Method for rapidly evaluating influence of reservoir scheduling on suitable habitat area of downstream fishes

Abstract

The invention relates to the technical field of computers, in particular to a method for rapidly evaluating the influence of reservoir scheduling on the suitable habitat area of downstream fishes. The method comprises the following steps: acquiring natural environment data of a river channel in a to-be-researched area; the boundary of the to-be-researched area is checked out, a triangular mesh is generated, and mesh smoothing processing is carried out; obtaining a triangular mesh chart with elevation interpolation surface data; constructing a two-dimensional hydrodynamic model; selecting working condition combinations of various water levels and flows, simulating hydrological and hydrodynamic characteristics of a downstream river channel, extracting water depth and flow velocity surface data as key environmental factors, and exporting grid data of a simulation result; and carrying out binarization processing on the environmental factors by using a binary classification method, determining the proportion of the number of grids in a key environmental factor interval range in the total number of grids, and obtaining the suitable habitat area of fishes in the downstream river channel under various reservoir dispatching combination working conditions. The method can quickly evaluate the spatial distribution of the suitable habitat of fishes in the downstream river under the influence of reservoir scheduling.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, in particular to a method for quickly evaluating the influence of reservoir operation on the area of suitable habitat for fish downstream. BACKGROUND

[0002] For the influence of reservoir operation on the area of suitable habitat for fish downstream, the commonly used methods are field monitoring and model simulation. Among them, the field monitoring method is time-consuming and labor-intensive, and can only monitor and analyze the specific reservoir water storage and release situation to identify the suitable habitat for this operation. The model simulation method is based on the simulation of hydrodynamic model, combined with the habitat requirements of fish for hydrological and hydrodynamic factors such as water depth and flow, to build suitable degree curves for each factor, and then to calculate the comprehensive suitability by weighting, and finally to estimate the available area by weighting. The process is relatively complex. SUMMARY

[0003] In view of the fact that the existing methods for evaluating the influence of reservoir operation on the area of suitable habitat for fish downstream cannot quickly and accurately quantify the area of suitable habitat for fish downstream under various combinations of water level and flow in reservoir operation, the present application combines the binary classification method and image data processing technology to quickly evaluate the spatial distribution of suitable habitat for fish downstream under the influence of reservoir operation on the basis of building a two-dimensional hydrodynamic model to simulate the hydrodynamic situation under various reservoir operation conditions, thereby providing efficient and reliable decision support for reservoir operation.

[0004] The technical solution adopted by the present application to solve the technical problem is:

[0005] A method for quickly evaluating the influence of reservoir operation on the area of suitable habitat for fish downstream, comprising the following steps:

[0006] S1, obtaining the natural environment data of the river channel in the area to be studied;

[0007] S2, checking out the boundary of the area to be studied, densely processing the boundary grid points of the area to be studied, generating triangular mesh and performing mesh smoothing processing;

[0008] S3, according to the geographical location longitude and latitude coordinates of the area to be studied after mesh smoothing processing, inserting the measured river section elevation data, calculating the elevation values of the remaining areas without elevation data, and obtaining the triangular mesh graph with elevation interpolation surface data covering the entire study area;

[0009] S4, setting the upstream and downstream boundaries and adjusting the parameters to build a two-dimensional hydrodynamic model;

[0010] S5, collecting reservoir water storage scheduling operation data, selecting a variety of water level and flow conditions of reservoir scheduling combinations, simulating the hydrological and hydrodynamic characteristics of the downstream river under the influence of reservoir scheduling, extracting water depth and flow velocity surface data as key environmental factors, and exporting grid data of the simulation results;

[0011] S6, obtaining the suitable interval range of the target fish to the key environmental factors, using binary classification method to binary process the environmental factors, determining the number of grids meeting the interval range of the key environmental factors, combining with image recognition technology, the proportion of the number of grids in the total number of grids, obtaining the fish suitable habitat area of the downstream river under various reservoir scheduling combination conditions.

[0012] In the above method for quickly evaluating the influence of reservoir scheduling on the downstream fish suitable habitat area, in S1, the natural environment data includes terrain data, flow data and water level data.

[0013] In the above method for quickly evaluating the influence of reservoir scheduling on the downstream fish suitable habitat area, in S2, the CAD drawing is used to frame the area to be studied, and the area to be studied with the selected boundary is imported into the grid processing software of MIKEZERO of MIKE21 two-dimensional hydrodynamic model.

[0014] In the above method for quickly evaluating the influence of reservoir scheduling on the downstream fish suitable habitat area, in S3, the elevation interpolation function in MIKEZERO is used to calculate the elevation values of the remaining areas without elevation data.

[0015] In the above method for quickly evaluating the influence of reservoir scheduling on the downstream fish suitable habitat area, in S4, the adjusted parameters include simulation equation order, simulation time, wind speed, evaporation amount and bottom material parameters;

[0016] In the above method for quickly evaluating the influence of reservoir scheduling on the downstream fish suitable habitat area, the simulation equation order is low order;

[0017] In the above method for quickly evaluating the influence of reservoir scheduling on the downstream fish suitable habitat area, the simulation time is 10-20 days;

[0018] In the above method for quickly evaluating the influence of reservoir scheduling on the downstream fish suitable habitat area, the wind speed, evaporation amount and bottom material parameters are selected as default values.

[0019] In the above method for quickly evaluating the influence of reservoir scheduling on the downstream fish suitable habitat area, in S5, the various water level conditions of reservoir water storage scheduling include the dead water level, flood control limit water level and normal water storage level of the hydropower station.

[0020] In the method for rapidly evaluating the influence of reservoir regulation on the suitable habitat area of fish downstream, the multiple flow conditions of the reservoir water storage and release regulation include the multi-year average flow in the dry season, the multi-year average flow and the multi-year average flow in the flood season of the river section downstream of the reservoir.

[0021] In the method for rapidly evaluating the influence of reservoir regulation on the suitable habitat area of fish downstream, in S6, the binary processing is to use the binary classification method to process the environmental factors as "suitable" and "unsuitable", determine the number of grids in the "suitable" interval range of the key environmental factors, and combine the image recognition technology to obtain the suitable habitat area of fish downstream under various reservoir regulation combination conditions according to the proportion of the total area of the study area and the grids meeting the suitable habitat conditions of fish in the total number of grids.

[0022] In the method for rapidly evaluating the influence of reservoir regulation on the suitable habitat area of fish downstream, the binary processing refers to setting 1 and 0 switches to represent the suitable and unsuitable habitats of fish, respectively, superimposing and analyzing the evaluation results of each key environmental factor, and using the logical multiplication rule, that is, the habitat is determined as "suitable" only when all factors are 1.

[0023] In the method for rapidly evaluating the influence of reservoir regulation on the suitable habitat area of fish downstream, in S6, the suitable habitat area of fish downstream under various reservoir regulation combination conditions is: wherein N is the total number of grids of the river channel fitted by the MIKE model, n is the number of grids meeting the flow velocity and water depth conditions, S is the area of the river basin studied, and s is the suitable habitat area.

[0024] In the method for rapidly evaluating the influence of reservoir regulation on the suitable habitat area of fish downstream, in S7, the influence of reservoir regulation on the suitable habitat area of fish downstream is evaluated according to the suitable habitat area of fish downstream under various reservoir regulation combination conditions, and the optimal water level-flow combination in the simulated condition is obtained by comparing the simulation results.

[0025] By the above technical solution, the present application has at least the following advantages:

[0026] The present application rapidly evaluates the influence of reservoir regulation on the suitable habitat area of fish downstream by coupling the hydrodynamic model and the binary classification method. Specifically, on the basis of constructing a two-dimensional hydrodynamic model to simulate the changes of hydrodynamic conditions under various reservoir regulation conditions, the binary classification method is used to conveniently set 1 and 0 switches to represent the suitable and unsuitable habitats of fish, respectively, and then the image recognition technology is combined to rapidly evaluate the spatial distribution of the suitable habitat of fish downstream under multiple reservoir regulation conditions, thereby providing efficient and reliable decision support for reservoir regulation.

[0027] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the rapid evaluation method of the present invention;

[0029] Figure 2 These are the grid diagram and measured interpolation diagram of the study area in this embodiment of the invention;

[0030] Figure 3 This is the MIKEZERO interpolation map of the study area in this embodiment of the invention;

[0031] Figure 4 This is the grid distribution assessment result of a suitable habitat based on a two-dimensional hydrodynamic model and a binary classification method, according to an embodiment of the present invention.

[0032] Figure 5 This is a bar chart showing the suitable habitat area assessment results for nine scenarios in this invention.

[0033] Figure 6 shows water depth data for nine scenarios according to embodiments of the present invention;

[0034] Figure 7 is a flow velocity data graph for nine scenarios according to embodiments of the present invention;

[0035] Figure 8 is a line graph showing the change in suitable habitat area for different water level-flow combinations according to an embodiment of the present invention. Detailed Implementation

[0036] To further illustrate the technical means and effects of the present invention in achieving the intended purpose, the following detailed description of the specific implementation methods, structures, features and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0037] like Figures 1-8 As shown in the figure, this embodiment discloses a method for rapidly assessing the impact of reservoir scheduling on the suitable habitat area of ​​downstream fish. Specifically, it is a method for assessing the impact of reservoir scheduling on the suitable habitat area of ​​downstream river fish, including the following steps:

[0038] S1, Obtain natural environmental data of the river channel in the area to be studied, including topographic data, flow data and water level data;

[0039] S2, the boundary of the area to be studied is selected, specifically, the area to be studied is framed by using CAD drawing, the selected boundary area to be studied is imported into the grid processing software of MIKEZERO of the MIKE21 two-dimensional hydrodynamic model, the boundary grid points of the area to be studied are densified, triangular grids are generated and grid smoothing is performed;

[0040] S3, according to the converted geographical position latitude and longitude coordinates of the area to be studied, the measured river section elevation data is inserted, the elevation values of the remaining areas without elevation data are calculated by using the elevation interpolation function in MIKEZERO, and the triangular grid graph with elevation interpolation surface data covering the entire study area is obtained;

[0041] S4, the upstream and downstream boundaries are set, and the related parameters are adjusted to build a two-dimensional hydrodynamic model;

[0042] S5, collect reservoir water storage and release operation data, select various water level and flow conditions of reservoir operation, simulate the hydrological and hydrodynamic characteristics of downstream river under the influence of reservoir operation, extract water depth and flow velocity surface data as key environmental factors (specifically, the water depth and flow velocity surface data at the end of simulation are extracted as key environmental factors), and export the grid data of simulation results;

[0043] S6, obtain the suitable interval range of the target fish to the key environmental factor, use binary classification method to process the environmental factor, determine the number of grids in the interval range of the key environmental factor, and combine image recognition technology to obtain the fish habitat area in the downstream river under various reservoir operation conditions.

[0044] Further, in S5, the various water level conditions of the reservoir water storage and release operation include the dead water level, the flood control limit water level and the normal water storage level of the hydropower station; the various flow conditions of the reservoir water storage and release operation include the average annual flow of the downstream river section in dry season, the average annual flow and the average annual flow in flood season.

[0045] In S6, the binary processing is to use binary classification method to process the environmental factor as "suitable" and "unsuitable", determine the number of grids in the "suitable" interval range of the key environmental factor, and combine image recognition technology to obtain the fish habitat area in the downstream river under various reservoir operation conditions according to the total area of the study area and the proportion of the grids meeting the fish "suitable" habitat conditions in the total grid number.

[0046] The binary processing refers to setting 1 and 0 switches to represent fish "suitable" and "unsuitable" habitat respectively, superimposing and analyzing the evaluation results of each key environmental factor, and adopting logic multiplication rule, that is, all factors are 1, only then the habitat is determined as "suitable".

[0047] Since flow velocity and water depth are key factors affecting fish habitat, different hydrological and hydrodynamic conditions have different effects on fish spawning, habitat and predation behavior. Therefore, the water depth and flow velocity surface data in S5 are extracted as key environmental factors.

[0048] The present application can quickly evaluate the spatial distribution of fish suitable habitat in the downstream river channel under the influence of reservoir operation, and provide efficient and reliable decision support for reservoir operation. In order to further illustrate the specific implementation steps and effects of the present embodiment, the present application is further illustrated by taking the influence of reservoir operation on the fish habitat suitable habitat area in the downstream river channel of Heishui River, a tributary of Jinshajiang River, as an example.

[0049] Heishui River is a first-order tributary on the left bank of Jinshajiang River, originating from Luoji Mountain between Zhaojue County and Puge County of Liangshan Yi Autonomous Prefecture in Sichuan Province, and flowing into Jinshajiang River at Huadan Town (now belonging to Baihetan Town) in Ningnan County. The research area selected in the present application is located at the end of the river section of Ningnan County, where it flows into Jinshajiang River, with a length of about 21.175 kilometers, a research area of 19.148 square kilometers, geographical coordinates between 102°43-102°53'E and 26°50-27°18'N, and rich fish resources, being one of the important fish habitats. There are hydropower facilities such as Laomuhu Hydropower Station and Songxin Hydropower Station in the upper reaches of the research area, which will affect the fish habitat downstream.

[0050] The method for quickly evaluating the influence of reservoir operation on the fish habitat suitable habitat area in the downstream river channel provided in the present embodiment comprises the following steps:

[0051] S1, collecting natural environment data such as terrain, flow, water level, etc. in the downstream river channel of Heishui River, a tributary of Jinshajiang River;

[0052] S2, using CAD drawing to frame the research area to be studied, checking the boundary of the research area to ensure that the field measured elevation data set is covered, importing the region into the grid processing software of MIKEZERO after the selection is completed, and performing intensive processing on the boundary grid points, generating triangular mesh, and smoothing the grid. After intensive processing, the number of generated grids is more, and the simulation result is more accurate. Smoothing can make the area of each small triangular mesh similar, so that each small mesh area is considered the same in calculation. The final selected starting point of the upper river section is 102.72E27.03N, and the ending point of the lower river section is 102.88E26.96N. The length of the river section in the research area is about 21.175 kilometers, the area of the research area is 19.148 square kilometers, and 23694 triangular meshes are generated;

[0053] S3, after the research area is framed and meshed, the measured section elevation data of Heishui River in this section are inserted into the research area according to the converted latitude and longitude coordinates, a total of 13 sections (Figure 2 After inserting the cross-sectional data, the elevation interpolation function in MIKEZERO was used to calculate the elevation values ​​for the remaining areas without elevation data. Interpolation was then performed, and fine-tuning was done based on the interpolated grid map. This process transformed multiple elevation line data into surface data, covering the entire study area. The final resulting grid map is a triangular grid map with interpolated elevation surface data. Figure 3 );

[0054] S4. Import the study area mesh generated by MIKEZERO into the FLOWMODEL module of the MIKE21 model, set the upstream and downstream boundaries, adjust the relevant parameters, and construct the MIKE21 two-dimensional hydrodynamic model.

[0055] S5. Collect reservoir scheduling and operation data, and select the hydropower station water storage and release water level parameters of 765m, 785m, and 825m to simulate the impact of reservoir scheduling on the river section water level; select the river flow parameters of 31.6m³ / s, 70m³ / s, and 118m³ / s to simulate the river section flow during the flood season and non-flood season, and obtain 9 different hydrological simulation results through permutation and combination (see Table 1).

[0056] S6, taking the round-mouthed copper fish as an example, water depth and current velocity were selected as two key factors to study its habitat suitability. Based on literature, the suitable ranges for water depth and current velocity for the round-mouthed copper fish and its juvenile populations were obtained. Accordingly, this invention sets the "suitable" range and binary values ​​for each factor as follows: water depth: 1.2–11.5 m, assigned a value of 1; others: 0; current velocity: 0.2–1.3 m / s, assigned a value of 1; others: 0. Only when both factors at a given location are 1 is it considered a "suitable" habitat. The 23,694 triangular mesh data points from each set of simulation data were exported, and Python code was used to filter the data. The spatial distribution of the filtered meshes meeting the conditions is as follows: Figure 4 As shown;

[0057] The research subject selected in this embodiment is the round-mouthed copper fish. By reviewing the literature, we obtained the suitability curves for water depth and current velocity of the round-mouthed copper fish and its juvenile populations, which have been successfully constructed through research. The results show that the optimal habitat depth for the round-mouthed copper fish is 1.2–11.5 m, and the optimal current velocity is 0.2–1.3 m / s. The optimal water temperature range for juvenile round-mouthed copper fish is 19.8–25.4℃, the optimal water depth is 0.4–3.95 m, and the optimal current velocity is 0.1–0.7 m / s.

[0058] This embodiment can also assess the impact of reservoir operation on the suitable habitat area for fish in downstream rivers. Specifically, it may include step S7, which assesses the impact of reservoir operation on the suitable habitat area for fish in downstream rivers based on the suitable habitat area for fish in downstream rivers under each reservoir operation combination. Based on the suitable habitat area for fish in downstream rivers under each reservoir operation combination, the assessment shows that, under the same flow conditions, as the water level increases from 765m to 825m, both the number and area of ​​grids meeting the criteria show a significant increasing trend. Taking a flow rate of 31.6 m³ / s as an example, as the water level rises from 765 m to 825 m, the number of "suitable" grids increases from 144 to 270, and the area increases from 0.1163 km² to 0.2182 km² (an increase of 87.5%). Analysis of the impact of reservoir flow rate changes on suitable habitats reveals that under the same water level, the trends in the number and area of ​​"suitable" grids are inconsistent with increasing flow rate. The interaction between flow rate and water level is significant; increased flow rate at higher water levels is more conducive to the formation of suitable habitats. An optimal flow rate may exist at a medium water level (785 m), while excessively high or low flow rates are detrimental to maintaining suitable habitats. Analysis of the impact of reservoir flow rate and water level combinations on suitable habitats shows that by maintaining a high water level of approximately 825 m and combining it with a flow rate adjustment of 118 m³ / s, the suitable habitat area for the round-mouthed copper fish can be maximized to 0.24 km², an increase of 106.4% compared to the minimum conditions. Figure 5 ).

[0059] The data required for this embodiment includes hydrological data from the Ningnan Hydrological Station and some research papers on the Heishui River; fish data from fish anthologies and related fish research literature (mainly *Cyprinus circinus*); and river channel data from NASA Earthdata satellite DEM image data (from the website https: / / dwtkns.com / srtm30m) and actual river channel measurement data. Parameters such as sediment, evapotranspiration, and wind speed were simulated using default values ​​from the FM model in MIKE21 due to a lack of data and the fact that some parameters had a relatively small impact on the simulation.

[0060] The hydrological model used in this embodiment is the MIKE21 hydrodynamic model, and a series of pre-processing and post-processing software are used to organize the required data.

[0061] The method for generating triangular meshes is constrained Delaunay triangulation, an extension of standard Delaunay triangulation. It satisfies the Delaunay criterion as much as possible while maintaining preset constraints. This method ensures that important geometric features are not destroyed during discretization and is often used in hydraulic modeling to handle complex boundaries and internal features. Its constraint properties guarantee that all meshes remain within the constraints.

[0062] After the study area was selected and gridded, the measured cross-sectional elevation data of the Heishui River section were inserted into the study area based on the converted latitude and longitude coordinates, totaling 13 cross-sections. Figure 2 After inserting the cross-sectional data, the elevation interpolation function in MIKEZERO was used to calculate the elevation values ​​for the remaining areas without elevation data. Interpolation was then performed, and fine-tuning was done based on the interpolated grid map. This process transformed multiple elevation line data into surface data, covering the entire study area. The final resulting grid map is a triangular grid map with interpolated elevation surface data. Figure 3 ).

[0063] In the preliminary simulation, it was found that the flow parameters stabilized after approximately 10 days of simulation, and then showed little change with increasing simulation days. Therefore, the total simulation time was 15 days, with a data recording step size of 1 day. After the simulation, the data from day 15 was extracted for subsequent processing and calculation. The calculated data included water surface elevation, absolute water depth, total water depth, real-time meridional velocity, real-time zonal velocity, real-time velocity value, and real-time flow direction. The key data to be extracted for calculation were the real-time velocity value and total water depth for subsequent HSC analysis. Finally, nine different hydrological simulation results were generated through permutations and combinations of three water conditions and three flow conditions. The 23,694 grid data points from each of the nine results were exported for subsequent calculations.

[0064] The study area mesh generated by MIKEZERO was imported into the FLOWMODEL software in MIKE21, and upstream and downstream settings were configured and relevant parameters were adjusted. Finally, based on relevant data and literature, the hydropower station's water storage and release parameters were selected from low to high as 765m, 785m, and 825m to simulate the impact of hydropower station operation on the river level. River flow parameters were selected from low to high as 31.6m³ / s, 70m³ / s, and 118m³ / s to simulate the river flow during flood and non-flood seasons. Specifically, 765m represents the dead water level of the hydropower station, 785m is the flood control limit water level, and 825m is the normal water level; 31.6m³ / s is the multi-year average flow during the dry season, 70m³ / s is the multi-year average flow, and 118m³ / s is the multi-year average flow during the flood season.

[0065] The HSC (Habitat Sustainable Criteria) binary classification method (also known as the 0-1 method) is a fundamental method in habitat suitability assessment. Its core idea is to divide habitat environmental factors into two states: "suitable" and "unsuitable." This method binarizes environmental factors by setting clear thresholds: a suitable state is assigned a value of 1, indicating that the environmental factor meets the species' survival needs; an unsuitable state is assigned a value of 0, indicating that the environmental factor does not meet the species' survival needs. The basic method involves first identifying key environmental factors, selecting environmental variables that significantly affect the survival of the target species based on their ecological habits, such as water depth and flow velocity; then setting threshold ranges, based on species ecological studies or field observation data, to clarify the suitable range for each environmental factor. The discrimination rule is that when the measured value of an environmental factor is within the suitable range, a value of S=1 is assigned; when the measured value exceeds the suitable range, a value of S=0 is assigned. Finally, the evaluation results of each environmental factor are superimposed and analyzed, usually using a logical multiplication rule, meaning that the habitat is considered suitable only when all factors are equal to 1.

[0066] This embodiment takes the assessment of river fish habitats as an example, selecting water depth and flow velocity as two key factors, and setting suitable ranges for each factor:

[0067] Water depth: 0.5-2.0m → [1]; Other → [0]

[0068] Flow velocity: 0.3-1.2 m / s → [1]; Other → [0]

[0069] A location is considered a suitable habitat only if both factors are 1.

[0070] Water depths of 1.2–11.5 m and flow velocities of 0.2–1.3 m / s were selected as screening criteria. Each group of 23,694 grid data points was screened to determine the number of grids meeting the criteria. Then, based on the total area of ​​the known study area and the proportion of grids meeting the criteria in the total number of grids, the suitable habitat area for *Cyprinus circinus* in this river section was determined. This was used to conduct habitat health diagnosis of *Cyprinus circinus* under the simulated conditions.

[0071] In this embodiment, water levels of 765m, 785m, and 825m and flow rates of 31.6m³ / s, 70m³ / s, and 118m³ / s were simulated. A total of nine sets of data were obtained through permutations and combinations, corresponding to nine different scenarios (see Table 1). The real-time flow velocity and total water depth data were extracted for calculation. The results are as follows: Figures 6-7 As shown in the figure. The real-time flow velocity value is the scalar value of the flow velocity in the vector direction in the current triangular grid, and the total water depth is the average water depth in the vertical direction from the water surface to the bottom within the grid area.

[0072] Table 1. Simulation analysis results of suitable habitat area under various reservoir operation conditions.

[0073]

[0074] Analysis of the simulation data from Figure 9 reveals the following overall characteristics: Among the total 23,694 triangular grids, the number of grids meeting the conditions of water depth 1.2-11.5m and flow velocity 0.2-1.3m / s ranged from 144 (765m / 31.6m³ / s) to 297 (825m / 118m³ / s), representing 0.6077%-1.2535% of the total grids. The total area of ​​suitable habitats meeting these conditions varied between 0.1163km² and 0.2400km², indicating significant differences in the physical space of suitable habitats under different hydrological conditions.

[0075] Nine sets of data, each containing 23,694 triangular meshes, were exported. Python code was then used to filter the data. As mentioned earlier, the filtering criteria were water depths of 1.2–11.5 m and flow velocities of 0.2–1.3 m / s. The filtering results are shown in Table 1. The spatial distribution of the meshes meeting the filtering criteria is as follows: Figure 4 As shown (a grid distribution diagram of the conditions for meeting the nine scenarios).

[0076] The number of suitable grids varied significantly across all nine simulated combinations. The maximum was 297 (825m water level - 118m³ / s flow rate combination), the minimum was 144 (765m water level - 31.6m³ / s flow rate combination), and the range was 153, indicating a 106.25% difference between the optimal and worst conditions.

[0077] The suitable area index also showed significant fluctuations, with a maximum area of ​​0.2400 km² (825 m - 118 m³ / s) and a minimum area of ​​0.1163 km² (765 m - 31.6 m³ / s), resulting in a large area difference of 0.1237 km². Since the total area of ​​the study area was fixed, the variation in suitable area was the same as the number of grid cells, both at 106.25%.

[0078] The optimal combination, with a water level of 825 m and a flow rate of 118 m³ / s, produced the most suitable grids (297) and the largest suitable area (0.2400 km²). The worst combination, with a water level of 765 m and a flow rate of 31.6 m³ / s, performed the worst, with only 144 suitable grids and an area of ​​0.1163 km².

[0079] Analysis of the variation range shows that the variation range caused by water level changes (up to 87.5%) is significantly greater than that caused by flow rate changes (up to about 20%), indicating that within the parameter range of this invention, water level is the dominant factor affecting the distribution of suitable habitats.

[0080] Average value analysis: Average number of suitable grids: 215.11, average suitable area: 0.1736 km², average percentage: 0.9138%.

[0081] Median analysis: Median number of suitable grids: 202 (785m-118m³ / s), median suitable area: 0.1632km², median percentage: 0.8525%.

[0082] The comparison between the mean and the median shows that the data distribution is right-skewed, indicating that some combinations have values ​​that are significantly higher than the average level.

[0083] The variances and standard deviations of each indicator were calculated as follows: Variance of suitable number of grids: 3228.61, Standard deviation: 56.82; Variance of suitable area: 0.0021, Standard deviation: 0.0458; Variance of proportion: 0.0546%, Standard deviation: 0.2337%.

[0084] Coefficient of variation (CV) analysis: CV for grid number = 26.41%, CV for area = 26.38%, and CV for percentage = 25.58%. These indicators suggest that the data has a moderate degree of variation, and the differences between different hydrological combinations are noteworthy.

[0085] Under the same flow rate conditions, as the water level rises from 765m to 825m, the number and area of ​​suitable grids both show a significant increasing trend. Taking a flow rate of 31.6 m³ / s as an example, as the water level rises from 765m to 825m, the number of suitable grids increases from 144 to 270, and the area increases from 0.1163 km² to 0.2182 km² (an increase of 87.5%).

[0086] The suitable habitat indicators at high water levels (825m) in hydropower stations are significantly better than those at medium and low water levels, indicating that higher water levels are more conducive to the formation of habitats with suitable water depth and flow velocity. This phenomenon may be related to the fact that the rise in water level leads to more areas entering the suitable water depth range.

[0087] Statistical analysis of the data grouped by water level yielded the following results: 1) 765m water level group (3 combinations): mean: 157 grids, 0.127 km², standard deviation: 12.49 grids, 0.0098 km², coefficient of variation: 7.96%, 7.72%. 2) 785m water level group: mean: 202 grids, 0.1632 km², standard deviation: 5.13 grids, 0.0041 km², coefficient of variation: 2.54%, 2.51%. 3) 825m water level group: mean: 282.33 grids, 0.2282 km², standard deviation: 13.65 grids, 0.0110 km², coefficient of variation: 4.83%, 4.82%.

[0088] Analysis revealed that rising water levels significantly increased suitable habitat indicators (P<0.01, hypothesis testing). The group with the medium water level (785m) showed the least variation, indicating that the impact of flow rate changes was relatively stable at this water level. The group with the high water level (825m) had the largest absolute value but a moderate coefficient of variation.

[0089] like Figure 8 As shown, under the same water level conditions for water storage and release at the hydropower station, the trends in the number and area of ​​suitable grids are inconsistent with the increase in flow rate. At a water level of 765m, the increase in flow rate leads to an increase in the number of suitable grids (from 144→168); at a water level of 785m, the increase in flow rate actually causes the number of suitable grids to first decrease and then increase (207→197→202); at a water level of 825m, the increase in flow rate continuously promotes an increase in the number of suitable grids (270→280→297).

[0090] The interaction between flow rate and water level is significant in influencing suitable habitat formation; under high water levels, increased flow rate is more conducive to the formation of suitable habitats. An optimal flow rate may exist under medium water levels (785m), while excessively high or low flow rates are detrimental to the maintenance of suitable habitats.

[0091] Statistical analysis of the data grouped by flow rate yielded the following results: 31.6 m³ / s flow rate group (3 combinations): mean: 207 samples, 0.1673 km², standard deviation: 63.00 samples, 0.0509 km²; 70 m³ / s flow rate group: mean: 212 samples, 0.1713 km², standard deviation: 60.21 samples, 0.0486 km²; 118 m³ / s flow rate group: mean: 222.33 samples, 0.1797 km², standard deviation: 66.69 samples, 0.0538 km². The results indicate that increased flow rate generally promotes the formation of suitable habitats, but the impact is significantly smaller than that of water level. The large intra-group variability suggests that the flow rate effect is constrained to some extent by water level conditions.

[0092] This invention reveals, through model analysis, the changes in the habitat of the round-mouthed copper fish in the lower reaches of the Jinsha River under the influence of hydropower development. For example... Figure 5As shown, in the temporal dimension, water level changes caused by hydropower station water storage and release are the dominant driving factor for habitat evolution (explaining approximately 93% of the variation). Under the condition of a high water level of 825m, the area of ​​suitable habitat increases significantly by 87.5% compared to the lowest water level, and this improvement effect tends to stabilize over time. Spatial distribution characteristics show that only about 0.91% of the spatial area of ​​suitable habitat continues to meet suitable conditions. The optimal hydrological combination of 825m-118m³ / s can make the area of ​​suitable habitat reach 0.24km², which is 107% higher than the worst combination. However, even under the optimal condition, its spatial proportion is still less than 1.3%, reflecting the high selectivity of target species for habitat conditions. The three water level conditions show a clear stepwise increase. Under the 825m water level, scenarios ⑦-⑨ have the largest habitat area (0.2182-0.2400km²). For every 20m increase in water level, the average habitat area increases by about 37.5%. Within the same water level group (such as scenarios ①-③ at 765m), the habitat area increases with increasing flow rate. However, an exception occurs at 785m (scenario ④ > scenario ⑤), which may be due to data errors or special hydrological conditions.

[0093] In the experimental statistics of this invention, by maintaining a high water level of about 825m and combining it with a flow rate of 118m³ / s, the suitable habitat area of ​​the round-mouthed copper fish can be maximized to 0.24km², which is 106.4% higher than the minimum conditions.

[0094] This invention focuses on the Heishui River, a tributary of the Jinsha River, and systematically reveals the changes in the physical habitat of the round-mouthed copper fish under the influence of hydropower development by coupling the MIKE21 hydrodynamic model with the HSC habitat suitability assessment method. The study found that water level changes are the dominant factor affecting habitat health. Under the simulated high water level of 825m, the suitable habitat area increased significantly by 87.5% compared to the low water level of 765m, and habitat connectivity was significantly improved. Flow regulation showed water level dependence; at the low water level of 765m, increasing the flow could increase the suitable area by 16.8%, while at the high water level of 825m, the flow effect weakened to 10%. The optimal scheduling combination of 825m-118m³ / s could generate a maximum suitable area of ​​0.2400km², an improvement of 106.4% compared to the worst-case scenario. Based on this, it is recommended to implement an ecological scheduling strategy of "high water level priority, flow coordination," focusing on maintaining the 825m base water level and coordinating with 118m³ / s flow regulation during key ecological periods. This invention not only provides a scientific basis for hydropower development and fish protection in the lower reaches of the Jinsha River, but its hydrodynamic-habitat coupling analysis method also provides a generalizable technical framework for management decisions of similar river ecosystems. Future research can further integrate multiple environmental factors and long-term monitoring data to improve the evaluation system.

[0095] Based on the findings of this study, the following recommendations can be made for the protection of the habitat of the roundmouth copper fish in water resource management by hydropower station management and river management authorities:

[0096] ①Since the impact of water level caused by the storage and release of water at hydropower stations is greater on fish than the impact of flow, priority should be given to maintaining the highest possible water level in the river section. The highest water level simulated in this experiment was 825m.

[0097] ② Regarding flow control, the best results can be obtained by appropriately increasing the flow rate to 118 m³ / s based on the high water level. The highest flow rate simulated in this experiment was 118 m³ / s.

[0098] ③ Consider establishing a reservoir scheduling scheme based on the present invention to maintain a high water level during key biological periods, such as the growth period and the breeding period. This requires combining the specific ecological needs of the round-mouthed copper fish and weighing the ecological benefits and water resource management costs of different combinations of hydrological conditions.

[0099] As can be seen from the above embodiments, the method proposed in this invention for rapidly assessing the impact of reservoir scheduling on the suitable habitat area of ​​fish in downstream rivers fully utilizes the advantages of a two-dimensional hydrodynamic model, which can flexibly set various reservoir scheduling conditions according to actual needs, and a binary classification method, which can conveniently set 1 and 0 switches to represent "suitable" and "unsuitable" habitats for fish, respectively. Through the coupling of the two, the spatial distribution of water depth and flow velocity in downstream rivers under various reservoir scheduling conditions is precisely simulated. Combined with existing empirical value ranges of "suitable" and "unsuitable" habitats for fish, image technology is used to quickly identify suitable habitats for fish and assess the impact of reservoir scheduling on the suitable habitat area of ​​fish in downstream rivers. This method overcomes the limitations of field monitoring methods, which identify suitable habitats based on the water storage and release results under the influence of a specific single reservoir scheduling, and model simulation methods, which are time-consuming, labor-intensive, and have complex processes for weighted calculation of comprehensive suitability and suitable habitat area. It rapidly assesses the ecological impact of reservoir scheduling, provides reliable results, and effectively improves decision-making efficiency.

[0100] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A method for rapidly assessing the impact of reservoir regulation on the area of ​​suitable fish habitat downstream, characterized in that, Includes the following steps: S1, Obtain natural environmental data of the river channel in the study area; S2, Select the boundary of the area to be studied, densify the boundary grid points of the area to be studied, generate a triangular grid, and perform grid smoothing. S3. Based on the latitude and longitude coordinates of the geographical location of the study area after grid smoothing, insert the measured elevation data of the river channel section, calculate the elevation values ​​of the remaining areas without elevation data, and obtain a triangular grid map covering the entire study area with elevation interpolation surface data. S4. Define the upstream and downstream boundaries, adjust the parameters, and construct a two-dimensional hydrodynamic model. S5: Collect reservoir water storage and release scheduling operation data, select various water level and flow conditions for reservoir scheduling, simulate the hydrological and hydrodynamic characteristics of downstream river channels affected by reservoir scheduling, extract water depth and velocity surface data as key environmental factors, and export grid data of simulation results. S6. Obtain the suitable range of key environmental factors for the target fish species. Use binary classification to binarize the environmental factors and determine the number of grids that meet the key environmental factor range. Combine with image recognition technology, determine the proportion of the number of grids in the total number of grids to obtain the suitable habitat area of ​​downstream river fish under various reservoir scheduling combinations.

2. The method for rapidly assessing the impact of reservoir scheduling on the suitable habitat area for downstream fishes according to claim 1, characterized in that, In S1, the natural environment data includes topographic data, flow data, and water level data.

3. The method for rapidly assessing the impact of reservoir scheduling on the area of ​​suitable habitat for downstream fishes according to claim 1, characterized in that, In S2, the area to be studied is selected using CAD drawing, and the selected area is imported into the MIKEZERO mesh processing software of the MIKE21 two-dimensional hydrodynamic model.

4. The method for rapidly assessing the impact of reservoir scheduling on the area of ​​suitable fish habitat downstream, as described in claim 1, is characterized in that... In S3, the elevation values ​​of the remaining areas without elevation data are calculated using the elevation interpolation function in MIKEZERO.

5. The method for rapidly assessing the impact of reservoir scheduling on the area of ​​suitable habitat for downstream fishes according to claim 1, characterized in that, In S4, the adjusted parameters include the order of the simulation equation, simulation time, wind speed, evaporation rate, and substrate parameters. The order of the simulation equations is low. The simulation period is 10-20 days; The wind speed, evaporation rate, and substrate parameters are set to default values.

6. The method for rapidly assessing the impact of reservoir scheduling on the area of ​​suitable fish habitat downstream, as described in claim 1, is characterized in that... In S5, the various water level conditions for reservoir water storage and release scheduling include the dead water level of hydropower station water storage, the flood control limit water level, and the normal water storage level; The various flow conditions for reservoir water storage and release scheduling include the multi-year average flow during the dry season, the multi-year average flow, and the multi-year average flow during the flood season in the downstream river section of the reservoir.

7. The method for rapidly assessing the impact of reservoir scheduling on the area of ​​suitable habitat for downstream fishes according to claim 1, characterized in that, In S6, the binarization process involves using a binary classification method to classify environmental factors as "suitable" or "unsuitable," determining the number of grids within the "suitable" range of key environmental factors, and combining image recognition technology to obtain the downstream river fish suitable habitat area under various reservoir scheduling combinations based on the total area of ​​the study area and the proportion of grids that meet the "suitable" habitat conditions for fish in the total number of grids.

8. The method for rapidly assessing the impact of reservoir scheduling on the area of ​​suitable habitat for downstream fishes according to claim 7, characterized in that, The binarization process refers to setting 1 and 0 switches to represent "suitable" and "unsuitable" habitats for fish, respectively, and performing superimposed analysis on the evaluation results of each key environmental factor. The logical multiplication rule is used, that is, the habitat is judged as "suitable" only when all factors are 1.

9. The method for rapidly assessing the impact of reservoir scheduling on the area of ​​suitable habitat for downstream fishes according to claim 1, characterized in that, In S6, the suitable habitat area for fish in the downstream river channel under various reservoir operation combinations is: ; Where N is the total number of grids fitted to the established MIKE model, n is the number of grids that meet the flow velocity and water depth conditions, S is the watershed area of ​​the studied river, and s is the area of ​​suitable habitat.

10. The method for rapidly assessing the impact of reservoir scheduling on the area of ​​suitable habitat for downstream fishes according to claim 1, characterized in that, It also includes the following steps: S7. Based on the suitable habitat area of ​​fish in the downstream river under each reservoir scheduling combination, assess the impact of reservoir scheduling on the suitable habitat area of ​​fish in the downstream river. Obtain the optimal water level-flow combination in the simulated conditions by simulating first and then comparing.

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