A digital twin watershed water environment arbitrary pollution scenario simulation method and system

Abstract

The present invention belongs to the technical field related to digital twin watershed water environment simulation and discloses a method and system for simulating arbitrary pollution scenarios in a digital twin watershed water environment. The method includes the following steps: setting the pollutant concentration and flow rate of each grid cell in the digital twin watershed water environment model at time t0; pollution occurs at time t1; setting a pollution treatment method for the location where pollution is input, and solving the pollutant concentration and flow rate at the location where pollution occurs based on different pollution treatment methods; for locations where pollution is not input, using a hydrodynamic pollutant migration model to update the pollutant concentration and flow rate at the location where pollution does not occur, thereby obtaining the pollutant concentration and flow rate at each location in the digital twin watershed water environment model after pollution occurs. Through this invention, the impact of not considering the pollution treatment method after pollution occurs in the watershed on the spread of pollution is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field related to digital twin river basin water environment simulation, and more specifically, relates to a method and system for simulating arbitrary pollution scenarios in the digital twin river basin water environment. Background Art

[0002] The development of digital twin river basins should be based on their specific characteristics and practical needs. As complex open systems, river basins, with their complex interweaving of lakes, reservoirs, and rivers, are highly uncertain. Existing modeling technologies are unable to respond in real time to water pollution incidents, such as sudden water pollution.

[0003] Journal of Environmental Management, Vol. 354, No. 120294, 2024, "Adaptive reservoir operation considering water quantity and quality objectives: Application of parallel cellular automata and sub-seasonal streamflow forecasts," links an adaptive optimization model with the CE-QUAL-W2 water quality simulation model to evaluate reservoir and outflow water quality. Water Science and Technology, Vol. 3, Vol. 89, 2024, "Water quality's responses to water energy variability of the Yangtze River," uses Mike21 to construct a hydrodynamic and water quality model of the Yangtze River mainstream to assess the impact of water quality changes in the basin. The models constructed using the above methods cannot respond to sudden water pollution problems in real time and do not consider the impact of different pollution treatment methods on pollution diffusion after pollution occurs, making it difficult to meet the requirements of digital twin basin construction.

[0004] Therefore, this study aims to address the challenge of real-time simulation and disposal of pollution problems in the construction of digital twin river basins, and to provide a theoretical basis and technical support for the construction of digital twin river basins. Summary of the Invention

[0005] In response to the above-mentioned defects or improvement needs of the existing technology, the present invention provides a method and system for simulating arbitrary pollution scenarios in the water environment of a digital twin river basin, which solves the problems of not being able to perform real-time pollutant diffusion analysis in the river basin and not considering the impact of pollution treatment methods on pollution diffusion after pollution occurs.

[0006] To achieve the above objectives, according to one aspect of the present invention, a method for simulating arbitrary pollution scenarios in a digital twin watershed water environment is provided, the method comprising the following steps:

[0007] Set the pollutant concentration and sewage flow rate of each grid cell in the digital twin watershed water environment model at time t0; input pollutants into the digital twin watershed water environment model at time t1;

[0008] For the location where pollutants are input, a pollution treatment method is set, and the pollutant concentration and flow rate at the location where the pollution occurs are solved according to different pollution treatment methods, wherein the pollution treatment methods include pollutant dilution and pollutant interception;

[0009] For locations where no pollutants are input, the pollutant concentration and flow at the location where pollution is input, as well as the pollutant concentration and flow at the location where no pollutants are input at time t0, are updated using the hydrodynamic pollutant migration model. In this way, the pollutant concentration and flow at each location after pollution occurs in the digital twin watershed water environment model are obtained.

[0010] Further preferably, when the pollution treatment method is pollutant dilution, the pollutant concentration and flow rate at the pollutant dilution position are calculated according to the following formula:

[0011]

[0012] in, is the grid pollutant concentration after dilution, is the pollutant concentration in the grid before dilution, is the flow rate of the diluted grid, is the flow rate of the grid before dilution, C k is the dilution concentration, q m is the diluent flow rate and K is the diffusion coefficient.

[0013] Further preferably, the concentration of the input pollutant C k The formula is as follows:

[0014]

[0015] Where v is the dilution factor of the pollutant.

[0016] Further preferably, when the pollution treatment method is the interception of pollutants, the pollutant concentration and flow rate at the location where the pollutant interception occurs are calculated according to the following formula:

[0017]

[0018] Where C is the pollutant concentration, Q lis the pollutant flow rate, K x , K y , K z are the diffusion coefficients in the x, y, and z directions respectively, u, v, and w are the velocity components in the x, y, and z directions respectively, and S c is the source and sink term entering or leaving the unit water body, h min and h max are the minimum water depth and the maximum water depth, respectively, b e is the intercept width.

[0019] Further preferably, the minimum water depth h min and maximum water depth h max The formula is as follows:

[0020] h max =max(Z r ,Z c )-Z e

[0021] h min =min(Z r ,Z c )-Z e

[0022] Among them, Z r and Z c are the water levels upstream and downstream of the interception point, Z e are intercept elevations, respectively.

[0023] Further preferably, the formula of the hydrodynamic migration model is as follows:

[0024]

[0025]

[0026] Among them, z is the vertical σ coordinate, u, v, w are the velocity components in the x, y, and z directions respectively, t is the time, m x and m y is the horizontal coordinate transformation scale factor, Q H is the source and sink term of the continuity equation, Q u and Q v is the source and sink term of the momentum equation, f e is the correlation coefficient of the Coriolis force, ρ0 is the reference density of the water body; ρ is the water body density; P is the additional hydrostatic pressure, g is the acceleration of gravity, w* is the vertical flow velocity in the Cartesian coordinate system, A v is the vertical eddy viscosity coefficient, C is the water quality index concentration, K x , K y , K z are the diffusion coefficients in the x, y, and z directions, respectively, and Sc It is the source and sink item entering or leaving the unit water body.

[0027] Further preferably, when calculating the pollutant concentration and flow rate at the location where the pollution occurs, the location where the pollution occurs is projected onto the grid unit in the digital twin watershed water environment model, so as to obtain the grid unit corresponding to the location where the pollution occurs in the digital twin watershed water environment model.

[0028] Further preferably, the grid unit corresponding to the pollution occurrence location in the digital twin watershed water environment model is calculated using a pre-calibrated correspondence between the pollution occurrence location and the grid unit.

[0029] According to another aspect of the present invention, a digital twin watershed water environment arbitrary pollution scene simulation system is provided, which includes an actuator for executing the above-mentioned digital twin watershed water environment arbitrary pollution scene simulation method.

[0030] According to another aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for simulating arbitrary pollution scenarios of the water environment of a digital twin river basin as described above is implemented.

[0031] In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:

[0032] 1. In the case of pollution in the digital twin watershed water environment, this invention divides the pollution treatment methods into two types: pollutant dilution and interception. Different pollutant concentration and flow calculations are used for different pollution treatment methods, which is highly targeted and accurate.

[0033] 2. The present invention updates the initial pollutant concentration and flow rate at the pollution site based on the input pollutant concentration and flow rate. Combining the original data with external disturbance data, the concentration at the pollution site after the pollution occurs is calculated. Simultaneously, the pollutant concentration and flow rate of other grid cells in the digital twin watershed water environment are updated based on changes in the concentration at the pollution site, achieving real-time updates of pollutant concentration and flow rate in the digital twin watershed water environment.

[0034] 3. The present invention further sets the height and width of pollution interception, updates the pollutant concentration and flow rate at the pollution site, and then updates the pollutant concentration and flow rate of other grids in the digital twin watershed water environment based on the pollutant concentration and flow rate of the grid unit at the pollution site. The changes in pollutant concentration and flow rate after pollutant interception are updated in real time based on actual conditions, with strong real-time performance.

[0035] 4. The present invention uses a hydrodynamic migration model to update the pollutant concentration and flow rate at locations other than the pollution site. This not only considers the impact of the pollutant concentration and flow rate at the pollution site on other grid cells, but also combines the current pollutant concentration and flow rate of other grid cells themselves, resulting in high calculation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a flow chart of a method for simulating arbitrary pollution scenarios of a digital twin watershed water environment constructed according to a preferred embodiment of the present invention;

[0037] Figure 2 Schematic diagrams of pollutant flow and a digital twin water environment model of the Danjiangkou River in accordance with a preferred embodiment of the present invention, wherein (a) is a schematic diagram of the pollutant flow at the inlet of the Danjiangkou Dam changing with time, and (b) is a schematic diagram of the digital twin water environment model of the Danjiangkou River;

[0038] Figure 3 The pollutant flow rate of the grid at Danjiangkou Dam in the digital twin watershed water environment model constructed according to the preferred embodiment of the present invention is set to 3000m at time t1. 3 Schematic diagram of simulation results of pollutant flow of all grids obtained by simulation after / s;

[0039] Figure 4 The pollutant flow rate of the grid at Danjiangkou Dam in the digital twin watershed water environment model constructed according to the preferred embodiment of the present invention is set to 5000m at time t1. 3 Schematic diagram of simulation results of pollutant concentrations of all grids obtained by simulation after / s;

[0040] Figure 5 The pollutant flow rate of the grid at Danjiangkou Dam in the digital twin watershed water environment model constructed according to the preferred embodiment of the present invention is set to 7000m at time t1. 3 Schematic diagram of simulation results of pollutant concentrations of all grids obtained by simulation after / s;

[0041] Figure 6 The pollutant flow rate of the grid at Danjiangkou Dam in the digital twin watershed water environment model constructed according to the preferred embodiment of the present invention is set to 9000m at time t1. 3 Schematic diagram of simulation results of pollutant concentrations of all grids obtained by simulation after / s;

[0042] Figure 7 The pollutant flow rate of the grid at Danjiangkou Dam in the digital twin watershed water environment model constructed according to the preferred embodiment of the present invention is set to 11000m at time t1. 3Schematic diagram of simulation results of pollutant concentrations of all grids obtained by simulation after / s;

[0043] Figure 8 This is a schematic diagram of a digital twin watershed water environment model of the Laoguan River tributary of the Danjiangkou Reservoir constructed according to the preferred embodiment 2 of the present invention;

[0044] Figure 9 The migration of pollutants in the next month if no measures are taken is constructed according to the second preferred embodiment of the present invention;

[0045] Figure 10 This is the simulation result of the pollutant concentration and flow after interception by the four-stage rubber dam constructed according to the preferred embodiment 2 of the present invention;

[0046] Figure 11 This is a simulation result of pollutant concentration and flow after adding polyferric sulfate dilution constructed according to the preferred embodiment 2 of the present invention. DETAILED DESCRIPTION

[0047] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0048] like Figure 1 As shown, the present invention provides a method for simulating arbitrary pollution scenarios in the water environment of a digital twin watershed. It can quickly construct corresponding pollution scenarios based on the pollution input location, pollutant concentration, sewage flow, and pollution disposal method of the pollution event, and establish a pollutant simulation model for arbitrary pollution scenarios based on the digital twin watershed, realizing the simulation of pollutants under different pollution scenarios, and providing support for pollution event warning, rehearsal, and emergency plans for the digital twin watershed system. The specific implementation steps of this method are:

[0049] (1) Location of input pollutants

[0050] Based on the location of the pollution point or the pollution situation, the pollution treatment method and pollution input point are preliminarily determined, and different sudden pollution simulation scenarios are quickly constructed, including pollution input location, pollutant concentration, sewage flow and pollution disposal method.

[0051] Pollution input locations, including pollution input points or pollution disposal points, can be selected and set in the digital twin watershed system by clicking. Points are represented by geographic coordinates (x, y). To facilitate model calculations, a coordinate attribute table is called to map the grid numbers to geographic coordinates before model simulation. This allows for quick conversion between geographic coordinates and model grid numbers, converting geographic coordinates (x, y) to model grid numbers (i, j).

[0052] The pollutant concentration settings for different pollution scenarios include the pollutant concentration time series C k =(c1,c2,…,c t ,…,c T ), the sewage flow setting includes the dilution flow time series q m =(q1,q2,…,q t ,…,q T ). Where k = 1, 2, ... represents the number of different pollutant concentration scenarios, and T represents the simulation time step.

[0053] Pollution disposal methods for pollution scenarios are divided into two types: pollution dilution and pollution interception, and the two methods can also be used in combination.

[0054] (a) Pollution dilution

[0055] According to the chemical reaction of the pollutant, the dilution factor v of the reactant is determined, thereby determining the concentration of the reactant and the dosage, and then setting the dilution concentration C k And simulated input flow q m For any point, the pollutant concentration calculation formula of its dosing grid is:

[0056]

[0057]

[0058] in, is the concentration after dilution, is the concentration before dilution. is the flow rate after dilution, is the flow rate before dilution. K is the diffusion coefficient.

[0059] (b) Pollution Interception

[0060] Set any point as a weir flow or other form as a boundary point to simulate the interception effect in pollution disposal. Suppose the flow rate of the upstream and downstream of the river with the interception dam at a certain moment is Q l , the method of approximating the exchange flow using the weir flow formula is as follows:

[0061]

[0062] Where: hmin and h max The following formulas are used for calculation:

[0063] h max =max(Z r ,Z c )-Z e

[0064] h min =min(Z r ,Z c )-Z e

[0065] Where: Z r and Z c is the water level upstream and downstream of the set point, Z e Set the elevation for the intercept, b e is the intercept width.

[0066] The following formula is used to calculate the concentration of pollutants:

[0067]

[0068] Where: C is the pollutant concentration; K x , K y , K z are the diffusion coefficients in the x, y, and z directions respectively; u, v, and w are the flow velocities in the x, y, and z directions respectively; S c It is the source and sink item entering or leaving the unit water body.

[0069] (2) For locations where no pollutants are input

[0070] Construct a digital twin watershed water environment arbitrary pollution scenario simulation model, which can simulate one or more combined pollution scenarios such as different pollution input locations, different pollutant concentrations, different sewage flow rates and pollution disposal methods.

[0071] The simulation model of arbitrary pollution scenarios in the digital twin watershed water environment is constructed based on the hydrodynamic equation and the pollutant migration and transformation equation. The hydrodynamic equation adopts the motion equation of conservation of momentum of incompressible fluid. The transport of pollutants in the water body and the physical, chemical, and biological transformation processes adopt the mass conservation equation group. The mass conservation equation group is:

[0072]

[0073] Where: C is the pollutant concentration; K x , K y , K z are the diffusion coefficients in the x, y, and z directions respectively; u, v, and w are the flow velocities in the x, y, and z directions respectively; S cIt is the source and sink item entering or leaving the unit water body.

[0074] The arbitrary pollution scenario simulation model of the digital twin river basin water environment is used to simulate pollutants in different pollution scenarios. The simulation results of different pollution scenarios are analyzed, and the diffusion direction, speed, impact range and impact degree of pollutants are compared to provide early warning, rehearsal and emergency plan support for the digital twin river basin system.

[0075] The hydrodynamic control equations of the model are as follows:

[0076]

[0077] Where z is the vertical σ coordinate, u, v, w are the velocity components in the x, y, and z directions respectively; t is time; m x and m y is the horizontal coordinate transformation scale factor; Q H is the source and sink term of the continuity equation; Q u and Q v is the source and sink term of the momentum equation; f e is the correlation coefficient of the Coriolis force; ρ0 is the reference density of water (1×10 3 kg / m 3 ); ρ is the water density; P is the additional hydrostatic pressure; g is the acceleration due to gravity (9.81 N / kg); w* is the vertical flow velocity in the Cartesian coordinate system (true vertical flow velocity); A v is the vertical eddy viscosity coefficient.

[0078] The present invention is further described in detail below with reference to examples.

[0079] Example 1:

[0080] This example assumes that the Danjiangkou Bridge is suddenly polluted and uses pollution treatment simulation technology to model it. Click the Danjiangkou Bridge location to set the pollution source location and concentration. The task is to determine the pollution arrival location and pollution duration under different reservoir operation plans based on the 2021 Hanjiang River flow and the most unfavorable hydrological characteristics. Figure 2 This is a schematic diagram of the configuration according to the preferred embodiment of the present invention, wherein (a) is a schematic diagram of the pollutant flow rate at the inlet of Danjiangkou Dam over time, and (b) is a schematic diagram of the digital twin watershed water environment model of Danjiangkou. In order to simulate the impact of the Hanjiang River pollution incident on the Danjiangkou Reservoir, especially Taocha (the water intake of the South-to-North Water Diversion Project Middle Route), a 3000m 3 / s、5000m 3 / s、7000m 3 / s、9000m 3 / s and 11100m 3 / sFive types of Danjiangkou Dam outflows, Figures 3 to 7 Set 3000m respectively 3 / s、5000m 3 / s、7000m 3 / s、9000m 3 / s and 11100m 3 / sSimulation results of pollutant concentration of Danjiangkou Dam flow.

[0081] Simulation results show that a larger outflow rate can more effectively and quickly remove pollutants. October is when inflow peaks, carrying pollutants into the Danjiangkou area. Increasing the downstream flow can accelerate pollutant removal in the area and ensure the safety of Taocha.

[0082] Example 2:

[0083] This example simulates and evaluates an accidental water pollution incident in a tributary of the Laogan River within the Danjiangkou Reservoir. The study simulates response options, including damming and coagulant injection, to rapidly assess their effectiveness in controlling the pollution. The simulation results are used to automatically generate a contingency monitoring plan and evaluate the effectiveness of implementing strategies such as damming, coagulant injection, and the contingency plan.

[0084] In the digital twin watershed system, real-time on-site monitoring data is fed back into the model, triggering alerts for sudden water pollution incidents and initiating simulations of pollution disposal at arbitrary locations within the digital twin watershed. A one-dimensional model was used to predict the migration of pollutants over a one-month period, assuming no action was taken. Pollutant concentrations at Guanyintang were used as the inlet concentrations for the Danjiangkou Reservoir to observe changes in pollutant concentrations. After assessing future risks and taking into account the actual conditions of the Laoguan River, simulations were conducted on the construction of a four-stage rubber dam at Fanqiao to intercept pollutants and release iron sulfate solvent.

[0085] Figure 8 This is a schematic diagram of the setup for the second sudden pollution simulation case. Figures 9 to 11 The simulation results are for no measures, a four-stage rubber dam interception scenario, and the introduction of polyferric sulfate dilution. It can be seen that the rubber dam mitigates the impact of pollutants downstream, and combined with the injection of coagulants, pollutants are reduced to acceptable levels before entering the reservoir.

[0086] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for simulating arbitrary pollution scenarios in a digital twin watershed water environment, characterized in that: The method comprises the following steps: Set the pollutant concentration and sewage flow rate of each grid cell in the digital twin watershed water environment model at time t0; input pollutants into the digital twin watershed water environment model at time t1; For the location where pollutants are input, a pollution treatment method is set, and the pollutant concentration and flow rate at the location where the pollution occurs are solved according to different pollution treatment methods, wherein the pollution treatment methods include pollutant dilution and pollutant interception; For locations where no pollutants have been input, the pollutant concentration and flow at the location where the pollution has been input are combined with the pollutant concentration and flow at the time t0 at the location where the pollution has not been input, and the pollutant concentration and flow at the location where the pollution has not been input are updated using the hydrodynamic pollutant migration model, thereby obtaining the pollutant concentration and flow at each location after the pollution occurs in the digital twin watershed water environment model; When the pollution treatment method is pollutant dilution, the pollutant concentration and flow rate at the pollutant dilution position are calculated according to the following formula: in, is the grid pollutant concentration after dilution, is the pollutant concentration in the grid before dilution, is the flow rate of the diluted grid, is the flow rate of the grid before dilution, C k is the dilution concentration, q m is the diluent flow rate, K is the diffusion coefficient; The concentration of the input pollutant C k The formula is as follows: Where v is the pollutant dilution factor; When the pollution treatment method is pollutant interception, the pollutant concentration and flow rate at the pollutant interception location are calculated according to the following formula: Where C is the pollutant concentration, Q l is the pollutant flow rate, K x , K y , K z are the diffusion coefficients in the x, y, and z directions respectively, u, v, and w are the velocity components in the x, y, and z directions respectively, and S c is the source and sink term entering or leaving the unit water body, h min and h max are the minimum water depth and the maximum water depth, respectively, b e is the width of the intercept and g is the acceleration due to gravity.

2. A digital twin watershed water environment arbitrary pollution scenario simulation method according to claim 1, characterized in that: The minimum water depth h min and maximum water depth h max The formula is as follows: h max =max(Z r ,Z c )-Z e h min =min(Z r ,WITH c )-WITH e Among them, Z r and Z c are the water levels upstream and downstream of the interception point, Z e are intercept elevations, respectively.

3. The method for simulating arbitrary pollution scenarios of a digital twin watershed water environment according to claim 1, characterized in that: The formula of the hydrodynamic pollutant transport model is as follows: Among them, z is the vertical σ coordinate, u, v, w are the velocity components in the x, y, and z directions respectively, t is the time, m x and m y is the horizontal coordinate transformation scale factor, Q H is the source and sink term of the continuity equation, Q u and Q v is the source and sink term of the momentum equation, f e is the correlation coefficient of the Coriolis force, ρ0 is the reference density of the water body; ρ is the water body density; P is the additional hydrostatic pressure, g is the acceleration of gravity, w* is the vertical flow velocity in the Cartesian coordinate system, A v is the vertical eddy viscosity coefficient, C is the water quality index concentration, K x , K y , K z are the diffusion coefficients in the x, y, and z directions, respectively, and S c It is the source and sink item entering or leaving the unit water body.

4. The method for simulating arbitrary pollution scenarios of a digital twin watershed water environment according to claim 1, characterized in that: When calculating the pollutant concentration and flow rate at the location where the pollution occurs, the location where the pollution occurs is projected onto the grid unit in the digital twin watershed water environment model to obtain the grid unit corresponding to the location where the pollution occurs in the digital twin watershed water environment model.

5. A method for simulating arbitrary pollution scenarios of a digital twin watershed water environment according to claim 4, characterized in that: The grid unit corresponding to the pollution occurrence location in the digital twin watershed water environment model is calculated using a pre-calibrated correspondence between the pollution occurrence location and the grid unit.

6. A digital twin watershed water environment arbitrary pollution scenario simulation system, characterized by: The system includes an actuator, which is used to execute a digital twin river basin water environment arbitrary pollution scenario simulation method as described in any one of claims 1-5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements a method for simulating arbitrary pollution scenarios in a digital twin river basin water environment as described in any one of claims 1 to 5.

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