A source tracing method, system, and medium for water pollution at monitoring sections in river basins.

Abstract

This invention belongs to the field of water pollution source tracing technology, and specifically relates to a source tracing method for water pollution at monitoring sections in river basins. The method includes collecting seven types of basic data, such as industrial and agricultural sources; screening out exceeding pollution standards and corresponding catchment area pollution sources through standardized preprocessing; constructing standardized topological relationships between four types of pollution sources, discharge channels, and exceeding pollution standards, and marking pollution sources without topological relationships; calculating the correlation between nodes based on topological type differences, and calculating spatial correlation for nodes without topological relationships; designing differentiated methods to calculate relative emissions for industrial, agricultural, and domestic sources; combining correlation and relative emissions to calculate a comprehensive correlation, and outputting the source tracing results after sorting. This invention solves the problems of existing water pollution source tracing technologies, such as the lack of systematic topological relationships, biased calculation dimensions, and inaccurate results.

Description

Technical Field

[0001] This invention belongs to the field of water pollution source tracing technology, and in particular relates to a source tracing method, system and medium for water pollution at monitoring sections of river basins. Background Technology

[0002] Current watershed water environment management has entered a new stage of refined management. National and local governments have successively issued relevant plans for water ecological environment protection, clearly requiring improved accuracy and timeliness in tracing water pollution sources, providing scientific and technical support for comprehensive watershed pollution control and water quality improvement. Taking key river basins within Chongqing Municipality involving national and municipal monitoring sections as an example, the complex distribution of water systems and diverse pollution sources, including widespread industrial, domestic, and agricultural sources with significantly different emission characteristics, places higher demands on the standardization, systematization, and precision of water pollution source tracing.

[0003] In the current watershed water pollution source tracing technology and its application, there are still many core issues that urgently need to be addressed, which directly affect the accuracy and practicality of the source tracing results. Specifically, these issues include: First, the topological relationship of the sewage discharge channels between pollution sources and monitoring sections has not been systematically constructed, and there is a lack of standardized logical association of "pollution source-pipeline network-sewage treatment plant-sewage discharge outlet into river-monitoring section", which makes it impossible to trace the pollution discharge path step by step. Second, source tracing calculations lack unified quantitative rules. Source tracing indicators such as spatial distance, water quality characteristics, and temporal changes have not formed standardized calculation and normalization methods, and source tracing results in different scenarios are not comparable. Third, the methods for calculating the emissions of pollution sources are not uniform. Differentiated accounting schemes have not been designed based on the availability of monitoring data for different pollution sources such as industry, agriculture, and domestic sources, making it difficult to accurately reflect the actual emission contributions of various pollution sources. Fourth, the source tracing is based on a single dimension, relying solely on spatial distance or a single water quality indicator for judgment. It does not integrate multi-dimensional information such as water pollution type, temporal variation similarity, and flow water quality characteristics, which can easily lead to biased source tracing results and make it impossible to accurately locate suspected pollution sources. Fifth, the source tracing methods in scenarios where topological relationships are missing are incomplete. There are no pollution sources with clear sewage discharge channels associated with them, and there is a lack of scientific spatial correlation quantification methods, resulting in low credibility of the source tracing results for this type of pollution source. Summary of the Invention

[0004] The technical problem solved by this invention is to provide a method, system and medium for tracing the source of water pollution at monitoring sections of river basins, so as to solve the problems of lack of systematic topological relationships, source tracing calculation dimensions and bias in the existing water pollution source tracing technology.

[0005] The basic solution provided by this invention is a source tracing method for water pollution at monitoring sections in river basins, comprising: S1: Collect basic data of the target river basin; the basic data includes industrial source data, agricultural source data, domestic source data, river network data, stormwater and sewage pipe network data of key industrial parks, sewage outlet data into the river, and cross-sectional water quality data; S2: Preprocess the basic data, statistically analyze the water quality exceeding the standard data in the basic data, and obtain the information of the exceeding sections corresponding to the water quality exceeding the standard data; S3: Based on the information of water pollution sources within the cross-sections exceeding the standards, construct the topological relationship of the water pollution sources; S4: For water pollution sources with established topological relationships, calculate the correlation between each associated topological node; for water pollution sources without established topological relationships, calculate the correlation between the exceeding section and the water pollution source; and obtain the relative emission of each water pollution source. S5: Calculate the comprehensive correlation based on the relative discharge of each water pollution source and the results of each correlation, and sort the water pollutants in the corresponding catchment area of ​​the exceeding section according to the magnitude of the comprehensive correlation, and output the comprehensive source tracing results.

[0006] Furthermore, S2 includes: S2-1: Obtain basic data for the target river basin; classify and standardize the structured data and vector layer spatial data in the basic data; verify and supplement the static data in the basic data; and finally establish a standardized basic database. S2-2: The core water quality factors for assessing the water environment quality of the target river basin are used as indicators for judging whether the water quality exceeds the standard; the water quality monitoring data of each monitoring section of the pre-processed basic data are extracted, and the threshold for judging whether each water quality factor exceeds the standard is divided according to the water environment functional zone of each monitoring section. S2-3: Perform threshold comparison on the water quality factors of the water quality monitoring data of each monitoring section one by one. If the monitoring value of a water quality factor is greater than the defined threshold for exceeding the standard, the water quality monitoring data is determined to be exceeding the standard; thus obtaining preliminary information on the exceeding sections. S2-4: Based on the statistical judgment results of S2-3, extract the full correlation information of the preliminary exceeding section information from the preprocessed standardized basic database, including basic section information, exceeding section characteristic information and section spatial correlation information, to form a standardized exceeding section information set; S2-5: Structure and integrate all the information sets of sections exceeding the standard to establish a database of information on sections exceeding the standard.

[0007] Furthermore, S3 includes: S3-1: Extract the catchment area from the spatial correlation information of the cross-sections exceeding the standard, and combine it with the preprocessed river network vector layer and the spatial location data of water pollution sources. Through spatial geographic overlay analysis, screen out the water pollution sources within the catchment area corresponding to the cross-sections exceeding the standard. S3-2: Integrate pipeline network data, river discharge outlet data, sewage treatment plant space and discharge connection data, and river network topology data within the catchment area of ​​the substandard section to establish a unified spatial coordinate system; S3-3: Extract pipeline nodes, pipeline junctions, and monitoring nodes from pipeline network data; extract river discharge outlets associated with exceeding standards from river discharge outlet data; extract sewage treatment plants from sewage treatment plant space and discharge connection data. S3-4: Using water pollution sources as upstream starting nodes, exceeding standard sections as downstream terminal nodes, and the objects extracted in S3-3 as intermediate nodes, a standardized topological relationship is constructed. S3-5: For water pollution sources within the catchment area of ​​the substandard section, where there is no connection between the sewage channel and the substandard section, it is characterized as having no topological relationship.

[0008] Furthermore, in S3-4, the standardized topological relations include four types of topological relations, namely: Type I topological relationship: Water pollution source Rainwater and sewage pipe network sewage treatment plant Sewage outlets into rivers Sections exceeding the standard; Second type of topological relationship: Water pollution source sewage treatment plant Sewage outlets into rivers Sections exceeding the standard; Third type of topological relationship: Water pollution source Sewage outlets into rivers Sections exceeding the standard; Fourth type of topological relationship: Water pollution source Rainwater and sewage pipe network Sewage outlets into rivers Sections exceeding the standard.

[0009] Furthermore, S4 includes: S4-1: Obtain four types of topological relationships, and extract the correlation between nodes based on the actual connected nodes in the topological relationships, following reverse tracing logic; including cross-section-outlet correlation. Outlet-pipeline correlation Discharge outlet-pollution source correlation Pipeline network-pollution source correlation ; S4-2: For water pollution sources without topological relationships, directly calculate the correlation between the exceeding section and the water pollution source. The expression is:

[0010] in, Let be the actual straight-line spatial distance between the i-th topologically unrelated water pollution source and the cross-section exceeding the standard. The maximum straight-line spatial distance between all topologically unrelated water pollution sources within the catchment area of ​​the section exceeding the standard; It represents the minimum spatial straight-line distance between all topologically unrelated water pollution sources within the catchment area of ​​the section exceeding the standard. Values ​​normalized to interval; S4-3: Classify water pollution sources into industrial, domestic, and agricultural sources, and calculate the relative emissions from industrial and domestic sources. Relative emissions from livestock and poultry farming in agricultural sources Relative emissions from aquaculture in agricultural sources Relative emissions from agricultural planting in agricultural sources .

[0011] Furthermore, in S4-1, the cross-section-outlet correlation... Based on the normalized value of the distance along the river between the exceeding section and the sewage outlet, and combined with the special scenario of exceeding the standard in the monitoring data of the sewage outlet and matching characteristic water quality factors, a default value is set, specifically: In typical scenarios, , The normalized value is the distance along the river between the section exceeding the standard and the sewage outlet into the river; In special scenarios where monitoring data from sewage discharge outlets into rivers exceeds standards, and where the sewage discharge outlets and the sections exceeding standards share the same water quality factors, it is determined that... ; Outlet-pipeline correlation Based on the correlation of water pollution type Correlation between flow rate and water quality Temporal variation similarity Pipeline distance correlation The sum of the four sub-indicators, normalized to a value of 100%. Interval; where: Correlation of water pollution types The water quality of sewage outlets and stormwater / sewage pipe networks is uniformly classified into four types: domestic sewage, livestock and poultry farming, urban non-point source pollution, agricultural non-point source pollution, construction disturbance pollution, industrial pollution, and ordinary stormwater pollution. The classification is based on the ratio of water quality factor concentrations to their relative change rates. If the two types of water pollution are the same, then... If they are inconsistent, then a judgment will be made. ; Flow rate and water quality correlation The summation of three sub-indicators—flow correlation, turbidity correlation, and conductivity correlation—between the sewage outfall and the stormwater and sewage pipe network nodes. Temporal variation similarity To ensure consistency of the trends in monitoring data of core water quality factors at river discharge outlets and stormwater / sewage pipe network nodes over time, based on the DTW algorithm; Pipeline distance correlation Based on the normalized value of the cumulative pipeline length of sewage outfalls and stormwater / sewage pipe network nodes. To take a value; Discharge outlet-pollution source correlation Normalized value based on the actual connection distance between sewage outfalls and water pollution sources For taking values, that is If the water pollution source and the sewage outlet into the river have the same water quality factors, then it is directly determined that... ; Pipeline network-pollution source correlation Based on the normalized value of the cumulative pipeline length of stormwater and sewage pipe networks and water pollution sources For taking values, that is .

[0012] Furthermore, S4-3 calculates the relative emissions from industrial and residential sources. Specifically: The relative discharge from industrial and domestic wastewater treatment plants is calculated in order of priority based on online monitoring data, electricity consumption data, and discharge permits, and an enterprise activity level index is introduced to characterize the production and operation status. Relative emissions from livestock and poultry farming in agricultural sources The annual pollution load is estimated using an output coefficient model and then converted to a daily average value. The expression is as follows:

[0013] in, Let t be the total number of livestock and poultry raised under the j-th farming model within the region; Let be the pollutant discharge coefficient of the t-th livestock and poultry under the j-th farming model. The number of species of livestock and poultry raised; Relative emissions from aquaculture in agricultural sources The annual pollution load is estimated using the input-output method and then converted to a daily average value. The expression is as follows:

[0014] in, , Let t represent the output and input of the t-th aquaculture category under the j-th aquaculture model; Let be the pollutant discharge coefficient of the t-th aquaculture species under the j-th aquaculture model. For the number of breeding models, For the number of aquaculture species; Relative emissions from agricultural planting in agricultural sources To estimate the annual value of nitrogen and phosphorus loss from surface runoff, and then convert it to a daily average, the expression is:

[0015] in, Let the nitrogen / phosphorus input be the amount of nitrogen / phosphorus entering the field under the j-th planting pattern. Let be the nitrogen / phosphorus loss coefficient under the j-th planting pattern. This refers to the number of planting patterns.

[0016] Furthermore, S5 includes: S5-1: Based on the different correlations in the topological relationship types, the weighted sum is multiplied by the corresponding relative emissions of water pollution sources to obtain the comprehensive correlation. S5-2: For water pollution sources for which no topological relationship has been established, the comprehensive correlation is obtained by multiplying the correlation between the exceeding section and the water pollution source by the relative discharge of the corresponding water pollution source. S5-3: Integrate the comprehensive correlation of all water pollution sources within the catchment area of ​​the section exceeding the standard, sort them according to the magnitude of the comprehensive correlation, and obtain the comprehensive source tracing results.

[0017] A source tracing system for water pollution at monitoring sections in river basins, applied to the aforementioned source tracing method for water pollution at monitoring sections in river basins, includes a data acquisition module, a preprocessing module, a topology module, a data processing module, and a source tracing result generation module, wherein: The data acquisition module is used to collect basic data of the target river basin; the basic data includes industrial source data, agricultural source data, domestic source data, river network data, key park stormwater and sewage pipe network data, sewage outlet data into the river, and cross-sectional water quality data; The preprocessing module is used to preprocess the basic data, count the water quality exceeding the standard data in the basic data, and obtain the information of the exceeding section corresponding to the water quality exceeding the standard data. The topology module is used to construct the topological relationships of water pollution sources within the cross-section information of exceeding the standard; The data processing module is used to calculate the correlation between nodes of each associated topological node for water pollution sources with established topological relationships; to calculate the correlation between the exceeding section and the water pollution source for water pollution sources without established topological relationships; and to obtain the relative emission of each water pollution source. The source tracing result generation module is used to calculate the comprehensive correlation based on the relative emissions of each water pollution source and the various correlation results, and to sort the water pollutants in the corresponding catchment area of ​​the exceeding section according to the magnitude of the comprehensive correlation, and output the comprehensive source tracing result.

[0018] A computer-readable storage medium storing a program or instructions that causes a computer to perform a source tracing method for water pollution at a monitoring section in a river basin, as described above.

[0019] The principle and advantages of this invention are as follows: The technical solution of this application takes the monitoring section exceeding the standard as the core and constructs a complete logical system of water pollution source-discharge channel-exceeding section to achieve accurate source tracing of water pollution. The specific process is as follows: First, seven categories of basic data are collected, including industrial sources, agricultural sources, domestic sources, river networks, pipe networks, sewage outlets into rivers, and section water quality. After standardized preprocessing, all water pollution sources in the exceeding section and the corresponding catchment area are screened to provide a standardized data source for source tracing calculation. Then, based on the actual pollution discharge path, four types of standardized topological relationships are constructed, and pollution sources without clear discharge channels are marked to form a classification source tracing basis of "with topology / without topology". Subsequently, for pollution sources with topological relationships, the correlation between nodes is calculated differently according to the topological type, including cross-section-outlet, outlet-pipeline, pipeline-pollution source, or outlet-pollution source. The DTW algorithm is introduced to calculate the water quality time series similarity, and distance normalization is used to calculate the spatial correlation. For pollution sources without topological relationships, the spatial correlation is directly calculated to achieve accurate quantification of the correlation degree. Then, combined with the availability of data for different pollution sources, a differentiated relative emission accounting method is designed. Finally, a corresponding comprehensive correlation calculation model is constructed based on the topological type. The pollution contribution is quantified by weighting / productting correlation and relative emission. After sorting, a source tracing list is output to complete accurate source tracing.

[0020] The advantages are: 1. Solving the problem of "lack of topological relationship between pollution source and monitoring section, making it impossible to trace the source step by step": By constructing four types of standardized topological relationships, the hierarchical connectivity logic of "pollution source-pipeline network-sewage treatment plant-sewage discharge outlet into river-exceeding section" is clarified. At the same time, pollution sources without topological relationships are marked, realizing "step-by-step tracing with topology and direct association without topology", filling the source tracing gap in the scenario of missing topological relationships and ensuring that the source tracing logic is consistent with the actual sewage discharge path; 2. To address the problem of "lack of unified rules for calculating source tracing relevance, resulting in incomparable results": Establish a standardized relevance calculation system, including distance normalization formulas, DTW time series similarity algorithms, and water pollution type classification rules, to unify the range of relevance values ​​for various types, enabling the relevance of different scenarios and different pollution sources to be compared and quantified, thereby improving the objectivity of source tracing results; 3. Solve the problem of "insufficient integration of multi-dimensional traceability indicators and large traceability deviation": integrate multi-dimensional indicators such as spatial distance, water quality characteristics, temporal changes, flow and turbidity to calculate correlation, avoid omissions and misjudgments caused by single indicator judgment, and significantly improve the accuracy of traceability results; 4. To address the problem of "inconsistent accounting for pollution source emissions, which fails to reflect actual contributions": Differentiated accounting methods are designed based on the emission characteristics of industrial, domestic, and agricultural sources (livestock / aquaculture / planting). The enterprise activity level index is used to characterize the production status, ensuring that the relative emission calculation is accurate and providing reasonable weights for comprehensive correlation calculation. 5. Solve the problem of "vague source tracing results that cannot guide precise governance": By comprehensively measuring the pollution contribution of relevant metrics, a standardized source tracing list is output in descending order of values. This clarifies the contribution priority, excess contribution factor, and confidence level of each pollution source, directly providing precise targets for pollution control, achieving "targeted governance," and improving the efficiency of comprehensive watershed water pollution control. Attached Figure Description

[0021] Figure 1 This is a flowchart of an embodiment of the present invention; Figure 2 This is a functional block diagram of an embodiment of the present invention. Detailed Implementation

[0022] The following detailed description illustrates the specific implementation method: The basic implementation examples are as follows: Figure 1 As shown: A source tracing method for water pollution at monitoring sections in a river basin, comprising: S1: Collect basic data for the target river basin; the basic data includes industrial source data, agricultural source data, domestic source data, river network data, stormwater and sewage pipe network data of key industrial parks, sewage outlet data into the river, and cross-sectional water quality data; in this embodiment, the detailed categories, data items, data fields, time resolution, and data types of the collected basic data are shown in Table 1 below: Table 1 Basic Data Information Table

[0023] During the collection of the above seven categories of basic data, standardized data formats are used for storage. Structured data and vector layer data are classified and managed. At the same time, a data collection and update mechanism is established, with static data being updated dynamically as needed and dynamic monitoring data being automatically collected synchronously at a predetermined time resolution. This ensures the integrity, accuracy, timeliness, and standardization of the basic data, meeting the calculation needs of the entire subsequent water pollution source tracing process.

[0024] S2: Preprocess the basic data, statistically analyze the water quality exceedance data in the basic data, and obtain the information of the exceeding sections corresponding to the water quality exceedance data; wherein, S2 includes: S2-1: Obtain basic data for the target river basin, classify and standardize the structured data and vector layer spatial data in the basic data; verify and supplement the static data in the basic data; finally, establish a standardized basic database; in this embodiment, for structured data, such as online monitoring data of various pollution sources, production electricity consumption data, monitoring data of sewage outlets into the river, and cross-sectional water quality monitoring data, the following processing is adopted: 1. Outlier cleanup: Remove zero and negative values ​​from the data that have no physical meaning. Outliers in the monitoring data should be identified and removed in principle; for water quality monitoring data of outlets, cross-sections, and pipeline nodes, invalid monitoring values ​​caused by equipment failure or human operation should be removed simultaneously. 2. Missing value imputation: For time series monitoring data with a small number of missing values, linear interpolation is used for imputation; for data with a missing value ratio exceeding [a certain percentage], [the imputation is performed]. Single-indicator monitoring data are marked as invalid data and stored separately, and are not included in subsequent calculations; 3. Duplicate value removal: Based on the data collection time, monitoring points, and monitoring indicator dimensions, redundant data that has been collected repeatedly is removed; 4. Unified time resolution: The time resolution of all dynamic monitoring data is unified to daily resolution. For hourly and 4-hourly high-frequency monitoring data, the daily average is calculated using the arithmetic mean method. If higher-precision power data is subsequently acquired, the time resolution can be simultaneously adjusted to the 4-hour resolution that matches the cross-sectional water quality monitoring to ensure data time sequence consistency.

[0025] For vector layer data, such as spatial vector layer data of river networks, pipe networks, sewage outfalls into rivers, monitoring sections, and pollution sources, perform the following processing: 1. Coordinate System 1: The geographic coordinate system of all spatial data is the National Geodetic Coordinate System 2000, and the projected coordinate system is matched with the standard projection of the target river basin area to ensure the accuracy of spatial location matching; 2. Layer Topology Validation: Perform topology error validation on the river network and pipeline network vector layers, correcting issues such as overlapping nodes, broken line features, and overlapping polygon features in the layers to ensure the accuracy of spatial topology relationships; 3. Attribute information completion: For key attribute information missing in the spatial layer (such as sewage outlet type, pipe diameter, monitoring section number, and pollution source industry type), complete it by combining on-site verification data or data filed with the competent authority.

[0026] For static basic data, such as enterprise entity information, pollutant discharge permit verification information, sewage treatment plant treatment capacity, and agricultural source breeding / planting parameters, the completeness and validity of the information are verified, data sources with missing key information are marked, and the information is supplemented and improved by connecting with the competent authority's platform. Finally, a standardized basic database is established, and all preprocessed data is stored in categories according to "data type - monitoring point - time dimension" to support rapid retrieval for subsequent source tracing calculations.

[0027] S2-2: The core water quality factors for assessing the water environment quality of the target river basin are used as indicators for determining exceedances; water quality monitoring data of each monitoring section are extracted from the pre-processed basic data, and exceedance thresholds for each water quality factor are determined according to the water environment functional zones of each monitoring section; in this embodiment, the core water quality factors first include chemical oxygen demand (COD), ammonia nitrogen (COD), and nitrogen dioxide (COD). Total phosphorus (TP), total nitrogen (TN), and watershed-specific pollutants such as antimony, thallium, manganese, and biotoxicity are used as indicators for determining whether a pollutant exceeds the standard. Subsequently, based on the water environment functional zoning categories of each monitoring section, including The class is matched with the corresponding limit value of the "Surface Water Environmental Quality Standard" as the threshold for judging whether each water quality factor exceeds the standard; S2-3: For each monitoring section, the water quality factors of the water quality monitoring data are compared against the threshold. If the monitored value of a water quality factor is greater than the defined threshold for exceeding the standard, the water quality monitoring data is determined to be exceeding the standard. Preliminary information on exceeding the standard sections is obtained. In this embodiment, when the monitoring data is determined to be exceeding the standard, the exceeding factor, the exceeding monitoring value, the exceeding multiple, and the data collection date are recorded simultaneously. The exceeding data are classified and statistically analyzed to form a "Statistical Table of Exceeding Standard Water Quality Data of Sections", which includes core information such as section number, exceeding date, exceeding factor, monitoring value, threshold, and exceeding multiple.

[0028] S2-4: Based on the statistical judgment results of S2-3, extract the full-volume correlation information of the preliminary exceeding section information from the preprocessed standardized basic database, including basic section information, exceeding section characteristic information, and spatial correlation information of the section, forming a standardized exceeding section information set; In this embodiment, the basic section information includes the unique number, name, spatial latitude and longitude coordinates, water environment functional zoning category, water quality monitoring frequency, routine monitoring factors, characteristic monitoring factors, administrative region and water system to which the monitoring point belongs; the exceeding section characteristic information includes the exceeding date, the type and number of exceeding water quality factors, the monitoring value, threshold, and exceeding multiple of each exceeding factor, as well as the temporal change trend of the exceeding factors (such as single exceeding or continuous multi-day exceeding); the spatial correlation information of the section includes the catchment area corresponding to the exceeding section (based on the analysis results of the catchment area based on the river network vector map layer), the main stream / tributary attributes of the river where the exceeding section is located, the distribution range of sewage outlets into the river within a certain range upstream and downstream of the section, and the distribution boundary of pollution sources around the section.

[0029] S2-5: Structure and integrate all the information sets of the sections exceeding the standard to establish a database of information on the sections exceeding the standard. The database supports searching and filtering by dimensions such as section number, date of exceeding the standard, and factor of exceeding the standard, to ensure that subsequent steps can quickly retrieve the full information of the sections exceeding the standard and carry out topological relationship construction and pollution source correlation calculation.

[0030] S3: Based on the information of water pollution sources within the cross-sections exceeding the standards, construct the topological relationships of the water pollution sources; wherein, S3 includes: S3-1: Extract the catchment area from the spatial correlation information of the cross-sections exceeding the standard, and combine it with the preprocessed river network vector layer and spatial location data of water pollution sources. Through spatial geographic overlay analysis, screen out the water pollution sources within the catchment area corresponding to the cross-sections exceeding the standard. In this embodiment, the screening rules and implementation requirements are as follows: 1. Using the catchment area of ​​the river where the pollution-affected section is located as the core boundary, a spatial vector intersection algorithm is used to overlay and match the spatial location data of industrial, agricultural, and domestic pollution sources with the vector map layer of the catchment area of ​​the pollution-affected section, thus filtering out all water pollution sources whose spatial location is within the catchment area. The process of the spatial vector intersection algorithm is as follows: First, the feature layers are loaded by loading the vector map layer of water pollution sources and the vector map layer of the catchment area of ​​the pollution-affected section into the GIS spatial analysis engine, and a second verification of the spatial coordinates of the layers is completed to ensure that there is no coordinate offset; then, a point-by-point spatial search is performed, using the vector features of the catchment area of ​​the pollution-affected section as the search boundary, and performing a point search on each point feature in the vector map layer of water pollution sources. The system performs a spatial location search, calling the GIS spatial analysis interface for determining if a point is within a polygon. Then, it uses spatial coordinate calculations to determine if the latitude and longitude coordinates of a point feature are within the closed polygon boundary of a polygon feature. This calculation relies on the spatial topology calculation capabilities of the GIS engine to automatically identify the boundary node coordinates and polygon topology of the polygon feature, comparing the spatial positional relationship between the point feature coordinates and the polygon feature boundary. Finally, it assigns a result value to each water pollution source point feature: if the point feature falls within the catchment area polygon feature, it is assigned a value of "match successful" and associated with the corresponding exceeding section's identification information; if the point feature is outside the catchment area polygon feature, it is assigned a value of "match failed" and is not included in subsequent source tracing calculations.

[0031] 2. The screened water pollution sources are classified and labeled according to type, namely industrial sources, agricultural sources (livestock and poultry breeding, aquaculture, and agricultural planting), and domestic sources (sewage treatment plants and scattered domestic pollution sources in urban / rural areas). A list of water pollution sources in the catchment area of ​​the exceeding section is established. The list includes core information such as the unique identifier of the pollution source, type, spatial coordinates, discharge method, and emission characteristic factors. 3. Conduct a preliminary assessment of the correlation of sewage discharge channels for the water pollution sources in the list, and mark the sewage discharge path type of each pollution source (such as discharge through the pipeline network, discharge after treatment by the sewage treatment plant, direct discharge into the river, etc.) to provide a basic classification basis for subsequent topological relationship construction.

[0032] S3-2: Integrate pipeline network data, river discharge outlet data, sewage treatment plant space and discharge connection data, and river network topology data within the catchment area of ​​the substandard section to establish a unified spatial coordinate system; S3-3: Extract pipeline nodes, pipeline junctions, and monitoring nodes from pipeline network data; extract river discharge outlets associated with exceeding standards from river discharge outlet data; extract sewage treatment plants from sewage treatment plant space and discharge connection data. S3-4: Using the water pollution source as the upstream starting node, the exceeding section as the downstream terminal node, and the objects extracted in S3-3 as intermediate nodes, a standardized topological relationship is constructed. In this embodiment, the core construction logic of the topological relationship is based on the actual flow direction of pollution discharge, following the flow principle of "upstream node to downstream node, pollution source to discharge outlet, and discharge outlet to exceeding section". The standardized topological relationship constructed in this application includes four types of topological relationships, namely: Type I topological relationship: Water pollution source Rainwater and sewage pipe network sewage treatment plant Sewage outlets into rivers Sections exceeding the standard; It is applicable to the collection of rainwater and sewage pipe networks in industrial parks / towns, which are then transported to sewage treatment plants for treatment. The effluent is discharged into rivers through sewage outlets and eventually flows to the water pollution source at the section exceeding the standard. When constructing the system, the specific route of the pipe network, the treatment process of the sewage treatment plant, and the water system connection relationship between the sewage outlet and the section exceeding the standard should be clearly defined. Second type of topological relationship: Water pollution source sewage treatment plant Sewage outlets into rivers Sections exceeding the standard; It is suitable for situations where sewage is directly discharged into a sewage treatment plant for treatment without the need for pipe network collection, and the effluent is discharged into the river through the sewage outlet and flows to the water pollution source at the section exceeding the standard. When constructing the system, the direct sewage discharge connection method between the pollution source and the sewage treatment plant, as well as the riverside location relationship between the sewage outlet and the section exceeding the standard should be clearly defined. Third type of topological relationship: Water pollution source Sewage outlets into rivers Sections exceeding the standard; It is applicable to the process of sewage treatment without pipe network and sewage treatment plant, where sewage is directly discharged into the river through the sewage outlet and flows to the water pollution source of the exceeding section (such as some industrial sources and agricultural sources that directly enter the river). When constructing, the sewage outlet's discharge destination, the distance along the river from the exceeding section, and the water system connection should be clearly defined. Fourth type of topological relationship: Water pollution source Rainwater and sewage pipe network Sewage outlets into rivers Sections exceeding the standard; This method is applicable to water pollution sources that are collected by rainwater and sewage pipe networks but are discharged directly into rivers through sewage outlets without being treated by sewage treatment plants, and flow to sections exceeding the standards. When constructing the system, the catchment area of ​​the pipe network, the connection nodes between the pipe network and the sewage outlet, and the water system connectivity between the sewage outlet and the section exceeding the standards should be clearly defined.

[0033] After the above four types of topological relationships are constructed, each topological relationship is assigned a unique identifier, and the connection attributes between each node are recorded, such as pipeline length, sewage outlet type, sewage treatment plant treatment capacity, etc., forming a topological relationship table of exceeding standard section-water pollution source. The table contains core content such as topological relationship identifier, pollution source information, intermediate node information, exceeding standard section information, node connection attributes, and pollution discharge flow direction.

[0034] S3-5: For water pollution sources within the catchment area of ​​the substandard section, where there is no connection between the sewage channel and the substandard section, it is characterized as having no topological relationship.

[0035] S4: For water pollution sources with established topological relationships, calculate the correlation between each associated topological node; for water pollution sources without established topological relationships, calculate the correlation between the exceeding section and the water pollution source; and obtain the relative emission of each water pollution source; wherein, S4 includes: S4-1: Obtain four types of topological relationships, and extract the correlation between nodes based on the actual connected nodes in the topological relationships, following reverse tracing logic; including cross-section-outlet correlation. Outlet-pipeline correlation Discharge outlet-pollution source correlation Pipeline network-pollution source correlation ;in: Cross-section-outlet correlation Based on the normalized value of the distance along the river between the exceeding section and the sewage outlet, and combined with the special scenario of exceeding the standard in the monitoring data of the sewage outlet and matching characteristic water quality factors, a default value is set, specifically: In typical scenarios, , The normalized value of the distance along the river between the section exceeding the standard and the sewage outlet into the river; where:

[0036] in, Let be the actual riverside distance between the i-th sewage outlet into the river and the section exceeding the standard; This represents the maximum distance along the river from all associated sewage outlets upstream of the section exceeding the standard. It is the minimum distance along the river from all associated sewage outlets flowing into the river upstream of the section exceeding the standard; In special scenarios where monitoring data from sewage discharge outlets into rivers exceeds standards, and where the sewage discharge outlets and the sections exceeding standards share the same water quality factors, such as antimony, thallium, manganese, and biotoxicity, the determination is made... ; Outlet-pipeline correlation Based on the correlation of water pollution type Correlation between flow rate and water quality Temporal variation similarity Pipeline distance correlation The sum of the four sub-indicators, normalized to a value of 100%. Interval; where: Correlation of water pollution types The water quality of sewage outlets and stormwater / sewage pipe networks is uniformly classified into four types: domestic sewage, livestock and poultry farming, urban non-point source pollution, agricultural non-point source pollution, construction disturbance pollution, industrial pollution, and ordinary stormwater pollution. The classification is based on the ratio of water quality factor concentrations to their relative change rates. If the two types of water pollution are the same, then... If they are inconsistent, then a judgment will be made. The specific criteria for judgment are as follows: 1. Domestic sewage type: Most domestic sewage discharge outlets; Judgment basis: TP / The COD concentration ratio is approximately 1:8:60, with a fluctuation range of 0.7-3 times. 2. Livestock and poultry farming type: Wastewater from areas involved in livestock and poultry farming will be affected. High concentration. Judgment criteria: COD / The overall concentration ratio is between 0.5 and 2.0; 3. Urban non-point source pollution: This typically occurs during the initial rainwater runoff phase in urban built-up areas, with a high proportion of COD concentration. After the initial rain, pollutant concentrations may return to the typical stormwater runoff pattern. Judgment criteria: TP / The COD concentration ratio is generally around 1:10:500, with a fluctuation range of 0.5-1.2 times. 4. Agricultural non-point source pollution: The catchment area contains a lot of farmland, and the water quality at the discharge outlet is mainly affected by fertilizers, pesticides, and soil erosion. The TP concentration is high, while the COD is not particularly high. Criteria for judgment: The ratio of TP concentration to total TP concentration is generally 1:1, with a fluctuation range of 0.5 to 1.2 times. 5. Construction disturbance type: Usually only TP shows a significant increase, sometimes pH (if monitored) also increases (affected by lime, cement, etc.). Judgment criterion: The relative rate of change of TP is greater than... ; 6. Industrial pollution type: This type of wastewater is more complex and usually causes COD, One, two, or more of the following factors (TP) showed a significant increase. Judgment criteria: COD, The relative rate of change of any factor of TP is greater than ; 7. Typical stormwater runoff type: COD, The overall TP water quality meets the Class IV water quality standard.

[0037] Flow rate and water quality correlation This is the sum of three sub-indices: flow correlation, turbidity correlation, and conductivity correlation, between the sewage outfall and the stormwater and sewage pipe network nodes. The flow correlation primarily uses the average daily flow rate under non-rainfall conditions for the three days prior to the pollution event as the normal flow curve, and the relative rate of change describes the flow fluctuation within the pipeline. The relative rate of change of node flow rate = (daily flow rate - normal flow rate) / normal flow rate. The relevant value table is shown in Table 2 below: Table 2. Values ​​for Flow Relevance

[0038] Turbidity correlation is calculated based on the range of turbidity at the pollution site on the day pollution occurs; turbidity typically ranges from 0.1 to 100 NTU. Initially discharged domestic wastewater (COD around 300) has a turbidity of approximately 80-90; diluted domestic wastewater (COD concentration 100) has a turbidity of approximately 30; relatively clean water (Class IV standard, with a COD of around 30, the overall turbidity is 2-5; Class V standard, with a COD of around 40, the overall turbidity is 4-10). The turbidity correlation range is shown in Table 3 below. Table 3. Turbidity Correlation Values

[0039] The conductivity correlation is calculated based on the range of node conductivity on the day pollution occurs, and the values ​​are shown in Table 4 below: Table 4. Correlation Values ​​for Conductivity

[0040] Temporal variation similarity To ensure consistency in the trends of core water quality factor monitoring data over time at river discharge outlets and stormwater / sewage pipe network nodes using the DTW algorithm, the core steps and formulas of the algorithm are as follows: Define the time series of water quality at sewage discharge outlets into rivers Water quality time series of pipeline nodes ; , This refers to the amount of monitoring data for the two types of sequences; Build The distance matrix, whose elements are Euclidean distances, is expressed as:

[0041] Find regular paths that satisfy boundary conditions, continuity, and monotonicity. ,in, , Indicates the length of the regularized path; The cumulative distance is calculated using the following expression:

[0042] The temporal similarity is calculated and normalized using the following expression:

[0043] The denominator K is primarily used to compensate for regularized paths of different lengths. The purpose of DTW (Time-Digital Transmission Weaving) is to extend and shorten two time series to obtain the shortest possible distance between them; this shortest distance is the final distance metric between the two time series. This requires selecting a path that minimizes the final total distance, i.e., the cumulative distance. .

[0044] The optimal path is the one that minimizes the accumulated distance along the path. This path can be obtained using a dynamic programming algorithm.

[0045] Pipeline distance correlation Based on the normalized value of the cumulative pipeline length of sewage outfalls and stormwater / sewage pipe network nodes. To obtain a value; the expression is:

[0046] in, Let be the actual cumulative pipeline length between the i-th pipeline node and the sewage discharge outlet into the river. This represents the maximum cumulative pipeline length of all associated pipeline nodes upstream of the sewage discharge outlet into the river. This is the minimum cumulative pipeline length of all associated pipeline nodes upstream of the sewage discharge outlet into the river.

[0047] Discharge outlet-pollution source correlation Normalized value based on the actual connection distance between sewage outfalls and water pollution sources For taking values, that is If the water pollution source and the sewage outlet into the river have the same water quality factors, then it is directly determined that... ; Pipeline network-pollution source correlation Based on the normalized value of the cumulative pipeline length of stormwater and sewage pipe networks and water pollution sources For the value to be taken, that is:

[0048] S4-2: For water pollution sources without topological relationships, directly calculate the correlation between the exceeding section and the water pollution source. The expression is:

[0049] in, Let be the actual straight-line spatial distance between the i-th topologically unrelated water pollution source and the cross-section exceeding the standard. The maximum straight-line spatial distance between all topologically unrelated water pollution sources within the catchment area of ​​the section exceeding the standard; It represents the minimum spatial straight-line distance between all topologically unrelated water pollution sources within the catchment area of ​​the section exceeding the standard. Values ​​normalized to interval; S4-3: Classify water pollution sources into industrial, domestic, and agricultural sources, and calculate the relative emissions from industrial and domestic sources. Relative emissions from livestock and poultry farming in agricultural sources Relative emissions from aquaculture in agricultural sources Relative emissions from agricultural planting in agricultural sources .

[0050] Calculate the relative emissions from industrial and residential sources. Specifically: The relative discharge volumes of wastewater treatment plants from industrial and domestic sources are calculated in the following order of priority: online monitoring data, electricity consumption data, and discharge permit limits. An enterprise activity level index is also introduced to characterize the production and operation status. Among these: Online monitoring data: The daily online monitoring value of pollutant emissions is directly used as the relative emission amount; No online monitoring data, no electricity usage data: ,in, The daily average value calculated based on the annual permitted emissions stipulated in the pollution discharge permit. The activity level index of the enterprise / wastewater treatment plant on that day is expressed as follows:

[0051] in, This refers to the actual electricity consumption data for the enterprise / sewage treatment plant on that day. Daily electricity consumption data for the past 12 months Quantiles.

[0052] Relative emissions from livestock and poultry farming in agricultural sources The annual pollution load is estimated using an output coefficient model and then converted to a daily average value. The expression is as follows:

[0053] in, Let t be the total number of livestock and poultry raised under the j-th farming model within the region; Let be the pollutant discharge coefficient of the t-th livestock and poultry under the j-th farming model. The number of species of livestock and poultry raised; Relative emissions from aquaculture in agricultural sources The annual pollution load is estimated using the input-output method and then converted to a daily average value. The expression is as follows:

[0054] in, , Let t represent the output and input of the t-th aquaculture category under the j-th aquaculture model; Let be the pollutant discharge coefficient of the t-th aquaculture species under the j-th aquaculture model. For the number of breeding models, For the number of aquaculture species; Relative emissions from agricultural planting in agricultural sources To estimate the annual value of nitrogen and phosphorus loss from surface runoff, and then convert it to a daily average, the expression is:

[0055] in, Let the nitrogen / phosphorus input be the amount of nitrogen / phosphorus entering the field under the j-th planting pattern. Let be the nitrogen / phosphorus loss coefficient under the j-th planting pattern. This refers to the number of planting patterns.

[0056] S5: Based on the relative emissions of each water pollution source and the results of each correlation, calculate the comprehensive correlation, and rank the water pollutants in the catchment area corresponding to the exceeding sections according to the magnitude of the comprehensive correlation, outputting the comprehensive source tracing results; wherein, S5 includes: S5-1: Based on the different correlations within the topological relationship types, a weighted sum is calculated and multiplied by the corresponding relative discharge volume of the water pollution source to obtain the comprehensive correlation. Specifically, for the first and fourth types of topological relationships, which contain a complete "section-outlet-pipeline-pollution source" link, wastewater treatment plants are the discharge link and do not have pipeline nodes; therefore, wastewater treatment plants are not included in the correlation calculation. Thus, the correlation of the first and fourth types of topological relationships includes the section-outlet correlation. Outlet-pipeline correlation Pipeline network-pollution source correlation The weighted sum of each correlation score, multiplied by the relative emissions of water pollution sources, yields the overall correlation score. The links for the second and third types of topological relationships are "section-outlet-pollution source", therefore only the section-outlet correlation is calculated. Discharge outlet-pollution source correlation The weighted average is then multiplied by the relative emissions to obtain the overall correlation.

[0057] S5-2: For water pollution sources for which no topological relationship has been established, the comprehensive correlation is obtained by multiplying the correlation between the exceeding section and the water pollution source by the relative discharge of the corresponding water pollution source. S5-3: Integrate the comprehensive correlation of all water pollution sources within the catchment area of ​​the exceeding section, sort them according to the magnitude of the comprehensive correlation, and obtain the comprehensive source tracing results. Among them, the larger the comprehensive correlation, the greater the possibility that the water pollution source contributes to the water quality of the exceeding section. The output results include pollution source number, pollution source name, pollution source type, spatial location, topological relationship type, correlation index, relative emission, comprehensive correlation, core water quality factors exceeding the standard, source tracing confidence, etc.

[0058] like Figure 2 As shown, in another embodiment of this example, a source tracing system for water pollution at river basin monitoring sections is also included, applied to the aforementioned source tracing method for water pollution at river basin monitoring sections. This system includes a data acquisition module, a preprocessing module, a topology module, a data processing module, and a source tracing result generation module, wherein: The data acquisition module is used to collect basic data of the target river basin; the basic data includes industrial source data, agricultural source data, domestic source data, river network data, key park stormwater and sewage pipe network data, sewage outlet data into the river, and cross-sectional water quality data; The preprocessing module is used to preprocess the basic data, count the water quality exceeding the standard data in the basic data, and obtain the information of the exceeding section corresponding to the water quality exceeding the standard data. The topology module is used to construct the topological relationships of water pollution sources within the cross-section information of exceeding the standard; The data processing module is used to calculate the correlation between nodes of each associated topological node for water pollution sources with established topological relationships; to calculate the correlation between the exceeding section and the water pollution source for water pollution sources without established topological relationships; and to obtain the relative emission of each water pollution source. The source tracing result generation module is used to calculate the comprehensive correlation based on the relative emissions of each water pollution source and the various correlation results, and to sort the water pollutants in the corresponding catchment area of ​​the exceeding section according to the magnitude of the comprehensive correlation, and output the comprehensive source tracing result.

[0059] It also includes a computer-readable storage medium storing a program or instructions that cause a computer to perform a source tracing method for water pollution at a river basin monitoring section as described above.

[0060] The above are merely embodiments of the present invention. Commonly known structures and characteristics are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A source tracing method for water pollution at monitoring sections in river basins, characterized in that: include: S1: Collect basic data of the target river basin; the basic data includes industrial source data, agricultural source data, domestic source data, river network data, stormwater and sewage pipe network data of key industrial parks, sewage outlet data into the river, and cross-sectional water quality data; S2: Preprocess the basic data, statistically analyze the water quality exceeding the standard data in the basic data, and obtain the information of the exceeding sections corresponding to the water quality exceeding the standard data; S3: Based on the information of water pollution sources within the cross-sections exceeding the standards, construct the topological relationship of the water pollution sources; S4: For water pollution sources with established topological relationships, calculate the correlation between each associated topological node; for water pollution sources without established topological relationships, calculate the correlation between the exceeding section and the water pollution source; and obtain the relative emission of each water pollution source. S5: Calculate the comprehensive correlation based on the relative discharge of each water pollution source and the results of each correlation, and sort the water pollutants in the corresponding catchment area of ​​the exceeding section according to the magnitude of the comprehensive correlation, and output the comprehensive source tracing results.

2. The source tracing method for water pollution at monitoring sections in a river basin according to claim 1, characterized in that: S2 includes: S2-1: Obtain basic data for the target river basin; classify and standardize the structured data and vector layer spatial data in the basic data; verify and supplement the static data in the basic data; and finally establish a standardized basic database. S2-2: The core water quality factors for assessing the water environment quality of the target river basin are used as indicators for judging whether the water quality exceeds the standard; the water quality monitoring data of each monitoring section of the pre-processed basic data are extracted, and the threshold for judging whether each water quality factor exceeds the standard is divided according to the water environment functional zone of each monitoring section. S2-3: Perform threshold comparison on the water quality factors of the water quality monitoring data of each monitoring section one by one. If the monitoring value of a water quality factor is greater than the defined threshold for exceeding the standard, the water quality monitoring data is determined to be exceeding the standard; thus obtaining preliminary information on the exceeding sections. S2-4: Based on the statistical judgment results of S2-3, extract the full correlation information of the preliminary exceeding section information from the preprocessed standardized basic database, including basic section information, exceeding section characteristic information and section spatial correlation information, to form a standardized exceeding section information set; S2-5: Structure and integrate all the information sets of sections exceeding the standard to establish a database of information on sections exceeding the standard.

3. The source tracing method for water pollution at monitoring sections in river basins according to claim 2, characterized in that: S3 includes: S3-1: Extract the catchment area from the spatial correlation information of the cross-sections exceeding the standard, and combine it with the preprocessed river network vector layer and the spatial location data of water pollution sources. Through spatial geographic overlay analysis, screen out the water pollution sources within the catchment area corresponding to the cross-sections exceeding the standard. S3-2: Integrate pipeline network data, river discharge outlet data, sewage treatment plant space and discharge connection data, and river network topology data within the catchment area of ​​the substandard section to establish a unified spatial coordinate system; S3-3: Extract pipeline nodes, pipeline junctions, and monitoring nodes from pipeline network data; extract river discharge outlets associated with exceeding standards from river discharge outlet data; extract sewage treatment plants from sewage treatment plant space and discharge connection data. S3-4: Using water pollution sources as upstream starting nodes, exceeding standard sections as downstream terminal nodes, and the objects extracted in S3-3 as intermediate nodes, a standardized topological relationship is constructed. S3-5: For water pollution sources within the catchment area of ​​the substandard section, where there is no connection between the sewage channel and the substandard section, it is characterized as having no topological relationship.

4. The source tracing method for water pollution at monitoring sections in river basins according to claim 3, characterized in that: In S3-4, the standardized topological relations include four types of topological relations, namely: Type I topological relationship: Water pollution source Rainwater and sewage pipe network sewage treatment plant Sewage outlets into rivers Sections exceeding the standard; Second type of topological relationship: Water pollution source sewage treatment plant Sewage outlets into rivers Sections exceeding the standard; Third type of topological relationship: Water pollution source Sewage outlets into rivers Sections exceeding the standard; Fourth type of topological relationship: Water pollution source Rainwater and sewage pipe network Sewage outlets into rivers Sections exceeding the standard.

5. The source tracing method for water pollution at monitoring sections of river basins according to claim 4, characterized in that: S4 includes: S4-1: Obtain four types of topological relationships, and extract the correlation between nodes based on the actual connected nodes in the topological relationships, following reverse tracing logic; including cross-section-outlet correlation. Outlet-pipeline correlation Discharge outlet-pollution source correlation Pipeline network-pollution source correlation ; S4-2: For water pollution sources without topological relationships, directly calculate the correlation between the exceeding section and the water pollution source. The expression is: in, Let be the actual straight-line spatial distance between the i-th topologically unrelated water pollution source and the cross-section exceeding the standard. The maximum straight-line spatial distance between all topologically unrelated water pollution sources within the catchment area of ​​the section exceeding the standard; It represents the minimum spatial straight-line distance between all topologically unrelated water pollution sources within the catchment area of ​​the section exceeding the standard. Values ​​normalized to interval; S4-3: Classify water pollution sources into industrial, domestic, and agricultural sources, and calculate the relative emissions from industrial and domestic sources. Relative emissions from livestock and poultry farming in agricultural sources Relative emissions from aquaculture in agricultural sources Relative emissions from agricultural planting in agricultural sources .

6. The source tracing method for water pollution at monitoring sections of river basins according to claim 5, characterized in that: In S4-1, the cross-section-outlet correlation Based on the normalized value of the distance along the river between the exceeding section and the sewage outlet, and combined with the special scenario of exceeding the standard in the monitoring data of the sewage outlet and matching characteristic water quality factors, a default value is set, specifically: In typical scenarios, , The normalized value is the distance along the river between the section exceeding the standard and the sewage outlet into the river; In special scenarios where monitoring data from sewage discharge outlets into rivers exceeds standards, and where the sewage discharge outlets and the sections exceeding standards share the same water quality factors, it is determined that... ; Outlet-pipeline correlation Based on the correlation of water pollution type Correlation between flow rate and water quality Temporal variation similarity Pipeline distance correlation The sum of the four sub-indicators, normalized to a value of 100%. Interval; where: Correlation of water pollution types The water quality of sewage outlets and stormwater / sewage pipe networks is uniformly classified into four types: domestic sewage, livestock and poultry farming, urban non-point source pollution, agricultural non-point source pollution, construction disturbance pollution, industrial pollution, and ordinary stormwater pollution. The classification is based on the ratio of water quality factor concentrations to their relative change rates. If the two types of water pollution are the same, then... If they are inconsistent, then a judgment will be made. ; Flow rate and water quality correlation The summation of three sub-indicators—flow correlation, turbidity correlation, and conductivity correlation—between the sewage outfall and the stormwater and sewage pipe network nodes. Temporal variation similarity To ensure consistency of the trends in monitoring data of core water quality factors at river discharge outlets and stormwater / sewage pipe network nodes over time, based on the DTW algorithm; Pipeline distance correlation Based on the normalized value of the cumulative pipeline length of sewage outfalls and stormwater / sewage pipe network nodes. To take a value; Discharge outlet-pollution source correlation Normalized value based on the actual connection distance between sewage outfalls and water pollution sources For taking values, that is If the water pollution source and the sewage outlet into the river have the same water quality factors, then it is directly determined that... ; Pipeline network-pollution source correlation Based on the normalized value of the cumulative pipeline length of stormwater and sewage pipe networks and water pollution sources For taking values, that is .

7. The source tracing method for water pollution at monitoring sections of river basins according to claim 6, characterized in that: The S4-3 section calculates the relative emissions from industrial and residential sources. Specifically: The relative discharge from industrial and domestic wastewater treatment plants is calculated in order of priority based on online monitoring data, electricity consumption data, and discharge permits, and an enterprise activity level index is introduced to characterize the production and operation status. Relative emissions from livestock and poultry farming in agricultural sources The annual pollution load is estimated using an output coefficient model and then converted to a daily average value. The expression is as follows: in, Let t be the total number of livestock and poultry raised under the j-th farming model within the region; Let be the pollutant discharge coefficient of the t-th livestock and poultry under the j-th farming model. The number of species of livestock and poultry raised; Relative emissions from aquaculture in agricultural sources The annual pollution load is estimated using the input-output method and then converted to a daily average value. The expression is as follows: in, , Let t represent the output and input of the t-th aquaculture category under the j-th aquaculture model; Let be the pollutant discharge coefficient of the t-th aquaculture species under the j-th aquaculture model. For the number of breeding models, For the number of aquaculture species; Relative emissions from agricultural planting in agricultural sources To estimate the annual value of nitrogen and phosphorus loss from surface runoff, and then convert it to a daily average, the expression is: in, Let the nitrogen / phosphorus input be the amount of nitrogen / phosphorus entering the field under the j-th planting pattern. Let be the nitrogen / phosphorus loss coefficient under the j-th planting pattern. This refers to the number of planting patterns.

8. The source tracing method for water pollution at monitoring sections of a river basin according to claim 7, characterized in that: S5 includes: S5-1: Based on the different correlations in the topological relationship types, the weighted sum is multiplied by the corresponding relative emissions of water pollution sources to obtain the comprehensive correlation. S5-2: For water pollution sources for which no topological relationship has been established, the comprehensive correlation is obtained by multiplying the correlation between the exceeding section and the water pollution source by the relative discharge of the corresponding water pollution source. S5-3: Integrate the comprehensive correlation of all water pollution sources within the catchment area of ​​the section exceeding the standard, sort them according to the magnitude of the comprehensive correlation, and obtain the comprehensive source tracing results.

9. A source tracing system for water pollution at monitoring sections in river basins, applied to the source tracing method for water pollution at monitoring sections in river basins as described in any one of claims 1-8, characterized in that: It includes a data acquisition module, a preprocessing module, a topology module, a data processing module, and a source tracing result generation module, among which: The data acquisition module is used to collect basic data of the target river basin; the basic data includes industrial source data, agricultural source data, domestic source data, river network data, key park stormwater and sewage pipe network data, sewage outlet data into the river, and cross-sectional water quality data; The preprocessing module is used to preprocess the basic data, count the water quality exceeding the standard data in the basic data, and obtain the information of the exceeding section corresponding to the water quality exceeding the standard data. The topology module is used to construct the topological relationships of water pollution sources within the cross-section information of exceeding the standard; The data processing module is used to calculate the correlation between nodes of each associated topological node for water pollution sources with established topological relationships; to calculate the correlation between the exceeding section and the water pollution source for water pollution sources without established topological relationships; and to obtain the relative emission of each water pollution source. The source tracing result generation module is used to calculate the comprehensive correlation based on the relative emissions of each water pollution source and the various correlation results, and to sort the water pollutants in the corresponding catchment area of ​​the exceeding section according to the magnitude of the comprehensive correlation, and output the comprehensive source tracing result.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program or instructions that cause a computer to execute a source tracing method for water pollution at a monitoring section in a river basin as described in any one of claims 1-8.

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