A method for identifying a protection threshold of aquatic organisms based on a four-water coupling model

Abstract

The application introduces a kind of aquatic organism protection threshold identification method based on four water coupling models, comprising: S1, constructing a watershed hydrological model, then inputting rainfall data, obtaining runoff output data;S2, constructing a river water power and water quality model, then inputting water quantity data, water level data and water quality concentration data, obtaining water quantity output data, flow velocity output data, water level output data, flow direction output data and water quality concentration output data;S3, determine the aquatic organism sampling point, and obtain the hydrology, hydrodynamic, water quality data of the corresponding aquatic organism sampling point through the watershed hydrological model and the river water power and water quality model;S4, extract the hydrology, hydrodynamic, water quality data matched with the aquatic organism sampling point from the model, construct a multi-factor coupling model based on random forest, and identify the aquatic organism protection threshold. Through the above design, the technical effect of solving the data matching in the aquatic organism protection threshold identification process is realized.

Description

Technical Field

[0001] This invention belongs to the field of aquatic ecology, specifically relating to a method for identifying aquatic organism protection thresholds based on a four-water coupling model. Background Technology

[0002] The four-process coupling generally refers to the coupling of hydrology, hydrodynamics, water quality, and aquatic life, basically covering the main processes of aquatic ecosystem simulation. Current coupling models primarily consider the first three processes (hydrology, hydrodynamics, and water quality) or the latter three (hydrodynamics, water quality, and aquatic life). Regardless of the approach, this leads to a gap in the aquatic ecosystem simulation process. This gap makes data acquisition difficult, especially hydrological data, which is often hard to match with aquatic biological data. This drawback has several causes, primarily a lack of basic data sufficient for model construction, or limitations in modeling techniques that render them unsuitable. To better match aquatic biological data, multi-process models are needed to obtain relevant data for subsequent analysis.

[0003] For example, Chinese patent CN115034425A discloses a method and apparatus for simulating and scheduling the dynamics of a composite community coupled with water quantity, water quality, and aquatic organisms. The method includes: Step S1, determining the research scenario, collecting measured data from the research area, and identifying the influencing factors and decision variables of population dynamics; Step S2, considering the interactions between multiple populations, the effects of water quantity and water quality, population immigration and emigration, and other factors, constructing a composite community dynamic model coupled with water quantity, water quality, and aquatic organisms; Step S3, calculating the niche width, environmental optimum, and competition coefficient parameters in the composite community dynamic model based on quantile regression and niche theory; Step S4, simulating the co-evolution process of multiple population systems in the composite community and determining the degree of influence of water quantity and water quality on the dynamics of the composite community. However, the model design lacks a physical mechanism and mainly relies on establishing response relationships between measured data.

[0004] Chinese patent CN109342675A discloses a method for determining the surface water quality safety threshold for the protection of aquatic organisms by antimony, comprising: step S1, collecting aquatic organism toxicity data of antimony; step S2, deriving the water quality benchmark value for the protection of aquatic organisms by antimony; and step S3, determining the surface water quality safety threshold for the protection of aquatic organisms by antimony. It also provides a method for water quality safety assessment using the surface water quality safety threshold for the protection of aquatic organisms by antimony. This method primarily uses the logistic distribution model to obtain the water quality benchmark value for the protection of aquatic organisms by antimony. However, it mainly considers the impact of one indicator on organisms, ignoring the comprehensive impact of other indicators on that indicator or aquatic organisms; that is, other factors are excluded during the factor screening process.

[0005] Because existing aquatic ecosystem simulations lack multi-process simulation technology and there is a problem of difficulty in obtaining parameters during the identification of aquatic organism protection thresholds, there is an urgent need to design a new method for identifying aquatic organism protection thresholds in order to solve the above problems. Summary of the Invention

[0006] To address the lack of multi-process simulation technology in existing aquatic ecosystem simulations and the difficulty in obtaining parameters during the identification of aquatic organism protection thresholds, this application designs an aquatic organism protection threshold identification method based on a four-water coupling model. By using hydrological and hydrodynamic water quality models to obtain data from corresponding aquatic organism sampling points, the protection threshold is calculated, thereby achieving the technical effect of solving the data matching problem in the identification of aquatic organism protection thresholds.

[0007] A method for identifying aquatic organism conservation thresholds based on a four-water coupling model includes the following steps:

[0008] Step S1: Construct a watershed hydrological model based on the TVGM model, then input rainfall data and obtain runoff output data;

[0009] Step S2: Construct a river hydrodynamic and water quality model based on the runoff data output by the watershed hydrological model and the measured water quality data. Then, input water volume data, water level data and water quality concentration data to obtain water volume output data, flow velocity output data, water level output data, flow direction output data and water quality concentration output data.

[0010] Step S3: Determine aquatic organism sampling points and obtain the corresponding hydrological, hydrodynamic, and water quality data of the aquatic organism sampling points through the watershed hydrological model and the river hydrodynamic and water quality model;

[0011] Step S4: Based on hydrological, hydrodynamic, and water quality data, construct a multi-factor coupling model based on random forest to identify aquatic life protection thresholds.

[0012] Preferably, the watershed hydrological model construction method in step S1 includes the following steps:

[0013] Step S101: First, collect watershed elevation DEM data, rain gauge data, rainfall data, watershed hydrological station data, and flow data;

[0014] Step S102: Use DEM data to delineate the watershed area in ArcGIS software and collect watershed information, including watershed name, watershed area, latitude and longitude, and memory length; finally, enter the information into a txt document.

[0015] Step S103: Divide the acquired rainfall and flow data into three parts, one part of which is used for calibration, one part for verification, and the last part for simulation; and save the processed data as a txt document.

[0016] Step S104: Input the data processed in step S103 into the TVGM model to complete the construction of the watershed hydrological model.

[0017] Preferably, the method for constructing the river hydrodynamic and water quality model in step S2 includes the following steps:

[0018] Step S201: Obtain data on river boundary, river topography, flow rate, water level, water quality concentration, and water temperature;

[0019] Step S202: Import the acquired high-resolution satellite image into ArcGIS software. Based on the river channel extent in the satellite image, use the built-in editing tools of ArcGIS software to outline the river channel to obtain the river channel surface layer, i.e., the river channel boundary. Import the drawn river channel boundary into GlobalMapper software and convert it into a format that Delft3D software can recognize. Divide the river channel into a grid in Delft3D and export it as a .grid file. This will give you the grid file needed to construct the river channel hydrodynamic and water quality model.

[0020] Step S203: Import the generated mesh file into the EFDC model and obtain the coordinates of the four corners of the mesh; take the average value of the X coordinates of the four corners and the average value of the Y coordinates of the four corners respectively, and calculate the coordinates of the center point of the mesh; according to the upstream and downstream order of the mesh, based on a small amount of measured cross-sectional data and the average slope of the terrain, calculate the elevation of the center point of each mesh; input the calculated mesh points into the EFDC model to obtain the river topography required by the model.

[0021] Step S204: Input the acquired water quality concentration, water level data, processed river topography, and flow rate obtained from the TVGM model simulation into the EFDC model to complete the construction of the river hydrodynamic water quality model.

[0022] Preferably, step S3 includes the following steps:

[0023] Step S301: Based on the measured location information of aquatic organism sampling points, place the aquatic organism sampling points at the corresponding midpoints of the river grid.

[0024] Step S302: Extract data from the model; After the river hydrodynamic and water quality model is completed, obtain the water quantity and water quality data of each grid based on the model simulation, and export it directly from the grid of the EFDC model.

[0025] Preferably, step S4 includes the following steps:

[0026] Step S401: The data extracted in steps S1-S3 above are integrated according to location and indicator type;

[0027] Step S402: Using the above data, establish a multi-factor coupling model based on random forest and calculate the indicator thresholds based on the IBI index.

[0028] The advantages and effects of this application are as follows:

[0029] This application presents a method for identifying aquatic organism protection thresholds based on a four-water coupling model. By using hydrological and hydrodynamic water quality models to obtain data from corresponding aquatic organism sampling points, and then calculating protection thresholds, the method achieves matching between aquatic ecological monitoring data and hydrological, hydrodynamic, and water quality element data. Ultimately, it realizes coupled modeling of multiple processes and multiple elements, identifies protection thresholds for aquatic organisms, and comprehensively reflects the complex impact of multiple indicators on aquatic organisms.

[0030] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the preferred embodiments of this application are described in detail below with reference to the accompanying drawings.

[0031] The above and other objects, advantages and features of this application will become more apparent to those skilled in the art from the following detailed description of specific embodiments in conjunction with the accompanying drawings. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In all drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0033] Figure 1 A flowchart of a method for identifying aquatic organism protection thresholds based on a four-water coupling model provided in this application;

[0034] Figure 2 In step S102 provided for this application, the information is entered into a status diagram of a txt document;

[0035] Figure 3 The hydrological model diagram of the TVGM watershed provided in this application;

[0036] Figure 4 A conceptual diagram of a simplified watershed hydrological model provided for this application;

[0037] Figure 5 The image provided in this application shows the effect of inputting the processed terrain, TVGM simulated flow rate, obtained water quality concentration and water level data into the EFDC model;

[0038] Figure 6 A rendering of the EFDC river hydrodynamic and water quality model provided for this application;

[0039] Figure 7 Data location map directly exported from the mesh of the EFDC model provided in this application

[0040] Figure 8 A graph showing the results of indicator threshold identification based on the IBI index provided for this application;

[0041] Figure 9 The watershed hydrological model simulation results provided in this application are shown in the figure.

[0042] Figure 10 A diagram showing the calibration and verification of flow rate and some water quality indicators provided for this application;

[0043] Figure 11 A flowchart for identifying key indicator thresholds for the protection of the biological integrity of large benthic organisms provided in this application. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. In the following description, specific details such as specific configurations and components are provided merely to help fully understand the embodiments of this application. Therefore, those skilled in the art should understand that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. In addition, for clarity and brevity, descriptions of known functions and structures are omitted in the embodiments.

[0045] It should be understood that the phrase "an embodiment" or "this embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "an embodiment" or "this embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0046] Furthermore, reference numerals and / or letters may be repeated in different examples within this application. Such repetition is for the purpose of simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or settings discussed.

[0047] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" in this article describes another type of relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " in this article generally indicates that the related objects before and after it are in an "or" relationship.

[0048] In this article, the term "at least one" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, "at least one of A and B" can mean: A exists alone, A and B exist simultaneously, or B exists alone.

[0049] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion.

[0050] Example 1

[0051] This embodiment mainly introduces the design of an aquatic organism protection threshold identification method based on a four-water coupling model, including the following steps:

[0052] Step S1: Construct a watershed hydrological model based on the TVGM model, then input rainfall data and obtain runoff output data; the watershed hydrological model construction method in step S1 includes the following steps:

[0053] Step S101: First, collect watershed elevation DEM data, rain gauge data, rainfall data (daily rainfall), watershed hydrological station data, and flow data (daily-scale flow). DEM data can be obtained from open-source websites on the Internet, and rainfall and flow data can be obtained from hydrological yearbooks.

[0054] Step S102: Use DEM data to delineate the watershed extent (including the entire watershed and sub-units) in ArcGIS software, and collect watershed information, including watershed name, watershed area, latitude and longitude, and memory length (the ratio of the watershed area to its perimeter); finally, input this information into a txt document, such as... Figure 2 As shown:

[0055] Step S103: Divide the acquired rainfall and flow data into three parts. One part of the data is used for calibration, another part is used for verification, and the last part is used for simulation. Save the processed data as a txt document. For example, if there is rainfall and flow data for ten years from 2013 to 2022, the data from 2013 to 2020 can be used to calibrate the model parameters, and then the data from 2021 to 2022 can be used to verify the model parameters. After the parameter calibration and verification are completed, the third part of the data, that is, the rainfall data of future years, can be used to simulate the hydrological runoff data of future years.

[0056] Step S104: Input the data processed in step S103 into the TVGM model (watershed nonlinear rainfall-runoff model), such as... Figure 3 As shown, the construction of the watershed hydrological model is now complete.

[0057] For information on obtaining watershed hydrological runoff data based on DTVGM, please refer to [link / reference needed]. Figure 4 , Figure 4 This is a conceptual diagram of a simplified watershed hydrological model. The left diagram shows the defined watershed area and the distribution of waterways and hydrological stations within the watershed. Based on the watershed hydrological model, by inputting rainfall data, the flow data for each cross-section can be obtained, which is the time and runoff graph on the right. First, a hydrological model of the entire watershed is established to simulate Q (Q represents the total flow at the watershed outlet cross-section). Then, the flow of sub-units (Q0~Q4) is simulated, thus obtaining the flow process (Qi) of the main stream and each tributary.

[0058] Step S2: Construct a river hydrodynamic and water quality model based on the runoff data output from the watershed hydrological model and the measured water quality data. Then, input water volume data, water level data, and water quality concentration data to obtain water volume output data, flow velocity output data, water level output data, flow direction output data, and water quality concentration output data. The method for constructing the river hydrodynamic and water quality model includes the following steps:

[0059] Step S201: The data to be collected includes the river boundary (shp, which can be drawn from the Ovi Map), river topography (xyz, which can be obtained by secondary processing based on DEM data), flow rate (obtained from hydrological yearbooks or TVGM), water level (hydrological yearbook), water quality concentration (COD, ammonia nitrogen, TP, nitrate, etc., which can be obtained from the National Surface Water Quality Automatic Monitoring Real-time Data Release System), and water temperature (hydrological yearbook).

[0060] Step S202: Import the obtained high-resolution satellite image into ArcGIS software. Then, using ArcGIS's built-in editing tools, outline the river channel area according to the satellite image to obtain the river channel surface layer, i.e., the river channel boundary. Import the drawn river channel boundary into GlobalMapper and convert it into a format that Delft3D can recognize. Divide the river channel into a mesh in Delft3D and export it as a .grid file. This will give you the mesh file needed for model construction.

[0061] Step S203: Import the generated grid into EFDC and obtain the coordinates of the four corners of the grid; calculate the coordinates of the grid center point by taking the average of the four X values ​​and the average of the four Y values ​​of the four corners of the grid; calculate the elevation of the center point of each grid according to the upstream and downstream order of the grid, based on a small amount of measured cross-sectional data and the average slope of the terrain; input the calculated grid points into the EFDC model to obtain the river topography required by the model.

[0062] Step S204: Input the acquired water quality concentration, water level data, processed river channel topography, and flow rate obtained from the TVGM model simulation into the EFDC model, such as... Figure 5 As shown, Qi represents the upstream and tributary flow rates, i.e., the flow rates simulated by the TVGM model, C represents the concentration values ​​of different indicators in the main stream and tributaries, and WL represents the downstream water level; thus, the hydrodynamic and water quality model of the river channel can be constructed.

[0063] Step S205, as follows Figure 6 As shown, the above process completes the construction of the EFDC river hydrodynamic and water quality model. By comparing measured and simulated data, the model is calibrated and verified. Based on the calibrated and verified model, data such as flow rate, water level, water quality, and flow velocity can be obtained for any grid and any cross-section.

[0064] Step S3: Identify aquatic organism sampling points and obtain the corresponding hydrological, hydrodynamic, and water quality data for these points using the watershed hydrological model and river hydrodynamic and water quality model. This step primarily uses the established hydrological-hydrodynamic water quality model to extract data from the corresponding sampling points. These points refer to aquatic organism sampling points because, when sampling aquatic organisms, it's not always possible to collect flow rate, velocity, water depth, and some water quality data at the corresponding points. However, by constructing the hydrodynamic and water quality model, these data at the corresponding time points can be directly simulated. Therefore, the steps are as follows:

[0065] Step S301: Determine aquatic organism sampling points. This process mainly involves assigning aquatic organism sampling points to corresponding grids based on the measured location information. This allows for a clear understanding of which time period and which grid in the model should be used to extract various types of data.

[0066] Step S302: Extract data from the model. After the EFDC model is built, water quantity and quality data for each grid can be obtained based on model simulation, and can be directly exported from the grid of the EFDC model. For example... Figure 7 As shown, the model constructed using hydrological and water quality data from points H1, H2, W1, and W2 can calculate hydrological and water quality data from aquatic biological sampling points S1, S2, S3, and S4. This includes flow rate, water level, water depth, flow velocity, water temperature, COD, ammonia nitrogen, DO, total phosphorus, and nitrate.

[0067] Step S4: Extract hydrological, hydrodynamic, and water quality elements matching the aquatic organism sampling points from the model, construct a multi-element coupled model based on random forest, and identify aquatic organism protection thresholds. This step mainly uses the Randomforest analysis package in R language. This package can be used to directly build a random forest model between multiple elements, identify the contribution of each element to aquatic biodiversity, and then determine the protection thresholds. Step S4 includes the following steps:

[0068] Step S401: The data extracted in steps S1-S3 above are integrated according to the sampling points and indicator types; the format of the organized data is as follows. Wherein S1~Sn are the sampling point numbers of aquatic organisms, F1~Fn are various indicators extracted by the model and other indicators not extracted by the model, the IBI index is the aquatic biodiversity index, and the random forest model is used to establish the relationship between F1~Fn and the IBI index;

[0069] Step S402: Using the above data, establish a multi-factor coupling model based on random forest, and calculate the indicator thresholds based on the IBI index; the identification results are as follows. Figure 8 As shown, ABCD represent the aquatic life integrity levels based on the IBI index. The higher the level, the stronger the aquatic life integrity. If D is the highest level, then the aquatic life integrity is stronger when index F1 is less than a and index F3 is less than c. Therefore, the threshold values ​​for protecting this integrity are a and c.

[0070] This application presents a method for identifying aquatic organism protection thresholds based on a four-water coupling model. By using hydrological and hydrodynamic water quality models to obtain data from corresponding aquatic organism sampling points, and then calculating protection thresholds, the method achieves matching between aquatic ecological monitoring data and hydrological, hydrodynamic, and water quality element data. Ultimately, it realizes coupled modeling of multiple processes and multiple elements, identifies protection thresholds for aquatic organisms, and comprehensively reflects the complex impact of multiple indicators on aquatic organisms.

[0071] Example 2

[0072] Based on the above embodiment 1, this embodiment mainly introduces the aquatic organism protection threshold identification method based on the four-water coupling model designed in this application, which was explored in a certain watershed and the protection threshold of benthic organisms in the watershed was analyzed.

[0073] 1. Watershed Hydrological Model Construction: The calibration and verification results of the watershed hydrological model constructed in step S1 are as follows: Figure 9 As shown.

[0074] 2. Construction of River Hydrodynamic and Water Quality Model: Using the flow data output in step S1, and the collected river water level and water quality data, the hydrodynamic and water quality model constructed in step S2 is calibrated and verified as follows. Figure 10 As shown.

[0075] 3. Data Extraction: Based on step S3, the data corresponding to the aquatic organism sampling points extracted based on the model and other source data are summarized in the table below. NO3, NH4, COD, WT (water temperature), SD (transparency), and Q (flow rate) were obtained through the EFDC model, while AT (air temperature) and RF (rainfall) were obtained from meteorological websites. IBI, the macrobenthic integrity index, was obtained through survey monitoring.

[0076] 4. Construction and Threshold Identification of Random Forest Model Based on Aquatic Organism Integrity: Based on the random forest model established in step 4, threshold indicators for the protection of macrobenthic organism integrity are identified, such as... Figure 11 As shown, a higher aquatic organism integrity index is more beneficial for aquatic organism conservation. Therefore, based on this model, it can be found that the macrobenthic organism integrity index is highest when the air temperature is below 14.78℃ and the ammonia nitrogen concentration is below 0.586 mg / L. In other words, in this watershed, to strengthen the protection of macrobenthic integrity, in addition to the influence of natural air temperature, the ammonia nitrogen concentration needs to be reduced to below 0.586 mg / L. Therefore, AT = 14.788℃ and NH4 = 0.586 mg / L are the protection thresholds for macrobenthic integrity in this watershed.

[0077] The above description is merely a preferred embodiment of the present invention and does not limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any changes, modifications, substitutions, integrations, and parameter alterations to these embodiments within the spirit and principles of the present invention, achieved through conventional substitutions or by achieving the same function without departing from the principles and spirit of the present invention, fall within the scope of protection of the present invention.

Claims

1. A method for identifying a protection threshold of aquatic organisms based on a four-water coupling model, characterized in that, Comprise the following steps: Step S1, based on the TVGM model, a watershed hydrological model is constructed, and then rainfall data is input to obtain runoff output data; Step S2, based on the runoff data output by the watershed hydrological model and the measured water quality data, a river water dynamic water quality model is constructed, and then water quantity data, water level data and water quality concentration data are input to obtain water quantity output data, flow velocity output data, water level output data, flow direction output data and water quality concentration output data; Step S3, determine the water sampling point of aquatic organism, and obtain the hydrology, hydrodynamics and water quality data of the corresponding water sampling point of aquatic organism through the watershed hydrological model and the river water dynamic water quality model; Step S4, according to the hydrology, hydrodynamics and water quality data, a multi-factor coupling model based on random forest is constructed to identify the protection threshold of aquatic organism; The method for constructing the watershed hydrological model in step S1 comprises the following steps: Step S101, first, collect the DEM data of the watershed elevation, rainfall station, rainfall data, watershed hydrological station and flow data; Step S102, divide the watershed range in the Arcgis software using the DEM data, and count the watershed information, which includes the watershed name, watershed area, longitude and latitude, and memory length; finally, the information is recorded as a txt document; Step S103, divide the obtained rainfall data and flow data into three parts, one part of the data is used for calibration, one part of the data is used for verification, and the last part of the data is used for simulation; and save the processed data as a txt document; Step S104, bring the data processed in step S103 into the TVGM model, that is, complete the construction of the watershed hydrological model; The method for constructing the river water dynamic water quality model in step S2 comprises the following steps: Step S201, obtain the data of river boundary, river terrain, flow, water level, water quality concentration and water temperature; Step S202, import the obtained high-resolution satellite map into the arcgis software, and according to the river range in the satellite map, use the editing tool of the arcgis software to outline in turn, that is, the river area layer, that is, the river boundary, can be obtained; import the depicted river boundary into the globalmapper software, and convert it into a format that can be recognized by the Delft3D software; divide the river grid in Delft3D, and export it as a.grid format; that is, the grid file required for constructing the river water dynamic water quality model can be obtained; Step S203, import the generated grid file into the EFDC model to obtain the coordinates of the four corners of the grid; take the average value of the four corner coordinates X and the average value of the four coordinates Y respectively to calculate the center point coordinates of the grid; according to the upstream and downstream ordering of the grid, based on a small amount of measured section data and the average slope of the terrain, the elevation of each center point of the grid is calculated; input the calculated grid points into the EFDC model, and the river terrain required by the model can be obtained; Step S204, input the obtained water quality concentration, water level data, processed river terrain and flow obtained by the TVGM model into the EFDC model, and the river water dynamic water quality model can be constructed.

2. The method for identifying the protection threshold of aquatic organisms based on the four-water coupling model according to claim 1, characterized in that, The step S3 comprises the following steps: Step S301, according to the point position information of the measured aquatic organism sampling points, the aquatic organism sampling points are dropped into the corresponding river channel grid points; Step S302, data is extracted from the model; after the river channel hydrodynamic water quality model is constructed, the water quantity and water quality data of each grid are obtained based on model simulation, and are directly exported from the grid of the EFDC model.

3. The method for identifying the protection threshold of aquatic organisms based on the four-water coupling model according to claim 1, characterized in that, The step S4 comprises the following steps: Step S401, the above step S1 S3 The extracted data is integrated according to the point and the index type. Step S402, using the above data, a multi-element coupling model based on random forest is established, and an index threshold value based on the IBI index is calculated.

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