A data screening method and system for soil pollution investigation

Abstract

The present application relates to the technical field of pollution monitoring, in particular to a data screening method and system for soil pollution investigation. The method analyzes each soil detection point under similar hydrogeological conditions according to the hydrogeological conditions, obtains the soil pollution performance degree according to the alarm level deviation of the depth layer under the similar hydrogeological conditions; according to the change of the soil pollution performance degree of the already alarmed position and the pollution influence hidden danger situation, combined with the distribution of the unalarmed position in the adjacent soil area, the pollution extension influence situation to the unalarmed position is analyzed; the influence of the already alarmed detection point on each unalarmed detection point is comprehensively considered, the pollution early warning index is obtained for early warning and auxiliary construction of the pollution plume schematic diagram. The present application reduces the pollution characterization analysis error by combining the difference of each hydrogeological condition, considers the diffusion and extension of soil pollution to obtain more accurate early warning evaluation results of each unalarmed point, and makes the display and analysis of the pollution situation more reliable and accurate.

Description

Technical Field

[0001] This invention relates to the field of pollution monitoring technology, and specifically to a data screening method and system for investigating soil pollution status. Background Technology

[0002] Soil pollution is becoming increasingly serious, making it crucial to understand its status. Soil pollution surveys can assess the real-time extent of soil contamination and provide early warnings for potentially contaminated areas. This provides a scientific basis for pollution control measures, mitigates the harm of soil pollution to the ecological environment, and enhances the sustainable development value of land resources.

[0003] To address the difficulties encountered in the actual investigation process of projects with large investigation areas and large amounts of testing data, it is necessary to conduct large-scale soil sampling and testing, screen and issue early warnings for testing points that may have pollution or potential pollution risks, thereby making the soil pollution analysis process more intuitive.

[0004] When screening soil monitoring points with abnormal pollution conditions, interpolation methods are often used to predict the pollution status of non-alarm points based on the pollution status of alarmed points. However, due to the migration and diffusion caused by groundwater, soil pollution in actual scenarios tends to spread. That is, some monitoring points that have not triggered alarms may be located in the direction of the diffusion influence of alarmed points and have a strong possibility of pollution. If the pollution diffusion trend is not considered for early warning, it will affect the data screening and prevention of soil monitoring points. Insufficient judgment accuracy will lead to excessive waste of resources or high pollution risk. Summary of the Invention

[0005] To address the aforementioned technical problems, the present invention aims to provide a data screening method and system for soil pollution status investigation, the specific technical solution of which is as follows:

[0006] This invention provides a data screening method for soil pollution status investigation, the method comprising:

[0007] The alarm status at different depths and various hydrogeological conditions at each detection point are obtained through the database; the alarm status includes: no alarm and alarmed, and the alarm level corresponding to each alarmed status is obtained.

[0008] Based on the alarm level of each alarm depth layer and the deviation of the alarm level between the corresponding monitoring point and other alarm monitoring points under each similar hydrogeological condition, the soil pollution performance of each alarm depth layer is obtained; by the number of non-alarm depth layers in the vicinity of each alarm depth layer and the soil pollution performance, the pollution impact risk of each alarm depth layer is obtained.

[0009] For each alert depth layer, based on the spatial distribution of non-alert depth layers in the vicinity, combined with the changes in pollution impact risk and soil pollution performance, a pollution extension vector for each alert depth layer is obtained; based on the distribution relationship and pollution extension vector between each non-alert depth layer and each alert depth layer in the vicinity, a soil pollution early warning index for each non-alert depth layer is obtained.

[0010] The monitoring points to be warned were selected by using soil pollution early warning indicators, and early warnings were issued based on the soil pollution early warning indicators of the monitoring points to be warned. A pollution plume map was constructed based on the soil pollution performance of the monitoring points that have been warned and the soil pollution early warning indicators of the monitoring points that have not been warned.

[0011] Furthermore, the method for obtaining the soil pollution performance level includes:

[0012] Under each hydrogeological condition, the monitoring points are clustered based on the approximation of hydrogeological condition information among the monitoring points to obtain similar condition groups;

[0013] For any alarmed depth layer, in any similar condition group in which the depth layer is located, calculate the difference in alarm level between the depth layer and each other alarmed detection point, and use the sum of all differences as the conditional pollution intensity index of the depth layer in the similar condition group; use the mean of the conditional pollution intensity index of the depth layer in all similar condition groups as the pollution intensity performance index of the depth layer.

[0014] The product of the pollution intensity index and the alert level at that depth is taken as the soil pollution performance level at that depth.

[0015] Furthermore, the method for obtaining the similarity condition set includes:

[0016] Each hydrogeological condition corresponds to a single-dimensional space. For any hydrogeological condition, all detection points are mapped to the single-dimensional space of that hydrogeological condition to obtain the sample points of that hydrogeological condition.

[0017] Density clustering is performed on all sample points in each single-dimensional space, and each resulting cluster is used as a similarity condition group.

[0018] Furthermore, the method for obtaining the pollution impact risk level includes:

[0019] For any alarmed depth layer, count the number of all non-alarmed depth layers within a preset neighborhood of that depth layer, and use this as the non-alarmed quantity.

[0020] The product of the negative correlation mapping of the number of non-alarms at this depth layer and the soil pollution performance level is normalized to obtain the pollution impact risk level of this depth layer.

[0021] Furthermore, the method for obtaining the contamination extension vector includes:

[0022] For any alarmed depth layer, each non-alarmed depth layer within a preset neighboring range of that depth layer is sequentially used as the analysis depth layer; each alarmed depth layer in the direction from that depth layer to the analysis depth layer is sequentially arranged to obtain the change sequence corresponding to the analysis depth layer;

[0023] Using the sequence of changes as the horizontal axis and the soil pollution manifestation of the alert depth layer as the vertical axis, the depth layers in the sequence of changes are mapped to obtain the coordinate system of changes in the depth layer of analysis. Straight lines are fitted to the points in the coordinate system of changes. When the slope of the fitted line is negative, the slope is negatively correlated to obtain the diffusion influence of the depth layer of analysis; otherwise, the preset diffusion value is used as the diffusion influence of the depth layer of analysis.

[0024] The product of the diffusion impact degree and the pollution impact hazard degree is used as the diffusion index; an impact vector is constructed in the direction from this depth layer to the analysis depth layer, and the magnitude of the impact vector is the diffusion index.

[0025] The sum of all influence vectors of the depth layer is used as the contamination extension vector of the depth layer.

[0026] Furthermore, the method for obtaining the soil pollution early warning indicators includes:

[0027] For any unalarmed depth layer, each alarmed depth layer within a preset neighborhood is sequentially taken as the target depth layer; the angle between the direction of the depth layer and the target depth layer and the pollution extension vector corresponding to the target depth layer is negatively correlated and normalized to obtain the angle influence index of the target depth layer.

[0028] The product of the angular influence index of the target depth layer and the magnitude of the contamination extension vector is used as the extension intensity index between the target depth layer and the target depth layer.

[0029] By combining the extension intensity index of this depth layer with that of all alarmed depth layers within a preset adjacent range, a soil pollution early warning index for this depth layer is obtained.

[0030] Furthermore, the method for obtaining the detection points to be warned includes:

[0031] Non-alarm detection points whose soil pollution early warning indicators exceed the preset screening threshold will be designated as detection points awaiting early warning.

[0032] Furthermore, the provision of early warning based on soil pollution early warning indicators at the monitoring points to be warned includes:

[0033] When the soil pollution early warning index is greater than or equal to the preset high warning value, the early warning detection point will be issued a high-level warning.

[0034] When the soil pollution early warning index is lower than the preset high warning value but higher than the preset low warning value, the early warning detection point will be issued a medium-level warning; the preset low warning value is lower than the preset high warning value.

[0035] When the soil pollution early warning index is less than or equal to the preset low warning value, the early warning detection point will be issued a low-level warning.

[0036] Furthermore, the method for obtaining the pollution plume map includes:

[0037] Construct a pollution plume map; where the pixel values ​​of the alarmed detection points are within the preset depth pixel value range, and the soil pollution performance of the alarmed detection points is inversely proportional to the pixel value.

[0038] Among the non-alarm detection points, the pixel value of the detection point to be warned is within the preset shallow pixel value range, and the soil pollution warning index of the detection point to be warned is inversely proportional to the pixel value of the coverage; the pixel value of the other non-alarm detection points is the maximum pixel value.

[0039] This invention also provides a data filtering system for soil pollution status investigation, including a mobile app module, a data filtering early warning module, and a table export module; the data filtering early warning module is used to implement the above-mentioned data filtering method for soil pollution status investigation; the mobile app module is used to input sampling information data templates into the database; and the table export module is used to export data.

[0040] The present invention has the following beneficial effects:

[0041] This invention analyzes soil monitoring points under similar hydrogeological conditions to reduce errors in pollution analysis caused by varying hydrogeological conditions. It then determines the soil pollution performance at a single depth layer based on the alarm level deviation under similar hydrogeological conditions. The pollution status of each monitoring point is obtained through adjustments to the hydrogeological conditions. Furthermore, based on changes in soil pollution performance and potential pollution impact at alarmed locations, and considering the distribution of non-alarmed locations in adjacent soil areas, the invention analyzes the pollution extension to non-alarmed locations. By analyzing the pollution spread from alarmed points, the invention integrates the impact of alarmed and non-alarmed monitoring points to obtain pollution warning indicators for early warning and assists in constructing a pollution plume diagram. This invention reduces pollution characterization analysis errors by incorporating differences in hydrogeological conditions and considers the diffusion and extension of soil pollution to obtain more accurate assessment results for non-alarmed locations, making the display and analysis of pollution status more reliable and accurate. Attached Figure Description

[0042] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 A flowchart of a data screening method for soil pollution status investigation provided in one embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram illustrating the filling out of a sampling record form according to an embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram illustrating the point number representation of a detection point according to an embodiment of the present invention;

[0046] Figure 4 This is a schematic diagram of sample point clustering provided in one embodiment of the present invention;

[0047] Figure 5 This is a schematic diagram of a pollution plume provided in one embodiment of the present invention. Detailed Implementation

[0048] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a data screening method and system for soil pollution status investigation proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0050] The following description, in conjunction with the accompanying drawings, details a specific scheme for a data screening method and system for soil pollution status investigation provided by the present invention.

[0051] For soil condition surveys with a large scope and a large amount of testing data, on-site sampling and testing are typically conducted, and the data is recorded and imported into a database for subsequent data analysis. Data filtering is used to improve the time efficiency of information processing and site selection for exceeding standards during report preparation. The soil pollution data survey platform includes a data filtering system for soil pollution status surveys, comprising a mobile app module, a data filtering and early warning module, and a table export module.

[0052] The mobile app module synchronizes data entered via the mobile app to the computer, automatically matching it to the sampling points. This avoids the slowness, error-proneness, and time-consuming matching process of manual data entry. In this embodiment, a sampling record form must be filled out when sampling at the detection points, synchronizing information such as sample number and depth to the PC. On the PC, the target indicators, detection methods, and detection limits can be selected for the collected samples, generating a COC (Certificate of Conformity) submission form. This facilitates subsequent data uploads by verifying whether the data was measured according to the prescribed methods and detection limits, checking for missing samples or indicators, and providing prompts if there are discrepancies with the COC submission form. Please refer to [link to relevant documentation]. Figure 2 The illustration shows a schematic diagram of filling out a sampling record form according to an embodiment of the present invention.

[0053] Import the table data, identify the location number of the detection point and the sample test result in the table data, and enter the corresponding detection value into the database. Multi-level alarms can be triggered based on the quality detection value. Please refer to [link / reference]. Figure 3 This illustration shows a schematic diagram of the location number representation of a detection point according to an embodiment of the present invention. To avoid data entry failures due to different data formats or indicator names from different detection units, a CAS number can be added to the indicator for easy matching.

[0054] After importing the data, other information such as lithology, depth, X coordinate, Y coordinate, zoning, XRF, and PID data can be entered simultaneously to supplement the database. When the record is modified, the database is updated synchronously.

[0055] The data filtering and early warning module reads data from the database, further analyzes and filters pollution conditions, and improves the early warning process. Please refer to [link / reference needed]. Figure 1 The diagram illustrates a data screening method for soil pollution status investigation according to an embodiment of the present invention, which includes the following steps:

[0056] S1: Obtain the alarm status at different depths of each detection point, as well as various hydrogeological conditions, through the database; the alarm status includes: no alarm and alarmed, and obtain the alarm level corresponding to each alarmed status.

[0057] Within the area requiring testing, testing points are determined using a uniform sampling method, and soil samples at different depths are collected from each testing point for testing. In this embodiment of the invention, sampling is performed at a depth of one meter from the soil surface, with a 2-meter interval between testing points. The specific sampling method can be adjusted according to the specific implementation situation and is not limited here.

[0058] The database can be used to obtain the alarm status of the detection points, including non-alarm status and alarm status. It can also obtain the alarm level under the alarm status. The higher the alarm level, the more serious the pollution.

[0059] Different hydrogeological conditions can introduce errors in the determination of heavy metals, volatile organic compounds (VOCs), and semi-volatile organic compounds (SOCs) in soil, thus making direct sampling, monitoring, and alarm systems insufficient for accurately characterizing soil pollution. Therefore, various hydrogeological conditions are retrieved from a database for subsequent classification and analysis. These hydrogeological conditions include: lithology, soil moisture content, permeability coefficient, organic matter content, and pH value, among others.

[0060] S2: Based on the alarm level of each alarm depth layer and the deviation of the alarm level between the corresponding monitoring point and other alarm monitoring points under each similar hydrogeological condition, obtain the soil pollution performance of each alarm depth layer; by the number of non-alarm depth layers in the vicinity of each alarm depth layer and the soil pollution performance, obtain the pollution impact risk level of each alarm depth layer.

[0061] Because different hydrogeological conditions can cause errors in the determination of heavy metals, volatile organic compounds and semi-volatile organic compounds in soil, resulting in pollution analysis errors, detection points with similar hydrogeological conditions are classified and analyzed to re-characterize the pollution performance of each depth layer.

[0062] Preferably, in this embodiment of the invention, the method for obtaining soil pollution performance includes:

[0063] First, under each hydrogeological condition, the detection points are clustered based on the approximation of hydrogeological condition information among the detection points to obtain similar condition groups. These similar condition groups are then used to analyze the detection points. In this embodiment of the invention, a unit-degree space is constructed, with each hydrogeological condition corresponding to a single-dimensional space. Approximate analysis is performed using this one-dimensional space. For any given hydrogeological condition, all detection points are mapped to the single-dimensional space of that hydrogeological condition to obtain sample points for that condition. The denser the distribution of sample points in the single dimension, the higher the degree of similarity.

[0064] Therefore, density clustering is performed on all sample points in each single-dimensional space, and each resulting cluster serves as a similarity condition group. In this embodiment of the invention, DBSCAN density clustering can be used as the clustering method. Clustering is a well-known technique among those skilled in the art and will not be elaborated upon here. Please refer to... Figure 4 This illustrates a schematic diagram of sample point clustering provided in an embodiment of the present invention.

[0065] Furthermore, for any alarmed depth layer, in any similar condition group to which the depth layer is located, the difference in alarm level between the depth layer and each other alarmed detection point is calculated. The sum of all differences is used as the conditional pollution intensity index of the depth layer in the similar condition group. By comparing the level deviation of each depth layer with other alarm situations in the similar condition group, the larger the difference, the more severe the alarm of the depth layer, and the stronger the corresponding pollution response of the depth layer in this similar condition group.

[0066] Then, the average value of the pollution intensity index of the depth layer in all similar condition groups is used as the pollution intensity performance index of the depth layer. By combining the characterization ability in different similar condition groups, the pollution performance ability adjusted by hydrogeological conditions is obtained.

[0067] Finally, the product of the pollution intensity index and the alert level at that depth is used as the soil pollution performance degree at that depth. The higher the soil pollution performance degree, the more severe the pollution at the monitoring point.

[0068] Next, because soil pollution has a diffusion and extension characteristic—that is, the detection area showing signs of soil pollution may extend to adjacent detection areas—the potential pollution impact of a single alerted depth layer on adjacent unalerted depth layers is calculated. Preferably, in this embodiment of the invention, the method for obtaining the pollution impact potential includes:

[0069] For any alarmed depth layer, the number of all non-alarmed depth layers within a preset neighboring range of that depth layer is counted as the non-alarm count. The fewer the number of non-alarmed detection points within a local area of ​​an alarmed depth layer, the greater the possibility of local pollution spread. In this embodiment of the invention, the preset neighboring range can be set to a radius of 15m centered on the depth layer. The specific range can be adjusted by the implementer according to the specific implementation situation, and is not limited here.

[0070] Therefore, the product of the negative correlation mapping of the number of non-alarms at this depth layer and the soil pollution performance is normalized to obtain the pollution impact risk level of this depth layer. The smaller the number of non-alarms, the greater the soil pollution performance level, indicating that the impact of pollution diffusion may be higher, and thus the greater the pollution impact risk level.

[0071] It should be noted that negative correlation mapping and normalization are techniques well known to those skilled in the art. Negative correlation mapping can be inverse proportional or negative exponential form, and normalization can be linear normalization or standard normalization, etc. The specific method is not limited here.

[0072] This concludes the preliminary analysis of the pollution status and potential pollution risks in the alerted depth layers.

[0073] S3: For each alerted depth layer, based on the spatial distribution of non-alerted depth layers in the vicinity, combined with the changes in pollution impact risk and soil pollution performance, obtain the pollution extension vector for each alerted depth layer; based on the distribution relationship and pollution extension vector between each non-alerted depth layer and each alerted depth layer in the vicinity, obtain the soil pollution early warning index for each non-alerted depth layer.

[0074] Since the spread of soil pollution tends to extend from high to low pollution levels, for the depth layer being analyzed, the degree of spread is reflected by changes in soil pollution characteristics and potential impacts. Combined with the spatial distribution of unalarmed depth layers in the vicinity, the direction of spread is reflected, thus obtaining a pollution extension vector that reflects the extension of pollution.

[0075] Preferably, in this embodiment of the invention, the method for obtaining the contamination extension vector includes:

[0076] First, for any given alert depth layer, each non-alert depth layer within a preset neighboring range is sequentially used as an analysis depth layer. The potential diffusion of each neighboring non-alert depth layer is then analyzed. Each alert depth layer in the direction from the given depth layer to the analysis depth layer is arranged sequentially to obtain the corresponding change sequence. Specifically, if no alert depth layer exists in a direction, no trend analysis is performed; instead, the pollution impact hazard level is directly used as the diffusion indicator.

[0077] Furthermore, using the sequence of changes as the horizontal axis and the soil pollution manifestation at the alert depth layer as the vertical axis, the depth layers in the sequence are mapped to obtain a coordinate system for the analysis depth layer, and the pollution change trend is analyzed. A straight line is fitted to the points in the coordinate system. When the slope of the fitted line is negative, the slope is negatively correlated to obtain the diffusion influence of the analysis depth layer. A negative slope indicates the possibility of pollution diffusion from high to low. The smaller the slope of the fitted line, the more severe the decreasing trend and the higher the diffusion possibility. Otherwise, when the slope is positive (zero), it does not represent a trend from high to low, indicating that the depth layer has minimal diffusion influence on the analysis layer. A preset diffusion value is used as the diffusion influence of the analysis depth layer. In this embodiment, the preset diffusion value is set to 0.1, but the specific value can be adjusted by the implementer.

[0078] By combining the overall and local pollution impact risk level of the depth layer analysis, the product of the diffusion impact level and the pollution impact risk level is used as a diffusion index to reflect the diffusion impact on the analysis depth layer.

[0079] Then, an influence vector is constructed along the direction from the current depth layer to the analysis depth layer. The magnitude of the influence vector is a diffusion index, representing the degree of contamination diffusion from a single alerted depth layer to each neighboring unalerted depth layer. All influence vectors are combined, and the sum of all influence vectors for that depth layer is used as the contamination extension vector for that depth layer, reflecting the main degree of contamination diffusion at that depth layer.

[0080] From the perspective of the unalert depth layer, it may be affected by multiple alert depth layers. Therefore, by combining the pollution diffusion effects of multiple adjacent alert depth layers, the situation where an alert is required for the unalert depth layer is determined. Preferably, in this embodiment of the invention, the method for obtaining soil pollution early warning indicators includes:

[0081] For any non-alarm depth layer, each alarmed depth layer within a preset neighborhood is taken as the target depth layer, and the impact of each alarmed depth layer is analyzed sequentially.

[0082] By performing a negative correlation mapping and normalization on the angle between the direction of the current depth layer and the target depth layer and the pollution extension vector corresponding to the target depth layer, the angular influence index of the target depth layer is obtained. The angular deviation between the distribution direction between depth layers and the main pollution direction of the target depth layer reflects the potential impact. The smaller the angle, the higher the pollution impact. Therefore, the angular influence index is obtained through negative correlation mapping.

[0083] Furthermore, the product of the angular influence index of the target depth layer and the magnitude of the pollution extension vector is used as the extension intensity index between the depth layer and the target depth layer. The more similar the pollution direction is, the higher the degree of pollution extension, and the greater the extension influence of the target depth layer, so the greater the extension intensity index.

[0084] Finally, by combining the extension intensity indices of this depth layer with those of all alerted depth layers within a preset adjacent range, a soil pollution early warning index for this depth layer is obtained. In this embodiment of the invention, the mean of the extension intensity indices of this depth layer and all alerted depth layers is normalized to obtain the soil pollution early warning index. The larger the soil pollution early warning index, the greater the extent of pollution diffusion and extension at the unalert detection point, and the higher the potential impact of pollution, thus requiring a stronger early warning.

[0085] S4: Select monitoring points to be warned based on soil pollution early warning indicators, and issue early warnings based on the soil pollution early warning indicators of the monitoring points to be warned; construct a pollution plume map based on the soil pollution performance of the monitoring points that have been warned and the soil pollution early warning indicators of the monitoring points that have not been warned.

[0086] For non-alarm detection points, those requiring alarms are initially screened. In this embodiment of the invention, non-alarm detection points with soil pollution early warning indicators exceeding a preset screening threshold are designated as detection points to be alerted. The preset screening threshold can be set to 0.68, and the specific value can be adjusted by the implementer.

[0087] For monitoring points requiring early warning, different levels of early warning are issued based on the soil pollution early warning index. The higher the index, the higher the warning level, indicating potentially more severe pollution. In this embodiment, when the soil pollution early warning index is greater than or equal to a preset high warning value, a high-level warning (Level 3) is issued for the monitoring point. When the index is less than the preset high warning value but greater than the preset low warning value, a medium-level warning (Level 2) is issued. When the index is less than or equal to the preset low warning value, a low-level warning (Level 1) is issued. It should be noted that the preset low warning value must be less than the preset high warning value to ensure the feasibility of the tiered early warning system. The preset low warning value can be set to 0.78, and the preset high warning value can be set to 0.88; the specific values ​​can be adjusted by the implementer.

[0088] Meanwhile, to assist in data filtering and updating of the soil pollution data survey platform, a pollution plume map can be constructed. In this embodiment of the invention, in the constructed pollution plume map, the pixel values ​​of the alarm detection points are within a preset depth pixel value range. The soil pollution performance of the alarm detection points is inversely proportional to the pixel value, that is, the alarm detection points are covered with a dark color, and the greater the soil pollution performance, the deeper the coverage, that is, the smaller the pixel value.

[0089] In non-alarm detection points, the pixel values ​​of detection points awaiting warning are within a preset shallow pixel value range. The soil pollution warning index of the detection point awaiting warning is inversely proportional to the pixel value of the coverage; that is, the detection point awaiting warning is covered with a light color, and the larger the soil pollution warning index, the deeper the coverage, i.e., the smaller the pixel value. In this embodiment of the invention, the preset depth pixel value range can be set to 0-100, and the preset shallow pixel value range can be 125-200. The specific pixel value range can be adjusted by the implementer according to the specific implementation situation.

[0090] For the remaining non-alarm detection points, the coverage pixel value is the maximum pixel value, which means the coverage pixel value for non-alarm detection points is 255. Please refer to [link / reference]. Figure 5 The diagram illustrates a pollution plume diagram provided in one embodiment of the present invention.

[0091] In summary, this invention analyzes soil monitoring points under similar hydrogeological conditions to reduce errors in pollution analysis caused by varying hydrogeological conditions. It then obtains the soil pollution performance at a single depth layer based on the alarm level deviation of each layer under similar hydrogeological conditions. The pollution status of each monitoring point is obtained through adjustments to the hydrogeological conditions. Furthermore, based on changes in soil pollution performance and potential pollution impact at alarmed locations, and considering the distribution of non-alarmed locations in adjacent soil areas, the invention analyzes the pollution extension to non-alarmed locations. By analyzing the pollution spread from alarmed points, the invention integrates the impact of alarmed and non-alarmed monitoring points to obtain pollution warning indicators for early warning and assists in constructing a pollution plume diagram. This invention reduces pollution characterization analysis errors by incorporating differences in hydrogeological conditions and considers the diffusion and extension of soil pollution to obtain more accurate assessment results for non-alarmed locations, making the display and analysis of pollution status more reliable and accurate.

[0092] The table export module is used to upload soil pollution early warning indicators with early warning detection points, as well as early warning status and pollution plume visualization effects to the soil pollution data survey platform. Through early warning screening, the detection rate, exceedance rate, and compliance rate can be further calculated and output as a statistical table for use in the survey report, providing a data basis for the planning of monitoring and prevention strategies.

[0093] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0094] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A data screening method for soil pollution status investigation, characterized in that, The method includes: The alarm status at different depths and various hydrogeological conditions at each detection point are obtained through the database; the alarm status includes: no alarm and alarmed, and the alarm level corresponding to each alarmed status is obtained. Based on the alarm level of each alarm depth layer and the deviation of the alarm level between the corresponding monitoring point and other alarm monitoring points under each similar hydrogeological condition, the soil pollution performance of each alarm depth layer is obtained; by the number of non-alarm depth layers in the vicinity of each alarm depth layer and the soil pollution performance, the pollution impact risk of each alarm depth layer is obtained. For each alert depth layer, based on the spatial distribution of non-alert depth layers in the vicinity, combined with the changes in pollution impact risk and soil pollution performance, a pollution extension vector for each alert depth layer is obtained; based on the distribution relationship and pollution extension vector between each non-alert depth layer and each alert depth layer in the vicinity, a soil pollution early warning index for each non-alert depth layer is obtained. The monitoring points to be warned were selected by using soil pollution early warning indicators, and early warnings were issued based on the soil pollution early warning indicators of the monitoring points to be warned. A pollution plume map was constructed based on the soil pollution performance of the monitoring points that have been warned and the soil pollution early warning indicators of the monitoring points that have not been warned.

2. The data screening method for soil pollution status investigation according to claim 1, characterized in that, The method for obtaining the soil pollution performance index includes: Under each hydrogeological condition, the monitoring points are clustered based on the approximation of hydrogeological condition information among the monitoring points to obtain similar condition groups; For any alarmed depth layer, in any similar condition group in which the depth layer is located, calculate the difference in alarm level between the depth layer and each other alarmed detection point, and use the sum of all differences as the conditional pollution intensity index of the depth layer in the similar condition group; use the mean of the conditional pollution intensity index of the depth layer in all similar condition groups as the pollution intensity performance index of the depth layer. The product of the pollution intensity index and the alert level at that depth is taken as the soil pollution performance level at that depth.

3. The data screening method for soil pollution status investigation according to claim 2, characterized in that, The method for obtaining the similarity condition group includes: Each hydrogeological condition corresponds to a single-dimensional space. For any hydrogeological condition, all detection points are mapped to the single-dimensional space of that hydrogeological condition to obtain the sample points of that hydrogeological condition. Density clustering is performed on all sample points in each single-dimensional space, and each resulting cluster is used as a similarity condition group.

4. The data screening method for soil pollution status investigation according to claim 1, characterized in that, The methods for obtaining the pollution impact risk level include: For any alarmed depth layer, count the number of all non-alarmed depth layers within a preset neighborhood of that depth layer, and use this as the non-alarmed quantity. The product of the negative correlation mapping of the number of non-alarms at this depth layer and the soil pollution performance level is normalized to obtain the pollution impact risk level of this depth layer.

5. The data screening method for soil pollution status investigation according to claim 1, characterized in that, The method for obtaining the contamination extension vector includes: For any alarmed depth layer, each non-alarmed depth layer within a preset neighboring range of that depth layer is sequentially used as the analysis depth layer; each alarmed depth layer in the direction from that depth layer to the analysis depth layer is sequentially arranged to obtain the change sequence corresponding to the analysis depth layer; Using the sequence of changes as the horizontal axis and the soil pollution manifestation of the alert depth layer as the vertical axis, the depth layers in the sequence of changes are mapped to obtain the coordinate system of changes in the depth layer of analysis. Straight lines are fitted to the points in the coordinate system of changes. When the slope of the fitted line is negative, the slope is negatively correlated to obtain the diffusion influence of the depth layer of analysis; otherwise, the preset diffusion value is used as the diffusion influence of the depth layer of analysis. The product of the diffusion impact degree and the pollution impact hazard degree is used as the diffusion index; an impact vector is constructed in the direction from this depth layer to the analysis depth layer, and the magnitude of the impact vector is the diffusion index. The sum of all influence vectors of the depth layer is used as the contamination extension vector of the depth layer.

6. The data screening method for soil pollution status investigation according to claim 1, characterized in that, The methods for obtaining the soil pollution early warning indicators include: For any unalarmed depth layer, each alarmed depth layer within a preset neighborhood is sequentially taken as the target depth layer; the angle between the direction of the depth layer and the target depth layer and the pollution extension vector corresponding to the target depth layer is negatively correlated and normalized to obtain the angle influence index of the target depth layer. The product of the angular influence index of the target depth layer and the magnitude of the contamination extension vector is used as the extension intensity index between the target depth layer and the target depth layer. By combining the extension intensity index of this depth layer with that of all alarmed depth layers within a preset adjacent range, a soil pollution early warning index for this depth layer is obtained.

7. The data screening method for soil pollution status investigation according to claim 1, characterized in that, The method for obtaining the detection points to be warned includes: Non-alarm detection points whose soil pollution early warning indicators exceed the preset screening threshold will be designated as detection points awaiting early warning.

8. The data screening method for soil pollution status investigation according to claim 1, characterized in that, The method of issuing early warnings based on soil pollution early warning indicators at the monitoring points to be warned includes: When the soil pollution early warning index is greater than or equal to the preset high warning value, the early warning detection point will be issued a high-level warning. When the soil pollution early warning index is lower than the preset high warning value but higher than the preset low warning value, the early warning detection point will be issued a medium-level warning; the preset low warning value is lower than the preset high warning value. When the soil pollution early warning index is less than or equal to the preset low warning value, the early warning detection point will be issued a low-level warning.

9. The data screening method for soil pollution status investigation according to claim 1, characterized in that, The method for obtaining the pollution plume map includes: Construct a pollution plume map; where the pixel values ​​of the alarmed detection points are within the preset depth pixel value range, and the soil pollution performance of the alarmed detection points is inversely proportional to the pixel value. Among the non-alarm detection points, the pixel value of the detection point to be warned is within the preset shallow pixel value range, and the soil pollution warning index of the detection point to be warned is inversely proportional to the pixel value of the coverage; the pixel value of the other non-alarm detection points is the maximum pixel value.

10. A data screening system for soil pollution status investigation, characterized in that, It includes a mobile app module, a data filtering and early warning module, and a table export module; the data filtering and early warning module is used to implement the data filtering method for soil pollution status investigation as described in claim 1; the mobile app module is used to input sampling information data templates into the database; and the table export module is used to export data.

Images