Multi-dimensional parameter coupled water pollution traceability method, device, equipment and storage medium

Abstract

The present application relates to the technical field of water pollution source tracing, and discloses a multi-dimensional parameter coupled water pollution source tracing method, device, equipment and storage medium. In the method, the first similarity is obtained by using the water quality information of each pollution source water body corresponding to the water body to be traced, the second similarity is obtained by using the characteristic pollutant content information of each pollution source water body corresponding to the water body to be traced, and the third similarity is obtained by using the three-dimensional fluorescence data of each pollution source water body corresponding to the water body to be traced. Finally, the comprehensive similarity between the water body to be traced and each pollution source water body is obtained by using a comprehensive similarity evaluation method, which overcomes the defect that only the pollution degree can be macroscopically judged and the specific pollution source cannot be locked in the related art. Moreover, the accuracy and reliability of water pollution source tracing are greatly improved by using the complementary optimization of multi-dimensional parameter coupling, which provides strong technical support for accurate management and efficient control of water pollution.

Description

Technical Field

[0001] This invention relates to the field of water pollution source tracing technology, specifically to a multi-dimensional parameter coupled water pollution source tracing method, apparatus, equipment, and storage medium. Background Technology

[0002] With the increasing severity of water pollution, strengthening the monitoring and control of water pollution is a very challenging task. Pollutant source tracing is a crucial aspect of water environment supervision, generally referring to the process of locating the source of pollutants in rivers when water quality abnormalities occur. Only by effectively tracing pollutant sources can environmental supervision be carried out and pollution sources be cut off.

[0003] The water pollution source tracing methods disclosed in the related technologies include the detection and analysis of water quality indicators such as chemical oxygen demand (COD), total phosphorus (TP), total nitrogen (TN), and ammonia nitrogen (NH3-N) in the water body to be traced and the water body suspected of being a pollution source, so as to obtain the basic status of water pollution and the pollution area.

[0004] However, the water pollution source tracing methods disclosed in related technologies can only obtain the overall pollution situation of the water body. Many different types of pollution sources can cause changes in these water quality indicators. Therefore, the water pollution source tracing methods disclosed in related technologies are difficult to pinpoint specific pollution sources. Summary of the Invention

[0005] This invention provides a method, apparatus, equipment, and storage medium for tracing water pollution sources using multidimensional parameter coupling, in order to solve the problem that water pollution source tracing methods disclosed in related technologies are difficult to pinpoint specific pollution sources.

[0006] In a first aspect, the present invention provides a multi-dimensional parameter-coupled method for tracing water pollution sources, the method comprising: Based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, the first similarity evaluation method is used to obtain the first similarity between the water body to be traced and each pollution source water body; the first similarity is used to identify the type of conventional pollutant indicators. Based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, the second similarity evaluation method is used to obtain the second similarity between the water body to be traced and each pollution source water body; the second similarity is used to identify the industry of pollutant source. Based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies, the third similarity evaluation method is used to obtain the third similarity between the water body to be traced and each pollution source water body; the third similarity includes fluorescence intensity vector similarity and probability distribution similarity; By combining the first, second, and third similarities of the water body to be traced to each pollution source water body, and using the comprehensive similarity assessment method, the comprehensive similarity of the water body to be traced to each pollution source water body is obtained, and the pollution source water body with the highest comprehensive similarity is taken as the pollution source of the water body to be traced.

[0007] Through the above implementation method, a first similarity is obtained by using the water quality information of each pollution source water body corresponding to the water body to be traced, a second similarity is obtained by using the characteristic pollutant content information of each pollution source water body corresponding to the water body to be traced, and a third similarity is obtained by using the three-dimensional fluorescence data of each pollution source water body corresponding to the water body to be traced. Finally, the comprehensive similarity between the water body to be traced and each pollution source water body is obtained through a comprehensive similarity evaluation method. This overcomes the shortcomings of related technologies that can only macroscopically judge the degree of pollution and cannot pinpoint specific pollution sources. When faced with pollution sources with highly similar conventional water quality indicators and characteristic pollutants, by introducing three-dimensional fluorescence spectral depth analysis based on Pearson correlation coefficient and relative entropy and giving it a higher decision weight, the accurate identification of pollution source "fingerprint" information is achieved, providing strong technical support for the precise treatment and efficient management of water pollution.

[0008] In one optional implementation, the first similarity evaluation method is used to obtain the first similarity between the water body to be traced and each pollution source water body based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, including: Based on the water quality information of the water body to be traced, and combined with the water quality information of the clean water body, the difference between the water quality information of the water body to be traced and the water quality information of the clean water body is determined, and used as the water quality information vector of the water body to be traced; the water quality information includes chemical oxygen demand, total phosphorus, total nitrogen and ammonia nitrogen content; Based on the water quality information vector of the water body to be traced, and combined with the water quality information of each pollution source water body, the cosine similarity evaluation method is used to obtain the cosine similarity between the water body to be traced and each pollution source water body, and this cosine similarity is determined as the first similarity between the water body to be traced and each pollution source water body.

[0009] Through the above implementation method, the cosine similarity evaluation method is used to calculate the degree of matching between the water body to be traced and the water quality information of each pollution source water body in terms of chemical oxygen demand, total phosphorus, total nitrogen, and ammonia nitrogen. This information is then determined as the first similarity between the water body to be traced and each pollution source water body. This transforms macroscopic water quality data into targeted feature vectors, laying a precise data foundation for subsequent multi-dimensional parameter coupling water pollution source tracing analysis.

[0010] In one optional implementation, based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, the second similarity evaluation method is used to obtain the second similarity between the water body to be traced and each pollution source water body, including: Based on the characteristic pollutant content information of the water body to be traced, and combined with the characteristic pollutant content information of the clean water body, the difference between the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of the clean water body is obtained, and is used as the characteristic pollutant vector of the water body to be traced; the characteristic pollutant content information includes heavy metal characteristic pollutant content information or organic characteristic pollutant content information. Based on the characteristic pollutant vectors of the water bodies to be traced, and combined with the characteristic pollutant content information of each pollution source water body, the cosine similarity evaluation method is used to obtain the cosine similarity between the water bodies to be traced and each pollution source water body, and this cosine similarity is determined as the second similarity between the water bodies to be traced and each pollution source water body.

[0011] Through the above implementation method, the cosine similarity evaluation method is used to calculate the degree of matching between the water body to be traced and the heavy metal pollutant content information or organic pollutant content information of each pollution source water body, and this degree of matching is determined as the second similarity between the water body to be traced and each pollution source water body. By focusing on the content information of directional pollutants, the targeting and accuracy of matching pollution source water bodies are further improved, effectively solving the source tracing problem caused by the complex migration and transformation of pollutants and the ambiguity of the correspondence between pollution sources during the water pollution source tracing process.

[0012] In one optional implementation, the step of obtaining the third similarity between the water body to be traced and each pollution source water body using a third similarity evaluation method, based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies, includes: For each polluted water body, the three-dimensional fluorescence data is combined with the three-dimensional fluorescence data of the water body to be traced. Using the preprocessing method of removing Rayleigh scattering and Raman scattering and the matrix size calibration method, the three-dimensional fluorescence data matrix of the water body to be traced and the corresponding polluted water body is obtained. The horizontal axis of the three-dimensional fluorescence data matrix is ​​used to represent the emission wavelength, and its vertical axis is used to represent the excitation wavelength. Based on the fluorescence intensity data of each excitation wavelength in the three-dimensional fluorescence data matrix of the water body to be traced and each pollution source water body, the similarity of the fluorescence intensity vector of the water body to be traced relative to each pollution source water body at the corresponding excitation wavelength is obtained by using the Pearson correlation coefficient and normalization method. Based on the emission spectrum fluorescence intensity data at each excitation wavelength in the normalized three-dimensional fluorescence data matrix of the water body to be traced and each pollution source water body, the probability distribution similarity of the water body to be traced relative to each pollution source water body at the corresponding excitation wavelength is obtained by using the probability distribution and relative entropy transformation methods. By combining the similarity of fluorescence intensity vectors and probability distributions of the water body to be traced relative to each pollution source water body at multiple excitation wavelengths, and using the average value evaluation method, the third similarity between the water body to be traced and each pollution source water body is obtained.

[0013] Through the above implementation method, the scattering interference of the three-dimensional fluorescence data is first removed and the matrix size is calibrated to ensure the consistency of the three-dimensional fluorescence data matrix. Then, the similarity of the fluorescence intensity vector is calculated using the Pearson correlation coefficient. The similarity of the probability distribution is obtained by combining the probability distribution and the relative entropy transformation. Then, the fluorescence intensity vector similarity and the probability distribution similarity are used to characterize the fluorescence intensity distribution characteristics of the three-dimensional fluorescence data. Finally, the similarity results under multiple excitation wavelengths are integrated by the average value evaluation method to form a third similarity. This effectively solves the source tracing problem caused by the similarity or lack of obvious fluorescence characteristics of some industry pollution sources, and provides highly discriminative spectral data support for multi-parameter coupling analysis.

[0014] In one optional implementation, the similarity of the fluorescence intensity vector of the water body to be traced to any polluted source water body at any excitation wavelength includes: , , in, This represents the similarity of the fluorescence intensity vectors of the water body to be traced to any pollution source water body at the excitation wavelength j. The Pearson correlation coefficient represents the fluorescence intensity data of each pollution source water body corresponding to the water body to be traced at the excitation wavelength j; This represents the fluorescence intensity data of the water body to be traced at emission wavelength i and excitation wavelength j; This represents the fluorescence intensity data of the polluted water body at emission wavelength i and excitation wavelength j; This represents the average fluorescence intensity data at excitation wavelength j in the three-dimensional fluorescence spectral matrix of the water body to be traced. This represents the average fluorescence intensity data at excitation wavelength j in the three-dimensional fluorescence spectral matrix of the polluted water body. This indicates the total number of rows in the three-dimensional fluorescence spectral matrix.

[0015] Through the above implementation method, the linear correlation between the emission spectrum fluorescence intensity data of the water body to be traced and the polluted water body under the same excitation wavelength is quantified by the Pearson correlation coefficient. Then, the range of values ​​of the correlation coefficient is unified by the normalization formula to obtain an intuitively comparable fluorescence intensity vector similarity. This method not only preserves the correlation characteristics of the fluorescence spectrum data between the water body to be traced and the polluted water body, but also eliminates the interference of negative correlation values ​​on subsequent comprehensive calculations. At the same time, it provides accurate and standardized basic data for subsequent calculation of the overall similarity of three-dimensional fluorescence spectra by combining probability distribution similarity.

[0016] In one optional implementation, the probability distribution similarity of the water body to be traced to any polluted source water body at any excitation wavelength includes: , , in, This indicates the similarity of the probability distribution of each pollution source water body corresponding to the water body to be traced at the excitation wavelength j; The relative entropy represents the probability distribution of fluorescence intensity of the water body to be traced at excitation wavelength j relative to the probability distribution of fluorescence intensity of the polluted water body at excitation wavelength j. This represents the probability value of fluorescence intensity at emission wavelength i and excitation wavelength j for the water body to be traced. This represents the probability value of fluorescence intensity at emission wavelength i and excitation wavelength j in the polluted water body. This indicates the total number of rows in the three-dimensional fluorescence spectral matrix.

[0017] Through the above implementation method, relative entropy is used to measure the degree of difference in the probability distribution function of fluorescence intensity between the water body to be traced and the polluted water body under the same excitation wavelength. Then, the relative entropy is mapped through the transformation formula to obtain the probability distribution similarity. This supplements the linear correlation analysis of vector similarity from the distribution characteristics of fluorescence intensity probability distribution data, further improving the identification and accuracy of three-dimensional fluorescence spectral data for pollution source matching.

[0018] In one optional implementation, the comprehensive similarity assessment method is used to obtain the comprehensive similarity of the water body to be traced to each pollution source water body based on the first, second, and third similarities. The water body with the highest comprehensive similarity is then identified as the pollution source of the water body to be traced. This includes: Obtain the weight coefficients of the first similarity, second similarity, and third similarity for each pollution source water body corresponding to the water body to be traced; wherein, the weight coefficients are obtained based on pollution source samples from different watersheds and industries, and the weight coefficient of the third similarity is configured to be greater than the weight coefficients of the first similarity and the second similarity. Based on the aforementioned weighting coefficients, and combining the first, second, and third similarities of the water body to be traced to each pollution source water body, a weighted summation method is used to obtain the comprehensive similarity of the water body to be traced to each pollution source water body. By comparing the overall similarity values ​​of all water bodies to be traced to each pollution source water body, the pollution source water body with the highest value is identified as the pollution source of the water body to be traced.

[0019] Through the above implementation method, the obtained weight coefficients are used to match the actual source tracing value of the first similarity, second similarity and third similarity in the comprehensive evaluation. Then, the first similarity, second similarity and third similarity are integrated by weighted summation to obtain a comprehensive similarity that can fully reflect the degree of matching of pollution sources. Finally, by comparing the value of the comprehensive similarity, the pollution source water body with the highest similarity is determined. This fully leverages the advantages of multi-dimensional parameter complementary optimization in the water pollution source tracing process, and effectively improves the accuracy and reliability of water pollution source tracing.

[0020] Secondly, the present invention provides a multi-dimensional parameter-coupled water pollution tracing device, the device comprising: The first evaluation module is used to obtain the first similarity between the water body to be traced and each pollution source water body based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, respectively, using the first similarity evaluation method; the first similarity is used to identify the type of conventional pollutant indicators; The second evaluation module is used to obtain the second similarity between the water body to be traced and each pollution source water body based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, respectively, using the second similarity evaluation method; the second similarity is used to identify the industry of pollutant source. The third evaluation module is used to obtain the third similarity between the water body to be traced and each pollution source water body based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies using the third similarity evaluation method; the third similarity includes fluorescence intensity vector similarity and probability distribution similarity. The comprehensive evaluation module is used to comprehensively evaluate the first, second, and third similarities of the water body to be traced to each pollution source water body. Using the comprehensive similarity assessment method, the comprehensive similarity of the water body to be traced to each pollution source water body is obtained, and the pollution source water body with the highest comprehensive similarity is taken as the pollution source of the water body to be traced.

[0021] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the multidimensional parameter coupling water pollution tracing method described in the first aspect or any corresponding embodiment.

[0022] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the multidimensional parameter-coupled water pollution tracing method described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0023] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating the multidimensional parameter coupling water pollution source tracing method according to an embodiment of the present invention; Figure 2 This is a three-dimensional fluorescence data map of the water body to be traced and the polluted water body in the first embodiment of the multi-dimensional parameter coupling water pollution tracing method according to the present invention; Figure 3 This is a three-dimensional fluorescence data map of the water body to be traced and the polluted water body in the second embodiment of the multi-dimensional parameter coupling water pollution tracing method according to the present invention; Figure 4 This is a three-dimensional fluorescence data map of the water body to be traced and the polluted water body in the third embodiment of the multi-dimensional parameter coupling water pollution tracing method according to the present invention; Figure 5 This is a structural block diagram of a multi-dimensional parameter-coupled water pollution tracing device according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0027] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0028] The water pollution source tracing methods disclosed in related technologies include conventional water quality index tracing, characteristic pollutant tracing, and three-dimensional fluorescence spectroscopy tracing.

[0029] Conventional water quality indicators, such as chemical oxygen demand (COD), total phosphorus (TP), total nitrogen (TN), and ammonia nitrogen (NH3), can reflect the basic state of water pollution and the area of ​​pollution by detecting and analyzing these indicators. However, this method only presents the degree of water pollution at a macroscopic level and cannot delve into the specific information of pollution sources. This is because conventional water quality indicators reflect the overall pollution situation of the water body; many different types of pollution sources can cause changes in these indicators, lacking specific targeting and making it difficult to pinpoint the specific pollution source using these indicators.

[0030] To overcome the aforementioned shortcomings, this invention provides a multi-dimensional parameter coupling method for tracing water pollution sources. It obtains a first similarity score using water quality information corresponding to each pollution source body in the water body to be traced; a second similarity score using characteristic pollutant content information corresponding to each pollution source body; and a third similarity score using three-dimensional fluorescence data corresponding to each pollution source body. Finally, a comprehensive similarity assessment method is used to obtain the overall similarity score between the water body to be traced and each pollution source body. This overcomes the shortcomings of related technologies that can only macroscopically determine the degree of pollution and cannot pinpoint specific pollution sources. Furthermore, by utilizing complementary optimization through multi-dimensional parameter coupling, it significantly improves the accuracy and reliability of water pollution source tracing, providing strong technical support for precise treatment and efficient management of water pollution.

[0031] According to an embodiment of the present invention, a method for tracing water pollution sources using multidimensional parameter coupling is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0032] This embodiment provides a multi-dimensional parameter-coupled water pollution source tracing method, which can be used in water treatment server terminals. Figure 1 This is a flowchart of a multi-dimensional parameter-coupled water pollution source tracing method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: S101, based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, the first similarity evaluation method is used to obtain the first similarity of the water body to be traced for each pollution source water body; the first similarity is used to identify the type of conventional pollutant indicators.

[0033] The water body to be traced is the water body whose specific pollution source needs to be identified using the water pollution source tracing method disclosed in this application, such as polluted surface water, groundwater, and piped water.

[0034] Polluted water bodies refer to the sources of water pollution suspected of being caused by the discharge of pollutants, including industrial enterprise sewage outlets, agricultural sewage outlets, and domestic sewage discharge outlets.

[0035] The first similarity evaluation method uses chemical oxygen demand, total phosphorus, total nitrogen, and ammonia nitrogen as core indicators. It calculates the similarity of water quality information between the water body to be traced and the polluted water body, and uses the calculation results as the first similarity between the water body to be traced and each polluted water body.

[0036] S102, based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, the second similarity evaluation method is used to obtain the second similarity of the water body to be traced for each pollution source water body; the second similarity is used to identify the industry of pollutant source.

[0037] Characteristic pollutant content information refers to the content information of pollutants in water bodies that are industry-specific or pollution source-specific, including the content information of heavy metal characteristic pollutants and the content information of organic characteristic pollutants.

[0038] The second similarity evaluation method uses the content information of characteristic pollutants as the core indicator. It is an evaluation method that calculates the similarity of the content information of characteristic pollutants between the water body to be traced and the water body from the pollution source. The calculation results are used as the second similarity between the water body to be traced and each water body from the pollution source.

[0039] S103, based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies, the third similarity evaluation method is used to obtain the third similarity of the water body to be traced to each pollution source water body; the third similarity includes fluorescence intensity vector similarity and probability distribution similarity.

[0040] Three-dimensional fluorescence data is water fluorescence intensity data obtained through three-dimensional fluorescence spectroscopy, which is matrix data composed of three dimensions: excitation wavelength, emission wavelength, and fluorescence intensity.

[0041] The third similarity evaluation method is based on three-dimensional fluorescence data. It involves preprocessing the data, calculating the similarity of fluorescence intensity vectors and probability distributions, and then averaging the results to obtain the final evaluation. The calculated results are used as the third similarity between the water body to be traced and each pollution source water body.

[0042] S104. Based on the first, second, and third similarities of the water body to be traced to each pollution source water body, the comprehensive similarity assessment method is used to obtain the comprehensive similarity of the water body to be traced to each pollution source water body, and the pollution source water body with the highest comprehensive similarity is taken as the pollution source of the water body to be traced.

[0043] The comprehensive similarity assessment method integrates the first, second, and third similarities and performs a weighted sum to obtain the comprehensive similarity score.

[0044] The comprehensive similarity refers to the weighted sum of the first, second, and third similarities. The higher the value, the better the match between the polluted water body and the water body to be traced.

[0045] This embodiment provides a multi-dimensional parameter coupling method for tracing water pollution sources. It obtains a first similarity score using water quality information corresponding to each pollution source body in the water body to be traced; a second similarity score using characteristic pollutant content information corresponding to each pollution source body; and a third similarity score using three-dimensional fluorescence data corresponding to each pollution source body. Finally, a comprehensive similarity evaluation method is used to obtain the overall similarity score between the water body to be traced and each pollution source body. This overcomes the shortcomings of related technologies that can only macroscopically determine the degree of pollution and cannot pinpoint specific pollution sources. Furthermore, by utilizing the complementary optimization of multi-dimensional parameter coupling, it significantly improves the accuracy and reliability of water pollution source tracing, providing strong technical support for the precise treatment and efficient management of water pollution.

[0046] This embodiment provides a multi-dimensional parameter-coupled water pollution source tracing method, which can be used in a water treatment server terminal. The process includes the following steps: S201. Based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, the first similarity evaluation method is used to obtain the first similarity of the water body to be traced to each pollution source water body.

[0047] Specifically, S201 above includes: S2011, Based on the water quality information of the water body to be traced and combined with the water quality information of the clean water body, determine the difference between the water quality information of the water body to be traced and the water quality information of the clean water body, and use it as the water quality information vector of the water body to be traced; the water quality information includes chemical oxygen demand, total phosphorus, total nitrogen and ammonia nitrogen content; S2012, based on the water quality information vector of the water body to be traced, combined with the water quality information of each pollution source water body, the cosine similarity evaluation method is used to obtain the cosine similarity between the water body to be traced and each pollution source water body, and it is determined as the first similarity between the water body to be traced and each pollution source water body.

[0048] For example, the first similarity between the water body to be traced and each pollution source water body includes: , in, This indicates the first similarity between the water body to be traced and each pollution source water body; The first water body representing the source of pollution A water quality information vector; The first water body to be traced The first water quality information vector and the first clean water body The difference between the water quality information vectors.

[0049] By using the cosine similarity evaluation method, the degree of matching between the water body to be traced and the water quality information of each pollution source body in terms of chemical oxygen demand, total phosphorus, total nitrogen, and ammonia nitrogen is calculated and determined as the first similarity between the water body to be traced and each pollution source body. This transforms macroscopic water quality data into targeted feature vectors, laying a precise data foundation for subsequent multi-dimensional parameter coupling water pollution source tracing analysis.

[0050] S202, based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, the second similarity evaluation method is used to obtain the second similarity between the water body to be traced and each pollution source water body. For details, please refer to [link / reference]. Figure 1 S102 of the illustrated embodiment will not be described again here.

[0051] S203, based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies, uses the third similarity evaluation method to obtain the third similarity between the water body to be traced and each pollution source water body. For details, please refer to [link to relevant documentation]. Figure 1 S103 of the illustrated embodiment will not be described again here.

[0052] S204. Based on the first, second, and third similarities of the water body to be traced to each pollution source water body, a comprehensive similarity assessment method is used to obtain the comprehensive similarity score of the water body to be traced to each pollution source water body. The pollution source water body with the highest comprehensive similarity score is then identified as the pollution source of the water body to be traced. For details, please refer to [link to relevant documentation]. Figure 1 S104 of the illustrated embodiment will not be described again here.

[0053] This embodiment provides a multi-dimensional parameter coupling method for tracing water pollution sources. It obtains a first similarity score using water quality information corresponding to each pollution source body in the water body to be traced; a second similarity score using characteristic pollutant content information corresponding to each pollution source body; and a third similarity score using three-dimensional fluorescence data corresponding to each pollution source body. Finally, a comprehensive similarity evaluation method is used to obtain the overall similarity score between the water body to be traced and each pollution source body. This overcomes the shortcomings of related technologies that can only macroscopically determine the degree of pollution and cannot pinpoint specific pollution sources. Furthermore, by utilizing the complementary optimization of multi-dimensional parameter coupling, it significantly improves the accuracy and reliability of water pollution source tracing, providing strong technical support for the precise treatment and efficient management of water pollution.

[0054] This embodiment provides a multi-dimensional parameter-coupled water pollution source tracing method, which can be used in a water treatment server terminal. The process includes the following steps: S301, based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, the first similarity evaluation method is used to obtain the first similarity score between the water body to be traced and each pollution source water body. For details, please refer to [link / reference]. Figure 1 S101 of the illustrated embodiment will not be described again here.

[0055] S302, based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, the second similarity evaluation method is used to obtain the second similarity of the water body to be traced to each pollution source water body.

[0056] Specifically, S302 above includes: S3021, Based on the characteristic pollutant content information of the water body to be traced, and combined with the characteristic pollutant content information of the clean water body, the difference between the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of the clean water body is obtained, and used as the characteristic pollutant vector of the water body to be traced; the characteristic pollutant content information includes heavy metal characteristic pollutant content information or organic characteristic pollutant content information. S3022, Based on the characteristic pollutant vector of the water body to be traced, and combined with the characteristic pollutant content information of each pollution source water body, the cosine similarity evaluation method is used to obtain the cosine similarity between the water body to be traced and each pollution source water body, and it is determined as the second similarity between the water body to be traced and each pollution source water body.

[0057] The characteristic pollutants of the water body to be traced can be represented as those that are 1.5 times or more higher than the background value of the clean water body.

[0058] For example, the second similarity of the water body to be traced to each pollution source water body includes: , in, This indicates the second similarity between the water body to be traced and each pollution source water body; The first water body representing the source of pollution A vector of pollutant content characteristics; The first water body to be traced The vector of the content of the first characteristic pollutant and the first characteristic pollutant content in the clean water body The difference between the vectors of the content of each characteristic pollutant.

[0059] By using the cosine similarity evaluation method, the degree of matching between the water body to be traced and the heavy metal or organic pollutant content information of each pollution source water body is calculated and determined as the second similarity to represent the water body to be traced and each pollution source water body. By focusing on the content information of directional pollutants, the targeting and accuracy of matching pollution source water bodies are further improved, effectively solving the source tracing problem caused by the complex migration and transformation of pollutants and the ambiguity of the correspondence between pollution sources in the process of water pollution source tracing.

[0060] S303, based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies, uses the third similarity evaluation method to obtain the third similarity between the water body to be traced and each pollution source water body. For details, please refer to [link to relevant documentation]. Figure 1 S103 of the illustrated embodiment will not be described again here.

[0061] S304: Based on the first, second, and third similarities of the water body to be traced to each pollution source water body, a comprehensive similarity assessment method is used to obtain the comprehensive similarity score of the water body to be traced to each pollution source water body. The pollution source water body with the highest comprehensive similarity score is then identified as the pollution source of the water body to be traced. For details, please refer to [link to relevant documentation]. Figure 1 S104 of the illustrated embodiment will not be described again here.

[0062] This embodiment provides a multi-dimensional parameter coupling method for tracing water pollution sources. It obtains a first similarity score using water quality information corresponding to each pollution source body in the water body to be traced; a second similarity score using characteristic pollutant content information corresponding to each pollution source body; and a third similarity score using three-dimensional fluorescence data corresponding to each pollution source body. Finally, a comprehensive similarity evaluation method is used to obtain the overall similarity score between the water body to be traced and each pollution source body. This overcomes the shortcomings of related technologies that can only macroscopically determine the degree of pollution and cannot pinpoint specific pollution sources. Furthermore, by utilizing the complementary optimization of multi-dimensional parameter coupling, it significantly improves the accuracy and reliability of water pollution source tracing, providing strong technical support for the precise treatment and efficient management of water pollution.

[0063] This embodiment provides a multi-dimensional parameter-coupled water pollution source tracing method, which can be used in a water treatment server terminal. The process includes the following steps: S401, based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, the first similarity evaluation method is used to obtain the first similarity score between the water body to be traced and each pollution source water body. For details, please refer to [link / reference]. Figure 1 S101 of the illustrated embodiment will not be described again here.

[0064] S402, based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, the second similarity evaluation method is used to obtain the second similarity between the water body to be traced and each pollution source water body. For details, please refer to [link / reference]. Figure 1 S102 of the illustrated embodiment will not be described again here.

[0065] S403, based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies, the third similarity evaluation method is used to obtain the third similarity of the water body to be traced to each pollution source water body.

[0066] Specifically, S403 includes: S4031, for each polluted water body, the three-dimensional fluorescence data is combined with the three-dimensional fluorescence data of the water body to be traced. Using the preprocessing method of removing Rayleigh scattering and Raman scattering and the matrix size calibration method, a three-dimensional fluorescence data matrix of the water body to be traced and the corresponding polluted water body is obtained; the horizontal axis of the three-dimensional fluorescence data matrix is ​​used to represent the emission wavelength, and its vertical axis is used to represent the excitation wavelength.

[0067] Because the three-dimensional fluorescence spectral matrices obtained from different instruments or different batches differ in the range and step size of excitation and emission wavelengths, direct calculations between three-dimensional fluorescence data matrices are not possible. Therefore, matrix size calibration of the three-dimensional fluorescence data of the water body to be traced is required.

[0068] For example, the matrix size calibration method can be implemented as spline interpolation, uniformly interpolating all the three-dimensional fluorescence data matrices to be compared to a preset standard matrix size. For instance, the excitation wavelength range is unified to 200nm-450nm, with an interval of 5nm; the emission wavelength range is unified to 250nm-600nm, with an interval of 2nm. After calibration, all data matrices of the water bodies to be traced and the polluted water bodies have the same number of rows and columns. The horizontal row is represented by i, and the total number is set to m, which is used to represent the emission wavelength. The vertical column is represented by j, and the total number is set to n, which is used to represent the excitation wavelength. Then, the value in the i-th row and j-th column represents the fluorescence intensity data under the emission wavelength i and the excitation wavelength j, which can ensure the accuracy of subsequent calculations.

[0069] S4032, based on the fluorescence intensity data of each excitation wavelength in the three-dimensional fluorescence data matrix of the water body to be traced and each pollution source water body, the similarity of the fluorescence intensity vector of each pollution source water body at the corresponding excitation wavelength is obtained by using the Pearson correlation coefficient and normalization method.

[0070] For example, the similarity of the fluorescence intensity vector of the water body to be traced to any pollution source water body at any excitation wavelength in S4032 above includes: , , in, This represents the similarity of the fluorescence intensity vectors of the water body to be traced to any pollution source water body at the excitation wavelength j. The Pearson correlation coefficient represents the fluorescence intensity data of each pollution source water body corresponding to the water body to be traced at the excitation wavelength j; This represents the fluorescence intensity data of the water body to be traced at emission wavelength i and excitation wavelength j; This represents the fluorescence intensity data of the polluted water body at emission wavelength i and excitation wavelength j; This represents the average fluorescence intensity data at excitation wavelength j in the three-dimensional fluorescence spectral matrix of the water body to be traced. This represents the average fluorescence intensity data at excitation wavelength j in the three-dimensional fluorescence spectral matrix of the polluted water body. This indicates the total number of rows in the three-dimensional fluorescence spectral matrix.

[0071] The linear correlation between the emission spectral fluorescence intensity data of the water body to be traced and the polluted water body under the same excitation wavelength is quantified by Pearson correlation coefficient. Then, the range of values ​​of the correlation coefficient is unified by normalization formula to obtain an intuitive and comparable vector similarity. This not only preserves the correlation characteristics of the fluorescence spectral data between the water body to be traced and the polluted water body, but also eliminates the interference of negative correlation values ​​on subsequent comprehensive calculations. At the same time, it provides accurate and standardized basic data for subsequent calculation of the overall similarity of three-dimensional fluorescence spectra by combining probability distribution similarity.

[0072] S4033, based on the emission spectrum fluorescence intensity data of each excitation wavelength in the normalized three-dimensional fluorescence data matrix of the water body to be traced and each pollution source water body, the probability distribution similarity of each pollution source water body at the corresponding excitation wavelength is obtained by using the probability distribution and relative entropy transformation method.

[0073] For example, the probability distribution similarity of the water body to be traced to any pollution source water body under any excitation wavelength in S4033 above includes: , , in, This indicates the similarity of the probability distribution of each pollution source water body corresponding to the water body to be traced at the excitation wavelength j; The relative entropy represents the probability distribution of fluorescence intensity of the water body to be traced at excitation wavelength j relative to the probability distribution of fluorescence intensity of the polluted water body at excitation wavelength j. This represents the probability value of fluorescence intensity at emission wavelength i and excitation wavelength j for the water body to be traced. This represents the probability value of fluorescence intensity at emission wavelength i and excitation wavelength j in the polluted water body. This indicates the total number of rows in the three-dimensional fluorescence spectral matrix.

[0074] The relative entropy is used to measure the difference in the probability distribution function of fluorescence intensity between the water body to be traced and the polluted water body under the same excitation wavelength. The relative entropy is then mapped through a transformation formula to obtain the probability distribution similarity. This supplements the linear correlation analysis of vector similarity from the perspective of the distribution characteristics of fluorescence intensity probability distribution data, further improving the identification and accuracy of three-dimensional fluorescence spectral data for pollution source matching.

[0075] S4034, combining the similarity of fluorescence intensity vectors and probability distributions of each pollutant source water body corresponding to the water body to be traced under multiple excitation wavelengths, and using the average value evaluation method, the third similarity of each pollutant source water body corresponding to the water body to be traced is obtained.

[0076] For example, the third similarity of the water body to be traced in S4034 above to each pollution source water body includes: , in, This indicates the third similarity between the water body to be traced and each pollution source water body; This represents the vector similarity of the j-th excitation wavelength for each pollutant water body to be traced. denoted by , represents the probability distribution similarity of the j-th group of excitation wavelengths for each pollutant source water body to be traced; n represents the number of columns in the three-dimensional fluorescence spectral matrix.

[0077] S404: Based on the first, second, and third similarities of the water body to be traced to each pollution source water body, a comprehensive similarity assessment method is used to obtain the comprehensive similarity score of the water body to be traced to each pollution source water body. The pollution source water body with the highest comprehensive similarity score is then identified as the pollution source of the water body to be traced. For details, please refer to [link to relevant documentation]. Figure 1 S104 of the illustrated embodiment will not be described again here.

[0078] This embodiment provides a multi-dimensional parameter coupling method for tracing water pollution sources. It obtains a first similarity score using water quality information corresponding to each pollution source body in the water body to be traced; a second similarity score using characteristic pollutant content information corresponding to each pollution source body; and a third similarity score using three-dimensional fluorescence data corresponding to each pollution source body. Finally, a comprehensive similarity evaluation method is used to obtain the overall similarity score between the water body to be traced and each pollution source body. This overcomes the shortcomings of related technologies that can only macroscopically determine the degree of pollution and cannot pinpoint specific pollution sources. Furthermore, by utilizing the complementary optimization of multi-dimensional parameter coupling, it significantly improves the accuracy and reliability of water pollution source tracing, providing strong technical support for the precise treatment and efficient management of water pollution.

[0079] This embodiment provides a multi-dimensional parameter-coupled water pollution source tracing method, which can be used in a water treatment server terminal. The process includes the following steps: S501, based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, the first similarity evaluation method is used to obtain the first similarity score between the water body to be traced and each pollution source water body. For details, please refer to [link to relevant documentation]. Figure 1 S101 of the illustrated embodiment will not be described again here.

[0080] S502, based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, the second similarity evaluation method is used to obtain the second similarity between the water body to be traced and each pollution source water body. For details, please refer to [link / reference]. Figure 1 S102 of the illustrated embodiment will not be described again here.

[0081] S503, based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies, uses the third similarity evaluation method to obtain the third similarity between the water body to be traced and each pollution source water body. For details, please refer to [link to relevant documentation]. Figure 1 S103 of the illustrated embodiment will not be described again here.

[0082] S504. By combining the first, second, and third similarities of the water body to be traced to each pollution source water body, and using the comprehensive similarity assessment method, the comprehensive similarity of the water body to be traced to each pollution source water body is obtained, and the pollution source water body with the highest comprehensive similarity is taken as the pollution source of the water body to be traced.

[0083] Specifically, the aforementioned S504 includes: S5041, obtain the weight coefficients of the first similarity, second similarity and third similarity of each pollution source water body corresponding to the water body to be traced; wherein, the weight coefficients are obtained based on pollution source samples from different watersheds and industries, and the weight coefficient of the third similarity is configured to be greater than the weight coefficients of the first similarity and the second similarity.

[0084] The weight coefficients for the first, second, and third similarities are weight coefficients trained using pollution source samples from different watersheds, regions, and industries.

[0085] Optionally, by training machine learning on a large amount of pollution source sample data, it can be found that when three-dimensional fluorescence spectral data has higher identifiability in water pollution source tracing, the weight coefficient of the third similarity should be given a higher weight.

[0086] For example, the weighting coefficient can be set as: the weighting coefficient of the first similarity. The weighting coefficient of the second similarity Weighting coefficients for the third similarity And satisfy This preferred range is based on extensive experimental data and can achieve the best traceability results in most scenarios.

[0087] S5042, based on the weighting coefficients, and combining the first similarity, second similarity, and third similarity of the water body to be traced to each pollution source water body, a weighted summation method is used to obtain the comprehensive similarity of the water body to be traced to each pollution source water body.

[0088] For example, the comprehensive similarity of the water body to be traced to each pollution source water body includes: , in: The weighting coefficient represents the first similarity between the water body to be traced and each pollution source water body; This represents the weighting coefficient of the second similarity between the water body to be traced and each pollution source water body; This represents the weighting coefficient indicating the first similarity between the water body to be traced and each pollution source water body.

[0089] S5043. Compare the comprehensive similarity values ​​of all water bodies to be traced to each pollution source water body, and obtain the pollution source water body with the highest value, which is determined to be the pollution source of the water body to be traced.

[0090] By utilizing the obtained weight coefficients and matching the actual source tracing value of the first, second, and third similarities in the comprehensive evaluation, and then integrating the first, second, and third similarities through weighted summation, a comprehensive similarity that can fully reflect the degree of matching of pollution sources is obtained. Finally, by comparing the magnitude of the comprehensive similarity values, the pollution source water body with the highest similarity is determined. This fully leverages the advantages of multi-dimensional parameter complementary optimization in the water pollution source tracing process, effectively improving the accuracy and reliability of water pollution source tracing.

[0091] This embodiment provides a multi-dimensional parameter coupling method for tracing water pollution sources. It obtains a first similarity score using water quality information corresponding to each pollution source body in the water body to be traced; a second similarity score using characteristic pollutant content information corresponding to each pollution source body; and a third similarity score using three-dimensional fluorescence data corresponding to each pollution source body. Finally, a comprehensive similarity evaluation method is used to obtain the overall similarity score between the water body to be traced and each pollution source body. This overcomes the shortcomings of related technologies that can only macroscopically determine the degree of pollution and cannot pinpoint specific pollution sources. Furthermore, by utilizing the complementary optimization of multi-dimensional parameter coupling, it significantly improves the accuracy and reliability of water pollution source tracing, providing strong technical support for the precise treatment and efficient management of water pollution.

[0092] For example, refer to Table 1 and Figure 2 As shown, Table 1 is used to represent the water quality information and characteristic pollutant content information between the water body to be traced and the polluted source water body. Figure 2 Three-dimensional fluorescence data maps used to represent the water body to be traced and the polluted water body, among which Figure 2 The horizontal axis represents the emission wavelength, denoted by Em, and the vertical axis represents the excitation wavelength, denoted by Ex.

[0093] Table 1. Water quality information and characteristic pollutant content information between the water body to be traced and the polluted source water body.

[0094] S1(X1)=0.9998, S1(X2)=0.9989, a=0.05; S2(X1)=0.9791, S2(X2)=0.9706, b=0.10; S3(X1)=0.6626, S3(X2)=0.5604, c=0.85; In summary, S(X1) = 0.7111 and S(X2) = 0.6233, indicating that the water pollution to be traced in this embodiment is caused by the enterprise corresponding to the polluted water body X1.

[0095] For example, refer to Table 2 and Figure 3As shown, Table 2 is used to represent the water quality information and characteristic pollutant content information between the water body to be traced and the polluted source water body. Figure 3 Three-dimensional fluorescence data maps used to represent the water body to be traced and the polluted water body, among which Figure 3 The horizontal axis represents the emission wavelength, denoted by Em, and the vertical axis represents the excitation wavelength, denoted by Ex.

[0096] Table 2. Water quality information and characteristic pollutant content information between the water body to be traced and the polluted source water body.

[0097] S1(Y1)=0.9998, S1(Y2)=0.9998, a=0.00; S2(Y1)=0.9806, S2(Y2)=0.9732, b=0.10; S3(Y1)=0.7109, S3(Y2)=0.5306, c=0.90; In summary, S(Y1) = 0.7379 and S(Y2) = 0.5749, indicating that the water pollution to be traced in this embodiment is caused by the enterprise corresponding to the polluted water body Y1.

[0098] For example, refer to Table 3 and Figure 4 As shown, Table 3 is used to represent the water quality information and characteristic pollutant content information between the water body to be traced and the polluted source water body. Figure 4 Three-dimensional fluorescence data maps used to represent the water body to be traced and the polluted water body, among which Figure 4 The horizontal axis represents the emission wavelength, denoted by Em, and the vertical axis represents the excitation wavelength, denoted by Ex.

[0099] Table 3. Water quality information and characteristic pollutant content information between the water body to be traced and the polluted source water body.

[0100] S1(Z1)=0.8137, S1(Z2)=0.8817, a=0.10; S2(Z1)=0.9989, S2(Z2)=0.5369, b=0.30; S3(Z1)=0.9973, S3(Z2)=0.9970, c=0.60; In summary, S(Z1) = 0.8876 and S(Z2) = 0.7898, indicating that the water pollution to be traced in this embodiment is caused by the enterprise corresponding to the polluted water body Z1.

[0101] To verify the effectiveness of the multidimensional parameter coupling method described in this invention, three control methods were set up in this experiment to identify pollution sources in the water bodies to be traced in the aforementioned Examples 1-3, and the identification accuracy was statistically analyzed.

[0102] Comparison Method 1 (Single Water Quality Index Method): Only the first similarity (S1) is used as the judgment criterion, and the pollution source with the highest S1 value is selected as the result.

[0103] Comparison Method 2 (Single Characteristic Pollutant Method): Only the second similarity (S2) is used as the judgment criterion, and the pollution source with the highest S2 value is selected as the result.

[0104] Compare with Method 3 (simple weighted average method): S1, S2, and S3 are weighted equally (a=b=c=1 / 3) and summed, and the pollution source with the highest comprehensive value is selected as the result.

[0105] The method of this invention: weighted summation is performed using the preferred weighting coefficients (a=0.05, b=0.10, c=0.85) in the embodiments.

[0106] Blind testing was conducted on 50 groups of water samples from known pollution sources, including those from the aforementioned embodiments. The results are shown in the table below:

[0107] Results Analysis: The comparative data shows that when pollution sources are highly similar in terms of conventional water quality indicators (such as Y1 and Y2 in Table 2), a single method is insufficient to distinguish them. However, this invention significantly improves the identification accuracy by assigning higher weights to three-dimensional fluorescence data and employing an analysis method that combines vector similarity and probability distribution similarity.

[0108] This embodiment also provides a multi-dimensional parameter-coupled water pollution tracing device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0109] This embodiment provides a multi-dimensional parameter-coupled water pollution source tracing device, such as... Figure 5 As shown, the device includes: The first evaluation module 510 is used to obtain the first similarity between the water body to be traced and each pollution source water body based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, respectively, using the first similarity evaluation method; the first similarity is used to identify the type of conventional pollutant indicators. The second evaluation module 520 is used to obtain the second similarity between the water body to be traced and each pollution source water body based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, respectively, using the second similarity evaluation method; the second similarity is used to identify the industry of pollutant source. The third evaluation module 530 is used to obtain the third similarity between the water body to be traced and each pollution source water body based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies using the third similarity evaluation method; the third similarity includes fluorescence intensity vector similarity and probability distribution similarity. The comprehensive evaluation module 540 is used to comprehensively evaluate the first, second, and third similarities of the water body to be traced to each pollution source water body. Using the comprehensive similarity evaluation method, the comprehensive similarity of the water body to be traced to each pollution source water body is obtained, and the pollution source water body with the highest comprehensive similarity is taken as the pollution source of the water body to be traced.

[0110] In some optional implementations, the first evaluation module 510 is specifically used for: Based on the water quality information of the water body to be traced, and combined with the water quality information of the clean water body, the difference between the water quality information of the water body to be traced and the water quality information of the clean water body is determined, and used as the water quality information vector of the water body to be traced; the water quality information includes chemical oxygen demand, total phosphorus, total nitrogen and ammonia nitrogen content; Based on the water quality information vector of the water body to be traced, and combined with the water quality information of each polluted sample water body, the cosine similarity evaluation method is used to obtain the cosine similarity between the water body to be traced and each polluted source water body, and this cosine similarity is determined as the first similarity between the water body to be traced and each polluted source water body.

[0111] In some optional implementations, the second evaluation module 520 is specifically used for: Based on the characteristic pollutant content information of the water body to be traced, and combined with the characteristic pollutant content information of the clean water body, the difference between the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of the clean water body is obtained, and is used as the characteristic pollutant vector of the water body to be traced; the characteristic pollutant content information includes heavy metal characteristic pollutant content information or organic characteristic pollutant content information. Based on the characteristic pollutant vectors of the water bodies to be traced, and combined with the characteristic pollutant content information of each pollution source water body, the cosine similarity evaluation method is used to obtain the cosine similarity between the water bodies to be traced and each pollution source water body, and this cosine similarity is determined as the second similarity between the water bodies to be traced and each pollution source water body.

[0112] In some optional implementations, the third evaluation module 530 is specifically used for: For each polluted water body, the three-dimensional fluorescence data is combined with the three-dimensional fluorescence data of the water body to be traced. Using the preprocessing method of removing Rayleigh scattering and Raman scattering and the matrix size calibration method, the three-dimensional fluorescence data matrix of the water body to be traced and the corresponding polluted water body is obtained. The horizontal axis of the three-dimensional fluorescence data matrix is ​​used to represent the emission wavelength, and its vertical axis is used to represent the excitation wavelength. Based on the fluorescence intensity data of each excitation wavelength in the three-dimensional fluorescence data matrix of the water body to be traced and each pollution source water body, the similarity of the fluorescence intensity vector of the water body to be traced relative to each pollution source water body at the corresponding excitation wavelength is obtained by using the Pearson correlation coefficient and normalization method. Based on the emission spectrum fluorescence intensity data at each excitation wavelength in the normalized three-dimensional fluorescence data matrix of the water body to be traced and each pollution source water body, the probability distribution similarity of the water body to be traced relative to each pollution source water body at the corresponding excitation wavelength is obtained by using the probability distribution and relative entropy transformation methods. By combining the similarity of fluorescence intensity vectors and probability distributions of the water body to be traced relative to each pollution source water body at multiple excitation wavelengths, and using the average value evaluation method, the third similarity between the water body to be traced and each pollution source water body is obtained.

[0113] In some optional implementations, the fluorescence intensity vector similarity between the water body to be traced and any polluted source water body at any excitation wavelength in the third evaluation module 530 includes: , , in, This represents the similarity of the fluorescence intensity vectors of the water body to be traced to any pollution source water body at the excitation wavelength j. The Pearson correlation coefficient represents the fluorescence intensity data of each pollution source water body corresponding to the water body to be traced at the excitation wavelength j; This represents the fluorescence intensity data of the water body to be traced at emission wavelength i and excitation wavelength j; This represents the fluorescence intensity data of the polluted water body at emission wavelength i and excitation wavelength j; This represents the average fluorescence intensity data at excitation wavelength j in the three-dimensional fluorescence spectral matrix of the water body to be traced. This represents the average fluorescence intensity data at excitation wavelength j in the three-dimensional fluorescence spectral matrix of the polluted water body. This indicates the total number of rows in the three-dimensional fluorescence spectral matrix.

[0114] In some optional implementations, the probability distribution similarity of the water body to be traced to any polluted source water body at any excitation wavelength in the third evaluation module 530 includes: , , in, This indicates the similarity of the probability distribution of each pollution source water body corresponding to the water body to be traced at the excitation wavelength j; The relative entropy represents the probability distribution of fluorescence intensity of the water body to be traced at excitation wavelength j relative to the probability distribution of fluorescence intensity of the polluted water body at excitation wavelength j. This represents the probability value of fluorescence intensity at emission wavelength i and excitation wavelength j for the water body to be traced. This represents the probability value of fluorescence intensity at emission wavelength i and excitation wavelength j in the polluted water body. This indicates the total number of rows in the three-dimensional fluorescence spectral matrix.

[0115] In some optional implementations, the comprehensive evaluation module 540 is specifically used for: Obtain the weight coefficients of the first similarity, second similarity, and third similarity for each pollution source water body corresponding to the water body to be traced; wherein, the weight coefficients are obtained based on pollution source samples from different watersheds and industries, and the weight coefficient of the third similarity is configured to be greater than the weight coefficients of the first similarity and the second similarity. Based on the aforementioned weighting coefficients, and combining the first, second, and third similarities of the water body to be traced to each pollution source water body, a weighted summation method is used to obtain the comprehensive similarity of the water body to be traced to each pollution source water body. By comparing the overall similarity values ​​of all water bodies to be traced to each pollution source water body, the pollution source water body with the highest value is identified as the pollution source of the water body to be traced.

[0116] The multi-dimensional parameter-coupled water pollution tracing device provided in this embodiment of the invention can execute the multi-dimensional parameter-coupled water pollution tracing method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0117] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0118] The following is a detailed reference. Figure 6This diagram illustrates a suitable structural design for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 601, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 602 or a program loaded from memory 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for the operation of the electronic device. The processor 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0119] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0120] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a memory 608, or installed from a ROM 602. When the computer program is executed by the processor 601, it performs the functions defined in the multidimensional parameter-coupled water pollution tracing method of the embodiments of the present invention.

[0121] Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention.

[0122] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the multi-dimensional parameter-coupled water pollution source tracing method shown in the above embodiments is implemented.

[0123] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0124] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A multi-dimensional parameter-coupled method for tracing water pollution sources, characterized in that, The method includes: Based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, the first similarity evaluation method is used to obtain the first similarity between the water body to be traced and each pollution source water body; the first similarity is used to identify the type of conventional pollutant indicators. Based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, the second similarity evaluation method is used to obtain the second similarity between the water body to be traced and each pollution source water body; the second similarity is used to identify the industry of pollutant source. Based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies, the third similarity evaluation method is used to obtain the third similarity between the water body to be traced and each pollution source water body; the third similarity includes fluorescence intensity vector similarity and probability distribution similarity; Specifically, based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies, a third similarity evaluation method is used to obtain the third similarity between the water body to be traced and each pollution source water body, including: For each polluted water body, the three-dimensional fluorescence data is combined with the three-dimensional fluorescence data of the water body to be traced. A preprocessing method to remove Rayleigh and Raman scattering lines and a matrix size calibration method are used to obtain a three-dimensional fluorescence data matrix of the water body to be traced and the corresponding polluted water body. The horizontal axis of the three-dimensional fluorescence data matrix represents the emission wavelength, and the vertical axis represents the excitation wavelength. The matrix size calibration method uses spline interpolation to unify the excitation wavelength range to 200nm-450nm with a 5nm interval, and the emission wavelength range to 250nm-600nm with a 2nm interval. Based on the fluorescence intensity data of each excitation wavelength in the three-dimensional fluorescence data matrix of the water body to be traced and each pollution source water body, the similarity of the fluorescence intensity vector of the water body to be traced relative to each pollution source water body at the corresponding excitation wavelength is obtained by using the Pearson correlation coefficient and normalization method. Based on the emission spectrum fluorescence intensity data at each excitation wavelength in the normalized three-dimensional fluorescence data matrix of the water body to be traced and each pollution source water body, the probability distribution similarity of the water body to be traced relative to each pollution source water body at the corresponding excitation wavelength is obtained by using the probability distribution and relative entropy transformation methods. By combining the similarity of fluorescence intensity vectors and probability distributions of the water body to be traced relative to each pollution source water body at multiple excitation wavelengths, the third similarity of the water body to be traced relative to each pollution source water body is obtained using the average value evaluation method. By combining the first, second, and third similarities of the water body to be traced to each pollution source water body, a comprehensive similarity assessment method is used to obtain the comprehensive similarity of the water body to be traced to each pollution source water body, and the pollution source water body with the highest comprehensive similarity is identified as the pollution source of the water body to be traced. The weight coefficients of the first, second, and third similarities in the comprehensive similarity assessment method are obtained by training based on pollution source samples from different watersheds, regions, and industries, and the weight coefficient of the third similarity is configured to be greater than the weight coefficients of the first and second similarities.

2. The method according to claim 1, characterized in that, Based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, the first similarity evaluation method is used to obtain the first similarity between the water body to be traced and each pollution source water body, including: Based on the water quality information of the water body to be traced, and combined with the water quality information of the clean water body, the difference between the water quality information of the water body to be traced and the water quality information of the clean water body is determined, and used as the water quality information vector of the water body to be traced; the water quality information includes chemical oxygen demand, total phosphorus, total nitrogen and ammonia nitrogen content; Based on the water quality information vector of the water body to be traced, and combined with the water quality information of each polluted sample water body, the cosine similarity evaluation method is used to obtain the cosine similarity between the water body to be traced and each polluted source water body, and this cosine similarity is determined as the first similarity between the water body to be traced and each polluted source water body.

3. The method according to claim 1, characterized in that, Based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, the second similarity evaluation method is used to obtain the second similarity between the water body to be traced and each pollution source water body, including: Based on the characteristic pollutant content information of the water body to be traced, and combined with the characteristic pollutant content information of the clean water body, the difference between the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of the clean water body is obtained, and is used as the characteristic pollutant vector of the water body to be traced; the characteristic pollutant content information includes heavy metal characteristic pollutant content information or organic characteristic pollutant content information. Based on the characteristic pollutant vectors of the water bodies to be traced, and combined with the characteristic pollutant content information of each pollution source water body, the cosine similarity evaluation method is used to obtain the cosine similarity between the water bodies to be traced and each pollution source water body, and this cosine similarity is determined as the second similarity between the water bodies to be traced and each pollution source water body.

4. The method according to claim 1, characterized in that, The similarity of the fluorescence intensity vector of the water body to be traced to any pollution source water body at any excitation wavelength includes: ， ， in, This represents the similarity of the fluorescence intensity vectors of the water body to be traced to any pollution source water body at the excitation wavelength j. The Pearson correlation coefficient represents the fluorescence intensity data of each pollution source water body corresponding to the water body to be traced at the excitation wavelength j; This represents the fluorescence intensity data of the water body to be traced at emission wavelength i and excitation wavelength j; This represents the fluorescence intensity data of the polluted water body at emission wavelength i and excitation wavelength j; This represents the average fluorescence intensity data at excitation wavelength j in the three-dimensional fluorescence spectral matrix of the water body to be traced. This represents the average fluorescence intensity data at excitation wavelength j in the three-dimensional fluorescence spectral matrix of the polluted water body. This indicates the total number of rows in the three-dimensional fluorescence spectroscopy matrix.

5. The method according to claim 1, characterized in that, The similarity of the probability distribution of the water body to be traced to any pollution source water body at any excitation wavelength includes: ， ， in, This indicates the similarity of the probability distribution of each pollution source water body corresponding to the water body to be traced at the excitation wavelength j; The relative entropy represents the probability distribution of fluorescence intensity of the water body to be traced at excitation wavelength j relative to the probability distribution of fluorescence intensity of the polluted water body at excitation wavelength j. This represents the probability value of fluorescence intensity at emission wavelength i and excitation wavelength j for the water body to be traced. This represents the probability value of fluorescence intensity at emission wavelength i and excitation wavelength j in the polluted water body. This indicates the total number of rows in the three-dimensional fluorescence spectroscopy matrix.

6. The method according to any one of claims 1 to 5, characterized in that, The first, second, and third similarities of the water body to be traced to each pollution source water body are used to obtain the comprehensive similarity assessment method for the water body to be traced to each pollution source water body. The pollution source water body with the highest comprehensive similarity is identified as the pollution source of the water body to be traced, including: Obtain the weight coefficients of the first similarity, second similarity, and third similarity for each pollution source water body corresponding to the water body to be traced; wherein, the weight coefficients are obtained based on pollution source samples from different watersheds and industries, and the weight coefficient of the third similarity is configured to be greater than the weight coefficients of the first similarity and the second similarity. Based on the aforementioned weighting coefficients, and combining the first, second, and third similarities of the water body to be traced to each pollution source water body, a weighted summation method is used to obtain the comprehensive similarity of the water body to be traced to each pollution source water body. By comparing the overall similarity values ​​of all water bodies to be traced to each pollution source water body, the pollution source water body with the highest value is identified as the pollution source of the water body to be traced.

7. A multi-dimensional parameter-coupled water pollution source tracing device, characterized in that, The device includes: The first evaluation module is used to obtain the first similarity between the water body to be traced and each pollution source water body based on the water quality information of the water body to be traced and the water quality information of multiple pollution source water bodies, respectively, using the first similarity evaluation method; the first similarity is used to identify the type of conventional pollutant indicators; The second evaluation module is used to obtain the second similarity between the water body to be traced and each pollution source water body based on the characteristic pollutant content information of the water body to be traced and the characteristic pollutant content information of multiple pollution source water bodies, respectively, using the second similarity evaluation method; the second similarity is used to identify the industry of pollutant source. The third evaluation module is used to obtain the third similarity between the water body to be traced and each pollution source water body based on the three-dimensional fluorescence data of the water body to be traced and the three-dimensional fluorescence data of multiple pollution source water bodies using the third similarity evaluation method; the third similarity includes fluorescence intensity vector similarity and probability distribution similarity. The third evaluation module is specifically used for: For each polluted water body, the three-dimensional fluorescence data is combined with the three-dimensional fluorescence data of the water body to be traced. A preprocessing method to remove Rayleigh and Raman scattering lines and a matrix size calibration method are used to obtain a three-dimensional fluorescence data matrix of the water body to be traced and the corresponding polluted water body. The horizontal axis of the three-dimensional fluorescence data matrix represents the emission wavelength, and the vertical axis represents the excitation wavelength. The matrix size calibration method uses spline interpolation to unify the excitation wavelength range to 200nm-450nm with a 5nm interval, and the emission wavelength range to 250nm-600nm with a 2nm interval. Based on the fluorescence intensity data of each excitation wavelength in the three-dimensional fluorescence data matrix of the water body to be traced and each pollution source water body, the similarity of the fluorescence intensity vector of the water body to be traced relative to each pollution source water body at the corresponding excitation wavelength is obtained by using the Pearson correlation coefficient and normalization method. Based on the emission spectrum fluorescence intensity data at each excitation wavelength in the normalized three-dimensional fluorescence data matrix of the water body to be traced and each pollution source water body, the probability distribution similarity of the water body to be traced relative to each pollution source water body at the corresponding excitation wavelength is obtained by using the probability distribution and relative entropy transformation methods. By combining the similarity of fluorescence intensity vectors and probability distributions of the water body to be traced relative to each pollution source water body at multiple excitation wavelengths, the third similarity of the water body to be traced relative to each pollution source water body is obtained using the average value evaluation method. The comprehensive evaluation module is used to comprehensively evaluate the first, second, and third similarities of the water body to be traced against each pollution source water body. Using a comprehensive similarity assessment method, the comprehensive similarity of the water body to be traced against each pollution source water body is obtained, and the pollution source water body with the highest comprehensive similarity is identified as the pollution source of the water body to be traced. The weight coefficients of the first, second, and third similarities in the comprehensive similarity assessment method are obtained by training based on pollution source samples from different watersheds, regions, and industries, and the weight coefficient of the third similarity is configured to be greater than the weight coefficients of the first and second similarities.

8. An electronic device, characterized in that, include: A memory and a processor are interconnected, the memory stores computer instructions, and the processor executes the computer instructions to perform the multidimensional parameter-coupled water pollution tracing method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the multidimensional parameter-coupled water pollution tracing method according to any one of claims 1 to 6.

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