Methods, apparatus, media and computer equipment for constructing urban water network models

Abstract

This application relates to a method, apparatus, medium, and computer equipment for constructing urban water network models. The method includes: establishing a coupled InfoWorks ICM-Delft 3D model based on an InfoWorks ICM model and a Delft 3D model; establishing an objective function based on the coupled InfoWorks ICM-Delft 3D model; and determining at least a flood control plan based on preset rules and the objective function. The apparatus uses the method described above. This application, by establishing a coupled InfoWorks ICM-Delft 3D model, then establishing an objective function, and finally training the objective function according to preset rules to determine the flood control plan, can better establish a drainage and flood control model for simulating and predicting flood control systems and tracing the source of water pollution. It also has high data processing efficiency and improves the accuracy of water depth prediction for non-monitoring units and the accuracy of water quality process change prediction.

Description

[Technical Field]

[0001] This application relates to the field of urban construction technology, and in particular to methods, apparatus, media and computer equipment for constructing urban water network models. [Background Technology]

[0002] In urban water resource management and urban flood control planning, it is becoming increasingly important to conduct systematic water network modeling for prediction. By establishing models, it is possible to simulate and analyze related processes such as urban hydrological cycles, water quality, and flooding. Furthermore, it is possible to predict surface water depth, monitor inland water quality, and trace the source of water pollution. Existing technology CN114925923B uses the InfoWorks ICM model to simulate and predict surface water depth, thereby improving the accuracy of water depth prediction for non-monitoring units. Existing technology CN116205134A improves the prediction accuracy of water quality process changes by simulating water pollution values ​​using Delft-3D technology.

[0003] However, in existing urban water resource management and flood control planning, the different data formats and data structures used by InfoWorks ICM and Delft3D lead to data integration and consistency issues during model coupling and data transfer. Furthermore, the computational efficiency is often low when dealing with processes such as hydrological cycles and flooding involved in urban water resource management and flood control planning. [Summary of the Invention]

[0004] To enable the establishment of water network models for system simulation and prediction, and to trace the sources of water pollution, and to improve the efficiency of handling processes such as hydrological cycles and flooding involved in urban water resource management and flood control planning, this invention establishes a coupled model using InfoWorks ICM-Delft 3D, then establishes an objective function, and finally trains the objective function according to preset rules to determine flood control planning.

[0005] The present invention proposes the following solution:

[0006] Methods for constructing urban water network models include:

[0007] Based on the InfoWorks ICM model and the Delft 3D model, establish a coupled model of InfoWorks ICM and Delft 3D;

[0008] Based on the coupled model of InfoWorks ICM-Delft 3D, establish the objective function;

[0009] Based on the preset rules and objective function, at least the flood control plan should be determined.

[0010] The method for constructing the urban water network model as described above, specifically the step of establishing a coupled InfoWorks ICM-Delft 3D model based on the InfoWorks ICM model and the Delft 3D model, includes:

[0011] Create InfoWorks ICM models and Delft 3D models;

[0012] Calibrate InfoWorks ICM models and Delft 3D models;

[0013] The calibrated InfoWorks ICM model and the calibrated Delft 3D model are coupled to generate a coupled InfoWorksICM-Delft 3D model, wherein the coupling includes at least horizontal spatial coupling, vertical spatial coupling, and input-output coupling.

[0014] The method for constructing the urban water network model as described above, including the steps of establishing the InfoWorks ICM model and the Delft 3D model, includes:

[0015] Obtain data from the drainage network;

[0016] Based on InfoWorks ICM software and drainage network data, generate an InfoWorks ICM model;

[0017] Verify the InfoWorks ICM model and determine the model parameter values;

[0018] Acquire target river information and generate a target river raster;

[0019] Based on the target river grid, determine the hydraulic boundary and pollutant concentration boundary of the target river;

[0020] A Delft 3D model is generated based on the hydraulic boundary and the pollutant concentration boundary.

[0021] The method for constructing the urban water network model as described above, wherein the coupled and calibrated InfoWorks ICM model and the calibrated Delft 3D model generate a coupled InfoWorks ICM-Delft 3D model, wherein the coupling includes at least the steps of horizontal spatial coupling, vertical spatial coupling, and input-output coupling, including:

[0022] Acquire the first observation data on the elevation of the target river surface and the second observation data on the pollutant concentration;

[0023] Based on the first and second observation data, generate the first tabular file of water surface elevation and pollutant time series required for the InfoWorks ICM model;

[0024] Determine the water surface elevation and pollutant time series of the discharge outlet in the InfoWorks ICM model, and update the InfoWorks ICM model database information through the first table file. The database information includes at least the water level curve, the pollutant process curve, and the inflow curve.

[0025] Based on the updated InfoWorks ICM model database information, a third table file is generated showing the time series of flow rates and pollutant concentrations at the emission outlets;

[0026] Based on the third table file, define the point source line pollution sources in the Delft 3D model, and convert the third table file into a disassembled file of the pollutant concentration and flow time series required for the Delft 3D model;

[0027] Based on the disassembled files, by running the Delft 3D model, time-series NC files of water surface elevation and pollutant concentration at various points in the target river basin are generated.

[0028] The method for constructing an urban water network model as described above, wherein the step of determining at least the flood control plan based on preset rules and an objective function includes:

[0029] Based on the objective function, determine the mutation strategy and control parameters of the objective function;

[0030] Based on the mutation strategy and control parameters of the objective function, a coupled model of InfoWorks ICM-Delft 3D is trained to determine the flood control plan.

[0031] The method for constructing an urban water network model as described above, the step of determining the mutation strategy and control parameters of the objective function based on the objective function, includes:

[0032] Choose the corresponding evaluation index, and its objective function f(X) i,G ) k The specific formula is as follows:

[0033]

[0034] In the formula, f(X) i,G ) k Let f(X) be the objective function value of the i-th individual at the k-th monitoring point in the G-th generation population. k,t Let X be the simulated value at time t for the k-th observation point; X is the parameter to be determined, X = (x1, x2, ..., xt). n );Y k,t The actual observed value at time t of the k-th observation point;

[0035] The objective function of the coupled model is determined as follows:

[0036]

[0037] The criteria for determining the parameters to be determined are as follows:

[0038]

[0039] In the formula, (x,y) are arbitrary geodetic coordinates; q is the pollution flow rate; c is the pollutant concentration; L(x,y) is the distance to the nearest node to (x,y); L max Let L(x,y) be the upper limit of the distance.

[0040] The apparatus for constructing an urban water network model includes:

[0041] The first module is used to create a coupled InfoWorksICM-Delft 3D model based on the InfoWorks ICM model and the Delft 3D model.

[0042] The second module is used to establish the objective function based on the coupled model of InfoWorks ICM-Delft 3D;

[0043] The determination module is used to determine at least the flood control plan based on preset rules and objective functions.

[0044] The urban water network model construction device described above, wherein the first construction module includes:

[0045] Create cells for building InfoWorks ICM models and Delft 3D models;

[0046] The calibration unit is used to calibrate InfoWorks ICM models and Delft 3D models;

[0047] A coupling unit is used to couple the calibrated InfoWorks ICM model and the calibrated Delft 3D model to generate a coupled InfoWorks ICM-Delft 3D model, wherein the coupling includes at least horizontal spatial coupling, vertical spatial coupling, and input-output coupling.

[0048] The establishment unit includes:

[0049] The first acquisition subunit is used to acquire data from the drainage network.

[0050] The first generation subunit is used to generate an InfoWorks ICM model network based on InfoWorks ICM software and drainage network data.

[0051] The first determining subunit is used to verify the InfoWorks ICM model network and determine the model parameter values;

[0052] The second generation subunit is used to acquire target river information and generate target river raster;

[0053] The second determining sub-unit is used to determine the hydraulic boundary and pollutant concentration boundary of the target river based on the target river grid.

[0054] The third generation sub-unit is used to generate a Delft 3D model based on the hydraulic boundary and the pollutant concentration boundary.

[0055] The coupling unit includes:

[0056] The second acquisition subunit is used to acquire the first observation data of the target river surface elevation and the second observation data of pollutant concentration.

[0057] The fourth generation subunit is used to generate a first table file of water surface elevation and pollutant time series required for the InfoWorks ICM model based on the first and second observation data.

[0058] The third determining subunit is used to determine the water surface elevation and pollutant time series of the discharge outlet in the InfoWorks ICM model, and to update the InfoWorks ICM model database information through the first table file. The database information includes at least the water level curve, the pollutant process curve and the inflow curve.

[0059] The fifth generation subunit is used to generate a third table file of time series of flow rate and pollutant concentration at the emission outlet based on the updated InfoWorks ICM model database information;

[0060] The processing subunit is used to define point source line pollution sources in the Delft 3D model based on the third table file, and convert the third table file into a disassembled file of pollutant concentration and flow time series required by the Delft 3D model;

[0061] The sixth generation subunit is used to generate time-series NC files of water surface elevation and pollutant concentration at various points in the target river basin by running the Delft 3D model based on the disassembled file.

[0062] The determining module includes:

[0063] The determination unit is used to determine the mutation strategy and control parameters of the objective function based on the objective function.

[0064] The training unit is used to train the coupled model of InfoWorks ICM-Delft3D based on the mutation strategy and control parameters of the objective function to determine the flood control plan.

[0065] The determining unit includes:

[0066] Choose the corresponding evaluation index, and its objective function f(X) i,G ) k The specific formula is as follows:

[0067]

[0068] In the formula, f(X) i,G ) k Let f(X) be the objective function value of the i-th individual at the k-th monitoring point in the G-th generation population. k,t Let X be the simulated value at time t for the k-th observation point; X is the parameter to be determined, X = (x1, x2, ..., xt). n );Y k,t The actual observed value at time t of the k-th observation point;

[0069] The objective function of the coupled model is determined as follows:

[0070]

[0071] The criteria for determining the parameters to be determined are as follows:

[0072]

[0073] In the formula, (x,y) are arbitrary geodetic coordinates; q is the pollution flow rate; c is the pollutant concentration; L(x,y) is the distance to the nearest node to (x,y); L max Let L(x,y) be the upper limit of the distance.

[0074] A computer-readable storage medium storing a computer program that, when executed by an urban water network model construction device, implements the urban water network model construction method described above.

[0075] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for constructing an urban water network model as described above.

[0076] This invention establishes a coupled model of InfoWorks ICM-Delft 3D, then establishes an objective function, and finally trains the objective function according to preset rules to determine flood control planning. This enables the establishment of a better drainage and flood control model for simulating and predicting flood control systems and tracing the source of water pollution. It also has high data processing efficiency and improves the accuracy of water depth prediction and water quality process change prediction for non-monitoring units. [Attached Image Description]

[0077] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0078] Figure 1 This is a flowchart of the method for constructing an urban water network model according to the first embodiment of the present invention;

[0079] Figure 2 yes Figure 1 Detailed flowchart of step S11;

[0080] Figure 3 yes Figure 2 Detailed flowchart of step S111;

[0081] Figure 4 yes Figure 2 Detailed flowchart of step S113;

[0082] Figure 5 yes Figure 1 Detailed flowchart of step S13;

[0083] Figure 6 This is a structural block diagram of the urban water network model construction device according to the second embodiment of the present invention;

[0084] Figure 7 yes Figure 6 Detailed structural block diagram of the first module 110;

[0085] Figure 8 yes Figure 7 A detailed structural block diagram of unit 111 is established in the middle;

[0086] Figure 9 yes Figure 7 Detailed structural block diagram of the intermediate coupling unit 113;

[0087] Figure 10 yes Figure 6 The detailed structural block diagram of module 130 is determined in the middle;

[0088] Figure 11 This is a structural block diagram of a computer device according to another embodiment of the present invention.

Detailed Implementation Methods

[0089] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Well-known modules, units, and their connections, links, communications, or operations are not shown or described in detail. Furthermore, the described features, architectures, or functions can be combined in any way in one or more embodiments. Those skilled in the art should understand that the various embodiments described below are only for illustrative purposes and not for limiting the scope of protection of the present invention. It is also readily understood that the modules, units, or processing methods in the various embodiments described herein and shown in the accompanying drawings can be combined and designed in various different configurations. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0090] The definitions of various terms or methods used in the following embodiments are, except where logically impossible, generally defined as broad concepts that can be implemented under the premise of the content disclosed in the embodiments. Under this understanding, all specific subordinate limitations of the terms or methods should be considered as part of the invention and should not be narrowly interpreted or biased simply because the specification does not disclose such a specific limitation. Similarly, provided that it is logically feasible, the order of the steps in the method is flexible and varied, and all specific subordinate limitations in the broad concepts of various terms or methods fall within the scope of protection of this invention.

[0091] First embodiment:

[0092] Please refer to Figures 1 to 5 As shown, this embodiment proposes a method for constructing an urban water network model, including S11-S13, wherein:

[0093] S11. Based on the InfoWorks ICM model and the Delft 3D model, establish a coupled model of InfoWorks ICM-Delft3D.

[0094] In this embodiment, the hardware platform of the coupled model mainly includes a server and a client computer; the server provides a cloud database for the multi-source monitoring system and a cloud data management platform for the client computer; the client computer mainly carries the running software required by the model, which includes at least Python programming software, InfoWorks ICM model software and Delft 3D model software.

[0095] The client computer obtains monitoring data through a VPN connection with the server, identifies and removes abnormal time periods and abnormal data points in the monitoring data, and then performs interpolation and smoothing processing through Sliner or Cubic functions to meet the monitoring data quality requirements of model calculation. The processed data is stored in the client computer in the form of a database for easy data reading during model operation.

[0096] As a preferred option rather than a specific limitation, step S11 includes S111-S113, wherein:

[0097] S111. Create the InfoWorks ICM model and the Delft 3D model.

[0098] In this embodiment, the corresponding drainage network model and sewage model are established using InfoWorks ICM software and Delft 3D software to better construct and solve the coupled model.

[0099] As a preferred option rather than a specific limitation, step S111 includes S1111-S1116, wherein:

[0100] S1111, Obtain data from the drainage network.

[0101] This embodiment utilizes existing basic data of the target area to obtain drainage network data, so as to obtain the drainage network data required for the target area, in order to facilitate InfoWorks ICM processing. The existing basic data includes at least satellite images and official database network distribution maps.

[0102] S1112. Generate an InfoWorks ICM model based on InfoWorks ICM software and drainage network data.

[0103] In this embodiment, the acquired drainage network data is imported into the InfoWorks ICM software for operation. After importing the network data, connectivity checks, engineering rationality checks, and longitudinal profile elevation information checks are performed to ensure accurate and stable generation of the InfoWorks ICM model, and stable and reliable operation.

[0104] S1113. Verify the InfoWorks ICM model and determine the model parameter values.

[0105] In this embodiment, the InfoWorks ICM software imports pipeline data and performs connectivity checks, engineering rationality checks, and longitudinal profile elevation information checks. Based on the actual needs of the model, it selects various time, physical, and mathematical parameters for the model. These parameters include at least the minimum baseflow depth, baseflow factor, slope at baseflow doubling point, minimum spatial step size, maximum spatial step size, lower-level Froude number, upper-level Froude number, minimum Presman slot width, Presman slot sensitivity coefficient, allowable depth, allowable flow rate, allowable water level, minimum water depth in the pipeline, maximum initial iteration count, time step, decomposition coefficient, and pipeline roughness coefficient. This allows for more accurate and reliable determination of model parameter values, making the InfoWorks ICM model run more stably and reliably.

[0106] S1114. Obtain target river information and generate target river raster.

[0107] This embodiment first obtains the target river information within the target area, selects the target river, and then uses an orthogonal rectangular grid system to divide the target river into grids to generate the target river grid, so as to facilitate stable and reliable data monitoring.

[0108] S1115. Based on the target river grid, determine the hydraulic boundary and pollutant concentration boundary of the target river.

[0109] In this embodiment, two open boundary sections of the target river are determined based on the target river grid. The two open boundary sections use water surface elevation monitoring data from sections 01# and 12#, and flow monitoring data from section 32#, respectively, as hydraulic boundaries. The conductivity monitoring data from sections 01# and 12# are used as pollutant concentration boundaries. The time series of pollutant concentrations at the water surface elevation monitoring data and the pollutant concentration boundaries are acquired by a distributed online monitoring instrument.

[0110] In this embodiment, the river flow of the target river is monitored by a distributed detector 32#. The flow meter 32# requires a measurement cross-section configuration. In order to improve the accuracy of river flow monitoring, the cross-section configuration of the flow sensor adopts the area function method. Then, the depth sounding data of the unmanned monitoring vessel is used, combined with the river water surface elevation monitoring data Z01# and Z12#, to calculate the absolute elevation and depth of the riverbed at various locations in the study area.

[0111] S1116. Generate a Delft 3D model based on the hydraulic boundary and pollutant concentration boundary.

[0112] In this embodiment, the obtained hydraulic boundary and pollutant concentration boundary are imported into Delft 3D software to generate the corresponding Delft 3D model, thereby enabling accurate and reliable calculation and analysis of the target river, and then determining the corresponding Delft 3D model parameters. The Delft 3D model parameters include at least the local time zone, time step, gravity, water density, riverbed bottom roughness formula, sliding conditions, 3D turbulence model, depth threshold, smoothing time, and edge depth.

[0113] S112, calibrate the InfoWorks ICM model and the Delft 3D model.

[0114] In order to ensure the stability of the model operation, this embodiment needs to calibrate the model. As the service time of the drainage pipe increases, the pipe elevation will shift to a certain extent, indicating the possibility of internal defects. Therefore, it is necessary to calibrate the drainage network of the target river in the InfoWorks ICM model. The calibration parameter is the bottom elevation inside the pipe, and the calibration index is NSE, with a maximum value of 1, and the higher the better.

[0115] This embodiment first calibrates the InfoWorks ICM model, selecting monitoring point #21 to analyze the calibration effect. The simulated and observed values ​​of water surface elevation and conductivity before and after calibration are compared. The water surface elevation and conductivity at the monitoring point show a trend close to the observed values ​​after calibration. If there is still a significant deviation from the observed values ​​overall, and the final NSE index is also low, it indicates that the calibration effect of the drainage network is not ideal, requiring further analysis. The reasons for the unsatisfactory calibration effect are as follows:

[0116] (1) The traditional method for measuring the bottom elevation of drainage pipes is to use a measuring rod. However, the manhole of the inspection well is generally narrow at the top and wide at the bottom, which often requires blind operation when measuring the bottom elevation of the pipe, making it difficult to guarantee the accuracy of the measurement.

[0117] (2) For drainage pipes that have been in use for a long time, the internal defects are more serious. Pipe defects such as tree roots, deformation, obstacles, and sediments that have a significant impact on the hydraulic characteristics of the pipes are common. However, the pipe simulation of the InfoWorks ICM model is based on the ideal model of the connection between two nodes, which cannot simulate real pipe defects. As a result, the calibration of the InfoWorks ICM model is difficult to achieve the actual operation effect of the pipe network model.

[0118] In this embodiment, the Delft 3D model is further calibrated. The parameters to be calibrated are the Manning coefficient in the horizontal direction of the riverbed, the Manning coefficient in the vertical direction of the riverbed, the horizontal eddy viscosity coefficient of the river, and the horizontal eddy diffusion coefficient of the river. The NSE index of the observed and simulated values ​​of the calibrated Delft 3D model is determined. If the observed and simulated values ​​are highly consistent, the Delft 3D model can realistically simulate the water surface elevation, water flow changes, and convection diffusion of pollutants in the river in the study area.

[0119] S113. Couple the calibrated InfoWorks ICM model and the calibrated Delft 3D model to generate a coupled InfoWorks ICM-Delft 3D model.

[0120] As a preferred option rather than a specific limitation, the coupling includes at least horizontal spatial coupling, vertical spatial coupling, and input-output coupling.

[0121] This embodiment couples the horizontal space, vertical space, and input / output separately, wherein:

[0122] The horizontal spatial coupling is such that the city's drainage network and rivers are in an upstream and downstream relationship in the urban drainage system. Therefore, the core of the horizontal spatial coupling between the two is that the coordinates of the discharge outlet in InfoWorks ICM and the coordinates of the pollution source access in Delft 3D are consistent.

[0123] The vertical spatial coupling is as follows: the water surface elevation of the urban drainage system is continuous. Combining the horizontal spatial coupling characteristics of InfoWorks ICM and Delft 3D, the vertical spatial coupling between the two is mainly manifested in the fact that the boundary water surface elevation of InfoWorks ICM and the river water surface elevation of Delft 3D are consistent.

[0124] The coupling of input and output is based on the principle of conservation of matter. The output matter of the drainage network should be conserved with the input matter of the river. Specifically, the discharge flow rate and discharge pollutant concentration of InfoWorks ICM should be consistent with the pollution source flow rate and pollution source concentration of Delft 3D.

[0125] As a preferred option rather than a specific limitation, step S113 includes steps S1131-S1136, wherein:

[0126] S1131. Obtain the first observation data of the target river surface elevation and the second observation data of pollutant concentration.

[0127] This embodiment first acquires first and second observation data to determine the water surface elevation and pollutant concentration, so as to make the subsequent file conversion process more stable and reliable.

[0128] S1132. Based on the first and second observation data, generate the first table file of water surface elevation and pollutant time series required for the InfoWorks ICM model.

[0129] In this embodiment, in order to enable the InfoWorks ICM model to reliably acquire parameter information, the acquired data needs to be transformed. Python can be used to integrate and process the data to generate a first table file, so that the InfoWorks ICM model can acquire parameters better and operate more effectively, resulting in better control.

[0130] S1133. Determine the water surface elevation and pollutant time series of the discharge outlet in the InfoWorks ICM model, and update the InfoWorks ICM model database information through the first table file.

[0131] This embodiment further determines the water surface elevation and pollutant time series of the discharge outlet in the InfoWorks ICM model, and combines them with the first table file to update the InfoWorks ICM model database information, thereby achieving real-time calibration and updating of the data, making the InfoWorks ICM model database information more comprehensive and reliable.

[0132] As a preferred option rather than a specific limitation, the database information includes at least water level curves, pollutant process curves, and inflow curves.

[0133] S1134. Based on the updated InfoWorks ICM model database information, generate a third table file containing the time series of flow rates and pollutant concentrations at the emission outlets.

[0134] This embodiment runs the InfoWorks ICM model and the updated InfoWorks ICM model database information to generate time series of flow and pollutant concentration at the emission outlet. The data is then automatically categorized. Similarly, Python can be used to automatically generate a third table file to ensure the stability and reliability of the control process.

[0135] S1135. Based on the third table file, define the point source line pollution sources in the Delft 3D model, and convert the third table file into a disassembled file of the pollutant concentration and flow time series required by the Delft 3D model.

[0136] In this embodiment, the third table file generated by running the InfoWorks ICM model is imported into the system. The point source line pollution source in the Delft 3D model is defined by using the time series at the emission outlet, and the compilation is started to convert the three table files into a disassembled file, i.e., a DIS file, so that the Delft 3D model can receive the corresponding parameters for processing.

[0137] S1136. Based on the disassembled file, generate time-series NC files of water surface elevation and pollutant concentration at various points in the target river basin by running the Delft 3D model.

[0138] In this embodiment, the Delft 3D model is started and run based on the disassembled file obtained by conversion. The disassembled file is imported and run to generate time series NC files of water surface elevation and pollutant concentration at various points in the entire target river basin, thereby constructing a coupled model.

[0139] S12. Based on the coupled model of InfoWorks ICM-Delft 3D, establish the objective function.

[0140] In this embodiment, after determining the coupled model of InfoWorks ICM-Delft 3D, a corresponding objective function needs to be established to enable mathematical calculation of the model. This makes the results clearer and more reliable, and establishing the objective function transforms the water network source tracing problem into a minimization problem with pollution source location and emission history as parameters. The pollution source location and emission parameters are the parameter combinations corresponding to the globally optimal solution that minimizes the objective function value. The objective function is the difference between the monitored values ​​of the multi-source monitoring system and the simulated values ​​of the model.

[0141] S13. Based on the preset rules and objective function, at least determine the flood control plan.

[0142] This embodiment trains and solves the objective function according to preset rules, which can at least determine the flood control plan. In addition, it can also trace the source of pollutants and track the pollution sources point by point. For urban flood control planning, the restriction of pollution emissions can play a significant role.

[0143] As a preferred option rather than a specific limitation, step S13 includes S131-S132, wherein:

[0144] S131. Based on the objective function, determine the mutation strategy and control parameters of the objective function.

[0145] In this embodiment, the evaluation indicators are first determined. These indicators include at least the sum of squared errors, mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and Nash efficiency coefficient (NSE). For tracing urban water pollution sources, NSE, commonly used in hydrological models, is adopted as the objective function of the preset algorithm. The objective function f(X) i,G ) k The specific formula is as follows:

[0146]

[0147] In the formula, f(X) i,G ) k Let f(X) be the objective function value of the i-th individual at the k-th monitoring point in the G-th generation population. k,t Let X be the simulated value at time t for the k-th observation point; X is the parameter to be determined, X = (x1, x2, ..., xt). n );Y k,t The actual observed value at time t of the k-th observation point;

[0148] The objective function f(X) of the entire system is expressed as:

[0149]

[0150] The range of NSE is [-1, +∞]. A smaller NSE value indicates a closer similarity between the simulated and observed time series. The minimum value is -1, indicating that the simulated and observed values ​​are completely identical. The goal of the DE algorithm is to find the parameter combination X(x1, x2…x) that minimizes f(X). n This combination of parameters represents the most likely contamination event attribute.

[0151] The method for setting the value of the parameter to be determined is as follows:

[0152] The parameters to be determined and the criteria for judgment are as follows:

[0153]

[0154] In the formula, x, y, q, and c are the parameters to be determined; (x, y) are arbitrary geodetic coordinates; q is the pollution flow rate; and m 3 / s; c is the pollutant concentration; L(x,y) is the distance to the nearest node at (x,y); L max The upper limit of distance L(x,y) is used. The design spacing of outdoor drainage inspection wells is generally 30-40m. In this embodiment, L can be set as the upper limit of distance. max The value is 10m, which ensures the uniqueness of the traceability node identification.

[0155] The method for determining the mutation strategy adopts the selection of Bernoulli, abbreviated as bin, specifically as follows:

[0156] best / 1 / bin

[0157] V i =X best +F(X r1 -X r2 );

[0158] rand / 1 / bin

[0159] V i =X r1 +F(X r2 -X r3 );

[0160] randtobest / 1 / bin

[0161] V i =X r1 +F(X best -X r1 )+F(X r2 -X r3 );

[0162] currenttobest / 1 / bin

[0163] V i =X i +F(X best -X i +X r1 -X r2 );

[0164] best / 2 / bin

[0165] V i =X best +F(X r1 +X r2 -X r3 -X r4 );

[0166] rand / 2 / bin

[0167] V i =X r1 +F(X r2 +X r3 -X r4 -X r5 );

[0168] In the formula, V i The i-th new mutated individual; X r1 ,X r2 ,X r3 ,X r4 ,X r5X represents distinct individuals randomly selected from the population. best The best individual in this generation of the population; F is the scaling factor.

[0169] In this embodiment, the strategy using best as the mutation operation basis has strong local search capability but weak global search capability; the strategy using rand as the operation mutation basis randomly selects the operation basis, has strong global search capability but weak local search capability and slow convergence speed; the strategies using randtobest / 1 / bin and currenttobest / 1 / bin as mutation operators have a relatively balanced global and local search capability, but the convergence speed is average. This approach may not be suitable for the pollution source tracing problem in this embodiment, where there are many local optima, and the early iterations mainly examine the algorithm's global search capability while the later iterations mainly examine the local search capability. Therefore, this embodiment chooses the randtobest / 1 / bin strategy, which offers a more balanced approach.

[0170] The method for controlling the parameters is as follows:

[0171] The population size is determined to be no less than 4. If the population is too small, the differences between individuals will decrease rapidly during iteration, easily causing the algorithm to converge prematurely before reaching the optimal solution, resulting in "premature convergence." If the population is too large, the computation time will be too long, and the algorithm performance will degrade. Generally, assuming the number of parameters to be solved is N, the population size is typically within the range of [10N, 20N]. The eye-tracking algorithm for water pollution source tracing has strong global search capabilities, and theoretically, the larger the population size, the higher the source tracing accuracy. However, in practice, the InfoWorks ICM-Delft 3D coupled model has a long running time, so the population size should not be too large. Considering the above factors, the population size is set to 15N.

[0172] Next, the scaling factor F is determined. F is the multiplier of the difference vector. Generally, the smaller F is, the stronger the algorithm's local search capability, but the longer the convergence time, and the more likely the algorithm will get stuck in a local optimum. If F is too large, the algorithm's local search capability will be insufficient. Setting an adaptive scaling factor F that decreases with the number of iterations can avoid premature convergence of the population and balance local and global search capabilities. Randomly and uniformly selecting F within the range of [0.5, 1] ​​can effectively avoid premature convergence. Since there may be multiple local optima in the pollution source tracing problem, this embodiment uses a random scaling factor F, which is randomly selected within the range of [0.5, 1] ​​to avoid premature convergence.

[0173] The crossover probability CR, the probability of generating a new individual, directly affects the diversity of the population. If CR is too small, mutated individuals are difficult to accept, the overall rule-finding ability weakens, and the population is prone to premature convergence. Conversely, if CR is too large, the population diversity is too high, which may lead to failure to meet the convergence conditions. Generally, the crossover probability CR takes a value between [0.5, 0.7]. To maintain strong search ability and a reasonable convergence speed, the crossover probability CR in this embodiment is set to 0.7.

[0174] Define the convergence condition, which can be set as "reaching the maximum number of iterations" or "the difference between individuals in the population is less than a set condition". When the objective function value of an individual in the population satisfies the set condition, the algorithm can be considered to have found the optimal solution. The specific condition formula is as follows:

[0175]

[0176] In the formula, atol is the absolute tolerance; tol is the relative tolerance; f(X) i ) represents individual X in the population. i The objective function value. In this embodiment, the maximum number of iterations can be set to 200, atol can be set to 0, and tol can be set to 0.001.

[0177] S132. Based on the mutation strategy and control parameters of the objective function, train the coupled model of InfoWorks ICM-Delft 3D to determine the flood control plan.

[0178] In this embodiment, after determining the mutation strategy and control parameters of the objective function, the coupled model is trained iteratively multiple times until the preset target situation is reached or the number of iterations overflows, thereby determining flood control planning or tracing the source of urban sewage and tracking pollution sources point by point. For urban flood control planning, pollution emission restrictions can play a significant role.

[0179] This embodiment establishes a coupled model of InfoWorks ICM-Delft 3D, then establishes an objective function, and finally trains the objective function according to preset rules to determine flood control planning. This enables the establishment of a better drainage and flood control model for simulating and predicting flood control systems and tracing the source of water pollution. It also has high data processing efficiency and improves the accuracy of water depth prediction and water quality process change prediction for non-monitoring units.

[0180] Second embodiment:

[0181] Please refer to Figures 6 to 10 As shown, this embodiment proposes a device 100 for constructing an urban water network model, including a first establishment module 110, a second establishment module 120, and a determination module 130, wherein:

[0182] The first creation module 110 is connected to the second creation module 120 and is used to create a coupled model of InfoWorks ICM-Delft 3D based on the InfoWorks ICM model and the Delft 3D model.

[0183] As a preferred embodiment rather than a specific limitation, the first establishment module 110 includes an establishment unit 111, a calibration unit 112, and a coupling unit 113, wherein:

[0184] Establishment unit 111, connected to calibration unit 112, is used to establish InfoWorks ICM models and Delft 3D models.

[0185] As a preferred embodiment rather than a specific limitation, the establishment unit 111 includes a first acquisition subunit 1111, a first generation subunit 1112, a first determination subunit 1113, a second generation subunit 1114, a second determination subunit 1115, and a third generation subunit 1116, wherein:

[0186] The first acquisition subunit 1111 is connected to the first generation subunit 1112 and is used to acquire data of the drainage network.

[0187] The first generation subunit 1112 is connected to the first determination subunit 1113 and is used to generate an InfoWorks ICM model network based on the data from the InfoWorks ICM software and the drainage network.

[0188] The first determining subunit 1113 is connected to the second generating subunit 1114 and is used to verify the InfoWorks ICM model network and determine the model parameter values.

[0189] The second generation subunit 1114, connected to the second determination subunit 1115, is used to acquire target river information and generate a target river raster.

[0190] The second determining subunit 1115, connected to the third generating subunit 1116, is used to determine the hydraulic boundary and pollutant concentration boundary of the target river based on the target river grid.

[0191] The third generation subunit 1116 is used to generate a Delft 3D model based on the hydraulic boundary and the pollutant concentration boundary.

[0192] The calibration unit 112, connected to the coupling unit 113, is used to calibrate the InfoWorks ICM model and the Delft 3D model.

[0193] The coupling unit 113 is used to couple the calibrated InfoWorks ICM model and the calibrated Delft 3D model to generate a coupled InfoWorks ICM-Delft 3D model. The coupling includes at least horizontal spatial coupling, vertical spatial coupling and input-output coupling.

[0194] As a preferred embodiment rather than a specific limitation, the coupling unit 113 includes a second acquisition subunit 1131, a fourth generation subunit 1132, a third determination subunit 1133, a fifth generation subunit 1134, a processing subunit 1135, and a sixth generation subunit 1136, wherein:

[0195] The second acquisition subunit 1131, connected to the fourth generation subunit 1132, is used to acquire the first observation data of the target river surface elevation and the second observation data of pollutant concentration.

[0196] The fourth generation subunit 1132, connected to the third determination subunit 1133, is used to generate a first table file of water surface elevation and pollutant time series required for the InfoWorks ICM model based on the first observation data and the second observation data.

[0197] The third determining subunit 1133, connected to the fifth generating subunit 1134, is used to determine the water surface elevation and pollutant time series of the discharge outlet in the InfoWorks ICM model, and to update the InfoWorks ICM model database information through the first table file. The database information includes at least the water level curve, the pollutant process curve, and the inflow curve.

[0198] The fifth generation subunit 1134, connected to the processing subunit 1135, is used to generate a third table file of time series of flow rate and pollutant concentration at the emission outlet based on the updated InfoWorks ICM model database information.

[0199] Processing subunit 1135, connected to the sixth generation subunit 1136, is used to define point source line pollution sources in the Delft 3D model according to the third table file, and convert the third table file into a disassembled file of pollutant concentration and flow time series required by the Delft 3D model.

[0200] The sixth generation subunit 1136 is used to generate time-series NC files of water surface elevation and pollutant concentration at various points in the target river basin by running the Delft 3D model based on the disassembled file.

[0201] The second creation module 120, connected to the determination module 130, is used to create an objective function based on the coupled model of InfoWorks ICM-Delft 3D.

[0202] Module 130 is used to determine at least the flood control plan based on preset rules and objective functions.

[0203] As a preferred embodiment rather than a specific limitation, the determining module 130 includes a determining unit 131 and a training unit 132, wherein:

[0204] The determination unit 131, connected to the training unit 132, is used to determine the mutation strategy and control parameters of the objective function based on the objective function.

[0205] The determining unit 131 includes:

[0206] Choose the corresponding evaluation index, and its objective function f(X) i,G ) k The specific formula is as follows:

[0207]

[0208] In the formula, f(X) i,G ) k Let f(X) be the objective function value of the i-th individual at the k-th monitoring point in the G-th generation population. k,t Let X be the simulated value at time t for the k-th observation point; X is the parameter to be determined, X = (x1, x2, ..., xt). n );Y k,t The actual observed value at time t of the kth observation point.

[0209] The objective function of the coupled model is determined as follows:

[0210]

[0211] The criteria for determining the parameters to be determined are as follows:

[0212]

[0213] In the formula, (x,y) are arbitrary geodetic coordinates; q is the pollution flow rate; c is the pollutant concentration; L(x,y) is the distance to the nearest node to (x,y); L max Let L(x,y) be the upper limit of the distance.

[0214] Training unit 132 is used to train the coupled model of InfoWorks ICM-Delft 3D based on the mutation strategy and control parameters of the objective function to determine the flood control plan.

[0215] This embodiment establishes a coupled model of InfoWorks ICM-Delft 3D, then establishes an objective function, and finally trains the objective function according to preset rules to determine flood control planning. This enables the establishment of a better drainage and flood control model for simulating and predicting flood control systems and tracing the source of water pollution. It also has high data processing efficiency and improves the accuracy of water depth prediction and water quality process change prediction for non-monitoring units.

[0216] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0217] This invention also provides a computer storage medium storing a computer program that, when executed by a processor, implements the urban water network model construction method as described in the above embodiments. Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the urban water network model construction method described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0218] Alternatively, if the integrated units of the present invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention, or the parts that contribute to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, terminal, or network device, etc.) to execute all or part of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, RAM, ROM, magnetic disks, or optical disks. Corresponding to the aforementioned computer storage medium, one embodiment also provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the method for constructing the urban water network model as described in the above embodiments.

[0219] This computer device can be a terminal, and its internal structure diagram can be as follows: Figure 11 As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for constructing an urban water network model. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0220] This embodiment establishes a coupled model of InfoWorks ICM-Delft 3D, then establishes an objective function, and finally trains the objective function according to preset rules to determine flood control planning. This enables the establishment of a better drainage and flood control model for simulating and predicting flood control systems and tracing the source of water pollution. It also has high data processing efficiency and improves the accuracy of water depth prediction and water quality process change prediction for non-monitoring units.

[0221] The technical features can be combined in any way. For the sake of brevity, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0222] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for constructing an urban water network model, characterized in that, include: Based on the InfoWorks ICM model and the Delft 3D model, establish a coupled model of InfoWorks ICM and Delft 3D; Based on the coupled model of InfoWorks ICM-Delft 3D, establish the objective function; Based on the preset rules and objective function, at least the flood control plan should be determined; The steps for determining at least the flood control plan based on preset rules and objective function include: Based on the objective function, determine the mutation strategy and control parameters of the objective function; Based on the mutation strategy and control parameters of the objective function, a coupled model of InfoWorks ICM-Delft 3D is trained to determine the flood control plan; The step of determining the mutation strategy and control parameters of the objective function based on the objective function includes: Choose the corresponding evaluation index and its objective function. The specific formula is as follows: ； In the formula, For the first The first generation of the population The first monitoring point The objective function value for each individual; For the first observation points Simulated values ​​from the time-matter model; For the parameters to be determined, ; No. observation points Actual observed value at any given time; The objective function of the coupled model is determined as follows: ； The criteria for determining the parameters to be determined are as follows: ； In the formula, For any geodetic coordinates; For pollution flow; The concentration of pollutants; To and Distance to the nearest node; for The maximum distance.

2. The method for constructing an urban water network model according to claim 1, characterized in that, The steps for establishing a coupled InfoWorks ICM-Delft 3D model based on the InfoWorks ICM model and the Delft 3D model include: Create InfoWorks ICM models and Delft 3D models; Calibrate InfoWorks ICM models and Delft 3D models; The calibrated InfoWorks ICM model and the calibrated Delft 3D model are coupled to generate a coupled InfoWorks ICM-Delft 3D model, wherein the coupling includes at least horizontal spatial coupling, vertical spatial coupling, and input-output coupling.

3. The method for constructing an urban water network model according to claim 2, characterized in that, The steps for establishing the InfoWorks ICM model and the Delft 3D model include: Obtain data from the drainage network; Based on InfoWorks ICM software and drainage network data, generate an InfoWorks ICM model; Verify the InfoWorks ICM model and determine the model parameter values; Acquire target river information and generate a target river raster; Based on the target river grid, determine the hydraulic boundary and pollutant concentration boundary of the target river; A Delft 3D model is generated based on the hydraulic boundary and the pollutant concentration boundary.

4. The method for constructing an urban water network model according to claim 2, characterized in that, The coupled and calibrated InfoWorks ICM model and the calibrated Delft 3D model are used to generate a coupled InfoWorks ICM-Delft 3D model. The coupling includes at least the steps of horizontal spatial coupling, vertical spatial coupling, and input-output coupling, including: Acquire the first observation data on the elevation of the target river surface and the second observation data on the pollutant concentration; Based on the first and second observation data, generate the first tabular file of water surface elevation and pollutant time series required for the InfoWorks ICM model; Determine the water surface elevation and pollutant time series of the discharge outlet in the InfoWorks ICM model, and update the InfoWorks ICM model database information through the first table file. The database information includes at least the water level curve, the pollutant process curve, and the inflow curve. Based on the updated InfoWorks ICM model database information, a third table file is generated showing the time series of flow rates and pollutant concentrations at the emission outlets; Based on the third table file, define the point source line pollution sources in the Delft 3D model, and convert the third table file into a disassembled file of the pollutant concentration and flow time series required for the Delft 3D model; Based on the disassembled files, by running the Delft 3D model, time-series NC files of water surface elevation and pollutant concentration at various points in the target river basin are generated.

5. A device for constructing an urban water network model, characterized in that, include: The first module is used to create a coupled InfoWorks ICM-Delft 3D model based on the InfoWorks ICM model and the Delft 3D model. The second module is used to establish the objective function based on the coupled model of InfoWorks ICM-Delft 3D; The determination module is used to determine at least the flood control plan based on preset rules and objective functions; The first establishment module includes: Create cells for building InfoWorks ICM models and Delft 3D models; The calibration unit is used to calibrate InfoWorks ICM models and Delft 3D models; A coupling unit is used to couple the calibrated InfoWorks ICM model and the calibrated Delft 3D model to generate a coupled InfoWorks ICM-Delft 3D model, wherein the coupling includes at least horizontal spatial coupling, vertical spatial coupling, and input-output coupling. The establishment unit includes: The first acquisition subunit is used to acquire data from the drainage network. The first generation subunit is used to generate the InfoWorksICM model network based on the InfoWorks ICM software and the drainage network data. The first determining subunit is used to verify the InfoWorks ICM model network and determine the model parameter values; The second generation subunit is used to acquire target river information and generate target river raster; The second determining sub-unit is used to determine the hydraulic boundary and pollutant concentration boundary of the target river based on the target river grid. The third generation sub-unit is used to generate a Delft 3D model based on the hydraulic boundary and the pollutant concentration boundary. The coupling unit includes: The second acquisition subunit is used to acquire the first observation data of the target river surface elevation and the second observation data of pollutant concentration. The fourth generation subunit is used to generate a first table file of water surface elevation and pollutant time series required for the InfoWorks ICM model based on the first and second observation data. The third determining subunit is used to determine the water surface elevation and pollutant time series of the discharge outlet in the InfoWorks ICM model, and to update the InfoWorks ICM model database information through the first table file. The database information includes at least the water level curve, the pollutant process curve and the inflow curve. The fifth generation subunit is used to generate a third table file of time series of flow rate and pollutant concentration at the emission outlet based on the updated InfoWorks ICM model database information; The processing subunit is used to define point source line pollution sources in the Delft 3D model based on the third table file, and convert the third table file into a disassembled file of pollutant concentration and flow time series required by the Delft 3D model; The sixth generation subunit is used to generate time-series NC files of water surface elevation and pollutant concentration at various points in the target river basin by running the Delft 3D model based on the disassembled file. The determining module includes: The determination unit is used to determine the mutation strategy and control parameters of the objective function based on the objective function. The training unit is used to train the coupled model of InfoWorks ICM-Delft 3D based on the mutation strategy and control parameters of the objective function to determine the flood control plan; The determining unit includes: Choose the corresponding evaluation index and its objective function. The specific formula is as follows: ； In the formula, For the first The first generation of the population The first monitoring point The objective function value for each individual; For the first observation points Simulated values ​​from the time-matter model; For the parameters to be determined, ; No. observation points Actual observed value at any given time; The objective function of the coupled model is determined as follows: ； The criteria for determining the parameters to be determined are as follows: ； In the formula, For any geodetic coordinates; For pollution flow; The concentration of pollutants; To and Distance to the nearest node; for The maximum distance.

6. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by the urban water network model construction device, implements the urban water network model construction method as described in any one of claims 1-4.

7. A computer device, characterized in that, The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for constructing an urban water network model as described in any one of claims 1-4.

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