A method for tracking underground water pollution channels in karst mines

Abstract

The present invention relates to the technical field of data processing, and in particular to a method for tracking groundwater pollution channels in karst mines. Groundwater flow data and pollutant concentration data of multiple monitoring points in karst mines are obtained, and the degree of water flow fluctuation and the degree of concentration trend change of various pollutants at the monitoring points are obtained according to the groundwater flow data and the pollutant concentration data. The overall pollutant concentration balance ratio of the monitoring points is obtained according to the concentration difference between various pollutants and another pollutant matched therewith. The characteristic distance between any two monitoring points is obtained according to the degree of water flow fluctuation, the degree of concentration trend change of various pollutants in the current and previous monitoring cycles, and the overall pollutant concentration balance ratio, so as to cluster the various monitoring points, improve the accuracy of the clustering results, realize the tracking of groundwater pollution channels in mines, avoid the interference of local monitoring points due to actual mine operations, and thus enhance the accuracy of pollution channel tracking.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method for tracking underground water pollution channels in karst mines. Background Art

[0002] Due to its unique hydrogeological characteristics, groundwater in karst areas flows rapidly and has complex paths. Mining, especially open-pit mining, slag storage, ore dissolution and other activities can easily cause the spread of groundwater pollution around the mining area, and pollutants spread rapidly to the water source through karst channels such as cracks and caves. The types of pollution mainly include heavy metals, acidic water, chemicals and radioactive substances. These pollutants persist in groundwater and spread through the karst groundwater system, which may seriously affect the regional ecology and human health. The purpose of tracking is to understand the transmission laws of pollution sources and pollutants, evaluate the spread range and impact of pollution, and thus provide a scientific basis for mine environmental protection, water resources management, and groundwater pollution prevention and control. The tracer method is currently one of the most commonly used methods for tracking groundwater pollution in karst areas. It tracks groundwater flow by using fluorescent dyes, chemical tracers or radioactive isotopes.

[0003] When tracking groundwater pollution channels in karst mines, clustering methods can be used to analyze the spatial distribution characteristics of pollutant concentrations and classify similar monitoring points into one category. In this way, potential sources of pollutants can be identified and how pollutants spread along groundwater flows can be understood. However, considering the particularity of hydrogeological conditions in karst areas and the strong permeability of mine wastewater, the amount and quality of groundwater often fluctuate greatly with mining activities, especially for monitoring points located near the mining area. This will affect the final clustering results and lead to deviations in the final pollutant channel tracking. Summary of the invention

[0004] In order to solve the technical problem that the clustering results are inaccurate when the existing clustering method is used to analyze the spatial distribution characteristics of pollutant concentrations, the purpose of the present invention is to provide a method for tracking groundwater pollution channels in karst mines. The technical solution adopted is as follows:

[0005] In a first aspect of the present invention, a method for tracing underground water pollution channels in a karst area mine is provided, comprising:

[0006] Acquire monitoring data of multiple monitoring points arranged in a karst mine in a current monitoring cycle, wherein the monitoring data includes groundwater flow data and pollutant concentration data;

[0007] According to the groundwater flow data, the water flow fluctuation degree of the monitoring point in the current monitoring period is obtained, and according to the pollutant concentration data, the concentration trend change degree of various pollutants at the monitoring point in the current monitoring period is obtained;

[0008] According to the difference between the concentration of various pollutants at the monitoring point and the concentration of another pollutant that matches it, the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period is obtained;

[0009] According to the degree of water flow fluctuation at the monitoring point in the current monitoring period, the concentration trend change of various pollutants at the monitoring point in the current monitoring period and the previous monitoring period, and the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period and the previous monitoring period, the characteristic distance between any two monitoring points is obtained;

[0010] According to the characteristic distance between any two monitoring points, each monitoring point is clustered.

[0011] In an exemplary embodiment, obtaining the water flow fluctuation degree of the monitoring point in the current monitoring period according to the groundwater flow data includes:

[0012] Obtaining a first water flow characteristic according to groundwater flow data of the monitoring point in a current monitoring period;

[0013] Obtaining groundwater flow data of the monitoring point in the previous monitoring period, and obtaining a second water flow characteristic based on the groundwater flow data of the monitoring point in the previous monitoring period;

[0014] According to the difference between the first water flow characteristic and the second water flow characteristic, the water flow fluctuation degree of the monitoring point in the current monitoring period is obtained.

[0015] In an exemplary embodiment, the concentration trend change of various pollutants at the monitoring point in the current monitoring period is obtained according to the pollutant concentration data, including:

[0016] For any pollutant, obtain the concentration data sequence of the pollutant in the pollutant concentration data of the monitoring point in the current monitoring period;

[0017] Obtaining the difference between the concentration data at two adjacent moments in the concentration data sequence;

[0018] According to the difference between the concentration data at two adjacent moments, the concentration trend change degree of the pollutant at the monitoring point in the current monitoring period is obtained.

[0019] In an exemplary embodiment, according to the difference between the concentration of various pollutants at the monitoring point and the concentration of another pollutant matched therewith, the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period is obtained, including:

[0020] According to the difference between the concentration of various pollutants at the monitoring point and the concentration of another pollutant that matches it, the concentration balance ratio of various pollutants at the monitoring point in the current monitoring period is obtained;

[0021] According to the concentration balance ratio of various pollutants at the monitoring point, the overall pollutant concentration balance ratio of the monitoring point is obtained.

[0022] In an exemplary embodiment, the process of matching each pollutant with another pollutant includes:

[0023] According to the pollutant concentration data of the monitoring points in the current monitoring period, the average concentration of various pollutants is obtained;

[0024] Sort the average concentrations of various pollutants in descending order to obtain an average concentration sequence;

[0025] The pollutants corresponding to two adjacent average concentrations in the average concentration sequence are regarded as two matching pollutants.

[0026] In an exemplary embodiment, according to the difference between the concentration of various pollutants at the monitoring point and another pollutant matched thereto, the concentration balance ratio of various pollutants at the monitoring point in the current monitoring period is obtained, including:

[0027] Obtaining the difference between the concentration of the first pollutant at each characteristic moment and the concentration of the second pollutant at the corresponding moment in the current monitoring period to obtain a concentration difference sequence; the first pollutant and the second pollutant are two matching pollutants, and the average concentration of the first pollutant is greater than the average concentration of the second pollutant;

[0028] Obtaining a first-order difference absolute value sequence of the concentration difference sequence;

[0029] The average value of the data in the first-order difference absolute value sequence is calculated, and the concentration equilibrium ratio of the first pollutant is obtained according to the average value, and the concentration equilibrium ratio is inversely proportional to the average value.

[0030] In an exemplary embodiment, the calculation formula of the concentration balance ratio is as follows:

[0031] ;

[0032] Where i represents the i-th monitoring point, m represents the m-th pollutant, is the concentration equilibrium ratio of the mth pollutant at the ith monitoring point in the current monitoring period, K represents the number of characteristic moments, k represents the kth characteristic moment, is the difference between the concentration of the mth pollutant at the i-th monitoring point in the current monitoring period at the k-th characteristic moment and the concentration of another pollutant that matches it at the k-th characteristic moment, is the difference between the concentration of the mth pollutant at the ith monitoring point in the current monitoring period at the k+1th characteristic moment and the concentration of another pollutant that matches it at the k+1th characteristic moment, Represents the normalization function.

[0033] In an exemplary embodiment, according to the degree of water flow fluctuation at the monitoring point in the current monitoring period, the concentration trend change degree of various pollutants at the monitoring point in the current monitoring period and the previous monitoring period, and the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period and the previous monitoring period, the characteristic distance between any two monitoring points is obtained, including:

[0034] According to the degree of water flow fluctuation at the monitoring point in the current monitoring period, and the degree of change in concentration trend of various pollutants at the monitoring point in the current monitoring period and the previous monitoring period, a first feature of various pollutants at the monitoring point in the current monitoring period is obtained, wherein the first feature is used to characterize the result of the association between the degree of water flow fluctuation and the degree of change in concentration trend of various pollutants at the monitoring point in the current monitoring period and the previous monitoring period;

[0035] According to the degree of water flow fluctuation at the monitoring point in the current monitoring period and the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period and the previous monitoring period, a second feature of the monitoring point in the current monitoring period is obtained, wherein the second feature is used to characterize the result of the association between the degree of water flow fluctuation and the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period and the previous monitoring period;

[0036] According to the first characteristics and the second characteristics of various pollutants at any two monitoring points, the characteristic distance between any two monitoring points is obtained.

[0037] In an exemplary embodiment, the calculation formula of the first feature is as follows:

[0038] ;

[0039] Among them, i represents the i-th monitoring point, m represents the m-th pollutant, is the first characteristic of the mth pollutant at the ith monitoring point in the current monitoring period, is the water flow fluctuation degree of the ith monitoring point in the current monitoring period, is the concentration trend change of the mth pollutant at the ith monitoring point in the current monitoring period, is the concentration trend change of the mth pollutant at the ith monitoring point in the previous monitoring period;

[0040] The calculation formula of the second feature is as follows:

[0041] ;

[0042] in, is the second feature of the ith monitoring point in the current monitoring period, is the overall pollutant concentration equilibrium ratio of the i-th monitoring point in the current monitoring period, It is the overall pollutant concentration equilibrium ratio of the ith monitoring point in the previous monitoring period.

[0043] In an exemplary embodiment, the calculation formula of the characteristic distance is as follows:

[0044] ;

[0045] in, is the characteristic distance between the i-th monitoring point and the j-th monitoring point in the current monitoring period, is the first characteristic of the mth pollutant at the jth monitoring point in the current monitoring period, M represents the number of pollutant types, is the second feature of the jth monitoring point in the current monitoring period.

[0046] The present invention has the following beneficial effects: first, according to the groundwater flow data, the degree of water flow fluctuation of the monitoring point in the current monitoring period is obtained, and according to the pollutant concentration data, the concentration trend change degree of various pollutants at the monitoring point in the current monitoring period is obtained; thereby, according to the difference between the concentration of various pollutants at the monitoring point and the concentration of another pollutant matched therewith, the overall pollutant concentration balanced ratio of the monitoring point in the current monitoring period is obtained, and then, according to the degree of water flow fluctuation of the monitoring point in the current monitoring period, the concentration trend change degree of various pollutants at the monitoring point in the current monitoring period and the previous monitoring period, as well as the overall pollutant concentration balanced ratio of the monitoring point in the current monitoring period and the previous monitoring period are weighed and comprehensively utilized to obtain the characteristic distance between any two monitoring points, thereby completing the clustering of each monitoring point, improving the accuracy of the clustering result, and realizing the tracking of the mine groundwater pollution channel, avoiding the interference of the actual mine operation activities on the local monitoring points. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flow chart of a method for tracing underground water pollution channels in karst mines provided by an embodiment of the present invention;

[0048] Figure 2 is a flow chart for obtaining the degree of water flow fluctuation provided by an embodiment of the present invention;

[0049] Figure 3It is a schematic diagram of groundwater pollution channels corresponding to two different pollution sources provided by an embodiment of the present invention;

[0050] Figure 4 It is a flow chart for obtaining the concentration trend variation of various pollutants provided by an embodiment of the present invention;

[0051] Figure 5 It is a flow chart for obtaining the overall pollutant concentration balance ratio of a monitoring point provided by an embodiment of the present invention;

[0052] Figure 6 is a flow chart for obtaining matching relationships between pollutants provided by an embodiment of the present invention;

[0053] Figure 7 is a flow chart for obtaining a concentration balance ratio provided by an embodiment of the present invention;

[0054] Figure 8 This is a flow chart of obtaining characteristic distance provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0056] Unless defined otherwise, 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 belongs.

[0057] In view of the complex hydrogeological conditions in the karst area, groundwater usually flows along karst fissures and cave systems. Therefore, according to the survey of professionals, multiple monitoring points are set up in the entire area from upstream to downstream of the possible pollution source of the mine according to the intersection of karst fissures or cave systems, low-lying areas or water collection points in the karst area, faults or fracture zones and other geological abnormal areas, so as to analyze the pollution situation of each monitoring point. It should be understood that the specific location of the monitoring point in the karst mine and the number of monitoring points are set according to actual needs.

[0058] Depending on the mining activities and the characteristics of the surrounding environment, different types of pollutants may enter the groundwater system, such as heavy metal ions lead (Pb), cadmium (Cd), zinc (Zn), copper (Cu), arsenic (As), etc.; toxic chemicals such as cyanide ( ), sulfate ( )、Ammonia nitrogen( ) etc. These substances may come from the ore processing process or mining waste. They are common pollutants in mining activities and cause long-term pollution to groundwater.

[0059] This embodiment provides a method for tracking underground water pollution channels in karst mines. Figure 1 As shown, the following steps are included:

[0060] Step 1: Obtain monitoring data from multiple monitoring points arranged in karst mines during the current monitoring period, including groundwater flow data and pollutant concentration data.

[0061] A water flow sensor is set at each monitoring point to detect the groundwater flow data at each monitoring point. In addition, an electrochemical sensor is also set at each monitoring point to detect the concentration data of various pollutants in the water body at each monitoring point. It should be understood that the number of types of pollutants detected and the specific types of each are set according to actual needs and are not limited here.

[0062] Set the monitoring period. The length of the monitoring period is set according to actual needs. The monitoring period includes multiple sampling moments.

[0063] The monitoring data of each monitoring point in the current monitoring period is obtained, and the monitoring data includes groundwater flow data and pollutant concentration data. Then, each monitoring point obtains groundwater flow data and pollutant concentration data in the current monitoring period, and the groundwater flow data includes the groundwater flow at multiple sampling moments of the corresponding monitoring point in the current monitoring period, and the pollutant concentration data includes various types of pollutant concentration data, and the various types of pollutant concentration data include the pollutant concentrations at multiple sampling moments of the corresponding monitoring point in the current monitoring period.

[0064] Moreover, according to the above method, the monitoring data of each monitoring point in the previous monitoring cycle is also obtained, and the previous monitoring cycle is the previous monitoring cycle adjacent to the current monitoring cycle.

[0065] Step 2: Based on the groundwater flow data, obtain the water flow fluctuation degree of the monitoring point in the current monitoring period, and based on the pollutant concentration data, obtain the concentration trend change degree of various pollutants at the monitoring point in the current monitoring period.

[0066] As mining construction activities proceed, mining often causes dramatic fluctuations in water volume due to the flow characteristics of groundwater in karst areas, thus affecting the stability of groundwater. The rise and fall of water levels may cause pollutants to be brought into the groundwater system, or spread to a wider area. At the same time, this process may destroy the pollutant diffusion characteristics corresponding to the original mining construction, which refers to the pollutant distribution characteristics presented by the original mining construction, which will cause the monitoring points on its pollution channel to show similar pollution performance. When the water volume at a certain monitoring point changes dramatically, it means that the current mining construction has broken the pollutant diffusion balance formed by the previous construction. Therefore, it is necessary to analyze the degree of water flow fluctuation at each monitoring point and the degree of change in the concentration trend of various pollutants.

[0067] For the convenience of explanation, any monitoring point is set as the first monitoring point, and the first monitoring point is used for explanation below.

[0068] According to the groundwater flow data of the first monitoring point in the current monitoring period, the water flow fluctuation degree is obtained. In an exemplary embodiment, the process of obtaining the water flow fluctuation degree is as follows: Figure 2 As shown, including:

[0069] Step 2-1: Obtain a first water flow characteristic based on groundwater flow data of a first monitoring point in a current monitoring period.

[0070] The first water flow characteristic of the first monitoring point is specifically the average value of the groundwater flow data of the first monitoring point in the current monitoring period, and the average value represents the overall characteristic of the water flow of the first monitoring point in the current monitoring period.

[0071] Step 2-2: Obtain groundwater flow data of the first monitoring point in the previous monitoring period, and obtain a second water flow characteristic based on the groundwater flow data of the monitoring point in the previous monitoring period.

[0072] Similarly, the second water flow characteristic of the first monitoring point is specifically the average value of the groundwater flow data of the first monitoring point in the previous monitoring cycle, and the average value serves as the overall characteristic of the water flow of the first monitoring point in the previous monitoring cycle.

[0073] Step 2-3: According to the difference between the first water flow characteristic and the second water flow characteristic, the water flow fluctuation degree of the first monitoring point in the current monitoring period is obtained.

[0074] The difference between the first water flow characteristic and the second water flow characteristic of the first monitoring point reflects the difference in water flow between the previous monitoring period and the current monitoring period, that is, the water flow fluctuation. Therefore, according to the difference between the first water flow characteristic and the second water flow characteristic, the degree of water flow fluctuation at the first monitoring point in the current monitoring period is obtained. Specifically: the absolute value of the difference between the first water flow characteristic and the second water flow characteristic of the first monitoring point is calculated, and the absolute value of the difference reflects the change in water flow in the current monitoring period compared with the previous monitoring period. The absolute value of the difference is normalized, and the normalized absolute value of the difference is used as the degree of water flow fluctuation at the first monitoring point in the current monitoring period. The normalization method in this embodiment can be a linear normalization method, or it can be the following method: , It represents the object that needs to be normalized, and exp represents the exponential function with the natural constant e as the base.

[0075] By using the above process, the water flow fluctuation degree of each monitoring point in the current monitoring period is obtained.

[0076] When groundwater is polluted in karst mines, the monitoring points on the same pollution channel will maintain relatively consistent pollutant characteristics. This is not only reflected in the relative consistency of the changing trends of various pollutant concentrations, but also in the relatively balanced ratio of multiple pollutant concentrations (different pollution sources will emit different combinations of pollutants and different ratios of pollutant concentrations).

[0077] like Figure 3 As shown, on the left and right are schematic diagrams of groundwater pollution channels corresponding to two different pollution sources, among which the distribution of groundwater pollution channels under the same pollution source is complex and intertwined.

[0078] According to the pollutant concentration data of the first monitoring point in the current monitoring period, the concentration trend change degree of various pollutants at the first monitoring point is obtained. In an exemplary embodiment, the process of obtaining the concentration trend change degree of various pollutants is as follows: Figure 4 As shown, including:

[0079] Step 2-4: For any pollutant, obtain the concentration data sequence of the pollutant in the pollutant concentration data of the first monitoring point in the current monitoring period.

[0080] Since the pollutant concentration data of the first monitoring point includes concentration data sequences of multiple types of pollutants, the concentration data sequence of each type of pollutant in the pollutant concentration data is obtained.

[0081] Step 2-5: Obtain the difference between the concentration data at two adjacent moments in the concentration data sequence.

[0082] Specifically: the absolute value of the difference between the concentration data at two adjacent moments in the concentration data sequence is obtained. The absolute value of the difference represents the degree of change of the concentration data at two adjacent moments. The larger the absolute value of the difference, the greater the difference between the concentration data at two adjacent moments.

[0083] Step 2-6: According to the difference in concentration data at two adjacent moments, the concentration trend change degree of the pollutant at the first monitoring point in the current monitoring period is obtained.

[0084] The average value of the difference in concentration data between all two adjacent moments is calculated, the average value is normalized, and the normalized result is used as the concentration trend change degree of the pollutant at the first monitoring point in the current monitoring period.

[0085] By adopting the above process, the concentration trend change degree of various pollutants at various monitoring points in the current monitoring cycle is obtained. Moreover, by adopting the above process, the concentration trend change degree of various pollutants at various monitoring points in the previous monitoring cycle is also obtained.

[0086] Step 3: Based on the difference between the concentration of various pollutants at the monitoring point and the concentration of another pollutant that matches it, the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period is obtained.

[0087] Next, consider the relatively balanced ratio of the concentrations of multiple pollutants. This is based on the fact that the same pollution source will present a relatively balanced concentration ratio of different pollutants at each monitoring point under the pollution channel. In this way, each monitoring point is analyzed. The following also takes the first monitoring point as an example. Figure 5 As shown, the process includes the following:

[0088] Step 3-1: According to the difference between the concentration of various pollutants at the first monitoring point and the concentration of another pollutant matching it, the concentration balance ratio of various pollutants at the first monitoring point in the current monitoring period is obtained.

[0089] First, it is necessary to determine the matching relationship between various pollutants, such as Figure 6 As shown, the details are as follows:

[0090] Step 3-1-1: Based on the pollutant concentration data of the first monitoring point in the current monitoring period, obtain the average concentration of various pollutants.

[0091] The concentration data of various pollutants in the pollutant concentration data of the first monitoring point in the current monitoring period are obtained, and then the average values ​​of the concentration data of various pollutants are calculated to obtain the average concentrations of various pollutants.

[0092] Step 3-1-2: Sort the average concentrations of various pollutants in descending order to obtain an average concentration sequence.

[0093] Step 3-1-3: The pollutants corresponding to two adjacent average concentrations in the average concentration sequence are regarded as two matching pollutants.

[0094] Specifically: suppose there are N average concentrations in the average concentration sequence, then the pollutant corresponding to the n-1th average concentration and the pollutant corresponding to the nth average concentration are taken as two matching pollutants, thereby obtaining multiple matching relationships, where n=2, 3, ..., N.

[0095] The pollutants corresponding to the n-1th average concentration and the pollutants corresponding to the nth average concentration are used as the matching relationship with the pollutants corresponding to the n-1th average concentration. Since there are no other average concentrations after the last average concentration in the average concentration sequence (i.e., the Nth average concentration), and the last average concentration in the average concentration sequence is the smallest average concentration, the pollutant with the smallest average concentration has a relatively low impact on the environment. Therefore, when matching pollutants, the matching relationship corresponding to the pollutant corresponding to the Nth average concentration is no longer obtained. The concentration equilibrium ratio of the pollutant with the smallest average concentration is no longer obtained in the subsequent calculation, and it is no longer involved in the calculation of the overall pollutant concentration equilibrium ratio.

[0096] Accordingly, we will obtain the matching relationship corresponding to the pollutant corresponding to the first average concentration, the matching relationship corresponding to the pollutant corresponding to the second average concentration, the matching relationship corresponding to the pollutant corresponding to the third average concentration, and so on until the pollutant corresponding to the N-1th average concentration, for a total of N-1 matching relationships.

[0097] Then, according to the matching relationship corresponding to each pollutant, we analyze whether the concentration balance ratio in the current monitoring period remains relatively consistent, and then use the weighted average method to analyze whether multiple pollutants maintain a relatively balanced concentration ratio relationship.

[0098] In an exemplary embodiment, the process of obtaining the concentration balance ratio is as follows: Figure 7 As shown, including:

[0099] Step 3-1-4: Obtain the difference between the concentration of the first pollutant at each characteristic moment in the current monitoring period and the concentration of the second pollutant at the corresponding moment to obtain a concentration difference sequence.

[0100] The first pollutant and the second pollutant are set to be two matching pollutants, and the average concentration of the first pollutant is greater than the average concentration of the second pollutant, that is, if the first pollutant is the pollutant corresponding to the n-1th average concentration, the second pollutant is the pollutant corresponding to the nth average concentration.

[0101] In this embodiment, the characteristic moment is the moment corresponding to the maximum concentration. Specifically: obtain each concentration maximum in the concentration data of the first pollutant in the current monitoring period, and obtain the moment corresponding to each concentration maximum as each characteristic moment of the first pollutant. Perform a concentration balance ratio comparison of the two pollutants based on the moment when the concentration changes significantly as reflected by the maximum point. Then, according to each characteristic moment of the first pollutant, obtain the concentration data of the corresponding moment in the concentration data of the second pollutant for each characteristic moment of the first pollutant, and define the kth characteristic moment of the second pollutant in the current monitoring period as the kth characteristic moment of the first pollutant.

[0102] Let K represent the number of characteristic moments in the concentration data of the first pollutant, and let k represent the kth characteristic moment, where k=1, 2, 3, ..., K.

[0103] Obtain the difference between the concentration of the first pollutant at the kth characteristic moment and the concentration of the second pollutant at the kth characteristic moment in the current monitoring period, where the difference is the absolute value of the difference. That is, by calculating the absolute value of the difference between the concentration of the first pollutant at the kth characteristic moment and the concentration of the second pollutant at the kth characteristic moment in the current monitoring period, K absolute values ​​of the concentration difference can be obtained, and according to these K absolute values ​​of the concentration difference, a concentration difference sequence is formed in the order of the characteristic moments.

[0104] Step 3-1-5: Obtain the first-order difference absolute value sequence of the concentration difference sequence.

[0105] Specifically: the absolute value of the difference between two adjacent data in the concentration difference sequence is calculated to obtain K-1 absolute values ​​of the difference, and a first-order difference absolute value sequence of the concentration difference sequence is sequentially constructed based on the obtained K-1 absolute values ​​of the difference.

[0106] Step 3-1-6: Calculate the average value of the data in the first-order difference absolute value sequence, and obtain the concentration equilibrium ratio of the first pollutant based on the average value. The concentration equilibrium ratio is inversely proportional to the average value.

[0107] In an exemplary embodiment, the calculation formula of the concentration balance ratio is given as follows:

[0108] ;

[0109] Where i represents the i-th monitoring point, m represents the m-th pollutant, is the concentration equilibrium ratio of the mth pollutant at the ith monitoring point in the current monitoring period, K represents the number of characteristic moments, k represents the kth characteristic moment, is the difference between the concentration of the mth pollutant at the i-th monitoring point in the current monitoring period at the k-th characteristic moment and the concentration of another pollutant matching it at the k-th characteristic moment (wherein the mth pollutant is equivalent to the first pollutant mentioned above, and the other pollutant matching the mth pollutant is equivalent to the second pollutant mentioned above), is the difference between the concentration of the mth pollutant at the ith monitoring point in the current monitoring period at the k+1th characteristic moment and the concentration of another matching pollutant at the k+1th characteristic moment, Represents the normalization function.

[0110] According to the above process, the concentration balance ratio of various pollutants at various monitoring points in the current monitoring period is obtained (excluding the concentration balance ratio of the pollutant with the smallest average concentration).

[0111] By matching pollutants with adjacent average concentrations, we can analyze the concentration balance ratio of various pollutants. The higher the value, the more balanced and consistent the concentration ratio between the corresponding two pollutants is at different times in the current monitoring period.

[0112] Step 3-2: According to the concentration balance ratio of various pollutants at the first monitoring point, the overall pollutant concentration balance ratio of the first monitoring point is obtained.

[0113] Step 3-1 obtains the concentration balance ratio of various pollutants at the first monitoring point, and then calculates the average value of the concentration balance ratio of various pollutants at the first monitoring point, and uses the average value as the overall pollutant concentration balance ratio of the first monitoring point.

[0114] Thus, the overall pollutant concentration balance ratio of each monitoring point in the current monitoring cycle is obtained. In addition, the overall pollutant concentration balance ratio of each monitoring point in the previous monitoring cycle is obtained by using the above process.

[0115] Step 4: According to the degree of water flow fluctuation at the monitoring point in the current monitoring period, the concentration trend change of various pollutants at the monitoring point in the current monitoring period and the previous monitoring period, and the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period and the previous monitoring period, the characteristic distance between any two monitoring points is obtained.

[0116] This step is to comprehensively determine the characteristic distance of the same pollution source between different monitoring points based on the degree of water flow fluctuation at the monitoring point.

[0117] For the determination of the characteristic distance of the same pollution source between different monitoring points, we should not only pay attention to the changing trend of pollutant concentration of the two, but also pay attention to the balanced ratio of the overall pollutant concentration of the two. At the same time, in this process, based on any monitoring point, it is necessary to select the relevant data corresponding to the current monitoring cycle and the previous monitoring cycle according to the degree of water flow fluctuation. This means that the greater the degree of water flow fluctuation, the more drastic the water flow change in the current monitoring cycle compared with the previous monitoring cycle, that is, the original balance of pollutant flow was broken with the start of mining operations. Therefore, greater attention should be paid to the relevant data of the previous monitoring cycle, and vice versa.

[0118] In an exemplary embodiment, Figure 8 As shown in FIG. 1 , the process of obtaining the feature distance includes:

[0119] Step 4-1: According to the water flow fluctuation degree of the first monitoring point in the current monitoring period, and the concentration trend change degree of various pollutants at the first monitoring point in the current monitoring period and the previous monitoring period, the first characteristics of various pollutants at the first monitoring point in the current monitoring period are obtained.

[0120] According to the water flow fluctuation degree of the first monitoring point in the current monitoring period obtained in the above steps, and the concentration trend change degree of various pollutants at the first monitoring point in the current monitoring period and the previous monitoring period, the first feature of various pollutants at the first monitoring point in the current monitoring period is obtained. The first feature represents the result of the association between the water flow fluctuation degree of the first monitoring point in the current monitoring period and the concentration trend change degree of various pollutants in the current monitoring period and the previous monitoring period. In an exemplary embodiment, the calculation formula of the first feature is as follows:

[0121] ;

[0122] in, is the first characteristic of the mth pollutant at the ith monitoring point in the current monitoring period, is the water flow fluctuation degree of the ith monitoring point in the current monitoring period, is the concentration trend change of the mth pollutant at the ith monitoring point in the current monitoring period, It is the concentration trend change degree of the mth pollutant at the ith monitoring point in the previous monitoring period.

[0123] By adopting the above process, the first characteristics of various pollutants at various monitoring points in the current monitoring period are obtained.

[0124] Step 4-2: According to the water flow fluctuation degree of the first monitoring point in the current monitoring cycle and the overall pollutant concentration balance ratio of the first monitoring point in the current monitoring cycle and the previous monitoring cycle, the second characteristic of the first monitoring point in the current monitoring cycle is obtained.

[0125] According to the water flow fluctuation degree of the first monitoring point in the current monitoring period obtained in the above steps, and the overall pollutant concentration balance ratio of the first monitoring point in the current monitoring period and the previous monitoring period, the second feature of the first monitoring point in the current monitoring period is obtained. The second feature represents the result of the association between the water flow fluctuation degree of the first monitoring point in the current monitoring period and the overall pollutant concentration balance ratio of the first monitoring point in the current monitoring period and the previous monitoring period. In an exemplary embodiment, the calculation formula of the second feature is as follows:

[0126] ;

[0127] in, is the second feature of the ith monitoring point in the current monitoring period, is the overall pollutant concentration equilibrium ratio of the i-th monitoring point in the current monitoring period, It is the overall pollutant concentration equilibrium ratio of the ith monitoring point in the previous monitoring period.

[0128] By adopting the above process, the second feature of each monitoring point in the current monitoring period is obtained.

[0129] Step 4-3: According to the first characteristics and second characteristics of various pollutants at any two monitoring points, obtain the characteristic distance between any two monitoring points.

[0130] The first characteristics and the second characteristics of various pollutants at any two monitoring points are integrated to obtain the characteristic distance between any two monitoring points. In an exemplary embodiment, the calculation formula of the characteristic distance is as follows:

[0131] ;

[0132] in, is the characteristic distance between the ith monitoring point and the jth monitoring point in the current monitoring cycle. The ith monitoring point and the jth monitoring point are two different monitoring points. is the first characteristic of the mth pollutant at the jth monitoring point in the current monitoring period, M represents the number of pollutant types (the number of pollutant types here refers to the number of pollutant types other than the pollutant with the smallest average concentration), is the second feature of the jth monitoring point in the current monitoring cycle. And the second feature The acquisition method and the first feature of the i-th monitoring point And the second feature The method of obtaining is the same.

[0133] The calculation formula of the characteristic distance is to first integrate the data of each monitoring point based on the current and previous monitoring cycles by assigning different weights, and define two different characteristics through the Euclidean distance method, so as to determine the characteristic distance of the same pollution source between different monitoring points.

[0134] By using the above process, the characteristic distance between any two monitoring points in the current monitoring period is obtained, that is, the characteristic distance of the same pollution source.

[0135] Step 5: Cluster each monitoring point according to the characteristic distance between any two monitoring points.

[0136] After obtaining the characteristic distance between any two monitoring points, each monitoring point can be clustered according to the characteristic distance between any two monitoring points. It should be understood that the clustering algorithm used is set according to actual needs. In an exemplary embodiment, each monitoring point is clustered by the k-means clustering algorithm, and the k parameter is preset to 4, so that 4 clusters are obtained. It should be understood that the monitoring points in each cluster present the characteristic performance of pollutants corresponding to the same pollution source, and according to the principle that water flows to lower places, the pollution channel of pollutants in each cluster can be determined according to the altitude of the monitoring point, and the pollution source and the diffusion path of the pollution can be clearly presented, so as to better formulate targeted pollution control and remediation measures according to the actual situation, and reduce the long-term harm of pollutants to groundwater.

[0137] Therefore, the present invention can weigh the degree of utilization of relevant data in the current monitoring cycle and the previous monitoring cycle by calculating the degree of water flow fluctuation at the monitoring point, taking into account the situation that the monitoring points under the same pollution source cannot completely present the same pollution characteristics due to the disruption of the previous pollutant diffusion equilibrium state under the influence of actual mining operations, and then comprehensively and fully utilize the relevant data of the current monitoring cycle and the previous monitoring cycle to make the various monitoring points under the same pollution source more accurately clustered into one category in the final clustering, thereby realizing the tracking of mine groundwater pollution channels and avoiding abnormal situations of individual monitoring points under the same pollution source caused by mining operations.

[0138] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0139] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for tracking underground water pollution channels in karst mines, characterized in that: include: Acquire monitoring data of multiple monitoring points arranged in a karst mine in a current monitoring cycle, wherein the monitoring data includes groundwater flow data and pollutant concentration data; According to the groundwater flow data, the water flow fluctuation degree of the monitoring point in the current monitoring period is obtained, and according to the pollutant concentration data, the concentration trend change degree of various pollutants at the monitoring point in the current monitoring period is obtained; According to the difference between the concentration of various pollutants at the monitoring point and the concentration of another pollutant matched therewith, the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period is obtained, including: according to the difference between the concentration of various pollutants at the monitoring point and the concentration of another pollutant matched therewith, the concentration balance ratio of various pollutants at the monitoring point in the current monitoring period is obtained; according to the concentration balance ratio of various pollutants at the monitoring point, the overall pollutant concentration balance ratio of the monitoring point is obtained; The method of obtaining the concentration balance ratio of various pollutants at the monitoring point in the current monitoring period according to the difference between the concentration of various pollutants at the monitoring point and the concentration of another pollutant matched therewith comprises the following specific steps: Obtain the difference between the concentration of the first pollutant at each characteristic moment and the concentration of the second pollutant at the corresponding moment in the current monitoring period to obtain a concentration difference sequence; the first pollutant and the second pollutant are two matching pollutants, and the average concentration of the first pollutant is greater than the average concentration of the second pollutant; obtain a first-order difference absolute value sequence of the concentration difference sequence; calculate the average value of the data in the first-order difference absolute value sequence, and obtain the concentration balance ratio of the first pollutant according to the average value, and the concentration balance ratio is inversely proportional to the average value; According to the degree of water flow fluctuation at the monitoring point in the current monitoring period, the concentration trend change of various pollutants at the monitoring point in the current monitoring period and the previous monitoring period, and the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period and the previous monitoring period, the characteristic distance between any two monitoring points is obtained; Cluster each monitoring point according to the characteristic distance between any two monitoring points; According to the clusters of each monitoring point, the characteristic performance of pollutants corresponding to the pollution source corresponding to the cluster is obtained, and the pollution channel of the pollutants in each cluster is determined in combination with the principle that water flows to lower places and the altitude of the monitoring point; The matching process of various pollutants with another pollutant includes: According to the pollutant concentration data of the monitoring points in the current monitoring period, the average concentration of various pollutants is obtained; Sort the average concentrations of various pollutants in descending order to obtain an average concentration sequence; The pollutants corresponding to two adjacent average concentrations in the average concentration sequence are regarded as two matching pollutants.

2. The method for tracing underground water pollution channels in karst mines as claimed in claim 1 is characterized in that: According to the groundwater flow data, the water flow fluctuation degree of the monitoring point in the current monitoring period is obtained, including: Obtaining a first water flow characteristic according to groundwater flow data of the monitoring point in a current monitoring period; Obtaining groundwater flow data of the monitoring point in the previous monitoring period, and obtaining a second water flow characteristic based on the groundwater flow data of the monitoring point in the previous monitoring period; According to the difference between the first water flow characteristic and the second water flow characteristic, the water flow fluctuation degree of the monitoring point in the current monitoring period is obtained.

3. The method for tracing underground water pollution channels in karst mines as claimed in claim 1 is characterized in that: According to the pollutant concentration data, the concentration trend change of various pollutants at the monitoring point in the current monitoring period is obtained, including: For any pollutant, obtain the concentration data sequence of the pollutant in the pollutant concentration data of the monitoring point in the current monitoring period; Obtaining the difference between the concentration data at two adjacent moments in the concentration data sequence; According to the difference between the concentration data at two adjacent moments, the concentration trend change degree of the pollutant at the monitoring point in the current monitoring period is obtained.

4. The method for tracing underground water pollution channels in karst mines as claimed in claim 1 is characterized in that: The calculation formula of concentration balance ratio is as follows: ； Where i represents the i-th monitoring point, m represents the m-th pollutant, is the concentration equilibrium ratio of the mth pollutant at the ith monitoring point in the current monitoring period, K represents the number of characteristic moments, k represents the kth characteristic moment, is the difference between the concentration of the mth pollutant at the i-th monitoring point in the current monitoring period at the k-th characteristic moment and the concentration of another pollutant that matches it at the k-th characteristic moment, is the difference between the concentration of the mth pollutant at the ith monitoring point in the current monitoring period at the k+1th characteristic moment and the concentration of another pollutant that matches it at the k+1th characteristic moment, Represents the normalization function.

5. The method for tracing underground water pollution channels in karst mines as claimed in claim 1, characterized in that: According to the degree of water flow fluctuation at the monitoring point in the current monitoring period, the concentration trend change of various pollutants at the monitoring point in the current monitoring period and the previous monitoring period, and the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period and the previous monitoring period, the characteristic distance between any two monitoring points is obtained, including: According to the degree of water flow fluctuation at the monitoring point in the current monitoring period, and the degree of change in concentration trend of various pollutants at the monitoring point in the current monitoring period and the previous monitoring period, a first feature of various pollutants at the monitoring point in the current monitoring period is obtained, wherein the first feature is used to characterize the result of the association between the degree of water flow fluctuation and the degree of change in concentration trend of various pollutants at the monitoring point in the current monitoring period and the previous monitoring period; According to the degree of water flow fluctuation at the monitoring point in the current monitoring period and the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period and the previous monitoring period, a second feature of the monitoring point in the current monitoring period is obtained, wherein the second feature is used to characterize the result of the association between the degree of water flow fluctuation and the overall pollutant concentration balance ratio of the monitoring point in the current monitoring period and the previous monitoring period; According to the first characteristics and the second characteristics of various pollutants at any two monitoring points, the characteristic distance between any two monitoring points is obtained.

6. A method for tracing underground water pollution channels in karst mines as claimed in claim 5, characterized in that: The calculation formula of the first feature is as follows: ； Among them, i represents the i-th monitoring point, m represents the m-th pollutant, is the first characteristic of the mth pollutant at the ith monitoring point in the current monitoring period, is the water flow fluctuation degree of the ith monitoring point in the current monitoring period, is the concentration trend change of the mth pollutant at the ith monitoring point in the current monitoring period, is the concentration trend change of the mth pollutant at the ith monitoring point in the previous monitoring period; The calculation formula of the second feature is as follows: ； in, is the second feature of the i-th monitoring point in the current monitoring period, is the overall pollutant concentration equilibrium ratio of the i-th monitoring point in the current monitoring period, It is the overall pollutant concentration equilibrium ratio of the ith monitoring point in the previous monitoring period.

7. A method for tracking underground water pollution channels in karst mines as claimed in claim 6, characterized in that the calculation formula of the characteristic distance is as follows: ； in, is the characteristic distance between the i-th monitoring point and the j-th monitoring point in the current monitoring period, is the first characteristic of the mth pollutant at the jth monitoring point in the current monitoring period, M represents the number of pollutant types, is the second feature of the jth monitoring point in the current monitoring period.

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