Polluted plume grading method, system and equipment and storage medium

Abstract

The embodiment of the invention provides a pollution plume grading method, system and equipment and a storage medium, and belongs to the technical field of underground water pollution intelligent management. The pollution plume grading method comprises the following steps: acquiring point pollution data; dividing a plurality of independent pollution plumes based on the point pollution data; carrying out pollution migration simulation on the pollution plume to obtain a corresponding simulated pollution plume; and predicting the duration when the factory boundary area concentration of the simulated pollution plume is greater than the preset concentration to obtain a duration prediction result, and grading the pollution plume based on the duration prediction result. According to the embodiment of the invention, the change of the pollution plume along with time is considered, migration simulation is performed on the divided pollution plume, the time when the concentration of the factory boundary region exceeds the standard is predicted, and the future pollution trend of the pollution plume is simulated and predicted, so that the pollution plume is divided, the accuracy and precision of pollution level division are improved, and the user experience is improved. The key area of enterprise pollution management is effectively reduced, and the enterprise pollution management efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of groundwater pollution management, and in particular to a pollution plume classification method, a pollution plume classification system, an electronic device and a readable storage medium. Background Art

[0002] Combined with the results of the first round of national surveys on soil and groundwater pollution, groundwater pollution in enterprises is widespread, especially for petroleum and petrochemical enterprises, where the detection rate of organic pollution in groundwater is high, and control and repair are urgently needed. Since the pollution distribution of the entire enterprise is often uneven, and the concentration of polluted areas is also significantly different, graded management of pollution plumes can effectively reduce the management workload and is conducive to gathering control forces. It is the trend of future enterprise site pollution management.

[0003] The existing groundwater pollution classification technology is mainly based on the multi-factor groundwater pollution risk assessment and classification of the analytic hierarchy process, and focuses on groundwater regional assessment and enterprise site assessment and classification. However, the above scheme does not take into account the time factor and the concentration of the factory boundary area, which makes the pollution classification results inaccurate and unreliable, which is not conducive to enterprises concentrating their superior forces to carry out pollution control. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a pollution plume classification method, system, device and storage medium to solve the above technical problems.

[0005] In order to achieve the above object, an embodiment of the present invention provides a pollution plume classification method, comprising:

[0006] Acquire point pollution data; wherein the point pollution data includes point pollution distribution data and point pollution concentration data;

[0007] Based on the point pollution data, a plurality of independent pollution plumes are divided;

[0008] Conduct pollution migration simulation on the pollution plume to obtain a corresponding simulated pollution plume;

[0009] Predicting the duration of time when the concentration of the simulated pollution plume in the factory boundary area is greater than the preset concentration, and obtaining a duration prediction result; wherein the concentration of the factory boundary area is the pollution concentration of the area where the pollution plume exceeds the preset boundary;

[0010] Pollution plumes are classified based on their duration predictions.

[0011] Optionally, dividing a plurality of independent pollution plumes based on the point pollution data includes:

[0012] Interpolating the point pollution data using an inverse distance interpolation method to obtain sheet pollution distribution data and sheet pollution concentration data;

[0013] Based on the sheet pollution distribution data and the sheet pollution concentration data, determining a plurality of high pollution concentration areas;

[0014] Determine whether there are overlapping areas between adjacent high-pollution concentration areas;

[0015] Adjacent areas with high pollution concentrations and no overlapping areas are treated as independent pollution plumes.

[0016] Optionally, the method further comprises:

[0017] If it is determined that there is an overlapping area between adjacent high-value pollution concentration areas, the maximum concentration of the overlapping area and the maximum concentration of the high-value area are determined based on the sheet pollution concentration data; wherein the maximum concentration of the high-value area is the maximum concentration of the high-value pollution concentration area including the overlapping area;

[0018] The maximum concentration of the overlapping area is compared with the maximum concentration of the high-value area. If the maximum concentration of the overlapping area is less than a preset multiple of the maximum concentration of the high-value area, the high-value pollution concentration area containing the overlapping area is segmented to obtain an independent pollution plume.

[0019] Optionally, the method further comprises:

[0020] If the maximum concentration of the overlapping area is greater than or equal to a preset multiple of the maximum concentration of the high-value area, the high-value pollution concentration areas including the overlapping area will be merged to obtain an independent pollution plume.

[0021] Optionally, the method further comprises:

[0022] Determine the concentration of the pollution plume out of the factory boundary based on the pollution plume, sheet pollution distribution data and sheet pollution concentration data;

[0023] Determine whether the concentration of the pollution plume in the factory boundary area is greater than the preset concentration;

[0024] If the concentration of the pollution plume in the factory boundary area is greater than the preset concentration, the pollution plume is classified as a first-level pollution plume.

[0025] Optionally, the performing pollution migration simulation on the pollution plume to obtain a corresponding simulated pollution plume includes:

[0026] If the concentration of the pollution plume at the factory boundary area is less than or equal to the preset concentration, the pollution plume shape information and simulation parameters of the pollution plume are determined based on the divided pollution plume and the sheet pollution data;

[0027] Based on the pollution plume shape information and simulation parameters of the pollution plume, a migration simulation is performed on the pollution plume to obtain a corresponding simulated pollution plume.

[0028] Optionally, the performing migration simulation on the pollution plume based on the pollution plume shape information and simulation parameters of the pollution plume to obtain a corresponding simulated pollution plume includes:

[0029] Based on the pollution plume shape information and simulation parameters of the pollution plume, migration simulation is performed on the pollution plume to obtain a corresponding pollution plume model;

[0030] Determine whether a fitting rate between an actual pollution concentration of the pollution plume and a simulated pollution concentration of a corresponding pollution plume model is greater than a preset fitting rate;

[0031] If so, the current migration simulation is determined to be successful, and the pollution plume model is saved as a simulated pollution plume corresponding to the pollution plume.

[0032] Optionally, the classifying the pollution plume based on the duration prediction result includes:

[0033] If it is determined that the predicted duration during which the concentration of the factory boundary area of ​​the simulated pollution plume is greater than the preset concentration is less than the first duration, the pollution plume corresponding to the simulated pollution plume is classified as a first-level pollution plume;

[0034] If it is determined that the predicted duration during which the concentration of the factory boundary area of ​​the simulated pollution plume is greater than the preset concentration is greater than the first duration but less than the second duration, the pollution plume corresponding to the simulated pollution plume is classified as a second-level pollution plume;

[0035] If it is determined that the predicted duration that the concentration of the simulated pollution plume at the factory boundary area is greater than the preset concentration is greater than the second duration, the pollution plume corresponding to the simulated pollution plume is classified as a third-level pollution plume.

[0036] In a second aspect of the embodiments of the present invention, a pollution plume classification system is provided, the system comprising:

[0037] A data acquisition module, used to acquire point pollution data; wherein the point pollution data includes point pollution distribution data and point pollution concentration data;

[0038] A pollution plume division module, used for dividing a plurality of independent pollution plumes based on the point pollution data;

[0039] A migration simulation module is used to simulate the migration of pollution plumes to obtain corresponding simulated pollution plumes;

[0040] A duration prediction module is used to predict the duration of time when the concentration of the simulated pollution plume in the factory boundary area is greater than a preset concentration, and obtain a duration prediction result; wherein the concentration of the factory boundary area is the pollution concentration of the area where the pollution plume exceeds the preset boundary;

[0041] The classification module is used to classify the pollution plume based on the duration prediction results.

[0042] Optionally, the pollution plume division module includes a data processing module and a region division module;

[0043] The data processing module is used for:

[0044] Interpolating the point pollution data using an inverse distance interpolation method to obtain sheet pollution distribution data and sheet pollution concentration data;

[0045] Based on the sheet pollution distribution data and the sheet pollution concentration data, determining a plurality of high pollution concentration areas;

[0046] The area division module is used for:

[0047] Determine whether there are overlapping areas between adjacent high-pollution concentration areas;

[0048] Adjacent areas with high pollution concentrations and no overlapping areas are treated as independent pollution plumes.

[0049] Optionally, the area division module is further used for:

[0050] If it is determined that there is an overlapping area between adjacent high-value pollution concentration areas, the maximum concentration of the overlapping area and the maximum concentration of the high-value area are determined based on the sheet pollution concentration data; wherein the maximum concentration of the high-value area is the maximum concentration of the high-value pollution concentration area including the overlapping area;

[0051] Compare the maximum concentration of the overlapping area with the maximum concentration of the high-value area: if the maximum concentration of the overlapping area is less than a preset multiple of the maximum concentration of the high-value area, segment the high-value pollution concentration area containing the overlapping area to obtain an independent pollution plume;

[0052] If the maximum concentration of the overlapping area is greater than or equal to a preset multiple of the maximum concentration of the high-value area, the high-value pollution concentration areas including the overlapping area will be merged to obtain an independent pollution plume.

[0053] Optionally, the migration simulation module is specifically used to:

[0054] Determining the pollution plume shape information and simulation parameters of the pollution plume based on the divided pollution plume and the sheet pollution data;

[0055] Based on the pollution plume shape information and simulation parameters of the pollution plume, a migration simulation is performed on the pollution plume to obtain a corresponding simulated pollution plume.

[0056] Optionally, the level division module is specifically used for:

[0057] If it is determined that the predicted duration during which the concentration of the factory boundary area of ​​the simulated pollution plume is greater than the preset concentration is less than the first duration, the pollution plume corresponding to the simulated pollution plume is classified as a first-level pollution plume;

[0058] If it is determined that the predicted duration during which the concentration of the factory boundary area of ​​the simulated pollution plume is greater than the preset concentration is greater than the first duration but less than the second duration, the pollution plume corresponding to the simulated pollution plume is classified as a second-level pollution plume;

[0059] If it is determined that the predicted duration that the concentration of the simulated pollution plume at the factory boundary area is greater than the preset concentration is greater than the second duration, the pollution plume corresponding to the simulated pollution plume is classified as a third-level pollution plume.

[0060] A third aspect of the present application provides an electronic device configured to execute the above-mentioned pollution plume classification method.

[0061] A fourth aspect of the present application provides a machine-readable storage medium having instructions stored thereon. When the instructions are executed by a processor, the processor is configured to execute the above-mentioned pollution plume classification method.

[0062] The embodiment of the present invention obtains point pollution data, divides pollution plumes based on the point pollution data, and then simulates the pollution migration of the pollution plumes to obtain corresponding simulated pollution plumes, predicts the time when the concentration of the simulated pollution plume at the factory boundary area is greater than the preset concentration, obtains the duration prediction result, and classifies the pollution plumes based on the duration prediction result to obtain pollution plumes of different levels. That is, the embodiment of the present invention classifies the pollution plumes, effectively narrows the key areas of pollution management of the enterprise, considers the changes of the pollution plumes over time, performs migration simulation on the divided pollution plumes to simulate the future pollution trend of the pollution plumes, and then predicts the time when the concentration at the factory boundary area exceeds the standard, and classifies the pollution plumes based on the duration prediction result, thereby improving the accuracy and precision of the pollution level classification, facilitating the enterprise groundwater pollution management, and improving the enterprise pollution management efficiency.

[0063] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0065] Figure 1 It is a schematic diagram of a flow chart of a pollution plume classification method provided by an embodiment of the present invention;

[0066] Figure 2It is a schematic diagram of the overall process of a pollution plume classification method provided by an embodiment of the present invention;

[0067] Figure 3 This is a schematic diagram of the pollution plume division at the site of Enterprise A;

[0068] Figure 4 This is a schematic diagram of the pollution plume division at the site of enterprise B;

[0069] Figure 5 This is a schematic diagram of the pollution plume division at the site of Enterprise C;

[0070] Figure 6 This is a schematic diagram of the pollution plume division at the enterprise D site;

[0071] Figure 7 This is a schematic diagram of the pollution plume division at the site of Enterprise E;

[0072] Figure 8 It is a schematic diagram of the architecture of a pollution plume classification system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0073] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0074] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0075] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0076] Embodiment 1

[0077] Please refer to Figure 1 , Figure 1 It is a schematic diagram of a flow chart of a pollution plume classification method provided in this embodiment.

[0078] Step S100: Acquire point pollution data; wherein the point pollution data includes point pollution distribution data and point pollution concentration data.

[0079] Point pollution data refers to enterprise pollution data, which only contains one type of pollution data, including point pollution distribution data and point pollution concentration data, as well as basic geological image maps, groundwater pollutant types, and hydrogeological simulation parameter library data. Among them, the hydrogeological simulation parameter library includes a public simulation database and an enterprise characteristic hydrogeological library. The public simulation parameter library includes industry standards, specification guidelines, and literature. As a public data set, the parameters in the public simulation parameter library are empirical value ranges within each standard, rather than a single value, and the empirical value range will not change during the simulation; the enterprise characteristic database can be directly entered according to the lithology catalog content in the site investigation report, without professional restrictions, and the system will automatically update the enterprise characteristic database data according to the hydrogeological conditions of the enterprise.

[0080] Step S200: Divide a plurality of independent pollution plumes based on the point pollution data.

[0081] Specifically, this embodiment uses the inverse distance difference method to interpolate single point pollution concentration data to obtain multiple sheet pollution data with an area of ​​not less than 10m*10m, the sheet pollution data includes sheet pollution distribution data and sheet pollution concentration data, based on the sheet pollution distribution data and the sheet pollution concentration data, it is possible to determine multiple pollution concentration high value areas, and further determine whether there are overlapping areas between the pollution concentration high value areas, if there is no overlapping area, the adjacent pollution concentration high value areas without overlapping areas are treated as independent pollution plumes; if there is an overlapping area, further based on the sheet pollution concentration data, the maximum concentration of the overlapping area and the maximum concentration of the high value area are determined, the maximum concentration of the high value area of ​​pollution concentration containing the overlapping area, and it is determined whether the maximum concentration of the overlapping area is less than a preset multiple of the maximum concentration of the high value area, if the maximum concentration of the overlapping area is less than a preset multiple of the maximum concentration of the high value area, the pollution concentration high value area corresponding to the overlapping area is segmented to obtain an independent pollution plume; if the maximum concentration of the overlapping area is greater than or equal to a preset multiple of the maximum concentration of the high value area, the pollution concentration high value areas corresponding to the overlapping area are merged to obtain an independent pollution plume. Among them, the preset multiple can be set by the enterprise's pollution management requirements and can be 50%.

[0082] It should be noted that in this embodiment, the maximum concentration of the high-value area of ​​the leftmost high-value pollution concentration area in the adjacent high-value pollution concentration area is compared with the maximum concentration of the overlapping area to segment or merge the adjacent high-value pollution concentration areas to obtain independent pollution plumes. If there is a high-value pollution concentration area whose left and right sides overlap with the adjacent high-value pollution concentration area, the left side of the high-value pollution concentration area is first judged and analyzed, and then the right side is judged and analyzed to separate the independent pollution plume.

[0083] Step S300: performing pollution migration simulation on the pollution plume to obtain a corresponding simulated pollution plume.

[0084] It should be understood that this embodiment is for the purpose of improving the efficiency of enterprise pollution management, and divides and grades enterprise pollution. Before step S300, it also includes determining the factory boundary area concentration of the pollution plume based on the pollution plume and the sheet pollution concentration data. The factory boundary area concentration is the pollution concentration of the area where the pollution plume exceeds the preset boundary. For example, the preset boundary can be the enterprise factory boundary, and the factory boundary area concentration is the pollution concentration of the part of the pollution plume that exceeds the enterprise factory boundary. After determining the factory boundary area concentration of the pollution plume, it is further determined whether the factory boundary area concentration of the pollution plume exceeds the preset concentration. If so, the pollution plume corresponding to the factory boundary area concentration is divided into a first-level pollution plume; if not, based on the divided pollution plume and the sheet pollution data, the pollution plume shape information and simulation parameter data are determined, and based on the pollution plume shape information and simulation parameters, the pollution plume is simulated for migration to obtain a simulated pollution plume. Wherein, the pollution plume shape information includes "I" type pollution plume and "L" type pollution plume.

[0085] In this embodiment, the water-soluble organic pollutant migration and diffusion model can be used to simulate the migration of the pollution plume to obtain a simulated pollution plume. Specifically, based on the pollution plume shape information and simulation parameters, the water-soluble organic pollutant migration and diffusion model is used to simulate the migration of the pollution plume to obtain a pollution plume model, and it is determined whether the fitting rate between the actual pollution concentration of the pollution plume and the simulated pollution concentration of the pollution plume model is greater than the preset fitting rate. If so, it is determined that the current migration simulation is successful, and the pollution plume model is saved as a simulated pollution plume; if not, it is determined that the current migration simulation has failed, and the migration simulation is performed again until the fitting rate between the actual pollution concentration of the pollution plume and the simulated pollution concentration of the pollution plume model is greater than the preset fitting rate, and the pollution plume model is saved as a simulated pollution plume.

[0086] It should be noted that for the "I" type pollution plume, only a single migration simulation is needed to meet the requirements. The migration simulation obtains the "I" type pollution plume model, and the pollution concentrations of three simulated concentration sampling points evenly distributed on the center line of the "I" type pollution plume model are taken. The pollution concentrations of these three simulated concentration sampling points can be measured concentrations or interpolated concentrations. It is determined whether the fitting rate between the actual pollution concentrations of these three simulated concentration sampling points and the simulated pollution concentrations of the "I" type pollution plume model is greater than the preset fitting rate. If not, three simulated concentration sampling points evenly distributed on the center line of the "I" type pollution plume model are reselected, and it is determined again whether the fitting rate between the actual pollution concentrations of these three simulated concentration sampling points and the simulated pollution concentrations of the "I" type pollution plume model is Whether it is greater than the preset fitting rate, until the fitting rate of the actual pollution concentration at the three simulated concentration sampling points and the simulated pollution concentration of the "I" type pollution plume model is greater than the preset fitting rate, save the current pollution plume model as the simulated pollution plume; if so, the current migration simulation is judged to be successful, and the current pollution plume model is used as the simulated pollution plume; for the "L" type pollution plume, it is necessary to judge the two groundwater flow directions of the "L" type pollution plume, divide the "L" type pollution plume into two "I" type pollution plumes and perform migration simulation for the two "I" type pollution plumes respectively, and judge whether the fitting rates of the simulated pollution concentrations of the two "I" type pollution plume models are both greater than the preset fitting rate. If so, the current migration simulation is judged to be successful, and the current pollution plume model is used as the simulated pollution plume.

[0087] Step S400: predicting the duration of time when the concentration of the simulated pollution plume in the factory boundary area is greater than a preset concentration, and obtaining a duration prediction result; wherein the concentration of the factory boundary area is the pollution concentration of the area where the pollution plume exceeds the preset boundary.

[0088] This embodiment can use a fully automatic growth curve analyzer (bioscreen) to predict the time when the concentration of the simulated pollution plume at the factory boundary area exceeds the preset concentration, and obtain the predicted time length that the concentration of each simulated pollution plume at the factory boundary area is greater than the preset concentration.

[0089] Step S500: classifying the pollution plumes based on the duration prediction results.

[0090] Specifically, if the predicted duration that the concentration of the simulated pollution plume at the factory boundary area is greater than the preset concentration is less than a first duration, the pollution plume corresponding to the simulated pollution plume is classified as a first-level pollution plume; if the predicted duration that the concentration of the simulated pollution plume at the factory boundary area is greater than the preset concentration is greater than the first duration but less than the second duration, the pollution plume corresponding to the simulated pollution plume is classified as a second-level pollution plume; if the predicted duration that the concentration of the simulated pollution plume at the factory boundary area is greater than the preset concentration is greater than the second duration, the pollution plume corresponding to the simulated pollution plume is classified as a third-level pollution plume.

[0091] For example, the first time period may be 2 years, and the second time period may be 8 years. According to the present application, if the predicted time period that the concentration of the simulated pollution plume at the factory boundary area is greater than the preset concentration is 1.5 years, the pollution plume corresponding to the simulated pollution plume is classified as a first-level pollution plume; if the predicted time period that the concentration of the simulated pollution plume at the factory boundary area is greater than the preset concentration is 6 years, the pollution plume corresponding to the simulated pollution plume is classified as a second-level pollution plume; if the predicted time period that the concentration of the simulated pollution plume at the factory boundary area is greater than the preset concentration is 9 years, the pollution plume corresponding to the simulated pollution plume is classified as a third-level pollution plume.

[0092] Figure 2 : is a schematic diagram of the overall process of this embodiment. First, point pollution data is obtained, and the point pollution data is interpolated using the inverse distance interpolation method to determine the high-value pollution concentration area, and whether there is an overlapping area between adjacent high-value pollution concentration areas. If there is an overlapping area, it is determined whether the maximum concentration of the overlapping area is less than a preset multiple of the maximum concentration of the high-value area. If so, the high-value pollution concentration area corresponding to the overlapping area is segmented to obtain an independent pollution plume. If not, the high-value pollution concentration areas corresponding to the overlapping area are merged to obtain an independent pollution plume. If there is no overlapping area, the adjacent high-value pollution concentration areas are taken as independent pollution plumes to determine whether the factory boundary concentration of the pollution plume is greater than the preset concentration. If so, the pollution plume is classified into the first level. If not, the pollution migration simulation is performed on the pollution plume based on the pollution plume shape information and simulation parameters. During the simulation process, a simulation is selected on the center line of the pollution plume. Concentration sampling points, determine whether the fitting rate between the actual pollution concentration of the pollution plume and the simulated pollution concentration of the pollution plume model is greater than the preset fitting rate, if not, reselect the simulated pollution concentration, if so, save the pollution plume model as a simulated pollution plume, and further predict the time when the factory boundary concentration of the simulated pollution plume is greater than the preset concentration, and obtain the duration prediction result, and determine that the predicted duration that the factory boundary area concentration of the simulated pollution plume is greater than the preset concentration is less than the first duration, then the pollution plume corresponding to the simulated pollution plume is classified as a first-level pollution plume; determine that the predicted duration that the factory boundary area concentration of the simulated pollution plume is greater than the preset concentration is greater than the first duration but less than the second duration, then the pollution plume corresponding to the simulated pollution plume is classified as a second-level pollution plume; determine that the predicted duration that the factory boundary area concentration of the simulated pollution plume is greater than the preset concentration is greater than the second duration, then the pollution plume corresponding to the simulated pollution plume is classified as a third-level pollution plume.

[0093] Example 1: Obtain point pollution data of the site of enterprise A, use the inverse distance interpolation method to interpolate the point pollution data, obtain sheet pollution concentration data and sheet pollution distribution data, and further determine multiple high-value pollution concentration areas. The high-value pollution concentration areas are as follows: Figure 3As shown, there is no overlapping area between two adjacent high-pollution concentration areas, so the adjacent high-pollution concentration areas are regarded as two independent pollution plumes, and both pollution plumes are "I" type pollution plumes. The preset concentration is set to 20. Based on the sheet pollution concentration data and the sheet pollution distribution data, it is determined that the concentrations of the factory boundary areas of the two "I" type pollution plumes exceeding the preset boundaries are both greater than 20. In this case, there is no need for migration simulation, and the two "I" type pollution plumes are classified as the first level.

[0094] Example 2: For the point pollution data of the site of Enterprise B, the inverse distance interpolation method is used to interpolate the point pollution data to obtain the sheet pollution concentration data and sheet pollution distribution data, and further determine multiple areas with high pollution concentration. The areas with high pollution concentration are as follows: Figure 4 As shown, there is an overlap between two adjacent high-pollution concentration areas. The maximum concentration of the high-pollution concentration area on the left is 28, and the maximum concentration of the overlapping area is 20. Obviously, 20≥50%*28, so the above two high-pollution concentration areas are merged to obtain an independent pollution plume, which is a type "I" pollution plume. The preset concentration is set to 20. Based on the sheet pollution concentration data and the sheet pollution distribution data, it is determined that the concentration of the factory boundary area of ​​the type "I" pollution plume exceeds the preset boundary by more than 20. In this case, the type "I" pollution plume does not require migration simulation, and is classified as the first level.

[0095] Example 3: For the point pollution data of the site of Enterprise C, the inverse distance interpolation method is used to interpolate the point pollution data to obtain the sheet pollution concentration data and sheet pollution distribution data, and further determine multiple areas with high pollution concentration. The areas with high pollution concentration are as follows: Figure 5As shown, there are three high-value pollution concentration areas from left to right, and there are overlaps between adjacent high-value pollution concentration areas. The maximum concentration of the leftmost high-value pollution concentration area is 28, and the maximum concentration of the overlapping area between the leftmost high-value pollution concentration area and the middle high-value pollution concentration area is 20. Obviously, 20≥50%*28, so the leftmost high-value pollution concentration area and the middle high-value pollution concentration area are merged, and the maximum concentration of the merged high-value pollution concentration area is 28, and the maximum concentration of the overlapping area between the merged high-value pollution concentration area and the rightmost high-value pollution concentration area is 12. Obviously, 12<50%*28, so the merged high-value pollution concentration area and the rightmost high-value pollution concentration area are divided into two independent pollution plumes, and both pollution plumes are "I" type pollution plumes. The preset concentration is set to 20. Based on the sheet pollution concentration data and sheet pollution distribution data , it is determined that the concentration of the factory boundary area of ​​the left "I" type pollution plume exceeds the preset boundary by more than 20, then the left "I" type pollution plume does not need migration simulation, and the "I" type pollution plume is divided into the first level. Based on the sheet pollution concentration data and the sheet pollution distribution data, it is determined that the concentration of the factory boundary area of ​​the right "I" type pollution plume exceeds the preset boundary does not exceed the preset concentration, then the migration simulation of the "I" type pollution plume is performed, and three simulated concentration sampling points are selected on the center line of the pollution plume. The preset fitting rate is set to 80%, and the simulation fitting rate is calculated. The simulation achievable fitting rate is 86%, which meets the accuracy requirements. The current pollution plume model is saved as a simulated pollution plume, and the duration of the factory boundary area concentration of the simulated pollution plume exceeds the preset concentration is predicted. It is obtained that the "I" type pollution plume does not have a factory boundary area concentration greater than 20 within 8 years from the current moment, and the "I" type pollution plume on the right is divided into the third level.

[0096] Example 4: For the point pollution data of the enterprise D site, the inverse distance interpolation method is used to interpolate the point pollution data to obtain the sheet pollution concentration data and the sheet pollution distribution data, and further determine multiple high pollution concentration areas. The high pollution concentration areas are as follows: Figure 6As shown, there are overlaps between adjacent high-value pollution concentration areas. The maximum concentration of the high-value pollution concentration area on the left is 28, and the maximum concentration of the overlapping area is 22. Obviously, 22≥50%*28. The two adjacent high-value pollution areas are merged to obtain an independent pollution plume, and the pollution plume is an "I" type pollution plume. The preset concentration is set to 20. Based on the sheet pollution concentration data and the sheet pollution distribution data, it is determined that the concentration of the factory boundary area of ​​the "I" type pollution plume beyond the preset boundary does not exceed 20. Therefore, a single migration simulation is performed on the "I" type pollution plume. Three evenly distributed simulated concentration sampling points are initially selected on the center line of the pollution plume, and the preset simulated concentration is set. The fitting rate is 80%, and the simulation fitting rate is calculated, and the achievable simulation fitting rate is 66%. Obviously, the fitting rate is lower than 80%, which does not meet the accuracy requirement. Three uniformly distributed simulation concentration sampling points are selected on the center line of the pollution plume for the first time, and the simulation fitting rate is calculated. The achievable simulation fitting rate is 90%, which meets the accuracy requirement. The current pollution plume model is saved as the simulated pollution plume, and the duration that the concentration of the simulated pollution plume in the factory boundary area exceeds the preset concentration is predicted. It is found that the concentration of the "I" type pollution plume in the factory boundary area will exceed 20 in the 3rd year and 6th month from the current moment, and the "I" type pollution plume is classified as the second level.

[0097] Example 5: For the point pollution data of the site of Enterprise E, the inverse distance interpolation method is used to interpolate the point pollution data to obtain the sheet pollution concentration data and sheet pollution distribution data, and further determine multiple areas with high pollution concentration. The areas with high pollution concentration are as follows: Figure 7As shown, there are overlaps between adjacent high-value pollution concentration areas. The maximum concentration of the high-value pollution concentration area on the left is 28, and the maximum concentration of the overlapping area is 20. Obviously, 20≥50%*28, so the two adjacent high-value pollution areas are merged to obtain an independent pollution plume. It can be seen from the figure that the pollution plume is an "L" type pollution plume. The preset concentration is set to 20. Based on the sheet pollution concentration data and the sheet pollution distribution data, it is determined that the concentration of the factory boundary area of ​​the "L" type pollution plume beyond the preset boundary does not exceed 20. The "L" type pollution plume needs to be divided into two "I" type pollution plumes for migration simulation. Three evenly distributed simulated concentration sampling points are selected on the center line of the "I" type pollution plume on the left. , set the preset fitting rate to 80%, calculate the simulation fitting rate, and obtain the achievable fitting rate of the "I" type pollution plume simulation on the left to be 86%, select three evenly distributed simulated concentration sampling points on the center line of the "I" type pollution plume on the right, calculate the simulation fitting rate, and obtain the achievable fitting rate of the "I" type pollution plume simulation on the right to be 90%, which meets the accuracy requirements, and merge the two "I" type simulated pollution plumes into an "L" type simulated pollution plume. The duration of the simulated pollution plume's concentration in the factory boundary area exceeding the preset concentration is predicted, and it is obtained that the "L" type pollution plume will begin to have a factory boundary area concentration exceeding 20 in the first year and 6 months from the current moment, and the "L" type pollution plume is classified as the first level.

[0098] This embodiment obtains point pollution data, divides pollution plumes based on the point pollution data, and then simulates the pollution migration of the pollution plumes to obtain simulated pollution plumes, predicts the time when the concentration of the simulated pollution plume in the factory boundary area is greater than the preset concentration, obtains the duration prediction result, and classifies the pollution plumes based on the duration prediction result to obtain pollution plumes of different levels. That is, the embodiment of the present invention classifies the pollution plumes, effectively narrows the key areas of pollution management of enterprises, considers the changes of pollution plumes over time, performs migration simulation on the divided pollution plumes to simulate the future pollution trend of the pollution plumes, and then predicts the time when the concentration in the factory boundary area exceeds the standard, and classifies the pollution plumes based on the duration prediction result, thereby improving the accuracy and precision of the pollution level classification, facilitating the groundwater pollution management of enterprises, and improving the pollution management efficiency of enterprises.

[0099] Embodiment 2

[0100] Please refer to Figure 8 , Figure 8 Schematic diagram of the architecture of a pollution plume classification system 200 provided in an embodiment of the present application.

[0101] The data acquisition module 210 is used to acquire point pollution data; wherein the point pollution data includes point pollution distribution data and point pollution concentration data.

[0102] The pollution plume division module 220 is used to divide a plurality of independent pollution plumes based on the point pollution data.

[0103] The migration simulation module 230 is used to simulate the migration of the pollution plume to obtain a corresponding simulated pollution plume. Specifically, the migration simulation module 230 determines the pollution plume shape information and simulation parameters of the pollution plume based on the divided pollution plume and the sheet pollution data; based on the pollution plume shape information and simulation parameters of the pollution plume, performs migration simulation on the pollution plume to obtain a corresponding simulated pollution plume.

[0104] The duration prediction module 240 is used to predict the duration of time when the concentration of the simulated pollution plume in the factory boundary area is greater than the preset concentration, and obtain a duration prediction result; wherein the concentration of the factory boundary area is the pollution concentration of the area where the pollution plume exceeds the preset boundary;

[0105] The level division module 250 is used to classify the pollution plume based on the duration prediction result to obtain pollution plumes of different levels. Specifically, if the level division module 250 determines that the predicted duration of the simulated pollution plume's factory boundary area concentration greater than the preset concentration is less than the first duration, the pollution plume corresponding to the simulated pollution plume is divided into the first level of pollution plume; if the predicted duration of the simulated pollution plume's factory boundary area concentration greater than the preset concentration is greater than the first duration but less than the second duration, the pollution plume corresponding to the simulated pollution plume is divided into the second level of pollution plume; if the predicted duration of the simulated pollution plume's factory boundary area concentration greater than the preset concentration is greater than the second duration, the pollution plume corresponding to the simulated pollution plume is divided into the third level of pollution plume.

[0106] The pollution plume division module 220 specifically includes a data processing module 221 and a region division module 222 .

[0107] The data processing module 221 is used to interpolate the point pollution data using the inverse distance interpolation method to obtain the sheet pollution distribution data and the sheet pollution concentration data;

[0108] Based on the patch pollution distribution data and the patch pollution concentration data, multiple areas with high pollution concentration are determined.

[0109] The area division module 222 is used for:

[0110] Determine whether there are overlapping areas between adjacent high-pollution concentration areas;

[0111] Adjacent areas with high pollution concentrations without overlapping areas are treated as independent pollution plumes;

[0112] If it is determined that there is an overlapping area between adjacent high-value pollution concentration areas, the maximum concentration of the overlapping area and the maximum concentration of the high-value area are determined based on the sheet pollution concentration data; wherein the maximum concentration of the high-value area is the maximum concentration of the high-value pollution concentration area containing the overlapping area;

[0113] Compare the maximum concentration of the overlapping area with the maximum concentration of the high-value area: if the maximum concentration of the overlapping area is less than a preset multiple of the maximum concentration of the high-value area, segment the high-value pollution concentration area containing the overlapping area to obtain an independent pollution plume;

[0114] If the maximum concentration of the overlapping area is greater than or equal to a preset multiple of the maximum concentration of the high-value area, the high-value pollution concentration areas including the overlapping area will be merged to obtain an independent pollution plume.

[0115] It should be understood that the device corresponds to the above-mentioned pollution plume classification method embodiment and can perform the various steps involved in the above-mentioned method embodiment. The specific functions of the device can be referred to in the above description. To avoid repetition, the detailed description is appropriately omitted here. The device includes at least one software function module that can be stored in a memory in the form of software or firmware or fixed in the operating system (OS) of the device.

[0116] Embodiment 3

[0117] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0118] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0119] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0120] Embodiment 4

[0121] An embodiment of the present invention further provides a computer-readable storage medium, on which instructions are stored. When the instructions are executed by a processor, the program is suitable for executing the steps of the contaminated plume classification method.

[0122] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0123] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0124] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0125] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0126] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe various possible combinations.

[0127] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist separately, or two or more modules can be integrated to form an independent part.

[0128] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0129] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A pollution plume classification method, characterized in that: include: Acquire point pollution data; wherein the point pollution data includes point pollution distribution data and point pollution concentration data; Based on the point pollution data, a plurality of independent pollution plumes are divided; Conduct pollution migration simulation on the pollution plume to obtain a corresponding simulated pollution plume; Predicting the duration of time when the concentration of the simulated pollution plume in the factory boundary area is greater than the preset concentration, and obtaining a duration prediction result; wherein the concentration of the factory boundary area is the pollution concentration of the area where the pollution plume exceeds the preset boundary; Pollution plumes are classified based on their duration predictions.

2. The pollution plume classification method according to claim 1, characterized in that: The step of dividing a plurality of independent pollution plumes based on the point pollution data includes: Interpolating the point pollution data using an inverse distance interpolation method to obtain sheet pollution distribution data and sheet pollution concentration data; Based on the sheet pollution distribution data and the sheet pollution concentration data, determining a plurality of high pollution concentration areas; Determine whether there are overlapping areas between adjacent high-pollution concentration areas; Adjacent areas with high pollution concentrations and no overlapping areas are treated as independent pollution plumes.

3. The pollution plume classification method according to claim 2, characterized in that: The method further comprises: If it is determined that there is an overlapping area between adjacent high-value pollution concentration areas, the maximum concentration of the overlapping area and the maximum concentration of the high-value area are determined based on the sheet pollution concentration data; wherein the maximum concentration of the high-value area is the maximum concentration of the high-value pollution concentration area including the overlapping area; The maximum concentration of the overlapping area is compared with the maximum concentration of the high-value area. If the maximum concentration of the overlapping area is less than a preset multiple of the maximum concentration of the high-value area, the high-value pollution concentration area containing the overlapping area is segmented to obtain an independent pollution plume.

4. The pollution plume classification method according to claim 3, characterized in that: The method further comprises: If the maximum concentration of the overlapping area is greater than or equal to a preset multiple of the maximum concentration of the high-value area, the high-value pollution concentration areas including the overlapping area will be merged to obtain an independent pollution plume.

5. The pollution plume classification method according to claim 2, characterized in that: The method further comprises: Determine the concentration of the pollution plume out of the factory boundary based on the pollution plume, sheet pollution distribution data and sheet pollution concentration data; Determine whether the concentration of the pollution plume in the factory boundary area is greater than the preset concentration; If the concentration of the pollution plume in the factory boundary area is greater than the preset concentration, the pollution plume is classified as a first-level pollution plume.

6. The pollution plume classification method according to claim 5, characterized in that: The step of simulating the pollution migration of the pollution plume to obtain a corresponding simulated pollution plume includes: If the concentration of the pollution plume at the factory boundary area is less than or equal to the preset concentration, the pollution plume shape information and simulation parameters of the pollution plume are determined based on the divided pollution plume and the sheet pollution data; Based on the pollution plume shape information and simulation parameters of the pollution plume, a migration simulation is performed on the pollution plume to obtain a corresponding simulated pollution plume.

7. The pollution plume classification method according to claim 6, characterized in that: The step of performing migration simulation on the pollution plume based on the pollution plume shape information and simulation parameters of the pollution plume to obtain a corresponding simulated pollution plume includes: Based on the pollution plume shape information and simulation parameters of the pollution plume, migration simulation is performed on the pollution plume to obtain a corresponding pollution plume model; Determine whether a fitting rate between an actual pollution concentration of the pollution plume and a simulated pollution concentration of a corresponding pollution plume model is greater than a preset fitting rate; If so, the current migration simulation is determined to be successful, and the pollution plume model is saved as a simulated pollution plume corresponding to the pollution plume.

8. The pollution plume classification method according to claim 1, characterized in that: The classifying of the pollution plume based on the duration prediction result comprises: If it is determined that the predicted duration during which the concentration of the factory boundary area of ​​the simulated pollution plume is greater than the preset concentration is less than the first duration, the pollution plume corresponding to the simulated pollution plume is classified as a first-level pollution plume; If it is determined that the predicted duration during which the concentration of the factory boundary area of ​​the simulated pollution plume is greater than the preset concentration is greater than the first duration but less than the second duration, the pollution plume corresponding to the simulated pollution plume is classified as a second-level pollution plume; If it is determined that the predicted duration that the concentration of the simulated pollution plume at the factory boundary area is greater than the preset concentration is greater than the second duration, the pollution plume corresponding to the simulated pollution plume is classified as a third-level pollution plume.

9. A pollution plume classification system, characterized in that: The system comprises: A data acquisition module, used to acquire point pollution data; wherein the point pollution data includes point pollution distribution data and point pollution concentration data; A pollution plume division module, used for dividing a plurality of independent pollution plumes based on the point pollution data; A migration simulation module is used to simulate the migration of pollution plumes to obtain corresponding simulated pollution plumes; A duration prediction module is used to predict the duration of time when the concentration of the simulated pollution plume in the factory boundary area is greater than a preset concentration, and obtain a duration prediction result; wherein the concentration of the factory boundary area is the pollution concentration of the area where the pollution plume exceeds the preset boundary; The classification module is used to classify the pollution plume based on the duration prediction results.

10. The pollution plume classification system according to claim 9, characterized in that: The pollution plume division module includes a data processing module and a region division module; The data processing module is used for: Interpolating the point pollution data using an inverse distance interpolation method to obtain sheet pollution distribution data and sheet pollution concentration data; Based on the sheet pollution distribution data and the sheet pollution concentration data, determining a plurality of high pollution concentration areas; The area division module is used for: Determine whether there are overlapping areas between adjacent high-pollution concentration areas; Adjacent areas with high pollution concentrations and no overlapping areas are treated as independent pollution plumes.

11. The pollution plume classification system according to claim 10, characterized in that: The area division module is also used for: If it is determined that there is an overlapping area between adjacent high-value pollution concentration areas, the maximum concentration of the overlapping area and the maximum concentration of the high-value area are determined based on the sheet pollution concentration data; wherein the maximum concentration of the high-value area is the maximum concentration of the high-value pollution concentration area including the overlapping area; Compare the maximum concentration of the overlapping area with the maximum concentration of the high-value area: if the maximum concentration of the overlapping area is less than a preset multiple of the maximum concentration of the high-value area, segment the high-value pollution concentration area containing the overlapping area to obtain an independent pollution plume; If the maximum concentration of the overlapping area is greater than or equal to a preset multiple of the maximum concentration of the high-value area, the high-value pollution concentration areas including the overlapping area will be merged to obtain an independent pollution plume.

12. The pollution plume classification system according to claim 10, characterized in that: The migration simulation module is specifically used for: Determining the pollution plume shape information and simulation parameters of the pollution plume based on the divided pollution plume and the sheet pollution data; Based on the pollution plume shape information and simulation parameters of the pollution plume, a migration simulation is performed on the pollution plume to obtain a corresponding simulated pollution plume.

13. The pollution plume classification system according to claim 9, characterized in that: The level division module is specifically used for: If it is determined that the predicted duration during which the concentration of the factory boundary area of ​​the simulated pollution plume is greater than the preset concentration is less than the first duration, the pollution plume corresponding to the simulated pollution plume is classified as a first-level pollution plume; If it is determined that the predicted duration during which the concentration of the factory boundary area of ​​the simulated pollution plume is greater than the preset concentration is greater than the first duration but less than the second duration, the pollution plume corresponding to the simulated pollution plume is classified as a second-level pollution plume; If it is determined that the predicted duration that the concentration of the simulated pollution plume at the factory boundary area is greater than the preset concentration is greater than the second duration, the pollution plume corresponding to the simulated pollution plume is classified as a third-level pollution plume.

14. An electronic device, characterized in that: include: A processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the machine-readable instructions are executed by the processor, the pollution plume classification method according to any one of claims 1 to 8 is performed.

15. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions for causing a machine to execute the pollution plume classification method according to any one of claims 1 to 8.

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