Water pollution source tracing and prediction method based on hydrodynamic-water quality coupling model

Abstract

This application provides a water pollution source tracing and prediction method based on a hydrodynamic-water quality coupling model, including: generating a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project-Yellow River to Jiqing section, importing the model file into the hydrodynamic model, calibrating the roughness and leakage coefficient based on the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establishing a hydrodynamic model adapted to the Yellow River to Jiqing section; updating the boundary file based on the water quality boundary conditions, importing the AD parameter file and the initial concentration values ​​of the water quality parameters into the convection-diffusion model, calibrating the longitudinal diffusion coefficient and attenuation coefficient based on the difference between the water quality parameter concentration simulation value output by the convection-diffusion model and the measured concentration value, and establishing a convection-diffusion model adapted to the Yellow River to Jiqing section; using the adapted hydrodynamic model and convection-diffusion model to trace and predict water pollution. This application can improve the accuracy and efficiency of water pollution source tracing and prediction.

Description

Technical Field

[0001] The present application relates to the technical field of water pollution control, and in particular to a water pollution source tracing and prediction method based on a hydrodynamic-water quality coupling model. Background Art

[0002] The Jiaodong Yellow River Water Diversion Project diverts Yellow River water from Binzhou City, Shandong Province, to Weihai City. Upon completion, the project will enable the coordinated allocation of water from the Yangtze River, the Yellow River, and local water, alleviating water resource shortages in Jiaodong and the entire province. During the water diversion process, it is necessary to identify both routine and emergent pollution sources within the Jiaodong Water Diversion Project and ensure water quality safety for typical sections of the project. This will ensure the safe flow and quality of water delivered by the Jiaodong Water Diversion Project, ultimately achieving the overall goal of "transporting clean water eastward through a single channel."

[0003] Based on the above work objectives, there is an urgent need to master the water quality transfer laws in typical channel sections of water diversion projects, provide a basis for studying the changing laws of various water quality indicators under various working conditions, and make scientific predictions on water quality changes under multiple scenarios, so as to better formulate corresponding water quality risk countermeasures. Summary of the Invention

[0004] In view of this, the purpose of the embodiments of the present application is to provide a water pollution tracing and prediction method based on a hydrodynamic-water quality coupling model, which can improve the accuracy and efficiency of water pollution tracing and prediction.

[0005] In a first aspect, an embodiment of the present application provides a method for tracing and predicting water pollution based on a hydrodynamic-water quality coupling model, the method comprising:

[0006] Generate a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project - Yellow River to Jiqing section, import the model file into the hydrodynamic model of MIKE11, calibrate the roughness and leakage coefficient of the hydrodynamic model based on the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establish a hydrodynamic model suitable for the Yellow River to Jiqing section; the model file includes a river network file, a section file, a time series file, a boundary file, an HD parameter file, and a simulation file;

[0007] The boundary file is updated based on the water quality boundary conditions, and the AD parameter file and the initial concentration values ​​of the water quality parameters are imported into the convection-diffusion model of MIKE11. The longitudinal diffusion coefficient and attenuation coefficient of the flow-diffusion model are calibrated based on the difference between the simulated water quality parameter concentration values ​​output by the convection-diffusion model and the measured water quality parameter concentration values, and a convection-diffusion model adapted to the Yellow River-Jinan-Qingdao section is established; the water quality parameters include TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus;

[0008] The hydrodynamic model and convection-diffusion model adapted to the Yellow River to Jiqing section are used to trace and predict water pollution in the Yellow River to Jiqing section.

[0009] In one possible implementation, generating a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project - Yellow River to Jiqing section, importing the model file into the hydrodynamic model of MIKE11, calibrating the roughness and leakage coefficient of the hydrodynamic model based on the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establishing a hydrodynamic model adapted to the Yellow River to Jiqing section includes:

[0010] Step 1.1: generating the river network file, including: generalizing the river network of the Yellow River-Jinan-Qingdao section of the diversion project into a one-dimensional river channel including water diversion outlets and water pumping stations; wherein the water pumping stations include Songzhuang Pumping Station, Wangnuo Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station;

[0011] Step 1.2: Generate the cross-section file, including: the Yellow River-Jinan-Qingdao water diversion channel is a trapezoidal cross-section open channel with a fixed channel shape, use the cross-section interpolation tool to process the cross-section measured data of the Yellow River-Jinan-Qingdao line section, and generate the cross-section file from the outlet gate to the Jihongtan Reservoir;

[0012] Step 1.3: Generate the time series file, including: setting the time axis to equal time intervals, setting the calculation step to 1 day, setting the time step to 180, selecting flow data within a specific time range, selecting the water level data of the same period for the lower boundary, and generating flow time series for two inflows, a specific water diversion, and a pumping station, as well as a lower boundary water level time series;

[0013] Step 1.4: Generate the boundary file, including: according to the engineering simulation, set the upper boundary as the outlet gate of the Yellow River-Jinan-Qingdao grit chamber, and select the flow at the Beidi culvert gate as the Yellow River water diversion volume; set the lower boundary as the inlet of the Jihongtan Reservoir; select flow as the boundary type of the upper boundary, control the lower boundary by water level, and associate the corresponding water level time series file; generalize the water confluence and diversion outlets as point sources, select point source as the boundary description, select flow as the boundary type, and associate the time flow series of each diversion outlet; set the diversion flow to a negative number to represent outflow; set the water confluence point as a point source, and associate the flow time series of the total inflow;

[0014] Step 1.5: Generate the HD parameter file, including: setting the measured initial values ​​of water level and flow as initial water level and initial flow; the channel lining of the Yellow River to Jiqing section is a full-section reinforced concrete lining, and the initial roughness ratio is: 0.015 for the diversion channel and outlet channel of Songzhuang Pump Station, Wangnuo Pump Station, Tingkou Pump Station, and Jihongtan Pump Station; 0.02 for the outlet gate of the sedimentation tank to the Mihe River inverted siphon, and 0.02 for the Mihe River inverted siphon to the The initial leakage coefficient is 0.018 for Tingkou Pumping Station and 0.024 for Tingkou Pumping Station to Jihongtan Pumping Station. The initial leakage coefficient is 1e-005 for the grit chamber outlet gate to the Bailang River inverted siphon gate, 1e-008 for the Bailang River inverted siphon gate to the Wugou River regulating gate, 1e-005 for the Wugou River regulating gate to Jihongtan Pumping Station, and 1e-005 for the diversion channel and outlet channel of Songzhuang Pumping Station, Wangnuo Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station.

[0015] Step 1.6: Generate the simulation file, including: integrating the river network file, the cross-section file, the time series file, the boundary file, and the HD parameter file to perform hydrodynamic simulation; select hydrodynamic as the model, select non-constant as the simulation mode, and set the time step to 30 minutes;

[0016] Step 1.7: Run the MIKE11 hydrodynamic model and calibrate the roughness and leakage coefficient until the difference between the simulated water level output by the hydrodynamic model and the measured water level meets the first calibration termination condition. This establishes a hydrodynamic model suitable for the Yellow River to Jinan-Qingdao section.

[0017] In one possible implementation, the boundary file is updated based on the water quality boundary conditions, the AD parameter file and the initial concentration values ​​of the water quality parameters are imported into the convection-diffusion model of MIKE11, and the longitudinal diffusion coefficient and attenuation coefficient of the flow-diffusion model are calibrated according to the difference between the simulated water quality parameter concentration values ​​output by the convection-diffusion model and the measured water quality parameter concentration values, so as to establish a convection-diffusion model adapted to the Yellow River-Jinan-Qingdao section, including:

[0018] Step 2.1: Set up the AD parameter file, including: setting the names of water quality parameters, namely TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; setting the concentration units of water quality parameters, all in mg / L;

[0019] Step 2.2: Define the longitudinal diffusion coefficient D = aV b ; Where V is the flow velocity, set the coefficient a, coefficient b, and minimum longitudinal diffusion coefficient D applicable to the entire domain min , maximum longitudinal diffusion coefficient D max , obtain the initial longitudinal diffusion coefficient of the Yellow River to Jiqing section;

[0020] Step 2.3: Set the initial concentration values ​​of each water quality parameter, including the global initial concentration value and the local initial concentration value associated with the river section name and mileage;

[0021] Step 2.4: Define the attenuation coefficient K, in d -1 , C=C0e -Kt , where C is the concentration after attenuation, in mg / L, C0 is the concentration before attenuation, in mg / L, and t is the time, in d; set the initial attenuation coefficient for each sub-section of the Yellow River-Jinan-Qingdao section;

[0022] Step 2.5: Add the water quality boundary condition to the boundary file;

[0023] Step 2.6: Import the AD parameter file and the initial concentration values ​​of each water quality parameter, set the result output file and save frequency, run the convection-diffusion model of MIKE11, calibrate the longitudinal diffusion coefficient and the attenuation coefficient corresponding to each water quality parameter, until the difference between the simulated concentration value of each water quality parameter output by the convection-diffusion model and its measured concentration value meets the second calibration termination condition, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section.

[0024] In one possible implementation, a hydrodynamic model and a convection-diffusion model adapted to the Yellow River-Jinan-Qingdao section are used to trace the source of water pollution in the Yellow River-Jinan-Qingdao section, including:

[0025] If it is detected that the concentration of the target water quality parameter at the target location within the Yellow River-Jinan-Qingdao section exceeds the concentration standard value, the concentration of the target water quality parameter at the target location and multiple reference locations associated with the target location will be imported into the convection-diffusion model, and based on the hydrodynamic model and the convection-diffusion model, the concentration change trend of the target water quality parameter within the area where the target location is located will be determined, and the pollution source of the target water quality parameter will be determined based on the concentration change trend.

[0026] In one possible implementation, a hydrodynamic model and a convection-diffusion model adapted to the Yellow River to Jiqing section are used to predict water pollution in the Yellow River to Jiqing section, including:

[0027] The proposed prediction time period and location points are input, and simulation data matching the proposed prediction time period and location points are searched from the simulation data sets of the hydrodynamic model and the convection-diffusion model.

[0028] In one possible implementation, the method further includes:

[0029] Establish hydrodynamic models and convection-diffusion models for several typical river basins;

[0030] According to the basic information of the watershed, calculate the similarity between the watershed to be processed and each typical watershed;

[0031] The hydrodynamic model and convection-diffusion model of the typical basin with the highest similarity to the basin to be treated are used to trace the source and predict water pollution in the basin to be treated.

[0032] In a possible implementation, the method further includes: using the convection-diffusion model as a basis, applying Ecolab to simulate the convection-diffusion process of a substance in a water body.

[0033] In a second aspect, an embodiment of the present application provides a water pollution source tracing and prediction device based on a hydrodynamic-water quality coupling model, the device comprising:

[0034] A hydrodynamic model establishment module is used to generate a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project - Yellow River to Jiqing section, import the model file into the MIKE11 hydrodynamic model, calibrate the roughness and leakage coefficient of the hydrodynamic model based on the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establish a hydrodynamic model suitable for the Yellow River to Jiqing section; the model file includes a river network file, a section file, a time series file, a boundary file, an HD parameter file, and a simulation file;

[0035] A convection-diffusion model establishment module is used to update the boundary file based on the water quality boundary conditions, import the AD parameter file and the initial concentration values ​​of the water quality parameters into the convection-diffusion model of MIKE11, calibrate the longitudinal diffusion coefficient and attenuation coefficient of the flow-diffusion model based on the difference between the simulated water quality parameter concentration values ​​output by the convection-diffusion model and the measured water quality parameter concentration values, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section; the water quality parameters include TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus;

[0036] The water pollution source tracing and prediction module is used to trace and predict the water pollution of the Yellow River to Jiqing section by using the hydrodynamic model and convection diffusion model adapted to the Yellow River to Jiqing section.

[0037] In a third aspect, an embodiment of the present application provides an electronic device comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory through the bus, and the processor executes the machine-readable instructions to execute the steps of the water pollution tracing and prediction method based on the hydrodynamic-water quality coupling model as described in any one of the first aspects.

[0038] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the water pollution tracing and prediction method based on the hydrodynamic-water quality coupling model described in any one of the first aspects are executed.

[0039] The water pollution source tracing and prediction method based on the hydrodynamic-water quality coupling model provided in the embodiment of the present application can improve the accuracy and efficiency of water pollution source tracing and prediction.

[0040] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 A flow chart of a water pollution source tracing and prediction method based on a hydrodynamic-water quality coupling model provided in an embodiment of the present application is shown;

[0043] Figure 2 A generalized diagram of a river network provided by an embodiment of the present application is shown;

[0044] Figure 3.1 A schematic diagram of the simulation results of the water level at the grit chamber outlet gate provided in an embodiment of the present application is shown;

[0045] Figure 3.2 A schematic diagram of the water level simulation results of the Jiaolai River inverted siphon provided in an embodiment of the present application is shown;

[0046] Figure 3.3 A schematic diagram of the water level simulation results of the inverted siphon gate of the Zhushui River provided in an embodiment of the present application is shown;

[0047] Figure 4.1 A schematic diagram of the verification result of the grit chamber outlet gate water level provided in an embodiment of the present application is shown;

[0048] Figure 4.2 A schematic diagram of the water level verification results of the Jiaolai River inverted siphon provided in an embodiment of the present application is shown;

[0049] Figure 4.3 A schematic diagram of the water level verification results of the inverted siphon gate of the Zhushui River provided in an embodiment of the present application is shown;

[0050] Figure 5A schematic structural diagram of a water pollution source tracing and prediction device based on a hydrodynamic-water quality coupling model provided in an embodiment of the present application is shown;

[0051] Figure 6 A schematic diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0053] The Jiaodong Yellow River Water Diversion Project diverts Yellow River water from Binzhou City, Shandong Province, to Weihai City. Upon completion, the project will enable the coordinated allocation of water from the Yangtze River, the Yellow River, and local water, alleviating water resource shortages in Jiaodong and the entire province. During the water diversion process, it is necessary to identify both routine and emergent pollution sources within the Jiaodong Water Diversion Project and ensure water quality safety for typical sections of the project. This will ensure the safe flow and quality of water delivered by the Jiaodong Water Diversion Project, ultimately achieving the overall goal of "transporting clean water eastward through a single channel."

[0054] Based on the above work objectives, there is an urgent need to master the water quality transfer laws in typical channel sections of water diversion projects, provide a basis for studying the changing laws of various water quality indicators under various working conditions, and make scientific predictions on water quality changes under multiple scenarios, so as to better formulate corresponding water quality risk countermeasures.

[0055] Based on the above problems, an embodiment of the present application provides a water pollution tracing and prediction method based on a hydrodynamic-water quality coupling model, which can improve the accuracy and efficiency of water pollution tracing and prediction.

[0056] The defects in the above solutions are the results obtained by the inventor after practice and careful research. Therefore, the process of discovering the above problems and the solutions proposed by this application for the above problems below should be the contributions made by the inventor to this application during the application process.

[0057] The technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. The components of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for which protection is claimed, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0058] To facilitate understanding of this embodiment, a water pollution source tracing and prediction method based on a hydrodynamic-water quality coupling model disclosed in an embodiment of the present application is first introduced in detail.

[0059] See also Figure 1 As shown, Figure 1 A flow chart of a method for tracing and predicting water pollution based on a hydrodynamic-water quality coupling model provided in an embodiment of the present application, the method comprising the following steps:

[0060] S101. Generate a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project - Yellow River to Jiqing section, import the model file into the hydrodynamic model of MIKE11, calibrate the roughness and leakage coefficient of the hydrodynamic model according to the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establish a hydrodynamic model suitable for the Yellow River to Jiqing section.

[0061] The model files include river network files, cross-section files, time series files, boundary files, HD parameter files, and simulation files.

[0062] S102. Update the boundary file based on the water quality boundary conditions, import the AD parameter file and the initial concentration values ​​of the water quality parameters into the convection-diffusion model of MIKE11, calibrate the longitudinal diffusion coefficient and attenuation coefficient of the flow-diffusion model according to the difference between the simulated value of the water quality parameter concentration output by the convection-diffusion model and the actual measured value of the water quality parameter concentration, and establish a convection-diffusion model that is suitable for the Yellow River-Jinan-Qingdao section of the line.

[0063] The water quality parameters include TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus.

[0064] S103. Use the hydrodynamic model and convection-diffusion model adapted to the Yellow River to Jiqing section to trace and predict water pollution in the Yellow River to Jiqing section.

[0065] This embodiment of the application uses MIKE11 software to trace and predict water pollution sources. MIKE11 is a watershed hydrological simulation software widely used in hydrodynamics, water quality, and hydraulic engineering simulation. MIKE11 software is versatile, offering automatic calibration, sensitivity analysis, and uncertainty analysis. It allows for customized simulation solutions and the combination of various modules to meet application needs.

[0066] (1) Principle of one-dimensional hydrodynamic model

[0067] The MIKE11 Hydrodynamics Module (HD) is a core component of the MIKE11 software system. It enables scientific and rational hydrodynamic simulations of most one-dimensional water bodies. It serves as the foundation and prerequisite for water quality models (convection-diffusion models), playing a crucial role. The Hydrodynamics Module uses the six-point Abbott-Ionescu finite difference method to solve the Saint-Venant equations, accurately simulating the hydrodynamic conditions during the study period. Because the basic equations for unsteady flow consist of continuity equations and equations of motion, they are applicable to both continuous and discontinuous quantities. The equations are shown below:

[0068] Continuity equation:

[0069]

[0070] Equations of motion:

[0071]

[0072] Where Q is the cross-sectional flow rate; x is the distance coordinate; h is the cross-sectional water level; t is the time coordinate; q is the lateral inflow; A is the cross-sectional area; α is the vertical velocity distribution coefficient; g is the acceleration of gravity; R is the hydraulic radius of the cross-sectional area; C is the resistance coefficient; b s is the width of the water surface.

[0073] (2) Principle of one-dimensional water quality model

[0074] The water quality module (AD) of the MIKE11 software is a tool specifically designed to study the migration and transformation of pollutants in water environments. It can simulate the transport and diffusion of pollutants in water environments under hydrodynamic conditions and analyze the distribution characteristics of pollutants in time and space. The transport process of pollutants in water bodies is mainly manifested as longitudinal diffusion. At the same time, the characteristics of the pollutants themselves determine the attenuation rate of the pollutants. Therefore, the control equation of the one-dimensional water quality model includes both the transport and diffusion terms and the attenuation terms of the pollutants. The control equation of the one-dimensional water quality model is as follows:

[0075] The basic equation of convection and diffusion in one-dimensional unsteady flow:

[0076]

[0077] Among them, A is the cross-sectional area, C is the concentration of water quality indicators; Q is the flow rate; x is the distance coordinate; t is the time coordinate; D is the diffusion coefficient; K is the comprehensive attenuation coefficient; C2 is the source and sink concentration; and q is the side inflow flow rate.

[0078] Calculation formula for the diffusion coefficient of water pollutants: D=aV b ; Where D is the diffusion coefficient, V is the flow velocity, and a and b are coefficients.

[0079] Calculation formula for water pollutant attenuation coefficient: C=C0e -Kt , where C is the concentration after decay, in mg / L; C0 is the concentration before decay, in mg / L; t is the time, in d; and the decay coefficient K, in d -1 .

[0080] This example builds a hydrodynamic module (HD) based on measured hydrological conditions and applies the convection-diffusion module (AD) to simulate the spatiotemporal evolution of river pollutants. The MIKE11's convection-diffusion module (AD) is built on top of the hydrodynamic module (HD), so the HD must be built first, followed by the AD.

[0081] Part 1: Building a hydrodynamic model

[0082] Step S101 generates a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project - Yellow River to Jiqing section, imports the model file into the hydrodynamic model of MIKE11, calibrates the roughness and leakage coefficient of the hydrodynamic model based on the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establishes a hydrodynamic model suitable for the Yellow River to Jiqing section. Specifically, it includes:

[0083] Step 1.1: Generate the river network file, including: generalizing the river network of the Yellow River-Jinan-Qingdao section, generalizing the Yellow River-Jinan-Qingdao section into a one-dimensional river channel with water diversion outlets and water pumping stations; wherein the water pumping stations include Songzhuang Pumping Station, Wangnuo Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station.

[0084] Specifically, the river network generalization should, in principle, make the generalized river network consistent with the actual situation in terms of water transmission and other aspects, and secondly, factors such as terrain conditions should also be considered. In the embodiment of the present application, reasonable system generalization is carried out according to the actual situation of the project. Download DEM data with a resolution of 90M under the wgs1984 projection coordinate system, extract the river vector file in Arcgis and import it into MIKE11 to automatically generate the generalized river channel of the Net file. In order to improve the efficiency of the simulation work, the shape of the river network generally needs to be generalized. The basic principle of river network generalization is to be able to scientifically simulate the hydrodynamic characteristics of the river while retaining the main river sections in the study area, so that the generalized river network is close to the actual situation in terms of storage capacity and water transmission capacity. The Yellow River to Jinan-Qingdao project has few tributaries in the study area and is an artificial water diversion channel with regular water diversion sections. Therefore, the river median line is selected as the river network line in the generalized model, and the project is generalized as a one-dimensional river channel from the outlet gate to the Jihongtan Reservoir. There are 11 water diversion outlets and 4 levels of water pumping stations along the project, including Songzhuang Pumping Station, Wangnuo Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station. Figure 2 As shown, Figure 2 The river network generalization diagram provided in the embodiment of this application is Figure 2 In the figure, the circle links represent the river channel and the boxes represent the 4-level water pumping stations.

[0085] Step 1.2: Generate the cross-section file, including: the water diversion channel of the Yellow River to Jiqing is a trapezoidal cross-section open channel with a fixed channel shape, use the cross-section interpolation tool to process the measured cross-section data of the Yellow River to Jiqing section, and generate a cross-section file from the outlet gate to the Jihongtan Reservoir.

[0086] Specifically, cross-section files are crucial information for modeling. They contain key information such as the cross-section's shape, hydraulic radius, river name, and river mileage. When creating cross-section files, the variability of the river network should be reflected as much as possible. Furthermore, during cross-section generalization, the consistency of hydraulic elements such as the cross-sectional area and wetted perimeter should be maintained as much as possible. The simulation range of the study area extends from the outlet gate to the Jihongtan Reservoir. Based on field research and channel cross-section data, the Yellow River-Jinan-Qingdao water diversion channel is an open channel with a trapezoidal cross-section, and its shape rarely varies. The cross-sectional data used in the embodiment of the present application are the collected measured data and the interpolated cross-sectional data, which are set as follows: (1) the measured original cross-sectional data are input into the cross-sectional editor, and the cross-sectional shape and point positions are observed from the image window to see if they are reasonable. If there are unreasonable points, the unreasonable data are corrected; (2) the intervals between cross-sectional data collected are long, the cross-sectional data are incomplete, and the model is very easy to diverge at the pump station. Therefore, the cross-sectional interpolation tool provided by the model is used to add new interpolated cross-sectional areas between cross-sectional areas with little change in shape and slope by linear interpolation, and interpolation is performed at intervals of 1000m to improve the simulation accuracy; (3) in order to reduce the instability of the model, a cross-sectional area with the same value as the cross-sectional area at the pump station is added 500m before the cross-sectional area of ​​the pump station. The cross-sectional types in the MIKE11 model are divided into four types: open channel, closed irregular, closed circular, and closed rectangular. The open channel type is selected based on the actual project situation.

[0087] Step 1.3: Generate the time series file, including: setting the time axis to equal time intervals, setting the calculation step to 1d, setting the time step to 180, selecting flow data within a specific time range, selecting the water level data of the same period for the lower boundary, and generating flow time series of two inflows, a specific water diversion, and a pumping station, as well as a lower boundary water level time series.

[0088] Specifically, a time series file is required for setting boundary conditions. Create a new time series file with the time axis set to equal time intervals, the calculation step size set to 1 day (1 day), and the time step size set to 180. Filter the existing inflow and diversion flow data, selecting flow data from January 1, 2021, to June 30, 2021, as the flow data for this specific time range. Select the water level data for this period as the lower boundary. Generate flow time series files for the two inflows, the partial diversion, and the pumping station, as well as a lower boundary water level time series file.

[0089] Step 1.4: Generate the boundary file, including: according to the engineering simulation, the upper boundary is set as the outlet gate of the Yellow River-Jinan-Qingdao grit chamber, and the flow at the Beidi culvert gate is selected as the Yellow River water diversion volume; the lower boundary is set as the inlet of the Jihongtan Reservoir; the boundary type of the upper boundary is selected as flow, the lower boundary is controlled by water level, and the corresponding water level time series file is associated; the water confluence and diversion outlets are generalized as point sources, the boundary description is selected as point source, the boundary type is flow, and the time flow series of each diversion outlet is associated; the diversion flow is set to a negative number to represent outflow; the water confluence point is set as a point source, and the flow time series of the total inflow is associated.

[0090] Specifically, boundary conditions include external boundaries (open boundaries) and internal boundaries (point sources, non-point sources, global domains, buildings, and closed boundaries), which represent the interaction between external environmental conditions and the model. Open boundaries describe the intersection of the model boundary and the external environment, simulating the starting point and outflow point. Open boundary types include riverbed elevation, inflow and outflow flow, water level, Qh relationship, sediment supply, and sediment transport. Internal boundaries, such as lateral inflow and outflow, can simulate the interaction between the interior of a river section and the river network. The principles for selecting boundary conditions are: the problem to be calculated must be mathematically well-posed, physically reasonable, and the results must be stable.

[0091] Step 1.5: Generate the HD parameter file, including: setting the measured initial values ​​of water level and flow as initial water level and initial flow; the channel lining of the Yellow River to Jiqing section is a full-section reinforced concrete lining, and the initial roughness ratio is: 0.015 for the diversion channel and outlet channel of Songzhuang Pump Station, Wangnuo Pump Station, Tingkou Pump Station, and Jihongtan Pump Station; 0.02 for the outlet gate of the sedimentation tank to the Mihe River inverted siphon, and 0.02 for the Mihe River inverted siphon to the The leakage coefficient for Tingkou Pumping Station is 0.018, and that for Tingkou Pumping Station to Jihongtan Pumping Station is 0.024; the initial leakage coefficient is: 1e-005 for the sedimentation tank outlet gate to the Bailang River inverted siphon gate, 1e-008 for the Bailang River inverted siphon gate to the Wugou River regulating gate, 1e-005 for the Wugou River regulating gate to Jihongtan Pumping Station, and 1e-005 for the locations of the water diversion channel and outlet channel of Songzhuang Pumping Station, Wangnoi Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station.

[0092] Specifically, parameter setting involves two main aspects: the initial conditions, namely the initial water level and flow rate, to ensure proper model operation. The second is the definition of parameters such as riverbed roughness and permeability. These should be determined based on the simulated river conditions and the model simulation results.

[0093] Initial Condition Setting: Typically, the initial flow rate is set to 0. However, in principle, the initial conditions should be set as close as possible to the actual hydrodynamic conditions at the time of the initial simulation. Therefore, the initial values ​​here are set to the initial values ​​measured during project operation.

[0094] Parameter Setting: Riverbed roughness is a key parameter used to measure the impact of riverbed roughness on river flow and conduct hydrological analysis. It is crucial for numerical simulations. Its determination is complex and difficult, as it is closely related to factors such as channel shape, channel roughness, and water level. Riverbed roughness can be determined using the riverbed resistance method (divided into uniform sections and three-layer regions), the resistance formula method (including the Manning coefficient M (typically 10-100), the Manning coefficient n (typically 0.01-0.1), the Xie Cai coefficient C, and the Darcy weir gap), the global value method, and the local value method. Field research revealed that the channel lining is a full-section reinforced concrete lining. The roughness ratio was initially set based on a combination of actual water diversion operations and previous empirical values.

[0095] The leakage coefficient simulates the amount of water lost to the ground during channel water transfer, significantly impacting the simulation results. The initial leakage coefficient is determined based on actual water transfer operations and construction plan data.

[0096] Step 1.6: Generate the simulation file, including: integrating the river network file, the section file, the time series file, the boundary file, and the HD parameter file to perform hydrodynamic simulation; select hydrodynamic as the model, select non-constant as the simulation mode, and set the time step to 30 minutes.

[0097] Specifically, the simulation file combines the files created in steps 1.1 through 1.5 to perform the hydrodynamic simulation. Once the above settings are complete, create the simulation file, select Hydrodynamic as the model, select Non-constant as the simulation mode, and set the time step to 30 minutes. On the Start page, select Start Simulation. On the Results page, output the specified file. This concludes the hydrodynamic simulation.

[0098] Step 1.7: Run the MIKE11 hydrodynamic model and calibrate the roughness and leakage coefficient until the difference between the simulated water level output by the hydrodynamic model and the measured water level meets the first calibration termination condition. This establishes a hydrodynamic model suitable for the Yellow River to Jinan-Qingdao section.

[0099] Specifically, the water level simulation and calibration parameter selection are carried out using the dispatching data from February 1 to May 1, 2021, provided by the Water Diversion Center, and the parameter verification is carried out using the dispatching operation data from June 1 to June 20, 2021. In order to ensure a certain degree of accuracy and reduce the divergence of the model, the simulation time step is set to 30 minutes. The hydrodynamic module mainly determines two parameters, namely the roughness and the leakage coefficient. First, the two parameter values ​​are preliminarily determined by field investigation and design parameters, and then the roughness and leakage coefficient are further calibrated in turn. Taking the measured water level of the selected observation section as the standard, adjust the parameter value so that the simulated water level basically matches the measured water level, reaching a reasonable error range.

[0100] (1) Establishing a hydrodynamic model - water level simulation

[0101] According to the changes in channel sections and actual operation data, three sections with complete and stable measured water level data were selected for water level simulation and parameter calibration, namely the sedimentation tank outlet gate, Jiaolai River inverted siphon gate, and Zhushui River inverted siphon gate. Figure 3.1 、 Figure 3.2 、 Figure 3.3 As shown, there are respectively a schematic diagram of the water level simulation results of the sedimentation tank outlet gate provided in the embodiment of the present application, a schematic diagram of the water level simulation results of the Jiaolai River inverted siphon gate, and a schematic diagram of the water level simulation results of the Zhushui River inverted siphon gate. Figure 3.1 、 Figure 3.2 、 Figure 3.3 The error between the simulated maximum water level and the measured maximum water level is small, with the absolute value of the error less than 0.2m and the relative error less than 3.42%, which can meet the requirements of general rivers and canals in water level simulation and satisfy the first calibration termination condition. It can be seen that the water level simulation of MIKE11 has a certain degree of accuracy, and the wave crests can basically reach consistency, but there are still certain errors, which may be caused by the following reasons: there is a small amount of cross-section data, which has a certain gap with the actual channel and is not accurate enough; the simulation time and collected data are limited, and other buildings in the project, such as inverted siphons and regulating gates, are not considered and are not included in the model simulation.

[0102] (2) Establishing a hydrodynamic model - hydrodynamic module verification

[0103] In order to verify the accuracy and rationality of the model parameters, the operating data from June 1 to June 20, 2021 were selected for verification. Figure 4.1 、 Figure 4.2 、 Figure 4.3 The following are the schematic diagrams of the verification results of the water level of the grit chamber outlet gate, the Jiaolai River inverted siphon gate, and the Zhushui River inverted siphon gate, respectively, provided in the embodiments of the present application. Figure 4.2 、 Figure 4.3 The absolute error between the simulated and measured maximum water levels at the three monitoring sections selected for model water level verification was less than 0.2 m, and the relative error was less than 1.57%, indicating that the parameter calibration was reasonable.

[0104] Part II: Constructing a Convection-Diffusion Model

[0105] In this part, you can use only the convection diffusion model to simulate the convection diffusion process of substances in water bodies, or you can use Ecolab to simulate the convection diffusion process of substances in water bodies based on the convection diffusion model.

[0106] Step S102 updates the boundary file based on the water quality boundary conditions, imports the AD parameter file and the initial concentration values ​​of the water quality parameters into the convection-diffusion model of MIKE11, calibrates the longitudinal diffusion coefficient and attenuation coefficient of the flow-diffusion model based on the difference between the simulated concentration values ​​of the water quality parameters output by the convection-diffusion model and the measured concentration values ​​of the water quality parameters, and establishes a convection-diffusion model that is suitable for the Yellow River-Jinan-Qingdao section. Specifically, it includes:

[0107] Step 2.1: Set up the AD parameter file, including: setting the names of water quality parameters, namely TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; setting the concentration units of water quality parameters, all in mg / L.

[0108] Specifically, set up seven simulated water quality parameters: TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus. Using only the AD module: On the component screen, enter the component name to be simulated on each line, and select mg / L as the concentration unit. Using the AD module as the foundation, use Ecolab to conduct in-depth water quality simulations, ensuring consistent component names and order.

[0109] Step 2.2: Define the longitudinal diffusion coefficient D = aV b ; Where V is the flow velocity, set the coefficient a, coefficient b, and minimum longitudinal diffusion coefficient D applicable to the entire domain min , maximum longitudinal diffusion coefficient D max , obtain the initial longitudinal diffusion coefficient of the Yellow River to Jiqing section.

[0110] Specifically, a and b are coefficients, which are entered in the first and second rows of the diffusion coefficient interface respectively; the third and fourth rows are the minimum D min and maximum D max If the value calculated according to the formula in step 2.2 exceeds the coefficient range, the maximum or minimum value is used. The diffusion coefficient is initially set to a global value, and the local value is modified later based on the calibration situation.

[0111] Step 2.3: Set the initial concentration values ​​of each water quality parameter, including the global initial concentration value and the local initial concentration value associated with the river section name and mileage.

[0112] Specifically, the initial conditions for the AD module are set based on the first measured values ​​to ensure model startup stability. To use only the AD module: enter the initial concentrations of each component in the Initial Conditions screen. For global initial conditions, select "Global." For local values, enter the river section name and mileage. To use Ecolab as the foundation for the AD module: define the initial conditions within Ecolab.

[0113] Step 2.4: Define the attenuation coefficient K, in d -1 , C=C0e-Kt , where C is the concentration after attenuation, in mg / L, C0 is the concentration before attenuation, in mg / L, and t is the time, in d; set the initial attenuation coefficient for each sub-section in the Yellow River-Jinan-Qingdao section.

[0114] Specifically, the attenuation coefficient (Decay) is a calibration coefficient. In this embodiment, the study area is divided into three sections (Export Gate-Songzhuang Pumping Station-Songzhuang Diversion Gate-Jihongtan Pumping Station), i.e., three sub-line sections, and the attenuation coefficient is set for each. The coefficient unit is preliminarily set through relevant research, and the attenuation coefficient is finally determined by calibration through measured data. Only AD module is used: for non-conservative material components, the appropriate attenuation coefficient is defined, and the unit is / day, i.e. d -1 ; Apply Ecolab based on the AD module: do not define the attenuation coefficient (Ecolab itself simulates the attenuation coefficient).

[0115] Step 2.5: Add the water quality boundary conditions to the boundary file.

[0116] Specifically, add water quality boundary conditions based on the HD boundary file. Save the collected raw boundary water quality data in the water quality boundary file. Due to the lack of measured data, the boundary concentrations are all constant. Some concentration values ​​are stored in another file and are measured values. Open the boundary file, select the boundary information definitions for the upper region, and enter the corresponding concentration values.

[0117] Step 2.6: Import the AD parameter file and the initial concentration values ​​of each water quality parameter, set the result output file and save frequency, run the convection-diffusion model of MIKE11, calibrate the longitudinal diffusion coefficient and the attenuation coefficient corresponding to each water quality parameter, until the difference between the simulated concentration value of each water quality parameter output by the convection-diffusion model and its measured concentration value meets the second calibration termination condition, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section.

[0118] Specifically, in the simulation file, select Advention-Dispersion; import the AD parameter file in the Input screen; enter the Simulation screen and define the initial conditions for the AD simulation; finally, define the output file name and save frequency, and enter the Start screen to begin the calculation. The parameters that require calibration for the AD module are the pollutant attenuation coefficient and the longitudinal diffusion coefficient. Three sections, spanning March 2023 to June 2024, were selected as validation sections, and measured data was compared with the simulated data. If the relative error for most results remains within 20%, the modeling requirements are generally met, thus satisfying the second calibration termination criterion.

[0119] Furthermore, in the water pollution source tracing and prediction method based on the hydrodynamic-water quality coupling model provided in the embodiment of the present application, a hydrodynamic model and a convection-diffusion model adapted to the Yellow River-Jinan-Qingdao section are used to trace the water pollution in the Yellow River-Jinan-Qingdao section, including:

[0120] If it is detected that the concentration of the target water quality parameter at the target location within the Yellow River-Jinan-Qingdao section exceeds the concentration standard value, the concentration of the target water quality parameter at the target location and multiple reference locations associated with the target location will be imported into the convection-diffusion model, and based on the hydrodynamic model and the convection-diffusion model, the concentration change trend of the target water quality parameter within the area where the target location is located will be determined, and the pollution source of the target water quality parameter will be determined based on the concentration change trend.

[0121] Among them, the target location is any detection location within the Yellow River-Jinan-Qingdao section, and the target water quality parameter is any one of the water quality parameters including TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus. If the concentration of the water quality parameter is less than or equal to its concentration standard value, it means that the concentration of the water quality parameter meets the water quality requirements and will not cause water quality deterioration; if the concentration of the water quality parameter is greater than its concentration standard value, it means that the concentration of the water quality parameter does not meet the water quality requirements and urgently needs to be treated. Multiple reference locations associated with the target location are selected based on the distance between the locations. For example, the area within the Yellow River-Jinan-Qingdao section that is less than 5km away from the target location is used as the reference area, and several reference locations are selected from the reference area at intervals of 500m, and the concentration of the target water quality parameters at the reference locations is tested. With the target location as the center, identify trends in the concentration of the target water quality parameter within the target location's area. For example, trends from high concentration to low concentration, or from low concentration to high concentration, or from low concentration to high concentration and then back again, will be used to identify the location with the highest concentration as the source of the target water quality parameter contamination. The target location's area must be larger than the reference area, and the area size can be adjusted based on actual conditions.

[0122] Furthermore, in the water pollution source tracing and prediction method based on the hydrodynamic-water quality coupling model provided in the embodiment of the present application, a hydrodynamic model and a convection-diffusion model adapted to the Yellow River-Jinan-Qingdao section are used to predict water pollution in the Yellow River-Jinan-Qingdao section, including:

[0123] The proposed prediction time period and location points are input, and simulation data matching the proposed prediction time period and location points are searched from the simulation data sets of the hydrodynamic model and the convection-diffusion model.

[0124] Furthermore, when exploring the law of water quality changes, the ideal state is to establish an adaptive hydrodynamic-water quality coupling model for each river basin. However, when there are too many tributaries, a large number of hydrodynamic-water quality coupling models need to be established. In order to reduce the workload of model establishment, several representative tributaries are selected from the numerous tributaries as typical river basins, and the coupling model of the typical river basin is used to trace and predict the water quality of similar non-typical river basins. The water pollution tracing and prediction method based on the hydrodynamic-water quality coupling model provided in the embodiment of the present application also includes:

[0125] Step 3.1: Establish hydrodynamic models and convection-diffusion models for several typical watersheds.

[0126] Step 3.2: Based on the basic information of the watershed, calculate the similarity between the watershed to be processed and each typical watershed.

[0127] Step 3.3: Using the hydrodynamic model and convection-diffusion model of the typical basin that is most similar to the basin to be treated, trace the source and predict the water pollution in the basin to be treated.

[0128] To improve the accuracy of similarity calculations, basic information should be enriched as much as possible. Using this basic information can maximize the restoration of watershed characteristics. Specifically, basic information can be processed into basic information vectors. By calculating the distance between these vectors, the representative watershed with the shortest distance is selected as the most similar representative watershed to the proposed watershed. Alternatively, a Kmeans clustering method can be used to cluster the proposed watershed and K representative watersheds. The representative watershed that is classified into the same category as the proposed watershed is selected as the representative watershed with the highest similarity to the proposed watershed.

[0129] Based on the same inventive concept, the embodiments of the present application also provide a water pollution tracing and prediction device based on a hydrodynamic-water quality coupling model corresponding to the water pollution tracing and prediction method based on a hydrodynamic-water quality coupling model. Since the principle of solving the problem by the device in the embodiments of the present application is similar to the above-mentioned water pollution tracing and prediction method based on a hydrodynamic-water quality coupling model in the embodiments of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0130] See also Figure 5 As shown, Figure 5 This is a schematic diagram of the structure of a water pollution source tracing and prediction device based on a hydrodynamic-water quality coupling model provided in an embodiment of the present application. The device includes:

[0131] A hydrodynamic model establishment module 501 is used to generate a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project - Yellow River to Jiqing section, import the model file into the hydrodynamic model of MIKE11, calibrate the roughness and leakage coefficient of the hydrodynamic model based on the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establish a hydrodynamic model suitable for the Yellow River to Jiqing section; the model file includes a river network file, a section file, a time series file, a boundary file, an HD parameter file, and a simulation file;

[0132] A convection-diffusion model establishment module 502 is configured to update the boundary file based on the water quality boundary conditions, import the AD parameter file and the initial concentration values ​​of the water quality parameters into the convection-diffusion model of MIKE11, calibrate the longitudinal diffusion coefficient and attenuation coefficient of the flow-diffusion model based on the difference between the simulated water quality parameter concentration values ​​output by the convection-diffusion model and the measured water quality parameter concentration values, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section of the line; the water quality parameters include TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus;

[0133] The water pollution source tracing and prediction module 503 is used to trace and predict the water pollution of the Yellow River to Jiqing section by using a hydrodynamic model and a convection-diffusion model adapted to the Yellow River to Jiqing section.

[0134] In one possible implementation, the hydrodynamic model establishment module 501 generates a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project - Yellow River to Jiqing section, imports the model file into the hydrodynamic model of MIKE11, calibrates the roughness and leakage coefficient of the hydrodynamic model based on the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establishes a hydrodynamic model adapted to the Yellow River to Jiqing section, including:

[0135] Step 1.1: generating the river network file, including: generalizing the river network of the Yellow River-Jinan-Qingdao section of the diversion project into a one-dimensional river channel including water diversion outlets and water pumping stations; wherein the water pumping stations include Songzhuang Pumping Station, Wangnuo Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station;

[0136] Step 1.2: Generate the cross-section file, including: the Yellow River-Jinan-Qingdao water diversion channel is a trapezoidal cross-section open channel with a fixed channel shape, use the cross-section interpolation tool to process the cross-section measured data of the Yellow River-Jinan-Qingdao line section, and generate the cross-section file from the outlet gate to the Jihongtan Reservoir;

[0137] Step 1.3: Generate the time series file, including: setting the time axis to equal time intervals, setting the calculation step to 1 day, setting the time step to 180, selecting flow data within a specific time range, selecting the water level data of the same period for the lower boundary, and generating flow time series for two inflows, a specific water diversion, and a pumping station, as well as a lower boundary water level time series;

[0138] Step 1.4: Generate the boundary file, including: according to the engineering simulation, set the upper boundary as the outlet gate of the Yellow River-Jinan-Qingdao grit chamber, and select the flow at the Beidi culvert gate as the Yellow River water diversion volume; set the lower boundary as the inlet of the Jihongtan Reservoir; select flow as the boundary type of the upper boundary, control the lower boundary by water level, and associate the corresponding water level time series file; generalize the water confluence and diversion outlets as point sources, select point source as the boundary description, select flow as the boundary type, and associate the time flow series of each diversion outlet; set the diversion flow to a negative number to represent outflow; set the water confluence point as a point source, and associate the flow time series of the total inflow;

[0139] Step 1.5: Generate the HD parameter file, including: setting the measured initial values ​​of water level and flow as initial water level and initial flow; the channel lining of the Yellow River to Jiqing section is a full-section reinforced concrete lining, and the initial roughness ratio is: 0.015 for the diversion channel and outlet channel of Songzhuang Pump Station, Wangnuo Pump Station, Tingkou Pump Station, and Jihongtan Pump Station; 0.02 for the outlet gate of the sedimentation tank to the Mihe River inverted siphon, and 0.02 for the Mihe River inverted siphon to the The initial leakage coefficient is 0.018 for Tingkou Pumping Station and 0.024 for Tingkou Pumping Station to Jihongtan Pumping Station. The initial leakage coefficient is 1e-005 for the grit chamber outlet gate to the Bailang River inverted siphon gate, 1e-008 for the Bailang River inverted siphon gate to the Wugou River regulating gate, 1e-005 for the Wugou River regulating gate to Jihongtan Pumping Station, and 1e-005 for the diversion channel and outlet channel of Songzhuang Pumping Station, Wangnuo Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station.

[0140] Step 1.6: Generate the simulation file, including: integrating the river network file, the cross-section file, the time series file, the boundary file, and the HD parameter file to perform hydrodynamic simulation; select hydrodynamic as the model, select non-constant as the simulation mode, and set the time step to 30 minutes;

[0141] Step 1.7: Run the MIKE11 hydrodynamic model and calibrate the roughness and leakage coefficient until the difference between the simulated water level output by the hydrodynamic model and the measured water level meets the first calibration termination condition. This establishes a hydrodynamic model suitable for the Yellow River to Jinan-Qingdao section.

[0142] In one possible implementation, the convection-diffusion model establishment module 502 updates the boundary file based on the water quality boundary conditions, imports the AD parameter file and the initial concentration values ​​of the water quality parameters into the convection-diffusion model of MIKE11, calibrates the longitudinal diffusion coefficient and attenuation coefficient of the flow-diffusion model based on the difference between the simulated water quality parameter concentration values ​​output by the convection-diffusion model and the measured water quality parameter concentration values, and establishes a convection-diffusion model adapted to the Yellow River-Jinan-Qingdao section, including:

[0143] Step 2.1: Set up the AD parameter file, including: setting the names of water quality parameters, namely TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; setting the concentration units of water quality parameters, all in mg / L;

[0144] Step 2.2: Define the longitudinal diffusion coefficient D = aV b ; Where V is the flow velocity, set the coefficient a, coefficient b, and minimum longitudinal diffusion coefficient D applicable to the entire domain min , maximum longitudinal diffusion coefficient D max , obtain the initial longitudinal diffusion coefficient of the Yellow River to Jiqing section;

[0145] Step 2.3: Set the initial concentration values ​​of each water quality parameter, including the global initial concentration value and the local initial concentration value associated with the river section name and mileage;

[0146] Step 2.4: Define the attenuation coefficient K, in d -1 , C=C0e -Kt , where C is the concentration after attenuation, in mg / L, C0 is the concentration before attenuation, in mg / L, and t is the time, in d; set the initial attenuation coefficient for each sub-section of the Yellow River-Jinan-Qingdao section;

[0147] Step 2.5: Add the water quality boundary condition to the boundary file;

[0148] Step 2.6: Import the AD parameter file and the initial concentration values ​​of each water quality parameter, set the result output file and save frequency, run the convection-diffusion model of MIKE11, calibrate the longitudinal diffusion coefficient and the attenuation coefficient corresponding to each water quality parameter, until the difference between the simulated concentration value of each water quality parameter output by the convection-diffusion model and its measured concentration value meets the second calibration termination condition, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section.

[0149] In one possible implementation, the water pollution source tracing prediction module 503, when tracing the source of water pollution in the Yellow River-Jinan-Qingdao section using a hydrodynamic model and a convection-diffusion model adapted for the Yellow River-Jinan-Qingdao section, includes:

[0150] If it is detected that the concentration of the target water quality parameter at the target location within the Yellow River-Jinan-Qingdao section exceeds the concentration standard value, the concentration of the target water quality parameter at the target location and multiple reference locations associated with the target location will be imported into the convection-diffusion model, and based on the hydrodynamic model and the convection-diffusion model, the concentration change trend of the target water quality parameter within the area where the target location is located will be determined, and the pollution source of the target water quality parameter will be determined based on the concentration change trend.

[0151] In one possible implementation, the water pollution source tracing prediction module 503, when predicting water pollution in the Yellow River-Jinan-Qingdao section using a hydrodynamic model and a convection-diffusion model adapted for the Yellow River-Jinan-Qingdao section, includes:

[0152] The proposed prediction time period and location points are input, and simulation data matching the proposed prediction time period and location points are searched from the simulation data sets of the hydrodynamic model and the convection-diffusion model.

[0153] In a possible implementation, the device further includes:

[0154] Typical coupled model building module, used to build hydrodynamic models and convection-diffusion models for multiple typical river basins;

[0155] The similar typical watershed search module is used to calculate the similarity between the watershed to be processed and each typical watershed based on the basic information of the watershed;

[0156] The water pollution analysis module is used to trace and predict the water pollution in the watershed to be processed by using the hydrodynamic model and convection-diffusion model of the typical watershed with the highest similarity to the watershed to be processed.

[0157] In a possible implementation, the device further includes: an Ecolab simulation module, configured to simulate the convection diffusion process of a substance in a water body using Ecolab based on the convection diffusion model.

[0158] The water pollution source tracing and prediction device based on the hydrodynamic-water quality coupling model provided in the embodiment of the present application can improve the accuracy and efficiency of water pollution source tracing and prediction.

[0159] See also Figure 6 As shown, Figure 6A schematic diagram of an electronic device provided in an embodiment of the present application, the electronic device 600 includes: a processor 601, a memory 602 and a bus 603, the memory 602 stores machine-readable instructions executable by the processor 601, and when the electronic device is running, the processor 601 communicates with the memory 602 through the bus 603, and the processor 601 executes the machine-readable instructions to perform the steps of the water pollution tracing and prediction method based on the hydrodynamic-water quality coupling model as described above.

[0160] Specifically, the above-mentioned memory 602 and processor 601 can be general-purpose memory and processor, which are not specifically limited here. When the processor 601 runs the computer program stored in the memory 602, it can execute the above-mentioned water pollution tracing and prediction method based on the hydrodynamic-water quality coupling model.

[0161] Corresponding to the above-mentioned water pollution tracing and prediction method based on the hydrodynamic-water quality coupling model, an embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by the processor, the steps of the above-mentioned water pollution tracing and prediction method based on the hydrodynamic-water quality coupling model are executed.

[0162] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0163] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of the present embodiment according to actual needs.

[0164] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0165] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0166] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The scope of protection of the present application is not limited thereto. Although the present application has been described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-mentioned embodiments within the technical scope disclosed in the present application, or perform equivalent replacements for some of the technical features thereof. These modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A water pollution source tracing and prediction method based on a hydrodynamic-water quality coupling model, characterized in that: The method comprises: Generate a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project - Yellow River to Jiqing section, import the model file into the hydrodynamic model of MIKE11, calibrate the roughness and leakage coefficient of the hydrodynamic model based on the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establish a hydrodynamic model suitable for the Yellow River to Jiqing section; the model file includes a river network file, a section file, a time series file, a boundary file, an HD parameter file, and a simulation file; The boundary file is updated based on the water quality boundary conditions, the water quality boundary conditions are added to the boundary file, the AD parameter file and the initial concentration values ​​of the water quality parameters are imported into the convection-diffusion model of MIKE11, and the longitudinal diffusion coefficient and attenuation coefficient of the flow-diffusion model are calibrated according to the difference between the simulated water quality parameter concentration values ​​output by the convection-diffusion model and the measured water quality parameter concentration values, so as to establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section; the water quality parameters include TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; Using a hydrodynamic model and convection-diffusion model adapted to the Yellow River to Jiqing section, we can trace and predict water pollution in that section. The method generates a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project - Yellow River to Jiqing section, imports the model file into the hydrodynamic model of MIKE11, calibrates the roughness and leakage coefficient of the hydrodynamic model according to the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establishes a hydrodynamic model adapted to the Yellow River to Jiqing section, including: Step 1.1: generating the river network file, including: generalizing the river network of the Yellow River-Jinan-Qingdao section of the diversion project into a one-dimensional river channel including water diversion outlets and water pumping stations; wherein the water pumping stations include Songzhuang Pumping Station, Wangnuo Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station; Step 1.2: Generate the cross-section file, including: the Yellow River-Jinan-Qingdao water diversion channel is a trapezoidal cross-section open channel with a fixed channel shape, use the cross-section interpolation tool to process the cross-section measured data of the Yellow River-Jinan-Qingdao line section, and generate the cross-section file from the outlet gate to the Jihongtan Reservoir; Step 1.3: Generate the time series file, including: setting the time axis to equal time intervals, setting the calculation step size to 1 day, setting the time step size to 180, selecting flow data within a specific time range, selecting the water level data for the same period at the lower boundary, and generating flow time series for two inflows, a specific water diversion, and a pumping station, as well as a lower boundary water level time series; wherein the flow data within the specific time range is the flow data from January 1, 2021 to June 30, 2021; Step 1.4: Generate the boundary file, including: according to the engineering simulation, set the upper boundary as the outlet gate of the Yellow River-Jinan-Qingdao grit chamber, and select the flow at the Beidi culvert gate as the Yellow River water diversion volume; set the lower boundary as the inlet of the Jihongtan Reservoir; select flow as the boundary type of the upper boundary, control the lower boundary by water level, and associate the corresponding water level time series file; generalize the water confluence and diversion outlets as point sources, select point source as the boundary description, select flow as the boundary type, and associate the time flow series of each diversion outlet; set the diversion flow to a negative number to represent outflow; set the water confluence point as a point source, and associate the flow time series of the total inflow; Step 1.5: Generate the HD parameter file, including: setting the measured initial values ​​of water level and flow as initial water level and initial flow; the channel lining of the Yellow River to Jiqing section is a full-section reinforced concrete lining, and the initial roughness ratio is: 0.015 for the diversion channel and outlet channel of Songzhuang Pump Station, Wangnuo Pump Station, Tingkou Pump Station, and Jihongtan Pump Station; 0.02 for the outlet gate of the sedimentation tank to the Mihe River inverted siphon, and 0.02 for the Mihe River inverted siphon to the The initial leakage coefficient is 0.018 for Tingkou Pumping Station and 0.024 for Tingkou Pumping Station to Jihongtan Pumping Station. The initial leakage coefficient is 1e-005 for the grit chamber outlet gate to the Bailang River inverted siphon gate, 1e-008 for the Bailang River inverted siphon gate to the Wugou River regulating gate, 1e-005 for the Wugou River regulating gate to Jihongtan Pumping Station, and 1e-005 for the diversion channel and outlet channel of Songzhuang Pumping Station, Wangnuo Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station. Step 1.6: Generate the simulation file, including: integrating the river network file, the cross-section file, the time series file, the boundary file, and the HD parameter file to perform hydrodynamic simulation; select hydrodynamic as the model, select non-constant as the simulation mode, and set the time step to 30 minutes; Step 1.7: Run the MIKE11 hydrodynamic model and calibrate the roughness and leakage coefficient until the difference between the simulated water level output by the hydrodynamic model and the measured water level meets the first calibration termination condition. This establishes a hydrodynamic model suitable for the Yellow River to Jinan-Qingdao section of the project. The boundary file is updated based on the water quality boundary conditions, the AD parameter file and the initial concentration values ​​of the water quality parameters are imported into the convection-diffusion model of MIKE11, and the longitudinal diffusion coefficient and attenuation coefficient of the flow-diffusion model are calibrated according to the difference between the simulated concentration values ​​of the water quality parameters output by the convection-diffusion model and the measured concentration values ​​of the water quality parameters, so as to establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section, including: Step 2.1: Set up the AD parameter file, including: setting the names of water quality parameters, namely TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; setting the concentration units of water quality parameters, all in mg / L; Step 2.2: Define the longitudinal diffusion coefficient D = aV b ; Where V is the flow velocity, set the coefficient a, coefficient b, and minimum longitudinal diffusion coefficient D applicable to the entire domain min , maximum longitudinal diffusion coefficient D max , obtain the initial longitudinal diffusion coefficient of the Yellow River to Jiqing section; Step 2.3: Set the initial concentration values ​​of each water quality parameter, including the global initial concentration value and the local initial concentration value associated with the river section name and mileage; Step 2.4: Define the attenuation coefficient K, in d -1 , C=C0e -Kt , where C is the concentration after attenuation, in mg / L, C0 is the concentration before attenuation, in mg / L, and t is the time, in d; set the initial attenuation coefficient for each sub-section of the Yellow River-Jinan-Qingdao section; Step 2.5: Add the water quality boundary condition to the boundary file; Step 2.6: Import the AD parameter file and the initial concentration values ​​of each water quality parameter, set the result output file and save frequency, run the MIKE11 convection-diffusion model, calibrate the longitudinal diffusion coefficient and the attenuation coefficient corresponding to each water quality parameter, until the difference between the simulated concentration value of each water quality parameter output by the convection-diffusion model and its measured concentration value meets the second calibration termination condition, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section; The method further comprises: Establish hydrodynamic models and convection-diffusion models for several typical river basins; According to the basic information of the watershed, calculate the similarity between the watershed to be processed and each typical watershed; The hydrodynamic model and convection-diffusion model of the typical basin with the highest similarity to the basin to be treated are used to trace the source and predict water pollution in the basin to be treated.

2. The water pollution source tracing and prediction method based on the hydrodynamic-water quality coupling model according to claim 1 is characterized in that: Using a hydrodynamic model and convection-diffusion model adapted to the Yellow River-Jinan-Qingdao section, we traced the source of water pollution in this section, including: If it is detected that the concentration of the target water quality parameter at the target location within the Yellow River-Jinan-Qingdao section exceeds the concentration standard value, the concentration of the target water quality parameter at the target location and multiple reference locations associated with the target location will be imported into the convection-diffusion model, and based on the hydrodynamic model and the convection-diffusion model, the concentration change trend of the target water quality parameter within the area where the target location is located will be determined, and the pollution source of the target water quality parameter will be determined based on the concentration change trend.

3. The water pollution source tracing and prediction method based on the hydrodynamic-water quality coupling model according to claim 1 is characterized in that: The water pollution of the Yellow River to Jilin and Qingdao section is predicted by using the hydrodynamic model and convection-diffusion model adapted to the Yellow River to Jilin and Qingdao section, including: The proposed prediction time period and location points are input, and simulation data matching the proposed prediction time period and location points are searched from the simulation data sets of the hydrodynamic model and the convection-diffusion model.

4. The water pollution source tracing and prediction method based on the hydrodynamic-water quality coupling model according to claim 1 is characterized in that: The method further includes: based on the convection-diffusion model, applying Ecolab to simulate the convection-diffusion process of the substance in the water body.

5. A water pollution source tracing and prediction device based on a hydrodynamic-water quality coupling model, characterized in that: The device comprises: A hydrodynamic model establishment module is used to generate a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project - Yellow River to Jiqing section, import the model file into the MIKE11 hydrodynamic model, calibrate the roughness and leakage coefficient of the hydrodynamic model based on the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establish a hydrodynamic model suitable for the Yellow River to Jiqing section; the model file includes a river network file, a section file, a time series file, a boundary file, an HD parameter file, and a simulation file; A convection-diffusion model establishment module is used to update the boundary file based on the water quality boundary conditions, add the water quality boundary conditions to the boundary file, import the AD parameter file and the initial concentration values ​​of the water quality parameters into the convection-diffusion model of MIKE11, calibrate the longitudinal diffusion coefficient and attenuation coefficient of the flow-diffusion model based on the difference between the simulated water quality parameter concentration values ​​output by the convection-diffusion model and the measured water quality parameter concentration values, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section; the water quality parameters include TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; The water pollution source tracing and prediction module is used to trace and predict water pollution in the Yellow River-Jinan-Qingdao section using a hydrodynamic model and convection-diffusion model adapted for the section. The hydrodynamic model establishment module generates a model file based on the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project - Yellow River to Jiqing section, imports the model file into the hydrodynamic model of MIKE11, calibrates the roughness and leakage coefficient of the hydrodynamic model based on the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and establishes a hydrodynamic model adapted to the Yellow River to Jiqing section, including: Step 1.1: generating the river network file, including: generalizing the river network of the Yellow River-Jinan-Qingdao section of the diversion project into a one-dimensional river channel including water diversion outlets and water pumping stations; wherein the water pumping stations include Songzhuang Pumping Station, Wangnuo Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station; Step 1.2: Generate the cross-section file, including: the Yellow River-Jinan-Qingdao water diversion channel is a trapezoidal cross-section open channel with a fixed channel shape, use the cross-section interpolation tool to process the cross-section measured data of the Yellow River-Jinan-Qingdao line section, and generate the cross-section file from the outlet gate to the Jihongtan Reservoir; Step 1.3: Generate the time series file, including: setting the time axis to equal time intervals, setting the calculation step size to 1 day, setting the time step size to 180, selecting flow data within a specific time range, selecting the water level data for the same period at the lower boundary, and generating flow time series for two inflows, a specific water diversion, and a pumping station, as well as a lower boundary water level time series; wherein the flow data within the specific time range is the flow data from January 1, 2021 to June 30, 2021; Step 1.4: Generate the boundary file, including: according to the engineering simulation, set the upper boundary as the outlet gate of the Yellow River-Jinan-Qingdao grit chamber, and select the flow at the Beidi culvert gate as the Yellow River water diversion volume; set the lower boundary as the inlet of the Jihongtan Reservoir; select flow as the boundary type of the upper boundary, control the lower boundary by water level, and associate the corresponding water level time series file; generalize the water confluence and diversion outlets as point sources, select point source as the boundary description, select flow as the boundary type, and associate the time flow series of each diversion outlet; set the diversion flow to a negative number to represent outflow; set the water confluence point as a point source, and associate the flow time series of the total inflow; Step 1.5: Generate the HD parameter file, including: setting the measured initial values ​​of water level and flow as initial water level and initial flow; the channel lining of the Yellow River to Jiqing section is a full-section reinforced concrete lining, and the initial roughness ratio is: 0.015 for the diversion channel and outlet channel of Songzhuang Pump Station, Wangnuo Pump Station, Tingkou Pump Station, and Jihongtan Pump Station; 0.02 for the outlet gate of the sedimentation tank to the Mihe River inverted siphon, and 0.02 for the Mihe River inverted siphon to the The initial leakage coefficient is 0.018 for Tingkou Pumping Station and 0.024 for Tingkou Pumping Station to Jihongtan Pumping Station. The initial leakage coefficient is 1e-005 for the grit chamber outlet gate to the Bailang River inverted siphon gate, 1e-008 for the Bailang River inverted siphon gate to the Wugou River regulating gate, 1e-005 for the Wugou River regulating gate to Jihongtan Pumping Station, and 1e-005 for the diversion channel and outlet channel of Songzhuang Pumping Station, Wangnuo Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station. Step 1.6: Generate the simulation file, including: integrating the river network file, the cross-section file, the time series file, the boundary file, and the HD parameter file to perform hydrodynamic simulation; select hydrodynamic as the model, select non-constant as the simulation mode, and set the time step to 30 minutes; Step 1.7: Run the MIKE11 hydrodynamic model and calibrate the roughness and leakage coefficient until the difference between the simulated water level output by the hydrodynamic model and the measured water level meets the first calibration termination condition. This establishes a hydrodynamic model suitable for the Yellow River to Jinan-Qingdao section of the project. The convection-diffusion model establishment module updates the boundary file based on the water quality boundary conditions, imports the AD parameter file and the initial concentration values ​​of the water quality parameters into the convection-diffusion model of MIKE11, calibrates the longitudinal diffusion coefficient and attenuation coefficient of the flow-diffusion model based on the difference between the simulated water quality parameter concentration values ​​output by the convection-diffusion model and the measured water quality parameter concentration values, and establishes a convection-diffusion model adapted to the Yellow River-Jinan-Qingdao section, including: Step 2.1: Set up the AD parameter file, including: setting the names of water quality parameters, namely TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; setting the concentration units of water quality parameters, all in mg / L; Step 2.2: Define the longitudinal diffusion coefficient D = aV b ; Where V is the flow velocity, set the coefficient a, coefficient b, and minimum longitudinal diffusion coefficient D applicable to the entire domain min , maximum longitudinal diffusion coefficient D max , obtain the initial longitudinal diffusion coefficient of the Yellow River to Jiqing section; Step 2.3: Set the initial concentration values ​​of each water quality parameter, including the global initial concentration value and the local initial concentration value associated with the river section name and mileage; Step 2.4: Define the attenuation coefficient K, in d -1 , C=C0e -Kt , where C is the concentration after attenuation, in mg / L, C0 is the concentration before attenuation, in mg / L, and t is the time, in d; set the initial attenuation coefficient for each sub-section of the Yellow River-Jinan-Qingdao section; Step 2.5: Add the water quality boundary condition to the boundary file; Step 2.6: Import the AD parameter file and the initial concentration values ​​of each water quality parameter, set the result output file and save frequency, run the MIKE11 convection-diffusion model, calibrate the longitudinal diffusion coefficient and the attenuation coefficient corresponding to each water quality parameter, until the difference between the simulated concentration value of each water quality parameter output by the convection-diffusion model and its measured concentration value meets the second calibration termination condition, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section; The device further comprises: Typical coupled model building module, used to build hydrodynamic models and convection-diffusion models for multiple typical river basins; The similar typical watershed search module is used to calculate the similarity between the watershed to be processed and each typical watershed based on the basic information of the watershed; The water pollution analysis module is used to trace and predict the water pollution in the watershed to be processed by using the hydrodynamic model and convection-diffusion model of the typical watershed with the highest similarity to the watershed to be processed.

6. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate through the bus, and the processor executes the machine-readable instructions to perform the steps of the water pollution tracing and prediction method based on the hydrodynamic-water quality coupling model as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the water pollution source tracing and prediction method based on the hydrodynamic-water quality coupling model as described in any one of claims 1 to 4.

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