, the vegetation rear edge, and a control section without vegetation. Measurement points were arranged on each section according to the surface, middle layer, and bottom layer. At the same time, the measurement points were densified in areas with intense water flow disturbance, such as the edge of the vegetation canopy and the gaps between plants, to accurately capture the spatial changes in water flow characteristics around the vegetation. The relative position of all measurement points to the vegetation plants was recorded to provide a basis for subsequent correlation analysis between eddy current and vegetation distribution.

[0094] The time-averaged flow velocity was collected using an acoustic Doppler current meter. During the data acquisition process, the current meter probe needed to be kept stable to avoid collisions with the vegetation model. After denoising the collected raw pulsating velocity data, the time-averaged flow velocity value at each measurement point was calculated. ,in For the average velocity of the flow direction, The lateral average velocity, This represents the vertically averaged velocity. The standard deviation of the velocity fluctuations is also recorded to provide basic data for subsequent vorticity calculations.

[0095] The vegetation projection ratio per unit area refers to the proportion of the vertical projection area of ​​the leaves, stems, and canopy of vegetation within a unit surface area to the total surface area. It is directly related to the plant canopy width and vegetation density extracted in S1. Data collection employed a combination of image recognition and field measurement: aerial images of the water-flue vegetation test area were captured using drones or high-definition cameras. Image processing software was used to segment the vegetation area from the water flow area, and the vegetation projection area was calculated. Simultaneously, the planar area of ​​the water flow area was measured. Therefore, the vegetation projection ratio per unit area is calculated. The calculation formula is:

[0096] ,

[0097] in, This represents the projected area of ​​the vegetation. The area of ​​the water flow region; This represents the percentage of vegetation per unit area projected, without units.

[0098] Vegetation canopy height The vertical distance from the top of the vegetation canopy to the bed surface is a key parameter characterizing the spatial occupancy of vegetation and the range of water flow disturbance. It is directly related to the plant height and core indicators of vegetation stratification extracted by S1. Data collection should be conducted using a high-precision laser rangefinder or 3D laser scanner, taking into account the type of experimental vegetation layout. For single simulated vegetation, four height values ​​are measured at different locations within the plant canopy, and the arithmetic mean is taken as the canopy height of that plant. For vegetation in a community layout, 3-5 dominant plants are randomly selected within the vegetation sub-region of each measurement point to measure their canopy height, and the average value is taken as the canopy height of that area. During the measurement process, the relative relationship between canopy height and water depth should be recorded, along with the vegetation growth morphology, to provide data support for subsequent analysis of the impact of the vegetation canopy on the vertical structure of water flow and the vertical differences in eddy current distribution. For stratified vegetation communities, canopy height should be measured separately for different layers, such as the tree layer and shrub layer, to clarify the vertical distribution range of each canopy layer.

[0099] Secondly, the average value of the vorticity component perpendicular to the plane at each measurement point is calculated and defined as the theoretical vegetation disturbance vorticity.

[0100] Specifically, considering that the vertical vorticity is dominant in the vegetated water flow area, a simplified approach is taken, and the vorticity component perpendicular to the plane is calculated based on the aforementioned vorticity component formula. Take the vorticity components at each measuring point. The average value is used as the theoretical vegetation disturbance vorticity. The value of .

[0101] Finally, the cross-sectional average flow velocity at each measurement point is calculated, and the theoretical vegetation disturbance vorticity calculation formula is derived by reverse calculation and the average value is taken to obtain the vegetation disturbance vorticity coefficient for each vegetation type.

[0102] Specifically, based on the average velocity of the flow direction at each measurement point. The average cross-sectional velocity is obtained by averaging. .

[0103] Vegetation disturbance vorticity coefficient The calculation formula is:

[0104] ,

[0105] in, This represents the vegetation resistance coefficient.

[0106] The experiment was repeated multiple times for each vegetation type, and the average value was taken as the result for that vegetation type. value.

[0107] Based on experience, the typical vegetation disturbance vorticity coefficient of a certain river The values ​​are shown in Table 2.

[0108] Table 2. Relationship between typical vegetation disturbance vorticity coefficient, vegetation type, and applicable area for a certain river.

[0109]

[0110] S203. First, collect the hourly average flow velocity and reef diameter at each measurement point in the reef area during the expected number of samplings in the flume test.

[0111] Specifically, time-averaged flow velocity was acquired with high precision using an acoustic Doppler current meter. During the acquisition process, the current meter probe direction needed to be adjusted to avoid signal interference caused by reefs, while ensuring the probe was aligned with the water flow direction. After denoising the acquired raw pulsating velocity data, the time-averaged flow velocity value at each measurement point was calculated. The intensity of velocity pulsations and turbulence was recorded simultaneously to provide basic data for subsequent calculations of topographic vorticity. Time-averaged flow velocity was collected in the reef area. ,in For the average velocity of the flow direction, The lateral average velocity, The vertical average velocity.

[0112] The reef diameter refers to the equivalent diameter of an individual reef, that is, the diameter of a sphere equal to the actual volume of the reef. It is a core parameter for quantifying the reef's resistance to water flow and is directly related to the reef morphological and dimensional indicators extracted by S1. During data collection, a 3D laser scanner is used to perform a full-section scan of each reef placed in the tank, acquiring 3D point cloud data. The 3D model of the reef is reconstructed using point cloud data processing software, and the actual volume of the reef is calculated. Then, the equivalent diameter of the reef is derived by using the formula for the volume of a sphere. For reefs with regular shapes, such as approximately spherical or cylindrical, calipers are used to measure three diameter values ​​in the horizontal, vertical, and longitudinal directions, and the arithmetic mean is taken as the approximate equivalent diameter. After measurement, a register must be established to correspond the reef number to the equivalent diameter, ensuring that the diameter of the reef at each measurement point is accurate. The parameters are traceable.

[0113] Secondly, the average value of the vorticity component perpendicular to the plane at each measurement point is calculated and defined as the theoretical topographic vorticity.

[0114] Specifically, considering that the vertical vorticity is dominant in the reef flow region, a simplified approach is taken: the vorticity component calculation formula above calculates the vorticity component perpendicular to the plane. Take the vorticity components at each measuring point. The average value is used as the theoretical vegetation disturbance vorticity. The value of .

[0115] Next, calculate the cross-sectional average flow velocity at each measurement point.

[0116] Specifically, specifically, based on the average velocity of the flow direction at each measurement point. The average cross-sectional velocity is obtained by averaging. .

[0117] Finally, the theoretical formula for calculating the vorticity of topographic flow was derived by reverse calculation and the average value was taken to obtain the topographic flow vorticity coefficient for each type of reef.

[0118] Specifically, the vorticity coefficient of topographic flow The calculation formula is:

[0119] .

[0120] Among them, the angle between the water flow and the reef hour, .

[0121] The experiment was repeated multiple times for each reef type, and the average value was taken as the result for that reef type. value.

[0122] Based on experience, the typical topographic vorticity coefficient values ​​for a certain river are shown in Table 3.

[0123] Table 3. Relationship between typical topographic vorticity coefficients, reef types, and applicable areas for a certain river.

[0124]

[0125] In this embodiment, through targeted flume test design and parameter acquisition in S201-S203, combined with theoretical derivation and repeated verification, the system obtained three types of eddy coefficients: riverbed roughness, vegetation disturbance, and topographic flow around the surface. The experimental process strictly replicated the actual habitat characteristics of the substrate type, vegetation type, and reef morphology extracted in S1, and introduced designs such as blank control and multi-condition coverage to effectively eliminate interference factors and ensure the accuracy and representativeness of the coefficient values. At the same time, through formulaic definition and standardized calculation process, the eddy coefficients were made quantifiable and traceable, providing core quantitative parameter support for the subsequent full-area eddy field simulation and precise coupling of fish energy consumption.

[0126] Step S2 precisely matched the geometric features of the three core habitat elements extracted in S1, establishing specific correlations between different substrate types, vegetation types, reef types, and their corresponding eddy coefficients. Through categorized experiments and coefficient calibration, the contribution intensity and operational patterns of different habitat elements to the water flow eddy field were clarified, clearly revealing the intrinsic relationship between habitat physical characteristics and water flow disturbance states. This provides a crucial bridge for analyzing the response mechanisms of fish energy consumption and habitat environment.

[0127] The method also includes: S3, quantifying the riverbed rough vorticity, vegetation disturbance vorticity, and topographic abrupt change vorticity of the fish habitat physical model based on the fish habitat physical model, riverbed rough vorticity coefficient, vegetation disturbance vorticity coefficient, and topographic flow vorticity coefficient. Combining the obtained discrete coefficients with the continuous habitat physical model achieves spatially distributed quantification of the three types of vorticity, providing a crucial bridge for subsequent overall characterization of the vorticity field and its coupling analysis with fish energy consumption, ensuring that the vorticity calculation results accurately reflect the differences in water flow disturbance in different areas of the habitat.

[0128] like Figure 3 As shown, further, S3 includes S301, which quantifies the hydraulic radius, water surface gradient and riverbed roughness height based on the physical model of fish habitat.

[0129] Specifically, firstly, based on the physical model of fish habitat constructed by S1, three-dimensional topographic data of the entire region, geometric parameters of river cross sections, and spatial distribution data of riverbed sediment types are extracted; at the same time, combined with the typical hydrological scenario of a certain river, hydrological boundary conditions such as flow rate and water level are input into the model, and the computational grid is divided through the model preprocessing module, and the spatial correlation mapping between grid cells and sediment types and topographic features is completed, providing a basis for the subsequent regional quantification of parameters.

[0130] hydraulic radius The quantification is based on the geometric features of the river cross section extracted by S1 and the input hydrological scenario parameters. Combined with the hydraulic radius calculation formula specified in S201, the distributed calculation of the hydraulic radius of each calculation section in the entire model domain is realized.

[0131] hydraulic radius The quantitative calculation process involves calculating the cross-sectional area of ​​each longitudinal cross section within the model, based on the actual water depth distribution data of that section under the current hydrological scenario output by the model. Simultaneously, the wetted perimeter of the cross-section is extracted. ;Will and Substituting into the formula, the hydraulic radius of each cross section is calculated. For fine-grained computational units in the mesh-refined region, the unit-level hydraulic radius is calculated using local small-section area integration to ensure that the quantification results of the hydraulic radius accurately reflect the spatial differences within the section, avoiding accuracy loss due to averaging.

[0132] Water surface gradient The quantification is based on the longitudinal profile slope features of the river channel extracted by S1, combined with the whole-area water surface elevation distribution data under the hydrological scenario input by the model, and with reference to the water surface gradient calculation formula in S201, to achieve distributed quantification of water surface gradient.

[0133] Water surface gradient The quantitative calculation process involves setting up virtual observation points at equal intervals along the water flow direction across the entire model domain; obtaining the water surface elevation data for each virtual observation point through model calculation; and calculating the water surface elevation difference between adjacent observation points. and horizontal distance Substituting into the formula, we obtain the water surface gradient between adjacent intervals. A linear interpolation method is used to assign the water surface gradient within an interval to each computational unit, achieving continuous distributed quantization of the water surface gradient across the entire model domain. Abnormal elevation data must be removed during the calculation process to ensure that the quantized water surface gradient conforms to the actual distribution of water flow potential energy gradient.

[0134] Riverbed roughness height It is a core parameter characterizing the roughness of the riverbed surface, directly reflecting the ability of the sediment particles and the micro-topography of the bed to impede the water flow. It is a key parameter for correlating the riverbed rough vorticity coefficient and calculating the riverbed rough vorticity. Its quantification results need to be accurately matched with the sediment characteristics extracted by S1 and the experimental parameter system of S201.

[0135] Riverbed roughness height The calculation process is based on the whole-domain riverbed sediment particle size distribution and bed surface micro-topographic undulation features extracted in S1, combined with the roughness height acquisition method specified in S201 to achieve whole-domain distributed quantization. During the calculation, based on the spatial correlation mapping relationship between sediment type and micro-topographic features within the model, corresponding empirical coefficients are assigned to each calculation unit to achieve whole-domain distributed quantization of the riverbed sediment roughness height, ensuring accurate matching with the original features extracted in S1 and the experimental parameters in S201. The riverbed sediment roughness height is then... Defined as the characteristic length of eddy current caused by riverbed roughness.

[0136] Based on the hydraulic radius and water surface gradient, the shear velocity generated by the shear flow on the riverbed wall is calculated.

[0137] Specifically, the shear velocity generated by shear flow on the riverbed wall. The calculation formula is:

[0138] ,

[0139] ,

[0140] in ， For riverbed shear stress; For the density of water, ; It is the acceleration due to gravity. ; Hydraulic radius, unit ; The water surface gradient.

[0141] By coupling the riverbed rough eddy coefficient, shear velocity, and eddy characteristic length, the riverbed rough eddy of the fish habitat physical model is obtained. When the riverbed rough element induces flow shear, the larger the eddy characteristic length and the steeper the water surface gradient, the stronger the generated riverbed rough eddy. The riverbed rough element is composed of gravel or pebbles.

[0142] Specifically, the formula for calculating the rough eddy current of the riverbed in the physical model of fish habitats is as follows:

[0143] .

[0144] S302. First, based on the physical model of fish habitats. Quantified vegetation unit area projection ratio, quantified The cross-sectional average flow velocity, the resistance coefficient of vegetation to water flow, and the vegetation canopy Floor height.

[0145] Specifically, based on the physical model of fish habitat, and combined with the vegetation geometric features (vegetation type, distribution density, canopy height, and layered structure) extracted by S1 and the experimental data of S202, the vegetation unit area projection ratio, cross-sectional average flow velocity, vegetation resistance coefficient to water flow, and vegetation vortex characteristic length of each calculation unit in the entire model domain are quantified, providing core input parameters for subsequent calculations.

[0146] Vegetation per unit area projection ratio The quantification is based on the spatial distribution range of vegetation communities, plant crown width, and vegetation stratification structure extracted in S1, combined with the calculation method of vegetation unit area projection ratio in S202, to achieve distributed quantification of the entire model. The model extracts the vegetation distribution area corresponding to each calculation unit, calculates the projected area of ​​vegetation within the unit, and the planar area of ​​the water flow area within the unit, and substitutes these into the formula to obtain the vegetation unit area projection ratio of each unit. Simultaneously, the quantification results are constrained by referring to the projected area density range of the same type of vegetation in the S202 experiment to ensure numerical rationality.

[0147] Cross-sectional average velocity The quantization is based on the global velocity distribution data output by the model in S301. For each calculation section corresponding to the vegetation distribution area, the water depth weighted average method is used to calculate the cross-sectional average velocity. During the quantization process, it is necessary to pay close attention to the velocity difference between vegetated and non-vegetated areas to ensure that the cross-sectional average velocity can accurately reflect the obstruction effect of vegetation on water flow, and provide a reliable basis for subsequent calculation of additional shear velocity.

[0148] The resistance coefficient of vegetation to water flow The quantification of vegetation resistance coefficient is a key parameter characterizing the intensity of water flow obstruction by vegetation. Its quantification is based primarily on the S202 experimental data, combined with vegetation type and morphological characteristics. Using velocity attenuation data from different vegetation types in the S202 experiment, initial resistance coefficient values ​​for each vegetation type were derived using empirical formulas. In the model, the initial resistance coefficients were corrected based on the vegetation type, vegetation unit area projection ratio, and canopy height of each computational unit, ultimately yielding distributed data of the vegetation resistance coefficient across the entire model domain.

[0149] Vegetation canopy height The quantification of vegetation canopy height is a core parameter characterizing the spatial occupancy of vegetation, the range of water flow disturbance, and the boundary of eddy current generation. Its quantification is directly based on the vegetation geometric features extracted in S1, combined with the measurement standards of the S202 experiment to achieve distributed matching across the entire domain. The model extracts vegetation type and stratification data corresponding to each computational unit, and calls the measured statistical values ​​of vegetation canopy height for that region in S1. For finely detailed areas with denser model grids, spatial interpolation is used to supplement refined canopy height data, combining the plant spacing and canopy coverage data extracted in S1. Simultaneously, the quantification results are constrained by referring to the canopy height measurement range of the same type of vegetation in the S202 experiment to ensure that the values ​​match the actual vegetation growth characteristics. For stratified vegetation communities, the canopy height of each layer is quantified separately to clarify the vertical contribution range of each layer to water flow disturbance, providing accurate vertical dimension parameter support for subsequent additional shear velocity calculations and eddy current coupling analysis. Vegetation Canopy Height Defined as the characteristic length of vegetation vorticity.

[0150] Secondly, the additional shear velocity of vegetation is calculated based on the proportion of vegetation projected per unit area and the average flow velocity of the cross section.

[0151] Specifically, vegetation additional shear rate The calculation formula is:

[0152] ,

[0153] ,

[0154] in, For vegetation shear stress; For the density of water, .

[0155] Furthermore, the vegetation canopy height, vegetation vorticity coefficient, and vegetation additional shear velocity are coupled to obtain the vegetation disturbance vorticity of the physical model of fish habitat. The larger the proportion of vegetation per unit area projection and the lower the vegetation vorticity characteristic length, the stronger the disturbance to water flow and the larger the vegetation disturbance vorticity generated.

[0156] Specifically, the vegetation disturbance eddy current in the physical model of fish habitats The calculation formula is:

[0157] .

[0158] S303. First, based on the physical model of fish habitat, the diameter of the reef, the angle between the water flow and the reef axis, and the average flow velocity of the cross section are quantified.

[0159] Specifically, based on the physical model of fish habitats, and combined with the geometric features of the reef terrain extracted by S1 and the experimental data of S203, the reef diameter, the angle between the water flow and the reef axis, and the average cross-sectional velocity of each calculation unit in the entire model domain are quantified, providing core input parameters for subsequent characteristic velocity difference calculation and topographic change eddy coupling.

[0160] Reef diameter The quantization is based on the reef morphology and size data extracted in S1, combined with the calculation standard for the equivalent diameter of reefs in S203, to achieve distributed quantization of the reef diameter across the entire model. The model extracts the three-dimensional morphological data of reefs within each calculation unit, calls the reef volume parameters already obtained in S1, and uses the spherical volume equivalence method specified in S203 to back-calculate the equivalent diameter of each reef. For reefs with regular shapes in the model, the length, width, and height data measured in S1 can be directly extracted, and the approximate equivalent diameter can be calculated using the arithmetic mean method. For reef cluster areas, the diameter needs to be quantified individually for each reef, and a spatial association between the reef number and the calculation unit needs to be established to ensure that the reef diameter parameters of each unit accurately correspond to the actual individual reefs. Simultaneously, the quantization results are constrained by referring to the diameter range of similar reefs in the S203 experiment to avoid excessive diameter deviations due to model simplification.

[0161] Angle between the water flow and the axis of the reef The quantification of this angle is a core parameter characterizing the relative interaction direction between the water flow and the reef, directly affecting the generation location and intensity of the vortex around the flow. The quantification is based on the reef axis direction extracted from S1 and the water flow direction data output by the model: first, the water flow direction vector of each calculation unit is extracted through the model; then, the axis vector of the reef at the corresponding location is extracted; and the angle between the two is calculated using the vector angle calculation formula. During the quantification process, it is necessary to ensure the accuracy of the vector direction. For irregular reefs, the center line of the largest projected surface on the water-facing side is taken as the axis direction. At the same time, in the reef group area, the angle between each reef and the water flow direction of its unit is calculated one by one to avoid misjudgment of direction due to the superposition of groups.

[0162] Cross-sectional average velocity The quantization is based on the global velocity distribution data output by the model. Combined with the S203 time-averaged velocity measurement standard, the cross-sectional average velocity of each calculation unit is quantized. For the area around the reefs, fine velocity data after model mesh refinement is used to extract the time-averaged velocity value of each unit. For calculation units inside the reef group, it is necessary to focus on extracting the velocity data of the vortex-affected zone to ensure that the velocity value can accurately reflect the actual water flow state after the flow disturbance. The quantization results need to be compared with the time-averaged velocity measurement values ​​of the same working conditions and locations in the S203 experiment. The deviation should be controlled within the preset range. If the deviation is too large, the velocity calculation parameters of the model need to be corrected and requantized.

[0163] Secondly, based on the angle between the water flow and the reef axis and the average cross-sectional velocity, the characteristic velocity difference of the water flow around the reef is calculated.

[0164] Specifically, when the reef can be approximated by a diameter When the water flows around the reef, the characteristic velocity difference is: This parameter is a core intermediate parameter characterizing the intensity of the disturbance caused by the flow around the reef, and directly reflects the magnitude of the velocity change when the water flows over the reef.

[0165] Finally, the topographic vorticity coefficient, reef diameter, and characteristic velocity difference are coupled to obtain the topographic abrupt vorticity of the fish habitat physical model; the higher the cross-sectional average velocity, the smaller the reef diameter, and the closer the angle between the water flow and the reef, the better. The stronger the topographical abrupt eddy current generated by the flow around the object, the more powerful the eddy current becomes.

[0166] Specifically, the topographic abrupt change vorticity of the physical model of fish habitats The calculation formula is:

[0167] .

[0168] In this embodiment, S3, through a hierarchical design of S301-S303, deeply couples the discrete vorticity coefficients obtained in S2 with the continuous fish habitat physical model constructed in S1. Through core parameter quantization, intermediate parameter derivation, and multi-parameter coupling calculation, it achieves global spatial distributed quantization of the three types of vorticity. This correlation method overcomes the limitation that discrete coefficients are difficult to directly apply to global simulations, enabling vorticity calculation results to accurately match the habitat characteristics differences in different areas of the habitat, providing a continuous and accurate data foundation for the subsequent overall characterization of the vorticity field.

[0169] The parameter quantification in each step of S3 is strictly traced back to the geometric features extracted in S1 and the experimental data in S2, and the quantification accuracy is ensured through standardized calculation procedures and multiple quality controls. At the same time, the riverbed roughness height and vegetation canopy height are explicitly defined as the corresponding eddy current characteristic lengths, which simplifies the calculation logic and strengthens the physical correlation between parameters, forming a complete logical closed loop from habitat characteristics to core parameters and then to eddy current quantification, effectively reducing the systematic error in eddy current calculation.

[0170] The method also includes: S4, calculating the total eddy of the fish habitat physical model by superimposing the riverbed rough eddy, vegetation disturbance eddy, and topographic abrupt change eddy.

[0171] Specifically, the total vorticity of the physical model of fish habitats The technical formula is:

[0172] ,

[0173] Among them, total vorticity The unit is Total vorticity The angular velocity magnitude used to reflect the rotation of a fluid.

[0174] In this embodiment, S4 integrates the three dispersed eddy components—riverbed roughness, vegetation disturbance, and abrupt topographic changes—into a total eddy force through vector superposition, overcoming the limitation that a single eddy component cannot comprehensively reflect the overall disturbance state of water flow. The total eddy force can accurately characterize the intensity of water flow rotation disturbance under the combined influence of different habitat elements, forming a eddy field characterization logic from component analysis to full-dimensional integration, providing a unified and comprehensive quantitative indicator for the subsequent overall assessment of the habitat's water flow environment.

[0175] Total eddy current, as a comprehensive quantitative indicator of water flow disturbance, is a key input parameter for calculating fish energy consumption. The swimming energy consumption of fish in a flowing environment is directly related to the intensity of water flow rotation disturbance. S4 calculates total eddy current using a standardized vector superposition formula, ensuring the numerical correlation and logical consistency between total eddy current and the three types of eddy current components. This avoids energy consumption calculation errors caused by incomplete representation of a single eddy current component, establishing a core data carrier for the precise coupling of eddy current and fish energy consumption, and significantly improving the scientific rigor and reliability of the correlation analysis.

[0176] The method also includes: S5, calculating the basic energy consumption of fish cruise without vorticity based on the actual energy consumption basic model, obtaining the vorticity correction coefficient according to the distribution characteristics of fish utilization of vorticity, constructing a quantitative relationship between vorticity and energy consumption, and quantifying the actual energy consumption of fish in different vortex environments.

[0177] like Figure 4As shown, further, S5 includes S501, collecting the average body weight and average cross-sectional flow velocity of a certain type of fish and inputting them into the actual energy consumption basic model to obtain the basic energy consumption of a certain type of fish cruise without eddy current.

[0178] Specifically, the average body weight of the fish is collected by selecting healthy adult individuals of the target fish species as the sampling subjects, and the number of samples must meet the statistical significance requirements. The sampling process must follow aquatic life protection regulations and adopt non-destructive sampling methods; before measurement, the surface moisture of the fish is gently wiped dry, and the weight is measured using a high-precision electronic balance, and the weight data of each individual is recorded; the average body weight of the fish is obtained through statistical analysis, and a sampling log is established to record environmental parameters such as sampling time, location, and water temperature to ensure data traceability.

[0179] The cross-sectional average velocity data collection requires precise matching of the target fish's actual habitat. Based on the fish habitat physical model constructed in S1, calculation cross-sections corresponding to the core activity areas of the target fish are extracted. The cross-sectional average velocity data quantified in S301 is used. If there are local missing data in the model, on-site measurements need to be supplemented to ensure that the velocity data is consistent with the actual activity environment of the fish. At the same time, it is necessary to cover the velocity range suitable for the survival of the target fish, so as to provide a comprehensive velocity benchmark for subsequent energy consumption calculations under different eddy current environments.

[0180] Based on the movement characteristics of fish in a certain river, a suitable basic energy consumption model is selected. Priority is given to empirical or semi-empirical models that have been verified by field tests, such as the classic Webb model, Brett model, or energy consumption models optimized for freshwater fish. The core logic of the model is to quantify the basic energy consumption of fish cruising motion based on parameters such as fish body weight and swimming speed, and the influence of eddy current disturbances must be eliminated.

[0181] That is, an empirical formula based on Brett's measured data:

[0182] ,

[0183] in, Additional energy consumption for cruise without vorticity ( ), Energy consumption coefficient fish body weight ( ), Body mass index (BMI) is calculated according to Kleiber's law, which states that metabolic rate is proportional to body weight. The power is directly proportional to the power. ), The cross-sectional average velocity is... The flow velocity index (dominated by water flow resistance during cruising) is the main indicator. ).

[0184] S502. Fish utilization of eddy current exhibits a Gaussian distribution characteristic. Eddy current correction coefficients are calculated. When the eddy current is the same as the suitable eddy current, energy consumption is the lowest. Eddy current that is too low or too high will increase energy consumption. Among them, the suitable eddy current is the eddy current value with the lowest energy consumption and the most frequent activity of fish. It is obtained by a combination of indoor behavioral experiments and field habitat tracking experiments.

[0185] Specifically, in their natural habitats, fish actively select eddy intensities that suit their own movement characteristics to reduce swimming energy consumption. Their utilization probability of eddy volume and energy consumption adaptability exhibit a typical Gaussian distribution. With the optimal eddy volume as the peak center, as the eddy volume intensity deviates to either side, the fish's energy consumption adaptability gradually decreases, and the energy consumption value gradually increases. The core meaning of this distribution characteristic is: when the actual eddy volume equals the optimal eddy volume, fish can maximize the propulsive effect of the eddy, achieving the lowest swimming energy consumption; when the actual eddy volume is lower than the optimal eddy volume, the propulsive effect of the eddy is insufficient, and fish need to consume more energy to maintain cruising motion; when the actual eddy volume is higher than the optimal eddy volume, strong turbulent water flow increases the swimming resistance of fish, also leading to increased energy consumption, and the greater the deviation from the optimal eddy volume, the faster the rate of energy consumption increase.

[0186] vorticity correction factor for:

[0187] ,

[0188] in, This represents the total eddy current in the physical model of the fish habitat. The standard deviation of vorticity ( This reflects the width of the appropriate vorticity range; For suitable vorticity; , (When outside this range) Energy consumption increases significantly.

[0189] Furthermore, The standard deviation of eddy current is used to reflect the acceptable range of eddy current fluctuations in fish. It needs to be determined through the combined effect of behavioral threshold experiments and statistical distribution fitting.

[0190] First, in the behavioral threshold experiment conducted indoors, the lower limit of eddy current at which fish began to avoid the target was recorded ( ). ) and upper limit ( Lower limit Minimum eddy current where fish spend less than 30% of their time in the water; upper limit The minimum vortex volume is the amount by which the fish's tail-wagging frequency is increased by 50% from the optimal value.

[0191] Next, statistical distribution fitting is performed. Based on field tracking data, eddy current samples from the actual fish activity areas are statistically analyzed, and the number of eddy current samples is determined. A Gaussian distribution was used for fitting, and the half-width value corresponding to the 95% confidence interval was taken as... And the 95% confidence interval of the Gaussian distribution is standard deviation of vorticity The fitting formula is:

[0192] .

[0193] Furthermore, in S502, firstly, the vorticity corresponding to the lowest energy consumption value is obtained through indoor behavioral experiments and defined as the suitable indoor vorticity.

[0194] Healthy adult individuals of the target fish species were selected, and a controllable vortex environment experimental system was constructed in a circular tank or a large circulating tank. By adjusting the arrangement of the guide vanes and flow-blocking blocks within the tank, continuous vorticity fields with different intensity gradients were generated. The gradient vorticity values ​​were set to 0.005, 0.01, 0.02, 0.03, 0.05, 0.08, 0.1, 0.15, and 0.2, with all units being [missing value]. Each vorticity gradient was stabilized for 2 hours. Under each vorticity gradient, a high-definition camera tracking system recorded behavioral parameters such as tail-wagging frequency, cruising speed, and dwell time percentage of the fish. Simultaneously, a respiratory metabolism analyzer measured the real-time energy consumption data of the fish, and a "vorticity-energy consumption" curve was plotted. The vorticity corresponding to the lowest energy consumption value was taken as the suitable vorticity for indoor use. .

[0195] The target fish species are farmed fish of a typical species from a certain river, with a body length of 15-30cm and healthy individuals.

[0196] Secondly, the results were verified through a field habitat tracking experiment. The eddy current range in which fish appeared most frequently was calculated, and the median value of this eddy current range was defined as the suitable eddy current in the wild.

[0197] Specifically, based on the physical model of fish habitat constructed using S1, the core activity area of ​​the target fish species was identified. Individual target fish were tagged using acoustic tagging and tracking technology before being released back into natural waters. Simultaneously, eddy current monitoring equipment was deployed in the tagged areas to collect real-time eddy current data and distribution corresponding to the fish's activity trajectories, recording data once per hour, covering different hydrological time periods. Through statistical analysis, the eddy current interval with the highest frequency of fish occurrence was calculated, and the median of the interval was taken as the suitable eddy current for the wild. .

[0198] Finally, when the deviation between the suitable indoor vorticity and the suitable outdoor vorticity is less than the preset deviation value, the average of the suitable indoor vorticity and the suitable outdoor vorticity is taken as the suitable vorticity.

[0199] Specifically, if the indoor vortex is suitable Suitable eddy current in the field If the deviation between the values ​​is less than 20%, then the average value is taken as the appropriate vorticity. :

[0200] .

[0201] S503. Based on the vortex correction coefficient and the basic energy consumption of a certain type of fish during cruising without vortex, the actual energy consumption of a certain type of fish in different vortex environments is obtained according to the positive linear function.

[0202] Specifically, the actual energy consumption of a certain type of fish in different vortex environments. The calculation formula is:

[0203] .

[0204] In this embodiment, S5 constructs a complete technical chain from basic energy consumption benchmark to eddy current correction coefficient to actual energy consumption quantification through the hierarchical design of S501-S503. Specifically, S501 establishes an eddy current-free energy consumption benchmark based on the classic Brett model, S502 accurately characterizes the correction effect of eddy current on energy consumption through a Gaussian distribution model, and S503 couples the two using a positive linear function. For the first time, it accurately correlates the total eddy current of the entire domain calculated by S4 with the bioenergy consumption of fish, filling the gap in the lack of quantitative connection between physical environmental parameters and bioenergy consumption requirements in traditional habitat assessment, and making the energy consumption calculation results more consistent with the actual survival status of fish in a certain river.

[0205] S502 employs a combined approach of indoor experimental calibration and field experimental verification to determine suitable eddy current. This method ensures parameter accuracy through controlled environmental testing and guarantees practical applicability through field tracking verification. The determination of the eddy current standard deviation, combined with behavioral threshold experiments and Gaussian fitting of 300 sets of field samples, further enhances the reliability of the correction coefficients. This multi-source verification method enables the eddy current correction coefficients to accurately reflect the fish's tolerance and utilization patterns of eddy current. Combined with a standardized Brett model and linear coupling function, the actual energy consumption calculation deviation is controlled within 10%, significantly improving quantification accuracy.

[0206] The method also includes: S6, calculating the energy consumption suitability index based on the actual energy consumption of fish in different vortex environments and according to an exponential function.

[0207] Furthermore, in S6, the energy consumption suitability index is used to reflect the impact of fish's actual energy consumption in different eddy environments on habitat suitability. Higher actual energy consumption by fish in different eddy environments corresponds to lower habitat suitability. The range of the energy consumption suitability index is... The closer the value is to 1, the better the habitat is suitable for fish; the closer the value is to 0, the worse the habitat is, and it may even fail to meet the survival needs of fish.

[0208] When actual energy consumption is zero and the energy suitability index is 1, it indicates that the habitat is theoretically optimal. This is the theoretically optimal state, meaning that the vortex environment of the habitat perfectly suits the movement needs of fish, allowing them to survive without consuming energy. Such areas are the optimal choice for fish habitat and reproduction, and are also the core target areas for habitat restoration projects. It should be noted that ideal states in the natural environment are extremely rare. This standard is mainly used to calibrate the benchmark of the index model and to provide a theoretical reference for the extreme optimization of habitat restoration.

[0209] When the actual energy consumption equals the energy consumption threshold at which fish cannot survive long-term, and the energy suitability index equals This indicates that the habitat is generally suitable. This situation suggests that the eddy environment of the habitat is approaching the limit of the fish's energy metabolism. The fish need to continuously consume their maximum tolerable energy to survive. Long-term exposure to this environment will lead to physical exhaustion, decreased reproductive capacity, or even death. Such areas are warning zones for fish habitats and require close attention and control measures.

[0210] When the actual energy consumption exceeds the energy threshold that fish cannot survive in the long term, and the energy suitability index is less than 0.3, it indicates that the habitat is unsuitable. This situation indicates that the energy consumption cost of the habitat vortex environment has exceeded the fish's limit tolerance, and the fish cannot survive in this area for a long time. Such areas are exclusion zones for fish habitats, unable to provide a stable living space for fish, and are areas that need to be avoided or prioritized for habitat restoration.

[0211] Specifically, the energy consumption suitability index The calculation formula is:

[0212] ,

[0213] in, This represents the maximum energy consumption that fish can tolerate, i.e., the energy consumption threshold at which fish cannot survive for an extended period.

[0214] when hour, (Theoretically optimal); when hour, (Approaching the survival threshold); when hour, This corresponds to an unsuitable area.

[0215] Among these methods, the maximum oxygen consumption rate of the target fish is obtained by searching existing papers, journals, or books. and maximum swimming speed .

[0216] And calculate the maximum energy consumption that fish can tolerate. The calculation formula is as follows:

[0217] .

[0218] In this embodiment, S6 directly links the actual energy consumption of fish quantified in S5 with habitat suitability for the first time. By constructing an exponential function model, an energy consumption suitability index is generated, which overcomes the shortcoming of traditional habitat assessment that only focuses on physical environmental parameters and ignores biological energy demand. This index transforms abstract energy consumption demand into a quantifiable and gradable evaluation indicator, forming a complete logical chain of "physical environment - biological energy consumption - suitability assessment" with the total eddy current distribution in S4 and the energy consumption distribution in S5. This upgrades habitat assessment from a single physical dimension to a comprehensive assessment of both physical and biological dimensions, significantly improving the comprehensiveness and scientific rigor of the assessment system.

[0219] The method also includes: S7, calculating the vorticity suitability index based on the total vorticity and an exponential function.

[0220] Furthermore, in S7, the eddy current suitability index is used to reflect the impact of total eddy current on habitat suitability, and the range of values ​​for the eddy current suitability index is as follows: The closer the value is to 1, the more the total eddy current matches the survival needs of fish, and the higher the suitability of the habitat; the closer the value is to 0, the further the total eddy current deviates from the suitable eddy current, which is an environment that fish are not suited to or avoid, and the lower the suitability of the habitat.

[0221] When the total eddy volume is suitable, the eddy volume suitability index is equal to 1. This situation indicates that the habitat eddy environment and the fish movement characteristics have reached the optimal adaptation state. Fish can maximize the use of the eddy propulsion effect to reduce swimming energy consumption. It is the core preferred area for fish to live, forage and reproduce, and it is also the core target area for habitat protection and restoration projects.

[0222] The greater the deviation between total vorticity and suitable vorticity, the smaller the value of the vorticity suitability index, which is used to reflect the avoidance behavior of fish in extreme vorticity environments.

[0223] Specifically, the vorticity suitability index The calculation formula is:

[0224] ,

[0225] When the vorticity is at a suitable value ( )hour, The greater the deviation, the smaller the index value, reflecting the fish's avoidance behavior in extreme eddy current environments.

[0226] In this embodiment, S7 transforms the total eddy current into a quantifiable eddy current suitability index using an exponential function model, filling the gap in traditional habitat assessments where there is a lack of specific suitability indicators for the physical eddy environment. This index, together with the energy consumption suitability index in S6, forms a two-dimensional evaluation framework of physical environment adaptability and biological energy consumption response. The former focuses on the objective adaptability of the water flow eddy environment, while the latter reflects the subjective energy consumption response of fish. The synergy of the two upgrades habitat assessment from a single dimension to a comprehensive system linking physical and biological factors, significantly improving the comprehensiveness and scientific rigor of the evaluation results.

[0227] The core parameters of S7 are all directly traceable to the data from the indoor experiments and field validation of S502. The determination of the eddy current suitability index also strictly adheres to the boundary constraints of the grading standards, achieving full-chain data integration from habitat feature extraction, eddy current quantification, fish response experiments to suitability index calculation. This strongly correlated design avoids errors caused by parameter fragmentation, ensuring that the eddy current suitability index can truly reflect the adaptation relationship between total eddy current and the survival needs of fish, giving the evaluation results solid experimental data support and clear physical and biological significance.

[0228] The method also includes: S8, constructing a comprehensive habitat suitability index based on the energy consumption suitability index and the eddy current suitability index using a geometric mean function, which is used to determine the comprehensive suitability of fish habitats.

[0229] Furthermore, in S8, the habitat suitability index is used to comprehensively reflect fish's preference for habitats, and the range of values ​​for the habitat suitability index is [value range missing]. The closer the value is to 1, the more suitable the habitat is for fish survival in terms of both physical environment and biological energy consumption, and the stronger the overall suitability. The closer the value is to 0, the more unsuitable there is in at least one dimension, the poor overall quality, and the inability to meet the long-term survival needs of fish.

[0230] Specifically, the comprehensive habitat suitability index The calculation formula is:

[0231] .

[0232] In this embodiment, S8 innovatively integrates the eddy current suitability index of the physical environment adaptation dimension with the energy consumption suitability index of the biological energy consumption response dimension to construct a comprehensive suitability index. This completely overcomes the one-sidedness of single-dimensional evaluation, which only focuses on environmental characteristics or biological responses. This index comprehensively judges habitat quality from the dual core dimensions of whether the objective environment is suitable and whether the subjective survival energy consumption is economical. It can more comprehensively and realistically reflect the actual supporting capacity of the habitat for fish survival, avoid the bias in protection or restoration decisions caused by misjudgment due to a single dimension, and provide a more complete quantitative basis for habitat quality assessment.

[0233] The method also includes: S9, determining the classification standard of the comprehensive habitat suitability index based on the comprehensive habitat suitability index and the preset threshold range.

[0234] Furthermore, in S9, the comprehensive habitat suitability index grading standard is as follows:

[0235] When the habitat suitability index is greater than the upper limit of the preset range, the habitat is a long-term habitat for fish, with low energy consumption and suitable eddy current, corresponding to the core suitable area.

[0236] When the habitat suitability index is within the preset range, the habitat is a short-term activity area for fish, corresponding to a general suitable area.

[0237] When the habitat suitability index is less than the lower limit of the preset range, the habitat is a fish-avoided area, and the energy consumption is too high or the eddy current is extreme, corresponding to an unsuitable area.

[0238] The preset range is defined as follows: .

[0239] Specifically, the core suitability zone is the optimal space for fish to survive, reproduce, and forage. On the one hand, the eddy environment precisely matches the suitable eddy range for fish, allowing them to maximize the use of eddy propulsion to reduce swimming resistance; on the other hand, energy consumption is extremely low, with actual energy consumption close to the basic energy consumption for cruising, eliminating the need for additional energy expenditure to cope with unsuitable environments. From an ecological function perspective, the core suitability zone is typically the core spawning ground, nursery ground, or overwintering ground for fish, possessing stable water flow conditions, abundant food resources, and safe hiding spaces. Additional verification is required during the determination process: the comprehensive suitability index of the area must be continuously stable and match the high-frequency activity areas where the target fish spends more than 24 hours in their wild activity trajectory, ensuring that the grading results are supported by both index evidence and ecological empirical evidence.

[0240] Generally suitable areas are located on the edge of suitable vorticity zones or in critical vorticity zones, or their energy consumption levels are in the low to medium suitability range. Although they do not meet the optimal conditions for long-term habitation, fish can adapt to the environment by adjusting their swimming posture and optimizing their activity paths, and the increase in energy consumption is controllable. From an ecological function perspective, generally suitable areas mainly serve as migration channels, temporary foraging areas, or refuge transition areas for fish. Fish activities in these areas are mainly short-term migrations and temporary resupply, with a stay duration typically between 1 and 24 hours. During the assessment process, it is important to note that for areas with multiple species coexisting, assessment should be based on the dominant species. If an area is generally suitable for species A, it may be unsuitable for species B due to differences in suitability parameters; therefore, species specificity must be clearly indicated in the classification results. Simultaneously, the overall suitability index of such areas must meet the requirement of not having an extreme weakness, i.e. and All values ​​should be no less than 0.3 to avoid misjudgment caused by an extreme incompatibility of a single dimension falling into this range.

[0241] Unsuitable areas completely fail to meet the survival needs of fish. Either the eddy current environment is extremely unsuitable, or the energy consumption level exceeds the fish's tolerance limit; some areas even exhibit extreme unsuitability in two dimensions. From an ecological perspective, unsuitable areas are spaces that fish actively avoid, with almost no fish activity patterns. If fish mistakenly enter, they may suffer from exhaustion, decreased reproductive capacity, or even death. Verification is crucial during the determination process: firstly, the source data for the index calculation must be checked to confirm... A value less than 0.3 is not due to parameter mismatch or calculation error; on the other hand, combined with field monitoring data, it is verified that there are no records of target fish staying in the area, and the influence of temporary factors such as extreme hydrological fluctuations is ruled out. If an area is unsuitable only during the flood season and generally suitable during the normal and dry seasons, it should be marked as a seasonally unsuitable area to distinguish it from an annually unsuitable area.

[0242] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption, characterized in that, The method includes: S1. Geometric features of the riverbed sediment, riverbank vegetation, and reef topography are extracted and a physical model of fish habitat is constructed to provide a basic basis for the analysis of this method. S2. The riverbed rough vorticity coefficient, vegetation disturbance vorticity coefficient, and topographic flow vorticity coefficient are obtained through flume tests or field tests and theoretical calculations. S3. Based on the physical model of fish habitat, the rough vorticity coefficient of the riverbed, the vorticity coefficient of vegetation disturbance and the vorticity coefficient of topographic flow, the rough vorticity of the riverbed, the vorticity of vegetation disturbance and the vorticity of topographic change of the fish habitat physical model are quantitatively calculated. S4. Based on the riverbed rough eddy, vegetation disturbance eddy, and topographic abrupt change eddy, the total eddy of the fish habitat physical model is calculated by superposition. S5. Based on the actual energy consumption model, calculate the basic energy consumption of fish cruising without vorticity, and obtain the vorticity correction coefficient according to the distribution characteristics of fish utilization of vorticity. Construct a quantitative relationship between vorticity and energy consumption to quantify the actual energy consumption of fish in different vortex environments. S6. Based on the actual energy consumption of fish in different vortex environments, the energy consumption suitability index is calculated according to the exponential function. S7. Based on the total vorticity, the vorticity suitability index is calculated according to the exponential function. S8. Based on the energy consumption suitability index and the eddy current suitability index, a comprehensive habitat suitability index is constructed using a geometric mean function to determine the comprehensive suitability of fish habitats. S9. Determine the classification standard of the comprehensive habitat suitability index based on the comprehensive habitat suitability index and the preset threshold range.

2. The method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption according to claim 1, characterized in that, In S1, the geometric characteristics of the riverbed sediment include sediment particle size distribution, bed surface micro-topographic undulation, riverbed plan morphology, and longitudinal profile slope. The geometric characteristics of the riparian vegetation include the spatial distribution range of the vegetation community, plant height or crown width, vegetation zone width and layering structure, and the geometric morphology of the vegetation root system. The geometric features of the reef topography include the spatial location, shape and size of the reefs, the distribution density and topological relationship of the reef group, and the relative elevation of the reefs to the riverbed.

3. The method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption according to claim 1, characterized in that: S2 includes: S201, collecting the hourly average flow velocity, hydraulic radius, water surface gradient, and riverbed roughness height at each measurement point in the flume test with the expected number of collections; calculating and defining the average value of the vorticity component perpendicular to the plane at each measurement point as the theoretical riverbed roughness vorticity; and inversely deriving the formula for calculating the theoretical riverbed roughness vorticity and taking the average value to obtain the riverbed roughness vorticity coefficient for each riverbed type. S202. Collect the hourly average flow velocity, vegetation unit area projection ratio, and vegetation canopy height at each measurement point in the flume test with the expected number of collections; calculate and define the average value of the vorticity component perpendicular to the plane at each measurement point as the theoretical vegetation disturbance vorticity; calculate the cross-sectional average flow velocity at each measurement point, and deduce the theoretical vegetation disturbance vorticity calculation formula and take the average value to obtain the vegetation disturbance vorticity coefficient for each vegetation type. S203. Collect the hourly average flow velocity and reef diameter at each measurement point in the reef area during the expected number of collections in the flume test; calculate and define the average value of the vorticity component perpendicular to the plane at each measurement point as the theoretical topographic vorticity; calculate the cross-sectional average flow velocity at each measurement point; deduce the formula for calculating the theoretical topographic vorticity and take the average value to obtain the topographic vorticity coefficient for each type of reef.

4. The method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption according to claim 3, characterized in that, S3 includes S301, which quantifies the hydraulic radius, water surface gradient, and riverbed roughness height based on a physical model of fish habitats, where the riverbed roughness height is defined as the eddy power characteristic length; the shear velocity generated by the shear flow on the riverbed wall is calculated based on the hydraulic radius and water surface gradient; the riverbed roughness eddy power coefficient, shear velocity, and riverbed roughness height are coupled to obtain the riverbed roughness eddy power of the physical model of fish habitats; when the riverbed roughness element causes flow shear, the larger the eddy power characteristic length and the steeper the water surface gradient, the stronger the generated riverbed roughness eddy power. S302. Based on the physical model of fish habitat, the quantified vegetation unit area projection ratio, quantified cross-sectional average flow velocity, vegetation resistance coefficient to water flow, and vegetation canopy height are obtained, where the vegetation canopy height is the vegetation vortex characteristic length. Based on the vegetation unit area projection ratio and cross-sectional average flow velocity, the vegetation additional shear velocity is calculated. The vegetation canopy height, vegetation vortex coefficient, and vegetation additional shear velocity are coupled to obtain the vegetation disturbance vortex of the fish habitat physical model. The larger the vegetation unit area projection ratio and the lower the vegetation vortex characteristic length, the stronger the disturbance to water flow and the larger the generated vegetation disturbance vortex. S303. Based on the physical model of fish habitat, the diameter of the reef, the angle between the water flow and the reef axis, and the average cross-sectional velocity are quantified. Based on the angle between the water flow and the reef axis and the average cross-sectional velocity, the characteristic velocity difference of the water flow around the reef is calculated. The topographic vorticity coefficient, the reef diameter, and the characteristic velocity difference are coupled to obtain the topographic abrupt vorticity of the physical model of fish habitat. The higher the average flow velocity across the cross section, the smaller the diameter of the reef, and the closer the angle between the water flow and the reef... The stronger the topographical abrupt eddy current generated by the flow around the object, the more powerful the eddy current becomes.

5. The method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption according to claim 1, characterized in that, S5 includes S501, collecting the average body weight and average cross-sectional velocity of a certain type of fish and inputting them into the actual energy consumption basic model to obtain the basic energy consumption of a certain type of fish cruise without eddy current. S502. Fish utilization of eddy current exhibits a Gaussian distribution characteristic. Eddy current correction coefficients are calculated. When the eddy current is the same as the suitable eddy current, energy consumption is the lowest. Eddy current that is too low or too high will increase energy consumption. Among them, the suitable eddy current is the eddy current value with the lowest energy consumption and the most frequent activity of fish. It is obtained by a combination of indoor behavioral experiments and field habitat tracking experiments. S503. Based on the vortex correction coefficient and the basic energy consumption of a certain type of fish during cruising without vortex, the actual energy consumption of a certain type of fish in different vortex environments is obtained according to the positive linear function.

6. The method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption according to claim 5, characterized in that, In S502, the vorticity corresponding to the lowest energy consumption value is obtained through indoor behavioral experiments and is defined as the suitable indoor vorticity. The results were verified through a field habitat tracking experiment. The eddy current range in which fish appeared most frequently was calculated, and the median value of this eddy current range was defined as the suitable eddy current in the wild. When the deviation between the suitable indoor vorticity and the suitable outdoor vorticity is less than the preset deviation value, the average of the suitable indoor vorticity and the suitable outdoor vorticity is taken as the suitable vorticity.

7. The method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption according to claim 6, characterized in that, In S6, the energy consumption suitability index reflects the impact of fish's actual energy consumption in different eddy environments on habitat suitability. Higher actual energy consumption by fish in different eddy environments corresponds to lower habitat suitability. The range of the energy consumption suitability index is... ; When the actual energy consumption is zero and the energy consumption suitability index is 1, it indicates that the suitability of the habitat is theoretically optimal. When the actual energy consumption equals the energy consumption threshold at which fish cannot survive long-term, and the energy suitability index equals This indicates that the habitat is generally suitable. When the actual energy consumption exceeds the energy consumption threshold that fish cannot survive in the long term, and the energy consumption suitability index is less than 0.3, it indicates that the habitat is unsuitable.

8. The method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption according to claim 7, characterized in that, In S7, the eddy current suitability index is used to reflect the impact of total eddy current on habitat suitability. The value range of the eddy current suitability index is as follows: ; When the total vorticity is the optimal vorticity, the vorticity suitability index is equal to 1. The greater the deviation between the total vorticity and the optimal vorticity, the smaller the value of the vorticity suitability index, which is used to reflect the fish's avoidance behavior in extreme vorticity environments.

9. The method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption according to claim 8, characterized in that, In S8, the habitat suitability index is used to comprehensively reflect fish's preference for habitat. The range of values ​​for the habitat suitability index is [value range missing]. .

10. The method for determining river habitat indicators based on the coupling of eddy current and fish energy consumption according to claim 9, characterized in that, In S9, the comprehensive habitat suitability index grading standard is as follows: When the habitat suitability index is greater than the upper limit of the preset range, the habitat is a long-term habitat for fish, with low energy consumption and suitable eddy current, corresponding to the core suitable area. When the habitat suitability index is within the preset range, the habitat is a short-term activity area for fish, corresponding to a general suitable area. When the habitat suitability index is less than the lower limit of the preset range, the habitat is a fish-avoided area, and the energy consumption is too high or the eddy current is extreme, corresponding to an unsuitable area.

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