Method for rapid assessment of the impact of reservoir operation on the area of suitable habitat for fish downstream

Abstract

The present application relates to the technical field of computer, especially to a method for quickly evaluating the influence of reservoir regulation on the fish habitat area in the downstream. The method comprises the following steps: obtaining the natural environment data of the river channel in the area to be studied; checking out the boundary of the area to be studied, generating a triangular mesh and performing mesh smoothing processing; obtaining a triangular mesh graph with elevation interpolation surface data; constructing a two-dimensional hydrodynamic model; selecting a variety of water level and flow rate working condition combinations, simulating the hydrological and hydrodynamic characteristics of the downstream river channel, extracting water depth and flow rate surface data as key environmental factors, and exporting the mesh data of the simulation results; using binary classification method to binarize the environmental factors, determining the proportion of the number of meshes within the range of the key environmental factors in the total number of meshes, and obtaining the fish habitat area in the downstream river channel under various reservoir regulation combinations. The present application can quickly evaluate the spatial distribution of the fish habitat in the downstream river channel affected by reservoir regulation.

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, 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 the insertion of the cross-section data, the elevation values of the remaining areas without elevation data are calculated by using the elevation interpolation function in MIKE ZERO, and the interpolation processing is performed, and the grid map after interpolation is fine-tuned to realize the formation of the surface data by interpolation of the multi-elevation line data to cover the entire study area. Finally, the grid map obtained is a triangular grid map with elevation interpolation surface data Figure 3 );

[0054] S4, the grid of the study area generated by MIKE ZERO is imported into the FLOWMODEL module of the MIKE21 model, the upstream and downstream boundaries are set, the related parameters are adjusted, and the MIKE21 two-dimensional hydrodynamic model is constructed;

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

[0056] S6, taking Coreius zenianus as an example, two key factors of water depth and flow velocity are selected to study the habitat suitability. According to the literature, the suitable interval range of Coreius zenianus and its juvenile population to water depth and flow velocity is obtained, and the "suitable" range of each factor and its binary assignment are set as follows: water depth: 1.2-11.5m is assigned as 1, and the others are 0; flow velocity: 0.2-1.3m / s is assigned as 1, and the others are 0; only when both factors of a point are 1, it is determined as "suitable" habitat. The 23694 triangular grid data of each group of simulation data are exported, and the data are screened by using python code, and the screened grid space distribution is as shown in Figure 4 ;

[0057] The research object selected in this embodiment is Coreius zenianus. By referring to the literature, the Coreius zenianus and its juvenile population to water depth and flow velocity are obtained, and the results show that the most suitable habitat water depth of Coreius zenianus is 1.2-11.5m, and the most suitable habitat flow velocity is 0.2-1.3m / s. The most suitable water temperature range of Coreius zenianus juvenile habitat is 19.8-25.4℃, the most suitable water depth is 0.4-3.95m, and the most suitable flow velocity is 0.1-0.7m / s.

[0058] The embodiment can also evaluate the influence of reservoir operation on the fish habitat area of the downstream river. Specifically, it can further include step S7: evaluating the influence of reservoir operation on the fish habitat area of the downstream river according to the fish habitat area of the downstream river under each reservoir operation combination. According to the fish habitat area of the downstream river under each reservoir operation combination, the influence of reservoir operation on the fish habitat area of the downstream river is evaluated. Under the same flow condition, with the water level rising from 765 m to 825 m, the number and area of the eligible grids show a clear increasing trend. Taking the flow of 31.6 m³ / s as an example, when 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%). The influence of reservoir operation flow change on the suitable habitat is analyzed: under the same water level condition, with the increase of flow, the number and area of the suitable grids show inconsistent trends, and the influence of flow on the suitable habitat is obviously interacted with the water level. Under the condition of high water level, the increase of flow is more conducive to the formation of suitable habitat. There may be an optimal flow value under the condition of medium water level (785 m), and too high or too low flow is not conducive to the maintenance of suitable habitat. The influence of reservoir operation flow and water level combination on the suitable habitat is analyzed. By maintaining a high water level of about 825 m and combining with a flow of 118 m³ / s, the suitable habitat area of Coreius guichenoti can be maximized to 0.24 km², which is an increase of 106.4% compared with the lowest condition Figure 5 ).

[0059] Among the required data of the embodiment, the hydrological data is from the Ningnan Hydrological Station and some research papers on the Heishui River, the fish data is from the Fish Register and related fish research literature (mainly Coreius guichenoti), and the river data is from the NASA Earthdata satellite DEM image data (from the website https: / / dwtkns.com / srtm30m) and actual river measurement data. Due to the lack of data and the small influence of some parameters on the simulation, the default values in the FM model of MIKE21 are used for simulation.

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

[0061] The method of generating triangular grids is a restricted Delaunay triangulation, which is an extension of the standard Delaunay triangulation. It meets the Delaunay criterion as much as possible under the premise of maintaining the preset constraint condition. This method can ensure that important geometric features are not damaged in the discretization process and is commonly used in hydraulic modeling to handle complex boundaries and internal features. The constraint feature can ensure that all grids are within the constraint range.

[0062] After the study area is framed and gridded, the measured cross-section elevation data of Heishui River in this section is inserted into the study area according to the converted latitude and longitude coordinates, a total of 13 cross-sections. Figure 2 After inserting the cross-section data, the elevation values of the remaining areas without elevation data are calculated using the elevation interpolation function in MIKEZERO to perform interpolation processing. According to the interpolated grid map, fine-tune the multi-elevation line data to form surface data through interpolation to cover the entire study area. Finally, the resulting grid map is a triangular grid map with elevation interpolation surface data. Figure 3

[0063] In the pre-test simulation, it was found that the simulation length reached about 10 days, and each flow state parameter reached stability. After that, the change was small with the increase of simulation days. Therefore, the total length of simulation was 15 days, and the data recording step was 1 day. After the simulation ended, the data of the 15th day was extracted for subsequent processing and calculation. The calculated data included water surface elevation, absolute water depth, total water depth, real-time flow velocity in the meridian direction, real-time flow velocity in the latitude direction, real-time flow velocity value, and real-time flow direction. The key data needed to extract and calculate were real-time flow velocity value and total water depth for subsequent HSC analysis. Finally, nine different hydrological simulation results were simulated by arranging and combining three water conditions and three flow conditions, and 23694 grid data of each group of nine results were exported for subsequent calculation.

[0064] The grid of the study area generated by MIKEZERO was imported into the FLOWMODEL software in MIKE21, and the upstream and downstream were set and the related parameters were adjusted. Finally, according to the selected water and electricity storage and release parameters in the literature, the water level of the river section was simulated by the operation of the hydropower station from low to high as 765m, 785m, 825m; the river flow condition parameters were selected from low to high as 31.6m³ / s, 70m³ / s, 118m³ / s to simulate the river flow in flood season and non-flood season. Among them, 765m is the dead water level of the hydropower station, 785m is the flood control limit water level of the hydropower station, and 825m is the normal water storage level of the hydropower station; 31.6m³ / s is the average annual runoff in dry season, 70m³ / s is the average annual runoff, and 118m³ / s is the average annual runoff in 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 results of suitable habitat area under different reservoir operation conditions

[0073]

[0074] Through the analysis of the simulation data of 9, the overall characteristics of the data are as follows: among the total of 23694 triangular grids, the number of grids meeting the conditions of water depth 1.2-11.5m and flow velocity 0.2-1.3m / s ranges from 144 (765m / 31.6m³ / s) to 297 (825m / 118m³ / s), accounting for 0.6077%-1.2535% of the total number of grids. The total area of suitable habitat area grids under the conditions ranges from 0.1163km² to 0.2400km², indicating that there are significant differences in physical space under different hydrological conditions.

[0075] The 9 sets of data, each with 23694 triangular grid data, were exported and screened using python code. As mentioned earlier, the screening criteria are grid data with water depth 1.2-11.5m and flow velocity 0.2-1.3m / s. The screening results are shown in Table 1, and the spatial distribution of the screened grids is shown in Figure 4 .

[0076] Among the simulated 9 combinations, the number of suitable grids shows significant differences. The maximum is 297 (825m water level-118m³ / s flow combination), the minimum is 144 (765m water level-31.6m³ / s flow combination), and the range is 153, indicating a difference of 106.25% between the optimal and the worst conditions.

[0077] The suitable area index also shows large fluctuations, with the maximum area being 0.2400km² (825m-118m³ / s) and the minimum area being 0.1163km² (765m-31.6m³ / s), with an area difference of 0.1237km². Since the total area of the study area is fixed, the difference in suitable area is the same as the number of grids, both being 106.25%.

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

[0079] The change range caused by water level change (up to 87.5%) is significantly greater than the change range caused by flow change (up to about 20%), indicating that within the parameter range of the application, water level is the dominant factor affecting the distribution of suitable habitats.

[0080] Average analysis: average suitable grid number: 215.11, average suitable area: 0.1736 km², average proportion: 0.9138%.

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

[0082] The comparison of mean and median shows that the data distribution has a right-skewed characteristic, indicating that some combinations have significantly higher values than the average.

[0083] The variance and standard deviation of each index are calculated as follows: variance of suitable grid number: 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: grid number CV = 26.41%, area CV = 26.38%, proportion CV = 25.58%, these indicators show that the data has a moderate degree of variation, and the differences between different hydrological combinations are worth attention.

[0085] Under the same flow conditions, with the water level rising from 765m to 825m, the number and area of suitable grids both show a significant increasing trend. For example, at a flow of 31.6 m³ / s, 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%) as the water level rises from 765m to 825m.

[0086] The suitable habitat indicators under the high water level (825m) of the hydropower station are significantly better than those under the medium and low water levels, indicating that higher water levels are more conducive to forming suitable habitat environments with water depth and flow rate. This phenomenon may be related to the fact that higher water levels cause more areas to enter the suitable water depth range.

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

[0088] Analysis found that the increase of water level significantly increased the suitable habitat index (P<0.01, hypothesis test), the minimum variation in the medium water level (785m) group, indicating that the flow change has a relatively stable effect at this water level, and the absolute value is the largest in the high water level (825m) group, but the coefficient of variation is moderate.

[0089] As shown in Figure 8 Under the same water level of the hydropower station, with the increase of flow, the change trend of the number and area of suitable grids is inconsistent. At 765m water level, the increase of flow leads to the increase of suitable grid number (from 144 to 168); at 785m water level, the increase of flow leads to the decrease and then the increase of suitable grid number (207 to 197 to 202); at 825m water level, the increase of flow continuously promotes the increase of suitable grid number (270 to 280 to 297).

[0090] The interaction between flow and water level on suitable habitat is obvious, and the increase of flow is more conducive to the formation of suitable habitat under high water level. There may be an optimal flow value under medium water level (785m), and too high or too low flow is not conducive to the maintenance of suitable habitat.

[0091] Statistical analysis of the data grouped by flow can be obtained: 31.6m³ / s flow group (3 combinations) mean: 207, 0.1673km², standard deviation: 63.00, 0.0509km². 70m³ / s flow group mean: 212, 0.1713km², standard deviation: 60.21, 0.0486km². 118m³ / s flow group mean: 222.33, 0.1797km², standard deviation: 66.69, 0.0538km². The results show that the increase of flow promotes the formation of suitable habitat, but the influence is significantly smaller than that of water level factor. The variation within the group is large, indicating that the flow effect is restricted by water level condition to a certain extent.

[0092] The present application reveals the change of habitat of Coreius guichenoti in the lower reaches of Jinsha River under the influence of hydropower development through model analysis. As shown in Figure 5The results showed that the water level change caused by the reservoir storage and release of the hydropower station was the dominant driving factor of habitat evolution (explained about 93% of the variation) in the time dimension. The suitable habitat area under the 825m high water level condition increased significantly by 87.5% compared with the lowest water level, and this improvement effect tended to be stable over time. The spatial distribution characteristics showed that only about 0.91% of the spatial area continuously met the suitable conditions, and the optimal hydrological combination of 825m-118m³ / s could make the suitable habitat area reach 0.24km², which increased by 107% compared with the worst combination. However, even under the optimal conditions, the spatial proportion was still less than 1.3%, which reflected the high selectivity of the target species to the habitat conditions. The three water level conditions showed a clear ladder-like increase, and the habitat area under the 825m water level condition (scenario ⑦-⑨) was the largest (0.2182-0.2400km²). With the increase of 20m of water level, the habitat area increased by an average of about 37.5%. Within the same water level group (such as 765m scenario ①-③), the habitat area showed an increasing trend with the increase of flow. However, there was an exception in the 785m group (scenario ④> scenario ⑤), which might be caused by data errors or special hydrological conditions.

[0093] In the experimental statistics of the present application, by maintaining a high water level of about 825m and combining with the flow regulation of 118m³ / s, the suitable habitat area of Coreius guichenoti can be maximized to 0.24km², which is increased by 106.4% compared with the lowest condition.

[0094] The present application takes the Heishui River, a tributary of the lower reaches of the Jinsha River, as the research object, and systematically reveals the changes of the physical habitat of Coreius guichenoti under the influence of hydropower development by coupling the MIKE21 hydrodynamic model with the HSC habitat suitability evaluation method. The research found that water level change is the dominant factor affecting habitat health. In the experiment, the suitable habitat area under the 825m high water level condition increased significantly by 87.5% compared with the 765m low water level, and the habitat connectivity improved significantly. Flow regulation showed water level dependence. When the water level was low (765m), the increase of flow could increase the suitable area by 16.8%, while when the water level was high (825m), the flow effect was weakened to 10%. The optimal combination of 825m-118m³ / s could produce a maximum suitable area of 0.2400km², which was increased by 106.4% compared with the worst scenario. Based on this, it is recommended to implement the ecological scheduling strategy of "high water level priority and flow coordination", focusing on maintaining a basic water level of 825m and coordinating the flow regulation of 118m³ / s in the key ecological period. The present application not only provides a scientific basis for fish protection in the lower reaches of the Jinsha River, but also provides a generalizable technical framework for the management decision of similar river ecosystems through the hydrodynamic-habitat coupling analysis method. Future research can further integrate multiple environmental factors and long-term monitoring data to perfect the evaluation system.

[0095] According to the results of the present application, the following suggestions can be made for the habitat protection of Coreius guichenoti by the management parties of hydropower stations and river management parties:

[0096] ①The water level influence caused by the water storage and release of the hydropower station is higher than the flow influence, and the water level of the river section should be maintained as high as possible. In this experiment, the highest water level obtained by simulation is 825 m.

[0097] ②In terms of flow control, the flow should be appropriately increased to 118 m³ / s based on the high water level to obtain the best effect. In this experiment, the highest flow obtained by simulation is 118 m³ / s.

[0098] ③The reservoir scheduling scheme based on the present application is considered to be established, and high water levels are maintained during critical biological periods, such as the growth period and the breeding period. The specific ecological needs of the Coreius guichenoti need to be considered, and the ecological benefits and water resource management costs of different hydrological condition combinations need to be weighed.

[0099] As can be seen from the above examples, the method for quickly evaluating the influence of reservoir scheduling on the suitable habitat area of fish in the downstream river channel proposed by the present application fully utilizes the two-dimensional hydrodynamic model to flexibly set various reservoir scheduling conditions according to actual needs, and the binary classification method can conveniently set 1 and 0 switches to represent the advantages of fish "suitable" and "unsuitable" habitats. Through the coupling of the two, the spatial distribution of water depth and flow velocity in the downstream river channel under various reservoir scheduling conditions is finely simulated, and combined with the existing experience value interval of fish "suitable" and "unsuitable" habitats, the image technology is used to quickly identify the suitable habitat of fish, evaluate the influence of reservoir scheduling on the suitable habitat area of fish in the downstream river channel, overcome the limitations of the field monitoring method for identifying suitable habitats under the influence of a single reservoir scheduling, and the time-consuming and laborious process of the model simulation method for weighted calculation of the comprehensive suitability and suitable habitat area. The ecological impact of reservoir scheduling is quickly evaluated, the results are reliable, and the decision-making effectiveness is effectively improved.

[0100] The above is only a preferred embodiment of the present application, and does not limit the present application in any form. Any simple modification, equivalent change and modification of the above embodiment according to the technical essence of the present application still belongs to the scope of the technical scheme of the present application.

Claims

1. A method for rapidly assessing the impact of reservoir operation on the area of suitable habitat for fish downstream, characterized in that, The method comprises the following steps: S1, obtaining natural environment data of a river channel in a to-be-studied area; S2, checking out the boundary of the to-be-studied area, performing intensive processing on the boundary grid points of the to-be-studied area, generating a triangular mesh and performing mesh smoothing processing; S3, inserting measured river cross-section elevation data according to the geographical position longitude and latitude coordinates of the to-be-studied area after the mesh smoothing processing, calculating the elevation values of the remaining areas without elevation data, and obtaining a triangular mesh graph covering the entire to-be-studied area and having elevation interpolation surface data; S4, importing the to-be-studied area mesh generated by MIKEZERO into the FLOWMODEL module of the MIKE21 model, setting the upstream and downstream boundaries, adjusting related parameters, constructing a MIKE21 two-dimensional hydrodynamic model, and the adjusted parameters include simulation equation order, simulation time, wind speed, evaporation amount and bottom material parameters; S5, collecting reservoir storage and release scheduling operation data, selecting various water level and flow conditions of reservoir scheduling, simulating the hydrological and hydrodynamic characteristics of the downstream river channel under the influence of reservoir scheduling, extracting water depth and flow velocity surface data as key environmental factors, and exporting the grid data of the simulation results; S6, obtaining the suitable interval range of the target fish to the key environmental factors, performing binaryzation processing on the environmental factors by using a binary classification method, determining the number of grids in the interval range of the key environmental factors, combining an image recognition technology, calculating the proportion of the number of grids in the total number of grids, and obtaining the fish suitable habitat area of the downstream river channel under various reservoir scheduling combination conditions.

2. The method of claim 1, wherein the natural environment data in S1 comprises terrain data, flow data and water level data.

3. The method of claim 1, wherein in S2, the to-be-studied area is framed by using CAD drawing, and the to-be-studied area with the checked boundary is imported into the grid processing software of MIKEZERO of the MIKE21 two-dimensional hydrodynamic model.

4. The method of claim 1, wherein in S3, the elevation values of the remaining areas without elevation data are calculated by using the elevation interpolation function in MIKEZERO.

5. The method of claim 1, wherein the simulation equation order is a low order; the simulation time is 10-20 days; the wind speed, evaporation amount and bottom material parameters are selected as default values.

6. The method of claim 1, wherein in S5, the various water level conditions of reservoir storage and release scheduling include the dead water level, the flood control limit water level and the normal water level of the reservoir storage; the various flow conditions of reservoir storage and release scheduling 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 downstream river section of the reservoir. ​ ​ ​ ​ ​ 7. The method of claim 1, wherein, In S6, the binarization processing is a binary classification method for processing the environmental factors as "suitable" and "unsuitable", determining the number of grids in the "suitable" range of the key environmental factors, and combining the image recognition technology to obtain the fish suitable habitat area in the downstream river under various reservoir operation conditions according to the proportion of the total area of the study area and the grids meeting the fish "suitable" habitat conditions in the total number of grids.

8. The method of claim 7, wherein, The binarization processing refers to setting 1 and 0 switches to represent the fish "suitable" and "unsuitable" habitats, respectively, superimposing and analyzing the evaluation results of each key environmental factor, and using the logical multiplication rule, i.e. all factors are 1, the habitat is determined as "suitable".

9. The method of claim 1, wherein, In S6, the fish habitat area in the downstream river channel under the various reservoir dispatching combinations is: ; N is the total number of grids fitted by the established MIKE21 two-dimensional hydrodynamic 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.

10. The method for rapidly assessing the impact of reservoir operations on downstream fish habitat area suitability according to claim 1, wherein, Further comprising the following steps: S7, according to the fish suitable habitat area in the downstream river under various reservoir operation conditions, evaluating the influence of reservoir operation on the fish suitable habitat area in the downstream river, and obtaining the optimal water level-flow combination in the simulated conditions by the method of simulation and comparison.

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