Comprehensive quantitative traceability method for karst groundwater pollution based on conventional hydrochemistry

Abstract

The invention relates to the technical field of karst groundwater pollution, and discloses a karst groundwater pollution comprehensive quantitative traceability method based on conventional hydrochemistry, which comprises the following steps: carrying out major element analysis on a groundwater sample to obtain first content data of each major element in the groundwater sample; judging whether the first content data corresponding to each major element in the underground water sample exceeds a first threshold value or not, and if so, determining that the corresponding major element is the corresponding pollution major element; measuring the content of trace elements in the underground water samples to obtain second content data corresponding to each trace element in each underground water sample, judging whether the second content data corresponding to each trace element exceeds a second threshold value or not, and if so, determining that the corresponding trace element is the corresponding polluted trace element; identifying various groundwater pollution source types corresponding to the to-be-detected area; and acquiring ground building information corresponding to the to-be-detected area, and determining each potential pollution source corresponding to each underground water pollution source type.

Description

Technical Field

[0001] The present invention relates to the technical field of groundwater pollution, and in particular to a comprehensive quantitative tracing method for karst groundwater pollution based on conventional water chemistry. Background Art

[0002] Groundwater is an important freshwater resource, and its quality is directly related to human health and the sustainable development of the ecological environment. However, with the acceleration of industrialization and urbanization, groundwater pollution is becoming increasingly serious. In karst areas, due to the particularity of the geological structure, groundwater pollution is particularly prominent.

[0003] Most existing methods for tracing the source of groundwater pollution rely mainly on qualitative analysis, which determines the pollution source by measuring the content of major and trace elements in groundwater. However, these methods can usually only provide qualitative information and cannot accurately quantify the contribution of each pollution source. The lack of quantitative analysis makes it difficult to assess the actual impact of different pollution sources, resulting in a lack of targeted governance measures, which may waste resources or fail to effectively solve the problem.

[0004] Based on this, there is an urgent need for a comprehensive quantitative tracing method for karst groundwater pollution based on conventional hydrochemistry, which can realize accurate quantitative identification of groundwater pollution sources and improve the accuracy and efficiency of groundwater pollution tracing. Summary of the invention

[0005] One of the purposes of the present invention is to provide a comprehensive quantitative tracing method for karst groundwater pollution based on conventional hydrochemistry, which can achieve accurate quantitative identification of groundwater pollution sources and improve the accuracy and efficiency of groundwater pollution tracing.

[0006] In order to achieve the above-mentioned purpose, a comprehensive quantitative tracing method for karst groundwater pollution based on conventional water chemistry is provided, which comprises the following steps:

[0007] S1. Based on a preset groundwater sampling point determination strategy, groundwater sampling points are determined for the area to be detected to form a groundwater sampling point set corresponding to the area to be detected;

[0008] S2. According to the formed groundwater sampling point set corresponding to the area to be detected, drilling sampling is performed at each groundwater sampling point, and based on the sampling depth corresponding to each groundwater sampling point, groundwater samples corresponding to the corresponding sampling depth are collected;

[0009] S3, according to the groundwater samples corresponding to each groundwater sampling point, performing major element analysis on the groundwater samples to obtain first content data of each major element in the groundwater samples, and judging whether the first content data corresponding to each major element in the groundwater samples exceeds a first threshold value, if so, the corresponding major element is the corresponding contamination major element;

[0010] S4. According to the groundwater samples corresponding to each groundwater sampling point, the content of trace elements in the groundwater samples is measured to obtain second content data corresponding to each trace element in each groundwater sample, and it is determined whether the second content data corresponding to each trace element exceeds a second threshold value. If so, the corresponding trace element is a corresponding contaminated trace element;

[0011] S5. According to the major elements corresponding to the major polluting elements and the trace elements corresponding to the trace polluting elements, based on the preset nitrate and nitrogen and oxygen isotopes, identify the types of groundwater pollution sources corresponding to the area to be detected;

[0012] S6. Input the first content data and the second content data corresponding to the major element of the pollution and the trace element of the pollution into a preset PMF model for quantitative source analysis, and calculate the pollutant contribution rate of each groundwater pollution source type corresponding to the area to be detected;

[0013] S7. Obtain the ground building information corresponding to the area to be detected, and based on the identified types of groundwater pollution sources corresponding to the area to be detected, determine the potential pollution sources corresponding to each type of groundwater pollution source in descending order of pollutant contribution rate of each type of groundwater pollution source.

[0014] Technical principles and effects of this scheme: In this scheme, firstly, based on the preset groundwater sampling point determination strategy, the groundwater sampling points of the area to be tested are determined to form a set of groundwater sampling points corresponding to the area to be tested, and the groundwater sampling points are reasonably selected to ensure that the groundwater quality status in the study area can be fully reflected.

[0015] Secondly, drilling sampling is carried out on each groundwater sampling point, and based on the sampling depth corresponding to each groundwater sampling point, the groundwater samples corresponding to the corresponding sampling depth are collected, and the contents of major elements and trace elements are respectively determined, and it is judged whether the first content data corresponding to each major element in the groundwater sample exceeds the first threshold value. If so, the corresponding major element is the corresponding polluted major element; at the same time, it is judged whether the second content data corresponding to each trace element exceeds the second threshold value. If so, the corresponding trace element is the corresponding polluted trace element, thereby realizing the determination of the corresponding polluted major elements and polluted trace elements.

[0016] Afterwards, based on the preset nitrate and nitrogen oxygen isotopes, the types of groundwater pollution sources corresponding to the area to be tested are identified, that is, the types of pollution sources are further refined by combining the analysis of nitrate and nitrogen oxygen isotopes.

[0017] Finally, by inputting the relevant data of major and trace elements of pollution into the PMF model, the specific contribution rate of each pollution source to the groundwater pollution in the area can be calculated, thereby achieving accurate quantification of the pollution source, and obtaining the ground building information corresponding to the area to be tested. Based on the identified types of groundwater pollution sources corresponding to the area to be tested, the potential pollution sources corresponding to each type of groundwater pollution source are determined in descending order of the pollutant contribution rate of each type of groundwater pollution source. That is, by obtaining ground building information and groundwater pollution source types, combined with historical pollutant emission data, potential pollution sources can be identified more comprehensively and accurately.

[0018] In this scheme, by combining a variety of analytical methods including major element analysis and trace element analysis, the pollution source can be identified more accurately and the possibility of misjudgment can be reduced. Secondly, the PMF model is used for quantitative source analysis, which can not only identify the pollution source, but also calculate the specific contribution ratio of each pollution source to groundwater pollution, realize accurate quantitative identification of groundwater pollution sources, improve the accuracy and efficiency of groundwater pollution source tracing, and help to scientifically formulate pollution prevention and control measures. In addition, combined with the ground building information corresponding to the area to be tested, based on the identified types of groundwater pollution sources corresponding to the area to be tested, the potential pollution sources corresponding to each type of groundwater pollution source are determined in descending order of the pollutant contribution rate of each type of groundwater pollution source, thereby realizing accurate and reliable tracing of the corresponding groundwater pollution.

[0019] Further, the method further comprises the following steps:

[0020] S8. According to each potential pollution source corresponding to a certain groundwater pollution source type, retrieve the historical pollutant emission data corresponding to each potential pollution source, and calculate the emission similarity between the pollutants emitted by each potential pollution source based on the historical pollutant emission data corresponding to each potential pollution source and a preset emission similarity calculation formula;

[0021] The emission similarity calculation formula is as follows:

[0022]

[0023] Where P ab is the emission similarity between two potential pollution sources a and b, H ai is the element content corresponding to element i corresponding to potential pollution source a, n is the total number of element types, w ab is the weight coefficient between potential pollution source a and potential pollution source b, is the corresponding weighting coefficient, A a is the area corresponding to the potential pollution source a, F ais the emission flow in the historical pollutant emission data corresponding to the potential pollution source a, and D is the distance between the potential pollution source a and the potential pollution source b;

[0024] S9, according to the emission similarity corresponding to each potential pollution source, based on a preset potential pollution source classification strategy, dividing each potential pollution source into multiple potential pollution source sets;

[0025] S10, randomly selecting a potential pollution source from each potential pollution source set, and determining the pollution level corresponding to the selected potential pollution source based on the historical pollutant emission data corresponding to the selected potential pollution source, and using the pollution level of the corresponding potential pollution source set as the pollution level;

[0026] S11. According to the pollution level corresponding to each potential pollution source set, based on the preset monitoring scheme matching strategy, the pollution monitoring scheme corresponding to each potential pollution source set is matched.

[0027] Beneficial effects: The emission similarity calculation formula is used to quantify the pollution emission relationship between different potential pollution sources, which improves the scientificity and accuracy of identification. Clustering divides potential pollution sources into multiple potential pollution source sets, which helps to reasonably allocate monitoring resources. For potential pollution source sets with higher pollution levels, the monitoring frequency and scope can be increased, while for potential pollution source sets with lower pollution levels, the monitoring intensity can be appropriately reduced, thereby optimizing resource allocation and improving monitoring efficiency. Randomly selecting a potential pollution source from each potential pollution source set for detailed evaluation reduces the cost and workload of comprehensive monitoring while ensuring representativeness. Based on the historical pollutant emission data corresponding to the selected potential pollution sources, the pollution level of the potential pollution source set is determined, which provides a scientific basis for formulating specific pollution control measures. According to the pollution level of each potential pollution source set, a personalized pollution monitoring plan is formulated to ensure that the control measures are more targeted and effective.

[0028] Furthermore, the preset potential pollution source classification strategy includes the following steps:

[0029] According to the emission similarity between various potential pollution sources corresponding to a certain groundwater pollution source type, the emission similarity is sorted from large to small to form a corresponding emission similarity ranking table;

[0030] According to the preset division ratio, the emission similarity ranking table is divided into three similarity sub-lists, and the header emission similarity corresponding to the header and the tail emission similarity corresponding to the tail of each of the three similarity sub-lists are selected;

[0031] Calculate the absolute value of the similarity difference between the head emission similarity of each similarity sublist and the tail emission similarities corresponding to the other two similarity sublists, and determine whether the corresponding absolute value of the similarity difference is less than a preset difference. If so, the two similarity sublists corresponding to the absolute value of the similarity difference are lists of the same type, and merge the corresponding two similarity sublists into the same similarity sublist. If not, the two similarity sublists corresponding to the absolute value of the similarity difference are not lists of the same type.

[0032] After all similarity sublists are judged, corresponding similarity sublists are obtained, potential pollution sources corresponding to each similarity sublist are identified, and potential pollution sources in the same similarity sublist are divided into the same potential pollution source set.

[0033] Beneficial effects: In this scheme, by calculating and ranking the emission similarities between various potential pollution sources, the scientificity and accuracy of the classification are ensured. This method can more finely identify potential pollution sources with similar emission characteristics, thereby better understanding the distribution and characteristics of the pollution sources. By dividing the emission similarity ranking table into three similarity sub-lists, and further judging and merging the similarity sub-lists, the meticulousness and rationality of the classification are ensured. By merging similarity sub-lists whose absolute values ​​of similarity differences are less than the preset differences, unnecessary repeated monitoring is reduced and resources are saved.

[0034] Furthermore, the preset monitoring scheme matching strategy is: if the pollution level is pollution level 1, the first pollution monitoring scheme is called; if the pollution level is pollution level 2, the second pollution monitoring scheme is called; if the pollution level is pollution level 3, the third pollution monitoring scheme is called.

[0035] Beneficial effects: The pollution levels of potential pollution sources are divided into primary, secondary and tertiary levels, and each level corresponds to a different monitoring plan, ensuring the pertinence and effectiveness of governance measures. The corresponding monitoring plan is called according to different pollution levels to avoid waste of resources and ensure efficient use of resources.

[0036] Furthermore, it also includes:

[0037] S12, when the pollution level corresponding to the corresponding potential pollution source is determined at the current sampling time, the historical pollution level corresponding to the corresponding potential pollution source at the historical sampling time is retrieved from the historical database;

[0038] S13. Calculate the pollution level change value of the corresponding potential pollution source based on the historical pollution level of the potential pollution source at the historical sampling time and the pollution level of the potential pollution source at the current sampling time. If the pollution level change value is greater than the preset change level threshold, switch the pollution level corresponding to the current sampling time to a higher pollution level, and call the pollution monitoring plan corresponding to the switched pollution level.

[0039] Beneficial effects: By retrieving the historical pollution levels in the historical database and comparing them with the pollution levels at the current sampling time, changes in pollution levels can be discovered in a timely manner. If the pollution level change value is greater than the preset change threshold, a higher pollution level can be immediately switched to a more stringent monitoring plan. This dynamic adjustment mechanism can capture dynamic changes in pollution in a timely manner, provide early warnings, and prevent pollution from spreading and worsening.

[0040] Furthermore, the preset groundwater sampling point determination strategy is:

[0041] According to the ground building data and the production and living data corresponding to each building, the area to be inspected is divided into functional areas, and the area to be inspected is divided into industrial sub-areas, agricultural sub-areas, living sub-areas and natural sub-areas;

[0042] According to each sub-area in the area to be detected, the area corresponding to each sub-area is calculated, and based on the preset sampling point setting density, the total number of sampling points corresponding to each sub-area is calculated;

[0043] Each sub-region is divided into a number of grids, and based on the total number of sampling points corresponding to each sub-region, the number of sampling points set in each grid of each sub-region is calculated, and the sampling points corresponding to the number of sampling points are randomly set on each grid in each sub-region to form a sampling point setting scheme corresponding to each sub-region, and N sampling point setting schemes corresponding to each sub-region are randomly generated;

[0044] Based on the preset sampling point setting rationality calculation formula, the sampling point setting rationality corresponding to each sampling point setting scheme is calculated in turn, and a random number Q between 0 and 1 is randomly generated, and the sampling point setting rationality corresponding to each sampling point setting scheme is associated with the corresponding random number Q;

[0045] Arrange the sampling points in descending order according to their rationality, and form a corresponding rationality arrangement table;

[0046] According to the preset selection ratio, the random number Q associated with the rationality of all sampling point settings in the rationality arrangement table is judged. If the corresponding random number Q is greater than the preset random threshold, the sampling point setting scheme corresponding to the rationality of the sampling point setting associated with the random number is selected, and the number of the corresponding selected sampling point setting schemes is counted to see whether they meet the corresponding preset selection ratio. If not, the sampling point setting schemes are selected from the rationality arrangement table in descending order until the corresponding preset selection ratio is met.

[0047] The calculation formula for the rationality of the preset sampling point setting is:

[0048]

[0049] Where L is the rationality of the sampling point setting, F is the sum of the distances from each sampling point in the sampling point setting scheme to the center point of the industrial sub-area, (x j ,y j ,k j ) is the position coordinate of a sampling point in the sampling point setting scheme, W1, W2 are the corresponding weighting coefficients;

[0050] After the selection is completed, the selected sampling point setting schemes are randomly combined in pairs to form corresponding setting combinations, and a preset number of sampling points are randomly selected for exchange to obtain the corresponding new sampling point setting schemes. After the exchange of all sampling point setting schemes is completed, the sampling point setting rationality of the corresponding new sampling point setting scheme is recalculated until the corresponding number of repetitions meets the preset number of iterations. The sampling point setting scheme with the largest sampling point setting rationality at this time is used as the groundwater sampling point set of the corresponding sub-area.

[0051] Beneficial effects: According to the ground building data and production and living data, the area to be tested is divided into industrial sub-areas, agricultural sub-areas, living sub-areas and natural sub-areas. This division method ensures the representativeness of the sampling points in different functional areas and can fully reflect the groundwater pollution status of each sub-area. Each sub-area is divided into several grids, and sampling points are randomly set in each grid. This method ensures the uniform distribution of sampling points in space and improves the representativeness of sampling points.

[0052] According to the area of ​​each sub-area and the preset sampling point setting density, the total number of sampling points corresponding to each sub-area is calculated. This method ensures the rational allocation of resources and avoids waste of resources. By randomly generating multiple sampling point setting schemes, and evaluating and selecting based on the preset sampling point setting rationality calculation formula, the diversity and rationality of the sampling point setting schemes are ensured. In particular, the setting of the corresponding random number Q can balance the selection probability of different sampling point setting schemes through the setting of the random number Q, and avoid excessive concentration of resources on a few highly rational schemes. In this way, monitoring resources can be allocated more reasonably to ensure that each scheme has a certain chance of being selected. The flexibility of decision-making is increased. In different situations, by adjusting the preset random threshold, sampling point setting schemes with different rationalities can be flexibly selected to meet different monitoring needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a flow chart of a comprehensive quantitative tracing method for karst groundwater pollution based on conventional water chemistry in Example 1 of the present invention. DETAILED DESCRIPTION

[0054] The following is further described in detail through specific implementation methods:

[0055] Embodiment 1

[0056] A comprehensive quantitative tracing method for karst groundwater pollution based on conventional hydrochemistry is basically as follows Figure 1 As shown, the following steps are included:

[0057] S1. Based on a preset groundwater sampling point determination strategy, groundwater sampling points are determined for the area to be detected to form a groundwater sampling point set corresponding to the area to be detected;

[0058] In this embodiment, the preset groundwater sampling point determination strategy is:

[0059] According to the ground building data and the production and living data corresponding to each building, the area to be inspected is divided into functional areas, and the area to be inspected is divided into industrial sub-areas, agricultural sub-areas, living sub-areas and natural sub-areas;

[0060] According to each sub-area in the area to be detected, the area corresponding to each sub-area is calculated, and based on the preset sampling point setting density, the total number of sampling points corresponding to each sub-area is calculated;

[0061] Each sub-region is divided into a number of grids, and based on the total number of sampling points corresponding to each sub-region, the number of sampling points set in each grid of each sub-region is calculated, and the sampling points corresponding to the number of sampling points are randomly set on each grid in each sub-region to form a sampling point setting scheme corresponding to each sub-region, and N sampling point setting schemes corresponding to each sub-region are randomly generated;

[0062] Based on the preset sampling point setting rationality calculation formula, the sampling point setting rationality corresponding to each sampling point setting scheme is calculated in turn, and a random number Q between 0 and 1 is randomly generated, and the sampling point setting rationality corresponding to each sampling point setting scheme is associated with the corresponding random number Q;

[0063] Arrange the sampling points in descending order according to their rationality, and form a corresponding rationality arrangement table;

[0064] According to the preset selection ratio, the random number Q associated with the rationality of all sampling point settings in the rationality arrangement table is judged. If the corresponding random number Q is greater than the preset random threshold, the sampling point setting scheme corresponding to the rationality of the sampling point setting associated with the random number is selected, and the number of the corresponding selected sampling point setting schemes is counted to see whether they meet the corresponding preset selection ratio. If not, the sampling point setting schemes are selected from the rationality arrangement table in descending order until the corresponding preset selection ratio is met.

[0065] The calculation formula for the rationality of the preset sampling point setting is:

[0066]

[0067] Where L is the rationality of the sampling point setting, F is the sum of the distances from each sampling point in the sampling point setting scheme to the center point of the industrial sub-area, (x j ,y j ,k j ) is the position coordinate of a sampling point in the sampling point setting scheme, W1, W2 are the corresponding weighting coefficients;

[0068] After the selection is completed, the selected sampling point setting schemes are randomly combined in pairs to form corresponding setting combinations, and a preset number of sampling points are randomly selected for exchange to obtain the corresponding new sampling point setting schemes. After the exchange of all sampling point setting schemes is completed, the sampling point setting rationality of the corresponding new sampling point setting scheme is recalculated until the corresponding number of repetitions meets the preset number of iterations. The sampling point setting scheme with the largest sampling point setting rationality at this time is used as the groundwater sampling point set of the corresponding sub-area.

[0069] S2. According to the formed groundwater sampling point set corresponding to the area to be detected, drilling sampling is performed at each groundwater sampling point, and based on the sampling depth corresponding to each groundwater sampling point, groundwater samples corresponding to the corresponding sampling depth are collected;

[0070] S3, according to the groundwater samples corresponding to each groundwater sampling point, performing major element analysis on the groundwater samples to obtain first content data of each major element in the groundwater samples, and judging whether the first content data corresponding to each major element in the groundwater samples exceeds a first threshold value, if so, the corresponding major element is the corresponding contamination major element;

[0071] S4. According to the groundwater samples corresponding to each groundwater sampling point, the content of trace elements in the groundwater samples is measured to obtain second content data corresponding to each trace element in each groundwater sample, and it is determined whether the second content data corresponding to each trace element exceeds a second threshold value. If so, the corresponding trace element is a corresponding contaminated trace element;

[0072] S5. According to the major elements corresponding to the major polluting elements and the trace elements corresponding to the trace polluting elements, based on the preset nitrate and nitrogen oxygen isotopes, the types of groundwater pollution sources corresponding to the area to be detected are identified; in this embodiment, the types of groundwater pollution sources include infiltration, water, soil and rock, and human life sewage.

[0073] S6. The first content data and the second content data corresponding to the main element corresponding to the main element of the pollution and the trace element corresponding to the trace element of the pollution are input as input data into a preset PMF model for quantitative source analysis, and the pollutant contribution rate of each groundwater pollution source type corresponding to the area to be detected is calculated. In this embodiment, the PMF model is a positive definite matrix factorization source analysis model.

[0074] The following steps are also included:

[0075] S7. Obtain the ground building information corresponding to the area to be detected, and determine the potential pollution sources corresponding to each type of groundwater pollution source based on the identified types of groundwater pollution sources corresponding to the area to be detected; in this embodiment, the ground building information includes the equipment information, pollution discharge information and personnel information in the ground building. Equipment information such as the type and name of a certain equipment,

[0076] S8. According to each potential pollution source corresponding to a certain groundwater pollution source type, retrieve the historical pollutant emission data corresponding to each potential pollution source, and calculate the emission similarity between the pollutants emitted by each potential pollution source based on the historical pollutant emission data corresponding to each potential pollution source and a preset emission similarity calculation formula;

[0077] The emission similarity calculation formula is as follows:

[0078]

[0079] Where P ab is the emission similarity between two potential pollution sources a and b, H ai is the element content corresponding to element i corresponding to potential pollution source a, n is the total number of element types, w ab is the weight coefficient between potential pollution source a and potential pollution source b, is the corresponding weighting coefficient, A a is the area corresponding to the potential pollution source a, F a is the emission flow in the historical pollutant emission data corresponding to the potential pollution source a, and D is the distance between the potential pollution source a and the potential pollution source b;

[0080] S9, according to the emission similarity corresponding to each potential pollution source, based on a preset potential pollution source classification strategy, dividing each potential pollution source into multiple potential pollution source sets;

[0081] The preset potential pollution source classification strategy includes the following steps:

[0082] According to the emission similarity between various potential pollution sources corresponding to a certain groundwater pollution source type, the emission similarity is sorted from large to small to form a corresponding emission similarity ranking table;

[0083] According to the preset division ratio, the emission similarity ranking table is divided into three similarity sub-lists, and the header emission similarity corresponding to the header and the tail emission similarity corresponding to the tail of each of the three similarity sub-lists are selected;

[0084] The similarity of the head of each similarity sublist is calculated with the similarity of the tail of the other two similarity sublists respectively, and it is determined whether the corresponding absolute value of the similarity difference is less than the preset difference. If so, the two similarity sublists corresponding to the absolute value of the similarity difference are lists of the same type, and the corresponding two similarity sublists are merged into the same similarity sublist. If not, the two similarity sublists corresponding to the absolute value of the similarity difference are not lists of the same type. In this embodiment, for example, the three similarity sublists are similarity sublist aa, similarity sublist ba, similarity sublist cb, similarity sublist db, similarity sublist dc ... List bb and similarity sublist cc, if the header emission similarity of similarity sublist aa is E1 and the footer emission similarity is K1, the header emission similarity of similarity sublist bb is E2 and the footer emission similarity is K2, and the header emission similarity of similarity sublist cc is E3 and the footer emission similarity is K3, then when calculating the absolute value of the similarity difference, we need to calculate |E1-K2|, |E1-K3|, |E2-K1|, |E2-K3|, |E3-K1|, |E3-K2| respectively, and realize the subsequent judgment by calculating the absolute values ​​of these similarity differences.

[0085] After all similarity sublists are judged, corresponding similarity sublists are obtained, potential pollution sources corresponding to each similarity sublist are identified, and potential pollution sources in the same similarity sublist are divided into the same potential pollution source set.

[0086] S10, randomly selecting a potential pollution source from each potential pollution source set, and determining the pollution level corresponding to the selected potential pollution source based on the historical pollutant emission data corresponding to the selected potential pollution source, and using the pollution level of the corresponding potential pollution source set as the pollution level;

[0087] S11. According to the pollution levels corresponding to each potential pollution source set, based on the preset monitoring scheme matching strategy, match the pollution monitoring scheme corresponding to each potential pollution source set. The preset monitoring scheme matching strategy is: if the pollution level is pollution level one, then call the first pollution monitoring scheme; if the pollution level is pollution level two, then call the second pollution monitoring scheme; if the pollution level is pollution level three, then call the third pollution monitoring scheme. In this embodiment, different pollution monitoring schemes correspond to different monitoring methods. For example, the first pollution monitoring scheme adopts low-frequency monitoring and conventional control measures to maintain a low pollution level. The third pollution monitoring scheme adopts high-frequency monitoring, strict control measures and rapid response mechanism to quickly respond to serious pollution problems.

[0088] The method further includes: S12, when the pollution level corresponding to the corresponding potential pollution source is determined at the current sampling time, retrieving the historical pollution level corresponding to the corresponding potential pollution source at the historical sampling time from the historical database;

[0089] S13. Calculate the pollution level change value of the corresponding potential pollution source based on the historical pollution level of the potential pollution source at the historical sampling time and the pollution level of the potential pollution source at the current sampling time. If the pollution level change value is greater than the preset change level threshold, switch the pollution level corresponding to the current sampling time to a higher pollution level, and call the pollution monitoring plan corresponding to the switched pollution level.

[0090] Embodiment 2

[0091] Compared with the first embodiment, the difference of this embodiment is that after determining the major element corresponding to the corresponding major element of pollution and the trace element corresponding to the trace element of pollution, the potential pollution source investigation data in the database is directly retrieved, the determined major element and trace element are matched with the potential pollution source investigation data, and the potential pollution source similar to the first content data and the second content data corresponding to the determined major element and trace element is identified, thereby completing the tracing of the potential pollution source. The preparation of the potential pollution source investigation data is conducted by the operator in advance according to the production and processing data and pollution discharge data corresponding to each place in the area to be detected.

[0092] In this embodiment, the rapid tracing of potential pollution sources is achieved by matching the similarity of elements and the content data corresponding to the elements, which greatly improves the efficiency of pollution tracing.

[0093] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is described too much here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field of the invention before the application date or priority date, can know all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A comprehensive quantitative tracing method for karst groundwater pollution based on conventional hydrochemistry, characterized by: The following steps are involved: S1. Based on a preset groundwater sampling point determination strategy, groundwater sampling points are determined for the area to be detected to form a groundwater sampling point set corresponding to the area to be detected; S2. According to the formed groundwater sampling point set corresponding to the area to be detected, drilling sampling is performed at each groundwater sampling point, and based on the sampling depth corresponding to each groundwater sampling point, groundwater samples corresponding to the corresponding sampling depth are collected; S3, according to the groundwater samples corresponding to each groundwater sampling point, performing major element analysis on the groundwater samples to obtain first content data of each major element in the groundwater samples, and judging whether the first content data corresponding to each major element in the groundwater samples exceeds a first threshold value, if so, the corresponding major element is the corresponding contamination major element; S4. According to the groundwater samples corresponding to each groundwater sampling point, the content of trace elements in the groundwater samples is measured to obtain second content data corresponding to each trace element in each groundwater sample, and it is determined whether the second content data corresponding to each trace element exceeds a second threshold value. If so, the corresponding trace element is a corresponding contaminated trace element; S5. According to the major elements corresponding to the major polluting elements and the trace elements corresponding to the trace polluting elements, based on the preset nitrate and nitrogen and oxygen isotopes, identify the types of groundwater pollution sources corresponding to the area to be detected; S6. Input the first content data and the second content data corresponding to the major element of the pollution and the trace element of the pollution into a preset PMF model for quantitative source analysis, and calculate the pollutant contribution rate of each groundwater pollution source type corresponding to the area to be detected; S7. Obtain the ground building information corresponding to the area to be detected, and based on the identified types of groundwater pollution sources corresponding to the area to be detected, determine the potential pollution sources corresponding to each type of groundwater pollution source in descending order of pollutant contribution rate of each type of groundwater pollution source.

2. The method for comprehensive quantitative tracing of karst groundwater pollution based on conventional water chemistry according to claim 1 is characterized in that: The following steps are also included: S8. According to each potential pollution source corresponding to a certain groundwater pollution source type, retrieve the historical pollutant emission data corresponding to each potential pollution source, and calculate the emission similarity between the pollutants emitted by each potential pollution source based on the historical pollutant emission data corresponding to each potential pollution source and a preset emission similarity calculation formula; The emission similarity calculation formula is as follows: Where P ab is the emission similarity between two potential pollution sources a and b, H ai is the element content corresponding to element i corresponding to potential pollution source a, n is the total number of element types, w ab is the weight coefficient between potential pollution source a and potential pollution source b, is the corresponding weighting coefficient, A a is the area corresponding to the potential pollution source a, F a is the emission flow in the historical pollutant emission data corresponding to the potential pollution source a, and D is the distance between the potential pollution source a and the potential pollution source b; S9, according to the emission similarity corresponding to each potential pollution source, based on a preset potential pollution source classification strategy, dividing each potential pollution source into multiple potential pollution source sets; S10, randomly selecting a potential pollution source from each potential pollution source set, and determining the pollution level corresponding to the selected potential pollution source based on the historical pollutant emission data corresponding to the selected potential pollution source, and using the pollution level of the corresponding potential pollution source set as the pollution level; S11. Develop pollution monitoring plans for each potential pollution source set based on the pollution level corresponding to each potential pollution source set.

3. The method for comprehensive quantitative tracing of karst groundwater pollution based on conventional water chemistry according to claim 2 is characterized in that: The preset potential pollution source classification strategy includes the following steps: According to the emission similarity between various potential pollution sources corresponding to a certain groundwater pollution source type, the emission similarity is sorted from large to small to form a corresponding emission similarity ranking table; According to the preset division ratio, the emission similarity ranking table is divided into three similarity sub-lists, and the header emission similarity corresponding to the header and the tail emission similarity corresponding to the tail of each of the three similarity sub-lists are selected; Calculate the absolute value of the similarity difference between the head emission similarity of each similarity sublist and the tail emission similarities corresponding to the other two similarity sublists, and determine whether the corresponding absolute value of the similarity difference is less than a preset difference. If so, the two similarity sublists corresponding to the absolute value of the similarity difference are lists of the same type, and merge the corresponding two similarity sublists into the same similarity sublist. If not, the two similarity sublists corresponding to the absolute value of the similarity difference are not lists of the same type. After all similarity sublists are judged, corresponding similarity sublists are obtained, potential pollution sources corresponding to each similarity sublist are identified, and potential pollution sources in the same similarity sublist are divided into the same potential pollution source set.

4. The comprehensive quantitative tracing method for karst groundwater pollution based on conventional water chemistry according to claim 3 is characterized by: The preset monitoring scheme matching strategy is: if the pollution level is level 1, the first pollution monitoring scheme is called; if the pollution level is level 2, the second pollution monitoring scheme is called; if the pollution level is level 3, the third pollution monitoring scheme is called.

5. The comprehensive quantitative tracing method for karst groundwater pollution based on conventional water chemistry according to claim 4 is characterized by: Also includes: S12, when the pollution level corresponding to the corresponding potential pollution source is determined at the current sampling time, the historical pollution level corresponding to the corresponding potential pollution source at the historical sampling time is retrieved from the historical database; S13. Calculate the pollution level change value of the corresponding potential pollution source based on the historical pollution level of the potential pollution source at the historical sampling time and the pollution level of the potential pollution source at the current sampling time. If the pollution level change value is greater than the preset change level threshold, switch the pollution level corresponding to the current sampling time to a higher pollution level, and call the pollution monitoring plan corresponding to the switched pollution level.

6. The comprehensive quantitative tracing method for karst groundwater pollution based on conventional water chemistry according to claim 1 is characterized by: The preset groundwater sampling point determination strategy is: According to the ground building data and the production and living data corresponding to each building, the area to be inspected is divided into functional areas, and the area to be inspected is divided into industrial sub-areas, agricultural sub-areas, living sub-areas and natural sub-areas; According to each sub-area in the area to be detected, the area corresponding to each sub-area is calculated, and based on the preset sampling point setting density, the total number of sampling points corresponding to each sub-area is calculated; Each sub-region is divided into a number of grids, and based on the total number of sampling points corresponding to each sub-region, the number of sampling points set in each grid of each sub-region is calculated, and the sampling points corresponding to the number of sampling points are randomly set on each grid in each sub-region to form a sampling point setting scheme corresponding to each sub-region, and N sampling point setting schemes corresponding to each sub-region are randomly generated; Based on the preset sampling point setting rationality calculation formula, the sampling point setting rationality corresponding to each sampling point setting scheme is calculated in turn, and a random number Q between 0 and 1 is randomly generated, and the sampling point setting rationality corresponding to each sampling point setting scheme is associated with the corresponding random number Q; Arrange the sampling points in descending order according to their rationality, and form a corresponding rationality arrangement table; According to the preset selection ratio, the random number Q associated with the rationality of all sampling point settings in the rationality arrangement table is judged. If the corresponding random number Q is greater than the preset random threshold, the sampling point setting scheme corresponding to the rationality of the sampling point setting associated with the random number is selected, and the number of the corresponding selected sampling point setting schemes is counted to see whether they meet the corresponding preset selection ratio. If not, the sampling point setting schemes are selected from the rationality arrangement table in descending order until the corresponding preset selection ratio is met. The calculation formula for the rationality of the preset sampling point setting is: Where L is the rationality of the sampling point setting, F is the sum of the distances from each sampling point in the sampling point setting scheme to the center point of the industrial sub-area, (x j ,y j ,k j ) is the position coordinate of a sampling point in the sampling point setting scheme, W1, W2 are the corresponding weighting coefficients; After the selection is completed, the selected sampling point setting schemes are randomly combined in pairs to form corresponding setting combinations, and a preset number of sampling points are randomly selected for exchange to obtain the corresponding new sampling point setting schemes. After the exchange of all sampling point setting schemes is completed, the sampling point setting rationality of the corresponding new sampling point setting scheme is recalculated until the corresponding number of repetitions meets the preset number of iterations. The sampling point setting scheme with the largest sampling point setting rationality at this time is used as the groundwater sampling point set of the corresponding sub-area.

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