Method for inverting environmental damage of river pollution event

Abstract

The invention discloses a method for inverting environmental damage of a river pollution event. The method comprises the following steps: establishing a river hydrodynamic mathematical model; establishing a pollutant diffusion mathematical model; extracting river pollutant monitoring data, and selecting characteristic values; setting a minimum value interval and a maximum value interval of the source intensity; performing inversion calculation and debugging on the pollutant diffusion mathematical model according to the monitoring data of the river pollutants and the minimum value and maximum value intervals of the source intensity, establishing correlation with limited historical monitoring data, and determining the source intensity of the historical pollutants; and inputting the determined pollutant source intensity into the pollutant diffusion mathematical model, and simulating the area of the polluted river channel, the water volume and the pollutant concentration. The method overcomes the defects that in the prior art, the historical pollutant source intensity is difficult to determine, the environment damage range and degree simulation work cannot be carried out due to the lack of source intensity data and the like, the pollutant source intensity and the environment damage range and degree can be inverted according to limited historical monitoring data, and the inversion precision is high.

Description

Technical Field

[0001] The present invention relates to the technical field of ecological environmental damage identification and assessment, and in particular to a method for inverting environmental damage caused by river pollution events. Background Art

[0002] Sudden pollution of rivers is a water pollution phenomenon in which the rate of deterioration of river water quality suddenly increases in a short period of time due to human behavior. It is sudden and accidental, with the characteristics of large rate of water quality change, rapid recovery of water quality to normal, easy formation of water pollution accidents, and difficulty in taking timely defensive measures, which affects the water ecological environment.

[0003] Due to their characteristics, sudden river pollution incidents are often difficult to detect in a timely manner, making it difficult to determine the source strength of pollutants in the pollution incidents afterwards.

[0004] Due to the strong fluidity of the river and the complex flow of the water system, pollution spreads very quickly and the paths are very complex, making it difficult to monitor in real time. The scope and extent of the pollution are also difficult to determine, which increases the difficulty of subsequent identification and assessment of ecological and environmental damage.

[0005] How to scientifically identify and assess the ecological and environmental damage caused by river pollution incidents, restore objective facts such as the source strength of pollutants, and objectively evaluate the consequences of the pollution caused is a serious issue.

[0006] Simulation research on sudden pollution incidents in existing rivers generally requires clear pollutant source strength data first, and then setting parameters to simulate the pollution range; if accurate pollutant source strength data is lacking, simulation work cannot be carried out.

[0007] The patent specification with publication number CN116882294A discloses a method for tracing the source of sudden water pollution in a river network based on the hierarchical solution of "river network-river channel", including the following steps: S1, construction of the topological relationship between nodes and river channels; S2, construction of river network water flow and water quality calculation model and generation of sample data; S3, determination of the river channel where the pollution source is located based on the BP neural network model; S4, construction and solution of the model for tracing the source of sudden water pollution in the river channel.

[0008] The patent specification with publication number CN102254081A discloses an algorithm for locating sudden river water pollution sources based on a random probability model, including: establishing a sudden river water pollution propagation model based on random probability; establishing a random probability model for observing sudden river water pollution concentration; and statistically locating sudden river water pollution sources.

[0009] The patent specification with publication number CN117973873A discloses a method for inverting and identifying pollution sources of sudden water pollution accidents in rivers. The steps of the method are first to establish a set of equations including river water area control equations, initial condition equations and boundary condition equations of the sudden water pollution accident, then set an observation section downstream of the sudden water pollution accident, test a set of time series monitoring data, establish an equation for the average concentration of pollutants in the section with respect to the monitoring data, and then use the least squares-radial basis matching method to invert the pollution source strength information.

[0010] The patent specification with the publication number CN114638114A discloses an emergency monitoring method and a tracing method for water pollution source tracing. The emergency monitoring method includes: obtaining the prior distribution information of the pollution source; setting up sentinel sections in the controlled waters, and setting up pollutant exceeding the standard response alarm, determining the current possible distribution and flow process of the pollution group; calculating the length of the pollution group; laying out the monitoring section spacing; determining the upstream and downstream positions of the emergency monitoring section; determining the sampling time interval and critical moment. The tracing method includes: after sampling, tracing the source by numerical inversion method, and updating the pollution source item through data assimilation and multi-source information fusion, and starting the pollution source investigation after obtaining the tracing results, and determining the location of the pollution source; evaluating the pollution hazard degree according to the pollution emission historical moment and the emission pollutant quality obtained by inversion, and conducting risk warning.

[0011] The patent specification with publication number CN117113027A discloses a pollution source tracing method and system based on water pollution. The pollution source tracing method includes: determining the monitored river and obtaining basic information of the monitored river; establishing a virtual model for the monitored river with reference to the basic information of the monitored river, performing water pollution monitoring at the observation point of the monitored river, determining the type and concentration of pollutants based on the water pollution monitoring data information, and determining the diffusion mode of pollutants in the monitored river according to the type of pollutants, using a river simulation model based on the location of the observation point and the concentration of pollutants to simulate water pollution and obtain water pollution simulation data using the pollutant diffusion method; and determining the pollution source by performing a placement analysis based on the water pollution simulation data. Summary of the invention

[0012] The present invention provides a method for inverting environmental damage caused by river pollution incidents, which overcomes the defects of the prior art that historical pollutant source strengths are difficult to determine and that the lack of source strength data will make it impossible to simulate the scope and extent of environmental damage. The pollutant source strength, scope and extent of environmental damage can be inverted based on limited historical monitoring data with high inversion accuracy.

[0013] A method for inverting environmental damage caused by river pollution incidents, comprising:

[0014] Establish a mathematical model of river hydrodynamics;

[0015] Establish mathematical models of pollutant diffusion;

[0016] Extract river pollutant monitoring data and select characteristic values ​​(such as pH, etc.);

[0017] Set the minimum and maximum ranges of source strength;

[0018] Inversely calculate and debug the pollutant diffusion mathematical model based on the river pollutant monitoring data and the minimum and maximum ranges of source strength, and establish correlation with limited historical monitoring data to determine the historical pollutant source strength (for example, it may include source strength concentration, source flow, etc.);

[0019] The determined pollutant source strength is input into the pollutant diffusion mathematical model to simulate the area of ​​polluted rivers, water volume and pollutant concentration.

[0020] In one embodiment, the hydrodynamic mathematical model includes:

[0021] The mass conservation equation:

[0022]

[0023] Momentum equation:

[0024]

[0025] Where: ζ is the water level; h is the still water depth; H is the total water depth, H = h + ζ; u and v are the vertical average flow velocities in the x and y directions respectively; g is the gravitational acceleration; f is the Coriolis force parameter; C z is Xie Cai coefficient; ε x , ε y are the horizontal eddy viscosity coefficients in the x and y directions respectively; t is the time; x and y are two directions perpendicular to each other on the horizontal plane.

[0026] In the process of establishing a mathematical model of river hydrodynamics, the calculation area and grid can be determined first, the calculation parameters can be selected, and then the model can be verified based on measured hydrological data. Furthermore, the calculation area can be divided using an unstructured grid (curved grid).

[0027] In the process of establishing the mathematical model of pollutant diffusion, the convection diffusion model can be used to simulate the pollutant emissions and their impacts. The control equation is:

[0028]

[0029] Where: c is the pollutant concentration; t is the time; x and y are two perpendicular directions on the horizontal plane; K x , K y are the diffusion coefficients in the x and y directions, respectively; u and v are the vertical average flow velocities in the x and y directions, respectively; H is the total water depth; f cis the pollution intensity of the pollution source;

[0030] Initial conditions: c(x,y)| t＝0 =c0(x,y); c0 is the initial concentration;

[0031] Boundary conditions:

[0032] On the closed boundary, since there is no material flux, its concentration value c is taken as zero;

[0033] On the open boundary, requirements are met

[0034] In the process of establishing a mathematical model of pollutant diffusion, the data of the monitoring point that is closest to the emission point and has the most regular waveform can be selected for model verification.

[0035] The method for inverting the pollutant source intensity and environmental damage of a river pollution incident can set the minimum and maximum source intensity intervals according to the discharge time, discharge scale, discharge method and / or discharge duration.

[0036] The present invention also provides a computer device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, and when the computer program is run, the processor executes the method for inverting environmental damage caused by river pollution incidents.

[0037] The present invention also provides a computer-readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a computer device, the computer device executes the method for inverting environmental damage caused by a river pollution incident.

[0038] The present invention also provides a computer program product, including a computer program, which, when executed by a computer device, enables the computer device to execute the method for inverting environmental damage caused by a river pollution incident.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The present invention uses historical and limited data to establish a linear correlation between source strength and data, thereby inverting the pollution source strength, which can solve the problem that river pollution events are difficult to monitor in real time and historical source strength is difficult to determine in the prior art;

[0041] The present invention first establishes a model, debugs and inverts the pollution source strength, and then simulates the pollution range according to the water flow movement and pollutant diffusion of the river, which solves the problem that the existing technology cannot carry out simulation work if the source strength data is missing. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1The figure is a flow chart of a method for inverting environmental damage of a river pollution incident according to the present invention.

[0043] Figure 2 Schematic diagram of the calculation area of ​​the hydrodynamic mathematical model of the embodiment.

[0044] Figure 3 This is a flow velocity and direction result diagram of the flow field analysis simulated by the hydrodynamic mathematical model of the embodiment.

[0045] Figure 4 This is a graph showing the actual measurement results of the pH value of the river in the example.

[0046] Figure 5 This is a graph showing the concentration of hydrochloric acid, a pollutant that is discharged illegally in an example.

[0047] Figure 6 For the example source flow is set to 0.5m 3 / s, the comparison curve between the actual pH value at the monitoring point and the value calculated by diffusion model simulation.

[0048] Figure 7 For the example source flow is set to 0.06m 3 / s, the comparison curve between the actual pH value at the monitoring point and the value calculated by diffusion model simulation.

[0049] Figure 8 For the example source flow is set to 0.01 m 3 / s, the comparison curve between the actual pH value at the monitoring point and the value calculated by diffusion model simulation.

[0050] Fig. 9 This is a source strength diagram of the Example Chemical Plant from May 24, 2019 to June 6, 2019.

[0051] Fig.10 This is a graph of the measured pH results from May 24 to June 6, 2019 in Example.

[0052] Fig.11 Graph showing the correlation between source strength concentration and measured pH (the measurement point closest to the discharge point) in the example.

[0053] Fig.12 The minimum pH distribution diagram in the calculation area for the example (source flow 0.06m 3 / s). DETAILED DESCRIPTION

[0054] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention.

[0055] In this example, indicators such as pH, total phosphorus, and fluoride ions in a river are polluted, but the specific amount of pollutants, source strength, scope, and degree of pollution are unknown.

[0056] See also Figure 1 , a method for inversion of environmental damage caused by river pollution incidents, comprising:

[0057] 1. Establish a mathematical model of river hydrodynamics.

[0058] The hydrodynamic mathematical model includes:

[0059] The mass conservation equation:

[0060]

[0061] Momentum equation:

[0062]

[0063] Where: ζ is the water level; h is the still water depth; H is the total water depth, H = h + ζ; u and v are the vertical average flow velocities in the x and y directions respectively; g is the gravitational acceleration, which can be taken as g = 9.81 m / s 2 ; f is the Coriolis force parameter; C z is Xie Cai coefficient; ε x , ε y are the horizontal eddy viscosity coefficients in the x and y directions respectively; t is the time; x and y are two directions perpendicular to each other on the horizontal plane.

[0064] In the process of establishing the mathematical model of river hydrodynamics, the calculation area and grid are first determined, the calculation parameters are selected, and then the model is verified based on the measured hydrological data.

[0065] The hydrodynamic mathematical model of this embodiment uses unstructured grids to divide the calculation area. Compared with general rectangular grid division, the curved grid can be closer to the boundary, so as to better simulate the flow state at the boundary and reduce the impact of the boundary.

[0066] like Figure 2 As shown in the figure, the calculation area is divided into unstructured grids, with a total of 23,274 calculation grids, and the grid scale near the study area is controlled at about 10m.

[0067] According to the river cross-section diagram, the main river channel in the study area is in an inverted trapezoidal shape, with a water depth of about 3m and other tributaries with a water depth of 0.6 to 1.2m.

[0068] Simulation flow field analysis. Figure 3This is the flow field diagram of the river near the study area. In general, the water flow direction is from northwest to southeast (usually called downstream), with an average flow velocity of 0.12m / s. When affected by the downstream tidal support, the flow direction changes to from southeast to northwest (usually called upstream), with an average flow velocity of 0.04m / s. The downstream flow of this river section lasts for a long time and has a high flow velocity; while the upstream flow of the river section lasts for a long time and has a low flow velocity. The overall flow of this river section is mainly downstream.

[0069] 2. Establish a mathematical model of pollutant diffusion.

[0070] The convection-diffusion model is used to simulate pollutant emissions and their impacts, and its control equation is:

[0071]

[0072] Where: c is the pollutant concentration; t is the time; x and y are two perpendicular directions on the horizontal plane; K x , K y are the diffusion coefficients in the x and y directions, respectively; u and v are the vertical average flow velocities in the x and y directions, respectively; H is the total water depth; f c is the pollution intensity of the pollution source;

[0073] Initial conditions: c(x,y)| t＝0 =c0(x,y); c0 is the initial concentration;

[0074] Boundary conditions:

[0075] On the closed boundary, since there is no material flux, its concentration value c is taken as zero;

[0076] On the open boundary, requirements are met

[0077] The pollutant diffusion and degradation coefficients are determined through on-site river testing, experimental studies of pollutants and river water samples.

[0078] The diffusion coefficient was tested on site in the river channel, taking 5m 2 / s.

[0079] The river water contains a certain amount of bicarbonate, carbonate and hydroxide (i.e. alkalinity). Due to the presence of alkalinity, the hydrochloric acid discharged in this case will buffer the pH of the river water to a certain extent, making the pH pollution range smaller than the theoretical calculated value. In this case, 8 surface water samples were collected from the river and titrated with pollutants in the laboratory. From the analysis of the test data, it can be seen that the average alkalinity is 111 mg / L, which is used to further determine the pollutant degradation (buffering) coefficient.

[0080] From the results of the measured water pH, we found that during the calculation period: 1) At the measurement point closest to the chemical plant's illegal discharge point, the pH curve has the most regular waveform, and the time interval between any two adjacent peaks (troughs) is the most uniform. 2) At the measurement point that is the second closest to the chemical plant's illegal discharge point, the pH curve has a relatively regular waveform, but the shape of the peak has been deformed, and the time interval between any two adjacent peaks (troughs) has also begun to become uneven. 3) At the measurement point that is the third closest to the chemical plant's illegal discharge point, the pH curve has been significantly deformed, and the time interval between any two adjacent peaks (troughs) has become quite uneven.

[0081] Therefore, in the process of establishing the mathematical model of pollutant diffusion, the data of the monitoring point closest to the emission point and with the most regular waveform of the curve are selected for model verification.

[0082] 3. Extract river pollutant monitoring data and select the characteristic value pH.

[0083] See also Figure 4 , the online monitoring and routine monitoring data of river pollutants were extracted and analyzed. The pH fluctuation from May 24, 2019 to June 6, 2019 was the most obvious, with a minimum value of 1.95 and an average value of 6.09.

[0084] 4. Set the minimum and maximum ranges for source strength according to the emission time, emission scale, emission method and / or emission duration.

[0085] Source strength concentration setting. Based on the investigation records of the by-product hydrochloric acid discharge mode, discharge scale, discharge time and discharge duration, the discharge pump flow, the diameter of the discharge pipeline and the river pH data, it is determined that the mass fraction of the illegally discharged waste hydrochloric acid is between 10% and 30%. After conversion, its molar concentration is about 3mol / L to 9mol / L. During the calculation period, the concentration of the pollutant hydrochloric acid illegally discharged is as follows: Figure 5 shown.

[0086] Source flow setting. The maximum source flow is 0.5m 3 / s, the minimum is 0. In this case, the total amount of by-product hydrochloric acid is controlled by controlling the source flow rate. A total of 50 source flows are set for trial calculation, see Table 1.

[0087] Table 1 Source flow settings

[0088]

[0089] 5. Based on the river pollutant monitoring data and the minimum and maximum source strength ranges, the pollutant diffusion mathematical model is inverted and debugged, and correlation is established with limited historical monitoring data to determine the historical pollutant source strength.

[0090] 5.1. Inversion and debugging

[0091] Figure 6 to Figure 8 Set the source flow rate to 0.01~0.5m 3 / s, the comparison curve of the measured pH value at the monitoring point and the value calculated by the diffusion model simulation. 3 / s, the pH corresponding to the peaks of each calculated value is lower than the measured pH value. Figure 6 , when the source flow is 0.5m 3 / s, the calculated peak values ​​are all smaller than the measured peak values, with a difference of -2.22 to 0.26, and the average absolute value of the error is 0.913, indicating that the total amount of hydrochloric acid emissions in the model is too large. Figure 7 From the pH comparison curve, it can be seen that the calculated value curve fits well with the measured value curve. The error calculation table also shows that the source flow rate is set to 0.06m 3 / s, the overall error of each peak value is better than that of other source flows, indicating that the setting value of this source flow is more reasonable. Figure 8 , when the source flow is 0.01m 3 / s, the calculated peak value and the measured peak value have deviated greatly, with a difference of 0.19 to 1.61, and the average absolute value of the error is 0.727. It can be seen from the figure that the total amount of hydrochloric acid discharged in the model has deviated greatly from the actual total amount of discharge. 3 / s, the pH corresponding to the peaks of each calculated value is greater than the measured pH value. Summary: The source flow rate is 0.06m 3 / s, the calculated peak value is very close to the measured peak value.

[0092] 5.2 Source Strength Calculation

[0093] When the source flow is 0.06m 3 / s, according to the diffusion model simulation calculation (the source strength concentration changes as Figure 5 As shown in the figure, from May 24, 2019 to June 6, 2019, the chemical plant discharged a total of 2,535 tons of 6 mol / L by-product hydrochloric acid. Fig. 9 shown.

[0094] 5.3. Establish correlation with limited historical monitoring data.

[0095] The time interval between the measured pH values ​​in 2018 and the first half of 2019 is too large (one data point every 4 hours), and the only measuring point is far away from the discharge point (about 8 km downstream along the river), so it cannot be directly used to infer the total discharge from January 1, 2018 to June 26, 2019. Therefore, this case adopts the method of establishing the correlation between source concentration and measured pH to estimate the total discharge from January 1, 2018 to June 26, 2019.

[0096] According to the measured pH from May 24 to June 6, 2019 ( Fig.10 ), during this period, there were seven obvious abnormalities in pH ( Fig.10 The seven peaks are boxed in the middle).

[0097] Source strength concentration (such as Figure 5 After being converted into pH value, there is an obvious correlation between it and the measured pH. After calculation by linear regression equation, the correlation between the two is as follows Fig.11 shown.

[0098] When the source flow is 0.06m 3 / s, according to the diffusion model simulation calculation, from January 2018 to June 2019, the pollutant emission companies emitted a total of 42,382 tons of 6 mol / L hydrochloric acid (total pollutant).

[0099] 6. Input the determined pollutant source strength into the pollutant diffusion mathematical model to simulate the area, water volume and pollutant concentration of the polluted river.

[0100] According to the test data: pH background value is 7.45. Input the source strength data of the maximum concentration inversion of each pollutant (hydrochloric acid, etc.) into the verified model.

[0101] According to the calculation results, the area of ​​water with pH ≤ 2 in the polluted area is about 3308m 2 The volume of polluted water is about 8269m3; the area of ​​water with pH ≤ 7.2 is about 2.87km 2 , the volume of contaminated water is about 7.16×10 6 m3.

[0102] For the distribution of the highest pollutant concentration in the calculation domain, see Fig.12 .

[0103] According to the model results, the lowest pH value in the calculation domain appears near the illegal discharge outlet, with the lowest pH being 1.95. With a pH limit of 7.2, the pollutants affect the farthest point along the river channel, about 14.6 km downstream.

[0104] In addition, it should be understood that after reading the above description of the present invention, those skilled in the art may make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the claims attached to this application.

Claims

1. A method for inverting environmental damage caused by river pollution incidents, characterized in that: include: Establish a mathematical model of river hydrodynamics; Establish mathematical models of pollutant diffusion; Extract river pollutant monitoring data and select characteristic values; Set the minimum and maximum ranges of source strength; The pollutant diffusion mathematical model is inversely calculated and debugged based on the river pollutant monitoring data and the minimum and maximum source strength intervals, and correlation is established with limited historical monitoring data to determine the historical pollutant source strength; The determined pollutant source strength is input into the pollutant diffusion mathematical model to simulate the area of ​​polluted rivers, water volume and pollutant concentration.

2. The method according to claim 1, characterized in that: The hydrodynamic mathematical model includes: The mass conservation equation: Momentum equation: Where: ζ is the water level; h is the still water depth; H is the total water depth, H = h + ζ; u and v are the vertical average flow velocities in the x and y directions respectively; g is the gravitational acceleration; f is the Coriolis force parameter; C z is Xie Cai coefficient; ε x , ε y are the horizontal eddy viscosity coefficients in the x and y directions respectively; t is the time; x and y are two directions perpendicular to each other on the horizontal plane.

3. The method according to claim 1, characterized in that In the process of establishing the mathematical model of river hydrodynamics, the calculation area and grid are first determined, the calculation parameters are selected, and then the model is verified based on the measured hydrological data; The calculation area is divided by using unstructured grids.

4. The method according to claim 1, characterized in that: In the process of establishing the mathematical model of pollutant diffusion, the convection diffusion model is used to simulate the pollutant emissions and their impacts. The control equation is: Where: c is the pollutant concentration; t is the time; x and y are two perpendicular directions on the horizontal plane; K x , K y are the diffusion coefficients in the x and y directions, respectively; u and v are the vertical average flow velocities in the x and y directions, respectively; H is the total water depth; f c is the pollution intensity of the pollution source; Initial conditions: c(x,y)| t＝0 =c0(x,y); c0 is the initial concentration; Boundary conditions: On the closed boundary, since there is no material flux, its concentration value c is taken as zero; On the open boundary, requirements are met 5. The method according to claim 1, characterized in that In the process of establishing the mathematical model of pollutant diffusion, the data of the monitoring point closest to the emission point and with the most regular waveform of the curve are selected for model verification.

6. The method according to claim 1, characterized in that Set the minimum and maximum source strength ranges based on the emission time, emission scale, emission method and / or emission duration.

7. A computer device comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, wherein: When the computer program is executed, the processor executes the method for inverting environmental damage caused by river pollution incidents as described in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores programs or instructions, and when the programs or instructions are executed by a computer device, the computer device executes the method for inverting environmental damage caused by a river pollution incident as described in any one of claims 1 to 6.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a computer device, the computer device executes the method for inverting environmental damage caused by a river pollution incident as described in any one of claims 1 to 6.

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