Water pollution tracing and predicting method based on hydrodynamic force-water quality coupling model

Abstract

The invention provides a water pollution traceability and prediction method based on a hydrodynamic force-water quality coupling model, and the method comprises the steps: generating a model file based on hydrological data and actually measured hydrological data of Jiaodong water transfer project-Huang-Jiaoqing line sections, and importing the model file into a hydrodynamic force model, according to the difference degree of a water level simulation value output by the hydrodynamic model and a water level measured value, calibration roughness and a leakage coefficient, establishing a hydrodynamic model matched with the Yellow-Jichi-Qi line section; the boundary file is updated based on the water quality boundary condition, the AD parameter file and the initial concentration value of the water quality parameter are imported into a convection diffusion model, the longitudinal diffusion coefficient and the attenuation coefficient are calibrated according to the difference degree between the water quality parameter concentration simulation value output by the convection diffusion model and the concentration measured value, and the convection diffusion model matched with the Huangxi Jicqing line section is established; and tracing and predicting water pollution by adopting an adaptive hydrodynamic model and a convective diffusion model. According to the invention, the accuracy and efficiency of water pollution tracing and prediction can be improved.

Description

Technical Field

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

[0002] The Jiaodong Yellow River Water Diversion Project is a water diversion project that diverts water from the Yellow River from Binzhou City, Shandong Province to Weihai City. After the project is completed, it will realize the joint dispatch of water from the Yangtze River, the Yellow River, and local water, thereby alleviating the shortage of water resources in Jiaodong and even the entire province. In the process of water diversion, it is necessary to clarify the conventional and sudden pollution sources of the Jiaodong Water Diversion Project, provide water quality safety guarantees for the typical channel sections of the Jiaodong Water Diversion Project, and then ensure the water volume and quality safety of the Jiaodong Water Diversion Project, and achieve the overall goal of "sending clean water to the east through one channel".

[0003] Based on the above work objectives, there is an urgent need to master the water quality transfer laws in typical canal sections of water diversion projects, to provide a basis for the study of the changing laws of various water quality indicators under various working conditions, and thus to 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 source tracing and prediction method based on a hydrodynamic-water quality coupling model, which can improve the accuracy and efficiency of water pollution source 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: 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; 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, and the AD parameter file and the initial concentration values ​​of the water quality parameters are imported into the convection diffusion model of MIKE11. According to the difference between the simulated value of the water quality parameter concentration output by the convection diffusion model and the measured value of the water quality parameter concentration, the longitudinal diffusion coefficient and the attenuation coefficient of the flow diffusion model are calibrated to establish a convection diffusion model suitable for the Yellow River to Jiqing line section; the water quality parameters include TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; 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.

[0006] In a possible implementation, the hydrological data and measured hydrological data of the Jiaodong Water Diversion Project-Yellow River to Jiqing section are used to generate a model file, the model file is imported into the hydrodynamic model of MIKE11, and the roughness and leakage coefficient of the hydrodynamic model are calibrated according to the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, so as to establish 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, generalizing the Yellow River-Jinan-Qingdao section into a one-dimensional river channel including a water diversion port and a water lifting pump station; wherein the water lifting pump station includes Songzhuang Pump Station, Wangnuo Pump Station, Tingkou Pump Station, and Jihongtan Pump Station; 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, and use the cross-section interpolation tool to process the cross-section measured data of the Yellow River to Jiqing section to generate a 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 to 1d, setting the time step to 180, selecting the flow data within a specific time range, selecting the water level data of the same period at the lower boundary, and generating the flow time series of two inflows, a specific water diversion and a pump station and the lower boundary water level time series; 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 sedimentation basin, and the flow at the Beidi culvert gate is selected as the water diversion volume of the Yellow River; the lower boundary is set as the inlet of the Jihongtan Reservoir; the boundary type of the upper boundary selects flow, the lower boundary is controlled by water level, and the corresponding water level time series file is associated; the water confluence and diversion are generalized as point sources, the boundary description selects point source, the boundary type is flow, and the time flow series of each diversion is associated; the diversion flow is set to a negative number to represent outflow; the water confluence point is set to a point source, and the flow time series of the total inflow is associated; 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-Jinan-Qingdao section is a full-section reinforced concrete lining, and the initial roughness ratio is: 0.015 for the water 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 inverted siphon gate, and 0.03 for the Mihe inverted siphon gate to the The value for Tingkou Pump Station is 0.018, and the value for Tingkou Pump Station to Jihongtan Pump 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 the Jihongtan Pump Station, and 1e-005 for the locations of the water diversion channel and outlet channel of Songzhuang Pump Station, Wangnuo Pump Station, Tingkou Pump Station, and Jihongtan Pump 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 hydrodynamic model of MIKE11 to calibrate the roughness and leakage coefficient until the difference between the simulated water level value output by the hydrodynamic model and the measured water level value meets the first calibration termination condition, and establish a hydrodynamic model suitable for the Yellow River to Jiqing section.

[0007] In a possible implementation, the boundary file is updated based on the water quality boundary condition, the AD parameter file and the initial concentration value of the water quality parameter 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 value of the water quality parameter concentration output by the convection diffusion model and the measured value of the water quality parameter concentration, and a convection diffusion model adapted to the Yellow River-Jinan-Qingdao line section is established, including: Step 2.1: Set up the AD parameter file, including: setting the names of water quality parameters, which are TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; setting the concentration units of water quality parameters, which are all 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-Jinan-Qingdao 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 of each sub-section in the Yellow River-Jinan-Qingdao section; Step 2.5: Add water quality boundary conditions 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 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 actual concentration value meets the second calibration termination condition, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section.

[0008] In a possible implementation, a hydrodynamic model and a convection-diffusion model adapted to the Yellow River to Jiqing section are used to trace the source of water pollution in the Yellow River to Jiqing 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 line 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 the concentration change trend of the target water quality parameter within the area where the target location is located will be determined based on the hydrodynamic model and the convection-diffusion model, and the pollution source of the target water quality parameter will be determined based on the concentration change trend.

[0009] In a 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: The proposed prediction time period and location point are input, and simulation data matching the proposed prediction time period and location point are searched from the simulation data sets of the hydrodynamic model and the convection-diffusion model.

[0010] In a possible implementation, the method further includes: 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 and predict the water pollution in the basin to be treated.

[0011] In a possible implementation, 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.

[0012] 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: A hydrodynamic model building 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 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; 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, import the AD parameter file and the initial concentration value of the water quality parameter 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 measured value of the water quality parameter concentration, and establish a convection diffusion model suitable for the Yellow River to Jiqing line 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 the water pollution of the Yellow River to Jiqing section by adopting the hydrodynamic model and convection-diffusion model adapted to the Yellow River to Jiqing section.

[0013] In the 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, and when the electronic device is running, the processor communicates with the memory 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 the first aspects.

[0014] 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.

[0015] 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.

[0016] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. 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 related drawings can be obtained based on these drawings without paying creative work.

[0018] 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; Figure 2 A generalized diagram of a river network provided by an embodiment of the present application is shown; Figure 3.1 A schematic diagram of the simulation result of the water level of the grit chamber outlet gate provided in the embodiment of the present application is shown; 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; 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; Figure 4.1 A schematic diagram of the verification result of the water level of the grit chamber outlet gate provided in an embodiment of the present application is shown; Figure 4.2 A schematic diagram of the water level verification result of the Jiaolai River inverted siphon provided in an embodiment of the present application is shown; Figure 4.3 A schematic diagram of the water level verification result of the inverted siphon gate of the Zhushui River provided in an embodiment of the present application is shown; Figure 5 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 is shown; Figure 6 A schematic diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0019] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme 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 part of the embodiments of the present application, rather than all of 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 claimed 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 belong to the scope of protection of the present application.

[0020] The Jiaodong Yellow River Water Diversion Project is a water diversion project that diverts water from the Yellow River from Binzhou City, Shandong Province to Weihai City. After the project is completed, it will realize the joint dispatch of water from the Yangtze River, the Yellow River, and local water, thereby alleviating the shortage of water resources in Jiaodong and even the entire province. In the process of water diversion, it is necessary to clarify the conventional and sudden pollution sources of the Jiaodong Water Diversion Project, provide water quality safety guarantees for the typical channel sections of the Jiaodong Water Diversion Project, and then ensure the water volume and quality safety of the Jiaodong Water Diversion Project, and achieve the overall goal of "sending clean water to the east through one channel".

[0021] Based on the above work objectives, there is an urgent need to master the water quality transfer laws in typical canal sections of water diversion projects, to provide a basis for the study of the changing laws of various water quality indicators under various working conditions, and thus to make scientific predictions on water quality changes under multiple scenarios, so as to better formulate corresponding water quality risk countermeasures.

[0022] 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.

[0023] The defects existing 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.

[0024] The technical solutions in the present application will be clearly and completely described below in conjunction with the drawings in 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 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 present 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 belong to the scope of protection of the present application.

[0025] 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.

[0026] 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: 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.

[0027] The model files include river network files, cross-section files, time series files, boundary files, HD parameter files, and simulation files.

[0028] 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 suitable for the Yellow River-Jinan-Qingdao section.

[0029] Wherein, the water quality parameters include TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus.

[0030] S103. Use the hydrodynamic model and convection-diffusion model suitable for the Yellow River to Jiqing section to trace and predict water pollution in the Yellow River to Jiqing section.

[0031] The embodiment of the present application uses MIKE11 software to achieve the tracing and prediction of water pollution. MIKE11 software is a watershed hydrological simulation software, which is widely used in hydrodynamics, water quality, water conservancy engineering simulation, etc. MIKE11 software has various functions, including automatic calibration, sensitivity, uncertainty analysis, etc., and can customize simulation solutions and combine various modules to meet application needs.

[0032] (1) Principle of one-dimensional hydrodynamic model The MIKE11 hydrodynamic module (HD) is the core component of the MIKE11 software system. It can conduct scientific and reasonable hydrodynamic simulation research on most one-dimensional water bodies. It is also the basis and premise of the water quality model (convection-diffusion model AD), and plays a very important role. The hydrodynamic module uses the 6-point Abbott-Ionescu finite difference method to solve the Saint-Venant equations and accurately simulate the hydrodynamic conditions during the study period. Because the basic equations of unsteady flow are composed of continuity equations and motion equations, they are applicable to both continuous and discontinuous physical quantities. The equations are as follows:

[0033] Continuity equation: Equations of motion: Among them, 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 gravity acceleration; R is the hydraulic radius of the cross-sectional area; C is the resistance coefficient; b s is the width of the water surface.

[0034] (2) Principle of one-dimensional water quality model The water quality module (AD) of MIKE11 software is a tool specifically used to study the migration and transformation laws 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 pollutants. Therefore, the control equation of the one-dimensional water quality model includes both the transport and diffusion terms and the attenuation terms of pollutants. The control equation of the one-dimensional water quality model is as follows:

[0035] The basic equation of convection-diffusion in one-dimensional unsteady flow: Among them, A is the cross-sectional area, C is the water quality index concentration; 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 sink concentration; and q is the side inflow flow.

[0036] The calculation formula of water pollutant diffusion coefficient is: D=aV b ; Where D is the diffusion coefficient, V is the flow velocity, and a and b are coefficients.

[0037] 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; decay coefficient K, in d -1 .

[0038] The embodiment of the present application establishes a hydrodynamic module (HD) based on measured hydrological conditions, and applies the convection diffusion module (AD) for calculation to simulate the spatiotemporal evolution of river pollutants. The convection diffusion module (AD) of MIKE11 is established based on the hydrodynamic module (HD), so it is necessary to build the hydrodynamic module (HD) first, and then build the convection diffusion module (AD).

[0039] Part I: Building a hydrodynamic model 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 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, specifically including: Step 1.1: Generate the river network file, including: generalize the river network of the Yellow River-Jinan-Qingdao section, and generalize the Yellow River-Jinan-Qingdao section into a one-dimensional river channel including water diversion outlets and water pumping stations; wherein the water pumping stations include Songzhuang Pumping Station, Wangno Pumping Station, Tingkou Pumping Station, and Jihongtan Pumping Station.

[0040] Specifically, the river network generalization should, in principle, make the generalized river network consistent with the actual situation in terms of water delivery, etc., 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 project situation. 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 a generalized river channel in 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 delivery capacity. There are few tributaries in the Yellow River-Jinan-Qingdao study area, which is an artificial water transfer channel with regular water transfer sections. Therefore, the median line of the river 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-level 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 for the embodiment of this application is Figure 2 In the figure, the circle links represent the river channel, and the squares represent the 4-level water pumping stations.

[0041] 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, and use the cross-section interpolation tool to process the cross-section measured data of the Yellow River to Jiqing line section to generate a cross-section file from the outlet gate to the Jihongtan Reservoir.

[0042] Specifically, the cross-section file is important information required for modeling, which contains key information such as the shape rules of the cross-section, the size of the hydraulic radius, the name of the river where it is located, and the mileage of the river where it is located. When establishing the cross-section file, the changes in the river network cross-section should be reflected as much as possible. At the same time, in the process of cross-section generalization, the consistency of hydraulic elements such as the cross-sectional area and the wetted perimeter should be ensured as much as possible. The simulation range of the study area is from the outlet gate to the Jihongtan Reservoir. According to the field visits and channel cross-section data, the water diversion channel of the Yellow River to Jiqing is an open channel with a trapezoidal cross-section, and the channel shape does not change much. 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) Input the measured original cross-sectional data into the cross-sectional editor, and observe whether the cross-sectional shape and point positions are reasonable from the image window. If there are unreasonable points, correct the unreasonable data; (2) The intervals between cross-sectional data collected are relatively long, the cross-sectional data are lacking, 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 interpolate at intervals of 1000m to improve the simulation accuracy; (3) In order to reduce the instability of the model, add a cross-sectional area with the same value as the cross-sectional area at the pump station 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 and closed irregular, closed circular, and closed rectangular. The open channel type is selected based on the actual project situation.

[0043] 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 at the lower boundary, and generating flow time series of two inflows, specific water diversions and pumping stations and lower boundary water level time series.

[0044] Specifically, the time series file is a necessary file for setting boundary conditions. Create a new time series file, set the time axis to equal time intervals, set the calculation step to 1d (1 day), and set the time step to 180. Filter the existing inflow and diversion flow data, select the flow data from January 1, 2021 to June 30, 2021 as the flow data within a specific time range, and select the water level data of the same period at the lower boundary. Generate two flow time series files for inflow, partial diversion, and pumping station, as well as the lower boundary water level time series file.

[0045] 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 sedimentation basin, and the flow at the north dike culvert is selected as the water diversion volume of the Yellow River; the lower boundary is set as the inlet of the Jihongtan Reservoir; the boundary type of the upper boundary selects flow, the lower boundary is controlled by water level, and the corresponding water level time series file is associated; the water confluence and diversion outlet are generalized as point sources, the boundary description selects 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.

[0046] Specifically, boundary conditions include external boundaries (open boundaries) and internal boundaries (point sources, non-point sources, global domains, buildings, closed boundaries), which can represent the interaction between external environmental conditions and the model. Among them, the open boundary describes the intersection of the model boundary and the external environment, simulating the starting point and outflow point. The boundary types of open boundaries 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 the river section and the river network. The principle of selecting boundary conditions is: the problem to be calculated must be mathematically well-posed, physically reasonable, and the results must be stable.

[0047] 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-Jinan-Qingdao section is a full-section reinforced concrete lining, and the initial roughness ratio is: 0.015 for the water 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 inverted siphon gate, and 0.03 for the Mihe inverted siphon gate to the The value for Tingkou Pumping Station is 0.018, and the value for the value between Tingkou Pumping Station and Jihongtan Pumping Station is 0.024. The initial leakage coefficient is: 1e-005 for the outlet gate of the sedimentation tank to the inverted siphon gate of Bailang River, 1e-008 for the inverted siphon gate of Bailang River to the regulating gate of Wugou River, 1e-005 for the regulating gate of Wugou River 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.

[0048] Specifically, there are two main aspects of parameter setting. One is the setting of initial conditions, that is, the setting of initial water level and flow, in order to ensure the normal operation of the model. The other is the definition of parameters such as riverbed roughness and permeability coefficient. These should be determined based on the simulated river conditions and model simulation conditions.

[0049] Initial condition setting Usually, the initial flow rate is often set to 0. However, in principle, when setting the initial conditions, it should be as consistent as possible with the actual hydrodynamic conditions at the initial simulation time. Therefore, it is set here to the initial value measured during the project operation.

[0050] Parameter setting: Riverbed roughness is an important parameter for measuring the impact of the roughness of the riverbed wall on the flow of the river and conducting hydrological analysis. It is the key to numerical simulation. It is closely related to factors such as the shape of the river channel, the roughness of the channel, and the height of the water level, and it is difficult and complicated to determine. The riverbed roughness can be determined by the riverbed resistance method (divided into uniform sections and three-layer areas), the resistance formula method (divided into Manning coefficient M, generally 10-100, Manning coefficient n, generally 0.01-0.1, Xie Cai coefficient C, Darcy weir gap), the global value method, and the local value method. Field investigations show that the channel lining is a full-section reinforced concrete lining. Combine the actual water diversion operation in the later stage with the previous experience value to preliminarily set the roughness.

[0051] The setting of leakage coefficient can simulate the water loss of the channel seeping into the ground during water transfer, which has an important impact on the simulation results. The leakage coefficient is initially set based on the actual water diversion operation and construction plan data in the later stage.

[0052] 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.

[0053] Specifically, the simulation file is to integrate the files created in step 1.1 to step 1.5 to perform hydrodynamic simulation. After the above settings are completed, create a simulation file, select hydrodynamics as the model, select non-constant as the simulation mode, and set the time step to 30 minutes. Select Start Simulation on the Start page, and output the specified file on the Results page. The hydrodynamic simulation is now complete.

[0054] Step 1.7: Run the hydrodynamic model of MIKE11 to calibrate the roughness and leakage coefficient until the difference between the simulated water level value output by the hydrodynamic model and the measured water level value meets the first calibration termination condition, and establish a hydrodynamic model suitable for the Yellow River to Jiqing section.

[0055] 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 is basically consistent with the measured water level, achieving a reasonable error range.

[0056] (1) Establishing a hydrodynamic model - water level simulation 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, they are respectively a schematic diagram of the simulation results of the water level of the sedimentation tank outlet gate, a schematic diagram of the simulation results of the water level of the Jiaolai River inverted siphon gate, and a schematic diagram of the simulation results of the water level of the Zhushui River inverted siphon gate provided in the embodiments of the present application. 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, the absolute value of the error is less than 0.2m, and the relative error is 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 accuracy, and the wave peaks can basically reach consistency, but there are still certain errors, which may be caused by the following reasons: there are few cross-section data, which have a certain gap with the actual channel and are not accurate enough; the simulation time and the collected data are limited, and the other buildings in the project, such as the inverted siphon and regulating gate, are not considered and cannot be included in the model simulation.

[0057] (2) Establishing a hydrodynamic model - hydrodynamic module verification 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 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 provided in the embodiments of the present application. Figure 4.2 , Figure 4.3 In the model water level verification, the absolute value of the error between the simulated highest water level and the measured highest water level in the three monitoring sections selected was less than 0.2m, and the relative error was less than 1.57%, indicating that the parameter calibration was reasonable.

[0058] Part II: Convection-Diffusion Modeling 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.

[0059] Step S102 updates the boundary file based on the water quality boundary conditions, imports the AD parameter file and the initial concentration value of the water quality parameter into the convection diffusion model of MIKE11, and calibrates 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 measured value of the water quality parameter concentration, and establishes a convection diffusion model suitable for the Yellow River-Jinan-Qingdao section, specifically 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.

[0060] Specifically, set seven simulated water quality parameters, namely TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus. Only use the AD module: In the component interface, enter the name of the component to be simulated in each row, and select mg / L as the concentration unit; use Ecolab based on the AD module to conduct in-depth water quality simulation, with consistent component names and sorting.

[0061] 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.

[0062] 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 taken. The diffusion coefficient is initially set to the global value, and the local value is modified later according to the calibration situation.

[0063] Step 2.3: Set the initial concentration value 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.

[0064] Specifically, the initial conditions of the AD module are set with the measured values ​​at the first time to ensure the stability of the model startup. Only use the AD module: enter the initial concentration value of each component in the initial condition interface; select "Global" if the initial condition is a global value; enter the river section name and mileage for local values; Apply Ecolab based on the AD module: define it in Ecolab.

[0065] 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 of each sub-section in the Yellow River-Jinan-Qingdao section.

[0066] Specifically, the attenuation coefficient (Decay) is a calibration coefficient. The embodiment of this application divides the study area into three sections (export gate-Songzhuang pumping station-Songzhuang water diversion gate-Jihongtan pumping station), that is, three sub-line sections, and sets their attenuation coefficients respectively. The coefficient unit is preliminarily set through relevant research, and the attenuation coefficient is finally determined through calibration through measured data. Only use AD module: define appropriate attenuation coefficients for non-conservative material components, the unit is / day, that is, d -1 ; Applying Ecolab based on the AD module: the attenuation coefficient is not defined (Ecolab itself simulates the attenuation coefficient).

[0067] Step 2.5: Add water quality boundary conditions to the boundary file.

[0068] Specifically, add water quality boundary conditions based on the HD boundary file. Save the collected original boundary water quality data in the water quality boundary file. Due to the lack of measured data, the boundary concentrations are all constant values. Some concentration values ​​are saved in another file and are measured values. Open the boundary file, select the boundary information definition of the upper area, and enter the corresponding concentration value.

[0069] 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 actual concentration value meets the second calibration termination condition, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section.

[0070] Specifically, in the simulation file, check Advention-Dispersion; import the AD parameter file in the Input interface; enter the simulation interface, define the initial condition selection of the AD simulation; finally define the result output file name and save frequency, and enter the Start interface to start the calculation. The parameters that the AD module needs to calibrate are the pollutant attenuation coefficient and the longitudinal diffusion coefficient. Three sections from March 2023 to June 2024 are selected as verification sections, and the measured data and simulation data are compared. If the relative error of most results is kept within 20%, it generally meets the modeling requirements, that is, it meets the second calibration termination condition.

[0071] 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 of the Yellow River-Jinan-Qingdao 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 line 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 the concentration change trend of the target water quality parameter within the area where the target location is located will be determined based on the hydrodynamic model and the convection-diffusion model, and the pollution source of the target water quality parameter will be determined based on the concentration change trend.

[0072] Among them, the target location is any detection location within the Yellow River-Jinan-Qingdao section, and the target water quality parameter is any water quality parameter among TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus. If the concentration of a 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 a 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, an area within the Yellow River-Jinan-Qingdao section that is less than 5 km away from the target location is used as a reference area, and several reference locations are selected from the reference area at intervals of 500 m, and the concentration of the target water quality parameter at the reference location is tested. With the target location as the center, find the changing trend of the target water quality parameter concentration within the target location, for example, from high concentration to low concentration, or from low concentration to high concentration, or from low concentration to high concentration and then from high concentration to low concentration, and take the location with the highest concentration as the source of the target water quality parameter pollution. Among them, the area where the above target location is located must be larger than the reference area, and the area size can be set at will according to the actual situation.

[0073] 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 to Jiqing section are used to predict water pollution in the Yellow River to Jiqing section, including: The proposed prediction time period and location point are input, and simulation data matching the proposed prediction time period and location point are searched from the simulation data sets of the hydrodynamic model and the convection-diffusion model.

[0074] 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 many 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 atypical 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: Step 3.1: Establish hydrodynamic models and convection-diffusion models for several typical watersheds.

[0075] Step 3.2: Based on the basic information of the watershed, calculate the similarity between the watershed to be processed and each typical watershed.

[0076] 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.

[0077] In order to improve the accuracy of similarity calculation, the basic information is enriched as much as possible, and the basic information can be used to restore the characteristics of the watershed to the greatest extent. Specifically, the basic information can be processed into a basic information vector, and the distance between the vectors is calculated, and the typical watershed with the shortest distance is used as the most similar typical watershed to the watershed to be processed. Alternatively, the Kmeans clustering method is used to cluster the watershed to be processed and K typical watersheds, and the typical watershed classified into the same category as the watershed to be processed is used as the typical watershed with the highest similarity to the watershed to be processed.

[0078] Based on the same inventive concept, the embodiment of the present application also provides a water pollution source tracing and prediction device based on a hydrodynamic-water quality coupling model corresponding to the water pollution source tracing and prediction method based on a hydrodynamic-water quality coupling model. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the water pollution source tracing and prediction method based on a hydrodynamic-water quality coupling model in the embodiment 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.

[0079] See also Figure 5 As shown, Figure 5 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 comprising: The hydrodynamic model building 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 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 adapted to 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 convection diffusion model establishment module 502 is used to update the boundary file based on the water quality boundary conditions, import the AD parameter file and the initial concentration value of the water quality parameter 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 measured value of the water quality parameter concentration, and establish a convection diffusion model suitable for the Yellow River to Jiqing line section; the water quality parameters include TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; The water pollution source tracing 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.

[0080] In a possible implementation, the hydrodynamic model building 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 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, generalizing the Yellow River-Jinan-Qingdao section into a one-dimensional river channel including a water diversion port and a water lifting pump station; wherein the water lifting pump station includes Songzhuang Pump Station, Wangnuo Pump Station, Tingkou Pump Station, and Jihongtan Pump Station; 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, and use the cross-section interpolation tool to process the cross-section measured data of the Yellow River to Jiqing section to generate a 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 to 1d, setting the time step to 180, selecting the flow data within a specific time range, selecting the water level data of the same period at the lower boundary, and generating the flow time series of two inflows, a specific water diversion and a pump station and the lower boundary water level time series; 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 sedimentation basin, and the flow at the Beidi culvert gate is selected as the water diversion volume of the Yellow River; the lower boundary is set as the inlet of the Jihongtan Reservoir; the boundary type of the upper boundary selects flow, the lower boundary is controlled by water level, and the corresponding water level time series file is associated; the water confluence and diversion are generalized as point sources, the boundary description selects point source, the boundary type is flow, and the time flow series of each diversion is associated; the diversion flow is set to a negative number to represent outflow; the water confluence point is set to a point source, and the flow time series of the total inflow is associated; 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-Jinan-Qingdao section is a full-section reinforced concrete lining, and the initial roughness ratio is: 0.015 for the water 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 inverted siphon gate, and 0.03 for the Mihe inverted siphon gate to the The value for Tingkou Pump Station is 0.018, and the value for Tingkou Pump Station to Jihongtan Pump 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 the Jihongtan Pump Station, and 1e-005 for the locations of the water diversion channel and outlet channel of Songzhuang Pump Station, Wangnuo Pump Station, Tingkou Pump Station, and Jihongtan Pump 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 hydrodynamic model of MIKE11 to calibrate the roughness and leakage coefficient until the difference between the simulated water level value output by the hydrodynamic model and the measured water level value meets the first calibration termination condition, and establish a hydrodynamic model suitable for the Yellow River to Jiqing section.

[0081] In a 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 value of the water quality parameter into the convection-diffusion model of MIKE11, and calibrates 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 measured value of the water quality parameter concentration, and establishes a convection-diffusion model adapted to the Yellow River-Jinan-Qingdao line section, including: Step 2.1: Set up the AD parameter file, including: setting the names of water quality parameters, which are TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; setting the concentration units of water quality parameters, which are all 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-Jinan-Qingdao 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 of each sub-section in the Yellow River-Jinan-Qingdao section; Step 2.5: Add water quality boundary conditions 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 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 actual concentration value meets the second calibration termination condition, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section.

[0082] In a possible implementation, the water pollution source tracing prediction module 503, when tracing the water pollution of the Yellow River to Jilin and Qingdao section by using a hydrodynamic model and a convection-diffusion model adapted to the Yellow River to Jilin and Qingdao section, includes: If it is detected that the concentration of the target water quality parameter at the target location within the Yellow River-Jinan-Qingdao line 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 the concentration change trend of the target water quality parameter within the area where the target location is located will be determined based on the hydrodynamic model and the convection-diffusion model, and the pollution source of the target water quality parameter will be determined based on the concentration change trend.

[0083] In a possible implementation, the water pollution source tracing prediction module 503, when using a hydrodynamic model and a convection-diffusion model adapted to the Yellow River to Jiqing section to predict water pollution in the Yellow River to Jiqing section, includes: The proposed prediction time period and location point are input, and simulation data matching the proposed prediction time period and location point are searched from the simulation data sets of the hydrodynamic model and the convection-diffusion model.

[0084] In a possible implementation, the device further includes: Typical coupling model building module, used to build hydrodynamic models and convection-diffusion models for multiple typical river basins; A 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 treated by using the hydrodynamic model and convection-diffusion model of the typical watershed with the highest similarity to the watershed to be treated.

[0085] In a possible implementation, the device further includes: an Ecolab simulation module, which is used to simulate the convection diffusion process of a substance in a water body using Ecolab based on the convection diffusion model.

[0086] The water pollution 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 tracing and prediction.

[0087] See also Figure 6 As shown, Figure 6 A 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, when the electronic device is running, the processor 601 communicates with the memory 602 via the bus 603, 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.

[0088] 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.

[0089] Corresponding to the above-mentioned water pollution tracing and prediction method based on the hydrodynamics-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 executed by the processor, the steps of the above-mentioned water pollution tracing and prediction method based on the hydrodynamics-water quality coupling model are executed.

[0090] Those skilled in the art can clearly understand that, for the convenience and simplicity 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 the present 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.

[0091] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0092] 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.

[0093] If the function is implemented in the form of a software function module and sold or used as an independent product, it 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, including several instructions for 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: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0094] 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 protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope 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 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; 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, and the AD parameter file and the initial concentration values ​​of the water quality parameters are imported into the convection diffusion model of MIKE11. According to the difference between the simulated value of the water quality parameter concentration output by the convection diffusion model and the measured value of the water quality parameter concentration, the longitudinal diffusion coefficient and the attenuation coefficient of the flow diffusion model are calibrated to establish a convection diffusion model suitable for the Yellow River to Jiqing line section; the water quality parameters include TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; 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.

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: The hydrological data and measured hydrological data of the Jiaodong Water Diversion Project-Yellow River to Jiqing section are used to generate a model file, the model file is imported into the hydrodynamic model of MIKE11, the roughness and leakage coefficient of the hydrodynamic model are calibrated according to the difference between the water level simulation value output by the hydrodynamic model and the measured water level value, and a hydrodynamic model adapted to the Yellow River to Jiqing section is established, including: Step 1.1: generating 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 including a water diversion port and a water lifting pump station; wherein the water lifting pump station includes Songzhuang Pump Station, Wangnuo Pump Station, Tingkou Pump Station, and Jihongtan Pump Station; 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, and use the cross-section interpolation tool to process the cross-section measured data of the Yellow River to Jiqing section to generate a 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 to 1d, setting the time step to 180, selecting the flow data within a specific time range, selecting the water level data of the same period at the lower boundary, and generating the flow time series of two inflows, a specific water diversion and a pump station and the lower boundary water level time series; 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 sedimentation basin, and the flow at the Beidi culvert gate is selected as the water diversion volume of the Yellow River; the lower boundary is set as the inlet of the Jihongtan Reservoir; the boundary type of the upper boundary selects flow, the lower boundary is controlled by water level, and the corresponding water level time series file is associated; the water confluence and diversion are generalized as point sources, the boundary description selects point source, the boundary type is flow, and the time flow series of each diversion is associated; the diversion flow is set to a negative number to represent outflow; the water confluence point is set to a point source, and the flow time series of the total inflow is associated; 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-Jinan-Qingdao section is a full-section reinforced concrete lining, and the initial roughness ratio is: 0.015 for the water 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 inverted siphon gate, and 0.03 for the Mihe inverted siphon gate to the The value for Tingkou Pump Station is 0.018, and the value for Tingkou Pump Station to Jihongtan Pump 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 the Jihongtan Pump Station, and 1e-005 for the locations of the water diversion channel and outlet channel of Songzhuang Pump Station, Wangnuo Pump Station, Tingkou Pump Station, and Jihongtan Pump 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 hydrodynamic model of MIKE11 to calibrate the roughness and leakage coefficient until the difference between the simulated water level value output by the hydrodynamic model and the measured water level value meets the first calibration termination condition, and establish a hydrodynamic model suitable for the Yellow River to Jiqing section.

3. The water pollution source tracing and prediction method based on the hydrodynamic-water quality coupling model according to claim 2 is characterized in that: The boundary file is updated based on the water quality boundary condition, the AD parameter file and the initial concentration value of the water quality parameter 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 value of the water quality parameter concentration output by the convection diffusion model and the measured value of the water quality parameter concentration, and a convection diffusion model adapted to the Yellow River-Jinan-Qingdao line section is established, including: Step 2.1: Set up the AD parameter file, including: setting the names of water quality parameters, which are TN, COD, sulfate, fluoride, chloride, permanganate index, and total phosphorus; setting the concentration units of water quality parameters, which are all 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-Jinan-Qingdao 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 of each sub-section in the Yellow River-Jinan-Qingdao section; Step 2.5: Add water quality boundary conditions 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 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 actual concentration value meets the second calibration termination condition, and establish a convection-diffusion model suitable for the Yellow River-Jinan-Qingdao section.

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 hydrodynamic model and convection-diffusion model adapted to the Yellow River to Jiqing section are used to trace the source of water pollution in the Yellow River to Jiqing 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 line 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 the concentration change trend of the target water quality parameter within the area where the target location is located will be determined based on the hydrodynamic model and the convection-diffusion model, and the pollution source of the target water quality parameter will be determined based on the concentration change trend.

5. 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 Ji'nan-Qingdao section is predicted by using the hydrodynamic model and convection-diffusion model adapted to the Yellow River to Ji'nan-Qingdao section, including: Input a proposed prediction time period and a location point, and search for simulation data matching the proposed prediction time period and the location point from the simulation data sets of the hydrodynamic model and the convection-diffusion model.

6. 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 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 and predict the water pollution in the basin to be treated.

7. 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 comprises: based on the convection diffusion model, applying Ecolab to simulate the convection diffusion process of the substance in the water body.

8. 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 building 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 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; 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, import the AD parameter file and the initial concentration value of the water quality parameter 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 measured value of the water quality parameter concentration, and establish a convection diffusion model suitable for the Yellow River to Jiqing line 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 the water pollution of the Yellow River to Jiqing section by adopting the hydrodynamic model and convection-diffusion model adapted to the Yellow River to Jiqing section.

9. 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 communicates with the memory via 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 7.

10. 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 method for tracing and predicting the source of water pollution based on a hydrodynamic-water quality coupling model as described in any one of claims 1 to 7.

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