Method and device for risk assessment of water body composite pollution sources based on evidence weight method

Abstract

The present application provides a method and device for risk assessment of water body composite pollution sources based on the method of weights of evidence. The method includes: obtaining pollutant detection data of each pollution source along the water diversion project; determining the sampling contribution value of pollution source i according to the detection data of each pollutant of pollution source i and the sampling weights of each pollutant of pollution source i, selecting the pollution source contribution value from the N sampling contribution values of the pollution sources, and selecting the pollutant weight from the N sampling weights of the pollutants; determining the sampling contribution value of the water diversion project according to the contribution value of each pollution source and the sampling weights of each pollution source, selecting the water diversion project contribution value from the N sampling contribution values of the water diversion project, and selecting the pollution source weight from the N second sampling weights of the pollution sources; generating a pollution risk assessment report according to the pollutant weight, the pollution source weight, the pollution source contribution value, and the water diversion project contribution value. The risk assessment method provided by the present application has strong adaptability and simple operation, and can improve the safety of water conveyance.

Description

Technical Field

[0001] This application relates to the technical field of pollution source risk assessment, and particularly to a method and device for risk assessment of water body composite pollution sources based on the weight-of-evidence method. Background Technique

[0002] With the rapid development of the construction of long-distance water diversion projects, the problem of water quality safety has become increasingly prominent, and it is particularly important to scientifically evaluate the pollution source risks. The water quality safety of water diversion projects is affected by the water quality of source water, water quality of water conveyance along the line, water quality of reservoirs and other pollution sources.

[0003] In practice, the source water quality risks mainly involve unstable source water quality, soil erosion, natural disasters, agricultural non-point source pollution; the water quality of water conveyance along the line involves garbage dumping along the line, illegal discharge of industrial sewage, agricultural non-point source pollution, emergencies, natural disasters; the reservoir water quality risks include uncontrollable factors such as endogenous pollution (including equipment failures, etc.) and abnormal biological proliferation. It is necessary to deeply analyze these risk factors to complete the risk assessment of pollution sources in water diversion projects, determine the main pollution sources, and thus provide a theoretical basis for water quality treatment in the water diversion project basin. Summary of the Invention

[0004] In view of this, the purpose of the embodiments of this application is to provide a method and device for risk assessment of water body composite pollution sources based on the weight-of-evidence method, which has strong adaptability, simple operation, and can improve the safety of water conveyance in water diversion projects.

[0005] In a first aspect, the embodiments of this application provide a method for risk assessment of water body composite pollution sources based on the weight-of-evidence method, and the risk assessment method includes:

[0006] Obtain the pollutant detection data of each pollution source along the line of the target water diversion project; among them, the pollution sources include source water, water conveyance along the line, and reservoir; the pollutants to be detected for each pollution source all include permanganate index, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, copper, zinc, fluoride, arsenic, lead, fecal coliforms, sulfate, chloride, nitrate, iron, and manganese;

[0007] According to the detection data of each pollutant of pollution source i and the first sampling weight of each pollutant of pollution source i, determine the first sampling contribution value of pollution source i, select the contribution value of pollution source i from the N first sampling contribution values of pollution source i, and select the weight of pollutant j of pollution source i from the N first sampling weights of pollutant j of pollution source i;

[0008] Determine the second sampling contribution value of the target water transfer project according to the contribution value of each pollution source along the target water transfer project and the second sampling weight of each pollution source. Select the contribution value of the target water transfer project from the N second sampling contribution values of the target water transfer project, and select the weight of pollution source i from the N second sampling weights of pollution source i;

[0009] Generate a pollution risk assessment report for the target water transfer project based on the pollutant weight, pollution source weight, pollution source contribution value of the pollution source, the N first sampling contribution values of the pollution source, the contribution value of the target water transfer project, and the N second sampling contribution values of the target water transfer project.

[0010] In a possible implementation manner, the obtaining of the pollutant detection data of each pollution source along the target water transfer project includes:

[0011] At any detection time point, collect the concentration of the pollutant to be detected of each pollution source along the target water transfer project;

[0012] Preprocess the collected pollutant concentration, and convert the pollutant concentration from which invalid characters have been removed into a floating point number for numerical calculation;

[0013] Take the ratio of the preprocessed pollutant concentration to the associated pollutant concentration standard value as the standardized pollutant concentration;

[0014] Take the average value of the standardized pollutant concentrations at each detection time point of pollutant j of pollution source i as the detection data of pollutant j of pollution source i.

[0015] In a possible implementation manner, the determining of the first sampling contribution value of pollution source i according to the detection data of each pollutant of pollution source i and the first sampling weight of each pollutant of pollution source i, selecting the contribution value of pollution source i from the N first sampling contribution values of pollution source i, and selecting the weight of pollutant j of pollution source i from the N first sampling weights of pollutant j of pollution source i includes:

[0016] Step 1.1: The first sampling weight p of pollutant j of pollution source i in the first sampling ij(1) is the preset initial pollutant weight; take the standardized result of the product of the first sampling weight p of pollutant j of pollution source i in the (n - 1)th sampling ij(n-1) and the detection data X of pollutant j of pollution source i ij as the first sampling weight p of pollutant j of pollution source i in the nth sampling ij(n) ;

[0017] Step 1.2: According to the first sampling weight p of pollutant j of pollution source i in the nth sampling ij(n) and the detection data X of pollutant j of pollution source i ij, adopt , calculate the first sampling contribution value WQI of the pollution source i at the nth sampling i(n) , where k is the total number of pollutants, n = 1, 2, 3, ……, N, and N is the specified number of samplings;

[0018] Step 1.3: Repeat Step 1.1 and Step 1.2 until the specified number of samplings N is completed, and obtain N first sampling contribution values WQI of the pollution source i i(n) ;

[0019] Step 1.4: Determine the contribution value WQI of the pollution source i according to the occurrence frequency of the first sampling contribution value WQI of the N samplings of the pollution source i i(n) ; i ;

[0020] Step 1.5: Determine the first sampling weight p of the pollutant j of the pollution source i at the nth sampling whose sampling times are the same as the contribution value WQI of the pollution source i i as the weight p of the pollutant j of the pollution source i ij(n) ; ij .

[0021] In a possible implementation manner, the determining the second sampling contribution value of the target water transfer project according to the contribution values of each pollution source along the target water transfer project and the second sampling weights of each pollution source, selecting the contribution value of the target water transfer project from the N second sampling contribution values of the target water transfer project, and selecting the weight of the pollution source i from the N second sampling weights of the pollution source i includes:

[0022] Step 2.1: The second sampling weight q of the pollution source i at the first sampling i(1) is the preset initial pollution source weight; The average value of the second sampling weight q of the pollution source i at the (n - 1)th sampling i(n-1) and the first sampling contribution value WQI of the pollution source i at the (n - 1)th sampling i(n-1) is used as the second sampling weight q of the pollution source i at the nth sampling i(n) ;

[0023] Step 2.2: According to the second sampling weight q of the pollution source i at the nth sampling i(n) and the first sampling contribution value WQI of the pollution source i at the nth sampling i(n) , adopt , calculate the second sampling contribution value WQI of the target water transfer project at the nth sampling (n) , where g is the total number of pollution sources, n = 1, 2, 3, ……, N, and N is the specified number of samplings;

[0024] Step 2.3: Repeat Step 2.1 and Step 2.2 until the specified number of samplings N is completed, and N second sampling contribution values WQI of the target water transfer project are obtained (n) ;

[0025] Step 2.4: Determine the contribution value WQI of the target water transfer project according to the occurrence frequency of the second sampling contribution value WQI of the N samplings of the target water transfer project (n) ;

[0026] Step 2.5: Determine the weight q of the pollution source i of the nth sampling with the same number of sampling times as the contribution value WQI of the target water transfer project i(n) as the weight q of the pollution source i i .

[0027] In a possible implementation manner, generating a pollution risk assessment report for the target water transfer project according to the pollutant weights, pollution source weights, pollution source contribution values of the pollution sources, the N first sampling contribution values of the pollution sources, the contribution value of the target water transfer project, and the N second sampling contribution values of the target water transfer project includes:

[0028] According to the weight p ij of the pollutant j of the pollution source i, determine the main pollutants, secondary pollutants, and weakly associated pollutants of the pollution source i; according to the contribution value WQI i of the pollution source i, and the preset classification rule for the contribution value of the pollution source, determine the pollution level of the pollution source i; generate a distribution map of the N first sampling contribution values WQI i(n) of the pollution source i;

[0029] According to the weight q i of the pollution source i, determine the main pollution sources, secondary pollution sources, and weakly associated pollution sources of the target water transfer project; according to the contribution value WQI of the target water transfer project, and the preset classification rule for the contribution value of the target water transfer project, determine the pollution level of the target water transfer project; generate a distribution map of the N second sampling contribution values WQI (n) of the target water transfer project;

[0030] In a possible implementation manner, the preset initial pollution source weights of the source water, water conveyance along the line, and reservoir are respectively: 0.4, 0.4, 0.2; the preset initial pollutant weights of permanganate index, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, copper, zinc, fluoride, arsenic, lead, fecal coliforms, sulfate, chloride, nitrate, iron, and manganese are respectively: 0.06, 0.07, 0.06, 0.10, 0.09, 0.09, 0.04, 0.04, 0.03, 0.09, 0.09, 0.06, 0.04, 0.04, 0.06, 0.02, 0.02.

[0031] In a possible implementation manner, the risk assessment method further includes:

[0032] Obtain the water area flowing positions, water flow rates, scales of factories, residences, and public facilities along the target water diversion project, and scales of ecological protection areas, nature reserves, and park green spaces along the line, and generate corresponding feature vectors;

[0033] Adopt the K-means clustering method to cluster the target water diversion project and the water diversion projects that have completed treatment according to the feature vectors of the target water diversion project, pollutant weights of pollution sources, pollution source weights, pollution source contribution values, and target water diversion project contribution values;

[0034] Generate reference treatment measures for the target water diversion project according to the treatment measures of the water diversion projects that have completed treatment and belong to the same category as the target water diversion project.

[0035] In a second aspect, an embodiment of the present application provides a risk assessment device for water body compound pollution sources based on the evidence weight method. The risk assessment device includes:

[0036] A data acquisition module, configured to acquire pollutant detection data of each pollution source along the target water diversion project; wherein, the pollution sources include source water, water conveyance along the line, and reservoirs; the pollutants to be detected for each pollution source all include permanganate index, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, copper, zinc, fluoride, arsenic, lead, fecal coliforms, sulfate, chloride, nitrate, iron, and manganese;

[0037] A first selection module, configured to determine the first sampling contribution value of pollution source i according to the detection data of each pollutant of pollution source i and the first sampling weights of each pollutant of pollution source i, select the contribution value of pollution source i from the N first sampling contribution values of pollution source i, and select the weight of pollutant j of pollution source i from the N first sampling weights of pollutant j of pollution source i;

[0038] A second selection module, configured to determine the second sampling contribution value of the target water diversion project according to the contribution values of each pollution source along the target water diversion project and the second sampling weights of each pollution source, select the contribution value of the target water diversion project from the N second sampling contribution values of the target water diversion project, and select the weight of pollution source i from the N second sampling weights of pollution source i;

[0039] A report generation module, configured to generate a pollution risk assessment report for the target water diversion project according to the pollutant weights, pollution source weights, pollution source contribution values of the pollution sources, the N first sampling contribution values of the pollution sources, the target water diversion project contribution value, and the N second sampling contribution values of the target water diversion project.

[0040] In a third aspect, an embodiment of the present application provides an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device runs, the processor communicates with the memory through the bus, and the processor executes the machine-readable instructions to perform the steps of the method for risk assessment of water body composite pollution sources based on the evidence weight method according to any one of the first aspect.

[0041] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, it performs the steps of the method for risk assessment of water body composite pollution sources based on the evidence weight method according to any one of the first aspect.

[0042] The method and device for risk assessment of water body composite pollution sources based on the evidence weight method provided by the embodiments of the present application have strong adaptability and simple operation, and can improve the safety of water conveyance in the water transfer project.

[0043] To make the above objects, features, and advantages of the present application more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, provides a detailed description as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] To more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and thus should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0045] Figure 1 Shows a flowchart of a method for risk assessment of water body composite pollution sources based on the evidence weight method provided by an embodiment of the present application;

[0046] Figure 2 Shows a flowchart of another method for risk assessment of water body composite pollution sources based on the evidence weight method provided by an embodiment of the present application;

[0047] Figure 3 Shows a flowchart of another method for risk assessment of water body composite pollution sources based on the evidence weight method provided by an embodiment of the present application;

[0048] Figure 4 Shows a schematic diagram of pollution source weights provided by an embodiment of the present application;

[0049] Figure 5 Shows a schematic diagram of water source pollutant weights provided by an embodiment of the present application;

[0050] Figure 6It shows the WQI distribution map of the Jiaodong Water Diversion Project provided by the embodiments of the present application;

[0051] Figure 7 It shows the WQI distribution map of the water source provided by the embodiments of the present application;

[0052] Figure 8 It shows the structural schematic diagram of a water body composite pollution source risk assessment device based on the evidence weight method provided by the embodiments of the present application;

[0053] Figure 9 It shows the schematic diagram of an electronic device provided by the embodiments of the present application. Detailed implementation manners

[0054] To make the purposes, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Usually, the components of the embodiments of the present application described and shown in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application to be protected, but only represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0055] At the present stage, with the rapid development of long-distance water diversion construction, the problem of water quality safety has become increasingly prominent, and it is particularly important to scientifically evaluate the pollution source risk. The water quality safety of the water diversion project is affected by the water quality of the source water, the water quality of the water conveyance along the line, the water quality of the reservoir, and other pollution source water qualities.

[0056] In practice, the source water quality risk mainly involves unstable source water quality, soil erosion, natural disasters, and agricultural non-point source pollution; the water quality of the water conveyance along the line involves garbage dumping along the line, industrial sewage illegal discharge, agricultural non-point source pollution, emergencies, and natural disasters; the reservoir water quality risk includes endogenous pollution (including equipment failures, etc.), biological abnormal proliferation and other uncontrollable factors. It is necessary to deeply analyze these risk factors to complete the pollution source risk assessment of the water diversion project, determine the main pollution sources, and thus provide a theoretical basis for the water quality treatment of the water diversion project basin.

[0057] Based on the above problems, the embodiments of the present application provide a water body composite pollution source risk assessment method and device based on the evidence weight method, which has strong adaptability, is easy to operate, and can improve the safety of water conveyance in the water diversion project.

[0058] Regarding the defects existing in the above solutions, they are all the results obtained by the inventors through practice and careful research. Therefore, the process of discovering the above problems and the solutions proposed by this application for the above problems in the following text should all be the contributions made by the inventors to this application during the process of this application.

[0059] Next, the technical solutions in this application will be clearly and completely described in conjunction with the accompanying drawings in this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. The components of this application usually described and illustrated in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of this application that is required to be protected, but only represents the selected embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of this application.

[0060] It should be noted that similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0061] For the convenience of understanding this embodiment, first, a method for risk assessment of water body composite pollution sources based on the evidence weight method disclosed in the embodiments of this application will be introduced in detail.

[0062] See Figure 1 as shown Figure 1 is a flowchart of a method for risk assessment of water body composite pollution sources based on the evidence weight method provided by the embodiments of this application. This risk assessment method includes:

[0063] S101. Obtain the pollutant detection data of each pollution source along the target water diversion project; among them, the pollution sources include source water, water conveyance along the line, and reservoirs; the pollutants to be detected for each pollution source all include permanganate index, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, copper, zinc, fluoride, arsenic, lead, fecal coliforms, sulfate, chloride, nitrate, iron, and manganese.

[0064] The pollution sources along the water conveyance line of the water diversion project include three types: source water, water conveyance along the line, and reservoirs (the total number of pollution sources g = 3). Obtain the detection data of the pollutants to be detected for each type of pollution source. The pollutants to be detected include at least the above 17 types. Among them, chemical oxygen demand is abbreviated as "COD", five-day biochemical oxygen demand is abbreviated as "BOD5", ammonia nitrogen is abbreviated as "NH3-N", total phosphorus (calculated as P), total nitrogen (calculated as N for lakes and reservoirs), fluoride (calculated as F - calculated), sulfate (calculated as SO4 2- calculated), chloride (calculated as Cl -Total nitrogen (calculated as N), nitrate (calculated as N). The detection data of different pollutants have the same dimension. For different pollutants, the detection data can be used to compare the concentration levels. The larger the detection data, the higher the pollutant concentration.

[0065] S102. Determine the first sampling contribution value of pollution source i according to the detection data of each pollutant of pollution source i and the first sampling weights of each pollutant of pollution source i. Select the contribution value of pollution source i from the N first sampling contribution values of pollution source i, and select the weight of pollutant j of pollution source i from the N first sampling weights of pollutant j of pollution source i.

[0066] For any pollution source i, obtain the detection data of k pollutants of pollution source i, and form a 1×k-dimensional vector (vector 1) from the detection data of k pollutants of pollution source i; sample the weights of k pollutants of pollution source i. To distinguish from the sampling weights of pollution source i in the following text, the sampling weights of k pollutants of pollution source i are called the first sampling weights, and the sampling weights of pollution source i are called the second sampling weights. Form another 1×k-dimensional vector (vector 2) from the first sampling weights of k pollutants of pollution source i, and the sum value of the first sampling weights of k pollutants of pollution source i is 1.

[0067] Take the dot product calculation result of vector 1 and vector 2 as the sampling contribution value of pollution source i. To distinguish from the sampling contribution value of the target water transfer project in the following text, the sampling contribution value of pollution source i is called the first sampling contribution value, and the sampling contribution value of the target water transfer project is called the second sampling contribution value.

[0068] It is necessary to sample the weights of k pollutants of pollution source i N times. There are N first sampling weights for pollutant j of pollution source i, and the N first sampling weights follow a normal distribution. Correspondingly, N first sampling contribution values of pollution source i are calculated, and the N first sampling contribution values also follow a normal distribution. According to the normal distribution of the N first sampling contribution values of pollution source i, select 1 first sampling contribution value from the N first sampling contribution values as the contribution value of pollution source i. Optionally, select the first sampling contribution value with the highest frequency as the contribution value of pollution source i. Take the first sampling weight of pollutant j of pollution source i that is consistent with the sampling times of the contribution value of pollution source i as the weight of pollutant j of pollution source i. For example, if the first sampling contribution value of the 213th (213≤N) sampling is taken as the contribution value of pollution source i, then take the first sampling weights of k pollutants of pollution source i in the 213th sampling as the weights of k pollutants of pollution source i.

[0069] After separately determining the contribution values of g pollution sources, normalize the contribution values of the pollution sources. Take the ratio of the contribution value of pollution source i to the sum of the contribution values of g pollution sources as the final contribution value of pollution source i, so that the contribution value of pollution source i is between 0 and 1.

[0070] It should be noted that the weights of the same pollutant in different pollution sources are independent and may be different numerically. For example, the weight of permanganate index in raw water is 0.03, and the weight of permanganate index in the reservoir is 0.05. The calculation processes of these two weights are not related to each other. The greater the weight of pollutant j in pollution source i, the greater the impact of pollutant j on the water quality of pollution source i. Pollutant j with a large weight is regarded as the main pollutant of pollution source i, pollutant j with a relatively large weight is regarded as the secondary pollutant of pollution source i, and pollutant j with a small weight is regarded as the weakly associated pollutant of pollution source i. According to the contribution value of the pollution source, the pollution level of the pollution source and the water quality pollution situation can be determined.

[0071] S103. Determine the second sampling contribution value of the target water transfer project according to the contribution values of each pollution source along the target water transfer project and the second sampling weights of each pollution source. Select the contribution value of the target water transfer project from the N second sampling contribution values of the target water transfer project, and select the weight of pollution source i from the N second sampling weights of pollution source i.

[0072] The weights of sampling g pollution sources are called the second sampling weights of the pollution sources. A 1×g-dimensional vector (vector 3) is composed of the second sampling weights of g pollution sources, and the sum of the second sampling weights of g pollution sources is 1; through the calculation in step S102, the normalized contribution values of g pollution sources are obtained, and another 1×g-dimensional vector (vector 4) is composed of the contribution values of g pollution sources, and the sum of the contribution values of g pollution sources is 1. Take the dot product calculation result of vector 3 and vector 4 as the second sampling contribution value of the target water transfer project.

[0073] Sample the weights of g pollution sources N times. Here, the number of weight samplings of pollution source i is consistent with the number of weight samplings of pollutant j of pollution source i in step S102. There are N second sampling weights for pollution source i, and the N second sampling weights follow a normal distribution. Correspondingly, N second sampling contribution values of the target water diversion project are calculated, and the N second sampling contribution values also follow a normal distribution. According to the normal distribution of the N second sampling contribution values of the target water diversion project, select 1 second sampling contribution value from the N second sampling contribution values as the contribution value of the target water diversion project. Optionally, select the second sampling contribution value with the highest frequency as the contribution value of the target water diversion project. Take the second sampling weight of pollution source i that is consistent with the number of samplings of the contribution value of the target water diversion project as the weight of pollution source i. For example, if the second sampling contribution value of the 167th (167 ≤ N) sampling is taken as the contribution value of the target water diversion project, then take the second sampling weight of pollution source i of the 167th sampling as the weight of pollution source i.

[0074] The greater the weight of pollution source i, the greater the impact of pollution source i on the water quality of the target water diversion project. Sort the g pollution sources according to the weights of the pollution sources from large to small to obtain the main pollution sources, secondary pollution sources, and weakly associated pollution sources. The pollution level and water quality pollution situation of the target water diversion project can be determined according to the contribution value of the target water diversion project. Optionally, the corresponding relationship between WQI classification, water quality, and WQI value is: Class I, clean, 0.1; Class II, fairly clean, 0.1 - 0.3; Class III, slightly polluted, 0.3 - 0.5; Class IV, moderately polluted, 0.5 - 1.0; Class V, severely polluted, 1.0 - 5.0; Class VI, extremely polluted, greater than 5.0.

[0075] S104. Generate a pollution risk assessment report for the target water diversion project based on the pollutant weights, source weights, source contribution values of the pollution sources, the N first sampling contribution values of the pollution sources, the contribution value of the target water diversion project, and the N second sampling contribution values of the target water diversion project.

[0076] The pollution risk assessment report of the target water diversion project includes the risk assessment results of the water body composite pollution sources. Specifically, it includes: the contribution value of the target water diversion project, which reflects the overall water quality pollution situation of the target water diversion project; the source contribution value, which reflects the water quality pollution situation of a certain pollution source; the source weight, which reflects the degree of influence of each pollution source on the water quality safety of the entire target water diversion project; the pollutant weight of the pollution source, which reflects the degree of influence of each pollutant on the water quality safety of a certain pollution source; the N second sampling contribution values of the target water diversion project, which reflect the normal distribution of the N sampling contribution values of the project; the N first sampling contribution values of the pollution source, which reflect the normal distribution of the N sampling contribution values of the pollution source.

[0077] The water body composite pollution source risk assessment method based on the evidence weight method provided by the embodiments of the present application has strong adaptability and is easy to operate, which can improve the safety of water conveyance in the water transfer project.

[0078] Further, as shown in Figure 2 shown, Figure 2 is a flowchart of another water body composite pollution source risk assessment method based on the evidence weight method provided by the embodiments of the present application. The obtaining of the pollutant detection data of each pollution source along the target water transfer project includes:

[0079] S1011. At any detection time point, collect the concentration of the pollutant to be detected of each pollution source along the target water transfer project.

[0080] In order to improve the accuracy of the pollutant detection data, at multiple detection time points, measure the concentration of the same pollutant of the same pollution source multiple times. The concentration of different pollutants has different dimensions.

[0081] S1012. Preprocess the collected pollutant concentration, and convert the pollutant concentration with invalid characters removed into a floating point number for numerical calculation.

[0082] Remove the invalid symbols such as ">", "<", "≥", "≤" contained in the collected pollutant concentration data, and convert it into a floating point number to ensure that the data can be used for numerical calculation.

[0083] S1013. Take the ratio of the preprocessed pollutant concentration to the associated pollutant concentration standard value as the standardized pollutant concentration.

[0084] Set a concentration standard value for each pollutant to standardize the concentration of each pollutant. For a certain pollutant, take the ratio of the preprocessed concentration of this pollutant obtained in step 1012 to the concentration standard value of this pollutant as the standardized concentration of this pollutant.

[0085] S1014. Take the average value of the standardized pollutant concentrations at each detection time point of pollutant j of pollution source i as the detection data of pollutant j of pollution source i.

[0086] Take the average value of the standardized pollutant concentrations at multiple detection time points of the same pollutant of the same pollution source as the detection data of this pollutant of this pollution source. The pollutant detection data obtained through steps S1012 to step S1014 has the same dimension.

[0087] As a possible implementation manner, in the water body composite pollution source risk assessment method based on the evidence weight method provided by the embodiments of the present application, Monte Carlo simulation is used to determine the pollutant weight, the pollution source contribution value, the pollution source weight, and the contribution value of the target water transfer project.

[0088] Specifically, the step of determining the first sampling contribution value of pollution source i according to the detection data of each pollutant of pollution source i and the first sampling weight of each pollutant of pollution source i, and selecting the contribution value of pollution source i from the N first sampling contribution values of pollution source i, and selecting the weight of pollutant j of pollution source i from the N first sampling weights of pollutant j of pollution source i includes:

[0089] Step 1.1: The first sampling weight p of pollutant j of pollution source i in the first sampling ij(1) is the preset initial pollutant weight; the first sampling weight p of pollutant j of pollution source i in the (n - 1)th sampling ij(n-1) is multiplied by the detection data X of pollutant j of pollution source i ij , and the standardized result is used as the first sampling weight p of pollutant j of pollution source i in the nth sampling ij(n) .

[0090] Referring to the public information on the impact of pollutants along the target water diversion project on water quality and combining with the work experience of water quality treatment, the initial pollutant weights are set. For example, the initial weights of permanganate index, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, copper, zinc, fluoride, arsenic, lead, fecal coliforms, sulfate, chloride, nitrate, iron, and manganese are set as: 0.06, 0.07, 0.06, 0.10, 0.09, 0.09, 0.04, 0.04, 0.03, 0.09, 0.09, 0.06, 0.04, 0.04, 0.06, 0.02, 0.02. The purpose of standardization is to make the sum of the first sampling weights of k pollutants of pollution source i equal to 1.

[0091] Step 1.2: According to the first sampling weight p of pollutant j of pollution source i in the nth sampling ij(n) and the detection data X of pollutant j of pollution source i ij , using , calculate the first sampling contribution value WQI of pollution source i in the nth sampling i(n) , where k is the total number of pollutants, n = 1, 2, 3,..., N, and N is the specified number of samplings.

[0092] Step 1.3: Repeat Step 1.1 and Step 1.2 until the specified number of samplings N is completed, and N first sampling contribution values WQI of pollution source i are obtained i(n) .

[0093] Set the number of samplings N according to the actual work needs. For example, set N = 1000.

[0094] Step 1.4: Determine the contribution value WQI of pollution source i according to the occurrence frequency of the first sampling contribution value WQI of N samplings of pollution source i i(n) of the occurrence frequency, determine the contribution value WQI of pollution source i i .

[0095] Optionally, the first sampling contribution value WQI with the highest occurrence frequency of pollution source i i(n) , is used as the contribution value WQI of pollution source i i .

[0096] Step 1.5: Determine the first sampling weight p of pollutant j of pollution source i in the nth sampling with the same sampling times as the contribution value WQI of pollution source i i , and determine it as the weight p of pollutant j of pollution source i ij(n) . ij .

[0097] The step of determining the second sampling contribution value of the target water transfer project according to the contribution value of each pollution source along the target water transfer project and the second sampling weight of each pollution source, and selecting the contribution value of the target water transfer project from the N second sampling contribution values of the target water transfer project, and selecting the weight of pollution source i from the N second sampling weights of pollution source i, includes:

[0098] Step 2.1: The second sampling weight q of pollution source i in the first sampling i(1) is the preset initial pollution source weight; the second sampling weight q of pollution source i in the (n - 1)th sampling i(n-1) and the average value of the first sampling contribution value WQI of pollution source i in the (n - 1)th sampling i(n-1) The normalized result is used as the second sampling weight q of pollution source i in the nth sampling i(n) .

[0099] Refer to the public information on the impact of pollution sources along the target water transfer project on water quality, and combine with the experience of water quality treatment work to set the initial pollution source weight. For example, set the initial weights of source water, water conveyance along the line, and reservoir to be: 0.4, 0.4, 0.2. The normalization process is to make the sum of the second sampling weights of g pollution sources equal to 1.

[0100] Step 2.2: According to the second sampling weight q of pollution source i in the nth sampling i(n) and the first sampling contribution value WQI of pollution source i in the nth sampling i(n) , use , calculate the second sampling contribution value WQI of the target water transfer project in the nth sampling (n) , where g is the total number of pollution sources, n = 1, 2, 3, ……, N, and N is the specified number of samplings.

[0101] Step 2.3: Repeat Step 2.1 and Step 2.2 until the specified number of samplings N is completed, and obtain the second sampling contribution value WQI of N target water transfer projects (n) .

[0102] Step 2.4: Determine the contribution value WQI of the target water transfer project according to the second sampling contribution value WQI of N samplings of the target water transfer project (n) 's frequency of occurrence

[0103] Optionally, take the second sampling contribution value WQI with the highest frequency of occurrence of the target water transfer project (n) as the contribution value WQI of the target water transfer project

[0104] Step 2.5: Determine the second sampling weight q of the pollution source i in the nth sampling with the same number of samplings as the contribution value WQI of the target water transfer project i(n) as the weight q of the pollution source i i .

[0105] Furthermore, in the water body composite pollution source risk assessment method based on the weight of evidence method provided in the embodiments of the present application, in Step S104, generating a pollution risk assessment report for the target water transfer project according to the pollutant weight, pollution source weight, pollution source contribution value of the pollution source, and the N first sampling contribution values of the pollution source, the contribution value of the target water transfer project, and the N second sampling contribution values of the target water transfer project includes:

[0106] Determine the main pollutants, secondary pollutants, and weakly associated pollutants of the pollution source i according to the weight p of the pollutant j of the pollution source i ij ; determine the pollution level of the pollution source i according to the contribution value WQI of the pollution source i i , and the preset classification rule for the contribution value of the pollution source; generate a distribution map of the N first sampling contribution values WQI i(n) of the pollution source i; determine the main pollution sources, secondary pollution sources, and weakly associated pollution sources of the target water transfer project according to the weight q of the pollution source i i ; determine the pollution level of the target water transfer project according to the contribution value WQI of the target water transfer project and the preset classification rule for the contribution value of the target water transfer project; generate a distribution map of the N second sampling contribution values WQI (n) of the target water transfer project. Among them, the abscissa of the contribution value distribution map is the contribution value, and the ordinate is the frequency of occurrence of the contribution value

[0107] Furthermore, when treating the water quality of the basin of the target water diversion project, the water quality treatment measures already used in other water diversion projects can be referred to. Select other water diversion projects with high similarity to the target water diversion project as the reference water diversion projects for water quality treatment measures. When determining the similarity, geographical location information of the water diversion project, water flow information, pollution of water quality by factories and residences on both sides of the water diversion project basin, and restoration of water quality by forest, grass and green land on both sides of the basin need to be considered. Try to comprehensively select the characteristics of the water diversion project to improve the accuracy of the selected reference water diversion project. See Figure 3 as shown Figure 3 is a flowchart of another method for risk assessment of water body compound pollution sources based on the evidence weight method provided by an embodiment of the present application. The risk assessment method further includes:

[0108] S301. Obtain the water flow position, water flow, scales of factories, residences and public facilities along the line, and scales of ecological protection areas, nature reserves and park green lands of the target water diversion project, and generate corresponding feature vectors.

[0109] Perform data processing on the water flow position, water flow, scales of factories, residences and public facilities along the line, and scales of ecological protection areas, nature reserves and park green lands of the obtained water diversion project to obtain multi-dimensional feature vectors that can be processed by a computer, and generate feature vectors of the target water diversion project and other water diversion projects that have completed treatment.

[0110] S302. Adopt the K-means clustering method to cluster the target water diversion project and the water diversion projects that have completed treatment according to the feature vectors of the target water diversion project, pollutant weights of pollution sources, pollution source weights, pollution source contribution values, and target water diversion project contribution values.

[0111] Process the feature vectors of the water diversion project, pollutant weights of pollution sources, pollution source weights, pollution source contribution values, and target water diversion project contribution values into multi-dimensional clustering input vectors. The dimension of the clustering input vectors should be greater than the dimension of the project feature vectors; input the clustering input vectors of the target water diversion project and the water diversion projects that have completed treatment, adopt the K-means clustering method, set the value of K, and obtain K categories of water diversion projects. Here, the value of K can be set to the total number of water diversion projects that have completed treatment, or the value of K can be calculated by K = a×A, where a is an adjustment coefficient, the value range of a is (0,1], and A is the total number of water diversion projects that have completed treatment. The value of a can be selected according to actual needs.

[0112] S303. Generate reference treatment measures for the target water diversion project according to the treatment measures of the water diversion projects that have completed treatment and belong to the same category as the target water diversion project.

[0113] Identify the completed water diversion projects of the same type as the target water diversion project as the reference water diversion projects. If there is only one reference water diversion project of the same type as the target water diversion project, determine the treatment measures of the reference water diversion project as the reference treatment measures for the target water diversion project; if there are multiple reference water diversion projects of the same type as the target water diversion project, determine the treatment measures that are consistent among the multiple reference water diversion projects as the reference treatment measures for the target water diversion project.

[0114] Taking the Jiaodong Water Diversion Project as an example, the evaluation process of the embodiments of this application is described as follows:

[0115] (1)Data collection and preprocessing

[0116] 1)Data reading: Read the pollutant concentrations collected at 9 different time points to obtain 9 data files (data1.csv to data9.csv).

[0117] 2)Removing invalid characters: Traverse each data file, remove the symbols ">", "<", "≥", "≤", and convert them into floating-point numbers to ensure that the data can be used for numerical calculations.

[0118] 3)Setting standard values: Set standard value arrays (standard_val1 and standard_val2) for each of the 17 pollutants to standardize the concentrations of each pollutant. It should be noted that the standardization array is a two-dimensional array with 17 rows and 1 column, containing 17 standard values of the original data; since the class III standard value of total nitrogen (lake reservoir, calculated as N) is 0.05, which is different from the other normal standard value of 0.2, the standard value array is set to 2 types.

[0119] (2)Data standardization and average value calculation

[0120] 1)Standardization: Divide the concentration of each pollutant by the corresponding standard value to compare the data under the same dimension.

[0121] 2)Calculating the average value: Perform an average calculation on the standardized data of each pollution source to obtain data1_avg, data2_avg, and data3_avg, which respectively represent the average pollutant concentrations of the water source, water conveyance route, and reservoir, that is, the detection data of pollutant j of pollution source i in step S101.

[0122] (3)Monte Carlo simulation sampling

[0123] 1)Simulation sampling times: Set the simulation sampling times to 10,000 times (N = 10,000) to ensure the reliability of the results.

[0124] 2) Sampling of pollution source weights: Use the normal distribution (norm.rvs) to generate sampling data of pollution source weights based on the initial pollution source weights (source_weights), and standardize it so that the sum of weights for each sampling is 1.

[0125] 3) Sampling of pollutant weights: Use the normal distribution (norm.rvs) to generate sampling data of pollutant weights based on the initial 17 pollutant weights (pollutant_weights), and standardize it so that the sum of weights for each sampling is 1.

[0126] (4) Risk contribution (the contribution value WQI of pollution source i i ) Calculation

[0127] 1) Calculate the risk contribution of each pollution source: For each pollution source, use the corresponding standardized mean value to perform a dot product calculation with the sampled pollutant weights to obtain the risk contributions of risk_source1 (water source), risk_source2 (water conveyance route), and risk_source3 (reservoir) for each sampling.

[0128] 2) Risk standardization: Divide the values of risk_source1, risk_source2, and risk_source3 by their sum to ensure that the relative proportion of each risk contribution is between 0 and 1.

[0129] (5) Calculate the overall WQI

[0130] Weighted summation: Perform a dot product calculation of the standardized risk contributions for each sampling with the sampled pollution source weights to obtain the overall WQI value (wqi_samples) for that sampling.

[0131] (6) Calculation of posterior weights

[0132] 1) Posterior weights of pollution sources: Calculate the mean value of weights_source_samples and the risk contributions of each pollution source, and standardize it to obtain the posterior weights of the pollution sources, that is, q in the above text i .

[0133] 2) Posterior weights of pollutants: Calculate the posterior weights of pollutants in different pollution sources by multiplying weights_pollutant_samples with data1_avg, data2_avg, and data3_avg, and standardize it, that is, p in the above text ij .

[0134] (7) Result output and visualization

[0135] 1) Output posterior weights and WQI statistics: Output the posterior weights of pollution sources and pollutants, as well as the mean and standard deviation of WQI.

[0136] 2) Visualize the weights of pollution sources: Use a bar chart to display the posterior weights of each pollution source. See Figure 4 shown in Figure 4 which is the schematic diagram of pollution source weights provided by the embodiment of this application. In Figure 4 it, the pollution sources include water sources, water conveyance routes, and reservoirs. The posterior weight of the pollution source (water source) is 0.427, the posterior weight of the pollution source (water conveyance route) is 0.382, and the posterior weight of the pollution source (reservoir) is 0.191.

[0137] 3) Visualize the weights of 17 pollutants: Display the posterior weights of each pollutant in water sources, water conveyance routes, and reservoirs. Here, taking the water source as an example, see Figure 5 shown in Figure 5 which is the schematic diagram of water source pollutant weights provided by the embodiment of this application. In Figure 5 it, the posterior weights of pollutants such as permanganate index, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, copper, zinc, fluoride, arsenic, lead, fecal coliforms, sulfate, chloride, nitrate, iron, and manganese in the pollution source (water source) are respectively shown.

[0138] 4) WQI distribution map: Draw a histogram and KDE curve of the overall WQI sample distribution to analyze the overall distribution trend of the water quality index. See Figure 6 shown in Figure 6 which is the WQI distribution map of the Jiaodong Water Diversion Project provided by the embodiment of this application. In Figure 6 it, the normal distribution of the WQI values of the Jiaodong Water Diversion Project obtained from 10,000 samplings is shown.

[0139] 5) WQI distribution of individual pollution sources: Draw the WQI distribution maps of water sources, water conveyance routes, and reservoirs to analyze the influence of each pollution source. Here, taking the water source as an example, see Figure 7 shown in Figure 7 which is the WQI distribution map of the water source provided by the embodiment of this application. In Figure 7 it, the normal distribution of the water source contribution values (water source WQI values) of the Jiaodong Water Diversion Project obtained from 10,000 samplings is shown. For water source pollutants, TN: has the highest weight, reaching 65.2%, indicating that TN in the water source is the most important pollutant and has a significant impact on water quality; permanganate index and chemical oxygen demand (COD): account for 4.62% and 6.07% respectively, being secondary pollutants; other indicators: such as total phosphorus, sulfate, chloride, etc. have relatively small weights and have a relatively minor impact on water quality, being weakly associated pollutants.

[0140] Based on the same inventive concept, in the embodiments of the present application, there is also provided a risk assessment device for water body composite pollution sources based on the evidence weight method corresponding to the risk assessment method for water body composite pollution sources based on the evidence weight method. Since the principle of solving problems by the device in the embodiments of the present application is similar to the above-mentioned risk assessment method for water body composite pollution sources based on the evidence weight method in the embodiments of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be elaborated.

[0141] See Figure 8 as shown Figure 8 is a schematic structural diagram of a risk assessment device for water body composite pollution sources based on the evidence weight method provided by an embodiment of the present application. The risk assessment device includes:

[0142] A data acquisition module 801, configured to acquire pollutant detection data of each pollution source along the target water diversion project line; wherein, the pollution sources include source water, water conveyance along the line, and reservoirs; the pollutants to be detected for each pollution source include permanganate index, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, copper, zinc, fluoride, arsenic, lead, fecal coliforms, sulfate, chloride, nitrate, iron, and manganese.

[0143] A first selection module 802, configured to determine the first sampling contribution value of pollution source i according to the detection data of each pollutant of pollution source i and the first sampling weight of each pollutant of pollution source i, select the contribution value of pollution source i from the N first sampling contribution values of pollution source i, and select the weight of pollutant j of pollution source i from the N first sampling weights of pollutant j of pollution source i.

[0144] A second selection module 803, configured to determine the second sampling contribution value of the target water diversion project according to the contribution values of each pollution source along the target water diversion project line and the second sampling weights of each pollution source, select the contribution value of the target water diversion project from the N second sampling contribution values of the target water diversion project, and select the weight of pollution source i from the N second sampling weights of pollution source i.

[0145] A report generation module 804, configured to generate a pollution risk assessment report for the target water diversion project according to the pollutant weights of the pollution sources, the pollution source weights, the pollution source contribution values, the N first sampling contribution values of the pollution sources, the contribution value of the target water diversion project, and the N second sampling contribution values of the target water diversion project.

[0146] In a possible implementation manner, when the data acquisition module 801 acquires the pollutant detection data of each pollution source along the target water diversion project line, it includes:

[0147] At any detection time point, collect the concentrations of the pollutants to be detected of each pollution source along the target water diversion project line.

[0148] Preprocess the collected pollutant concentrations, and convert the pollutant concentrations from which invalid characters have been removed into floating-point numbers for numerical calculation;

[0149] Take the ratio of the preprocessed pollutant concentration to the associated pollutant concentration standard value as the standardized pollutant concentration;

[0150] Take the average value of the standardized pollutant concentrations at each detection time point of pollutant j of pollution source i as the detection data of pollutant j of pollution source i.

[0151] In a possible implementation manner, when the first selection module 802 determines the first sampling contribution value of pollution source i according to the detection data of each pollutant of pollution source i and the first sampling weights of each pollutant of pollution source i, and selects the contribution value of pollution source i from the N first sampling contribution values of pollution source i, and selects the weight of pollutant j of pollution source i from the N first sampling weights of pollutant j of pollution source i, it includes:

[0152] Step 1.1: The first sampling weight p of pollutant j of pollution source i for the first sampling ij(1) is the preset initial pollutant weight; take the normalization result of the product of the first sampling weight p of pollutant j of pollution source i for the (n - 1)th sampling ij(n-1) and the detection data X of pollutant j of pollution source i ij as the first sampling weight p of pollutant j of pollution source i for the nth sampling ij(n) ;

[0153] Step 1.2: According to the first sampling weight p of pollutant j of pollution source i for the nth sampling ij(n) and the detection data X of pollutant j of pollution source i ij , use to calculate the first sampling contribution value WQI of pollution source i for the nth sampling i(n) , where k is the total number of pollutants, n = 1, 2, 3, ……, N, and N is the specified number of samplings;

[0154] Step 1.3: Repeat Step 1.1 and Step 1.2 until the specified number of samplings N is completed, and obtain N first sampling contribution values WQI of pollution source i i(n) ;

[0155] Step 1.4: Determine the contribution value WQI of pollution source i according to the occurrence frequency of the first sampling contribution values WQI of pollution source i for N samplings i(n) ; i ;

[0156] Step 1.5: The one associated with the contribution value WQI of pollution source i iThe first sampling weight p of pollutant j of pollution source i for the nth sampling with the same number of sampling times ij(n) , is determined as the weight p of pollutant j of pollution source i ij .

[0157] In a possible implementation manner, when the second selection module 803 determines the second sampling contribution value of the target water transfer project according to the contribution values of each pollution source along the target water transfer project and the second sampling weights of each pollution source, and selects the contribution value of the target water transfer project from the N second sampling contribution values of the target water transfer project and selects the weight of pollution source i from the N second sampling weights of pollution source i, it includes:

[0158] Step 2.1: The second sampling weight q of pollution source i for the first sampling i(1) is the preset initial pollution source weight; the average value of the second sampling weight q of pollution source i for the (n - 1)th sampling i(n-1) and the first sampling contribution value WQI of pollution source i for the (n - 1)th sampling i(n-1) is used as the standardized result of the second sampling weight q of pollution source i for the nth sampling i(n) ;

[0159] Step 2.2: According to the second sampling weight q of pollution source i for the nth sampling i(n) and the first sampling contribution value WQI of pollution source i for the nth sampling i(n) , adopt , calculate the second sampling contribution value WQI of the target water transfer project for the nth sampling (n) , where g is the total number of pollution sources, n = 1, 2, 3,..., N, and N is the specified number of sampling times;

[0160] Step 2.3: Repeat Step 2.1 and Step 2.2 until the specified number of sampling times N is completed, and obtain N second sampling contribution values WQI of the target water transfer project (n) ;

[0161] Step 2.4: Determine the contribution value WQI of the target water transfer project according to the occurrence frequency of the second sampling contribution value WQI of the target water transfer project for N samplings (n) ;

[0162] Step 2.5: The second sampling weight q of pollution source i for the nth sampling with the same number of sampling times as the contribution value WQI of the target water transfer project i(n) , is determined as the weight q of pollution source i i .

[0163] In a possible implementation manner, when generating a pollution risk assessment report for the target water diversion project according to the pollutant weights, pollution source weights, pollution source contribution values of pollution sources, N first sampling contribution values of pollution sources, the contribution value of the target water diversion project, and N second sampling contribution values of the target water diversion project, the report generation module 804 includes:

[0164] According to the weight p of pollutant j of pollution source i ij , determine the main pollutants, secondary pollutants, and weakly associated pollutants of pollution source i; according to the contribution value WQI of pollution source i i , and the preset grading rules for pollution source contribution values, determine the pollution level of pollution source i; generate a distribution map of the N first sampling contribution values WQI of pollution source i i(n) .

[0165] According to the weight q of pollution source i i , determine the main pollution sources, secondary pollution sources, and weakly associated pollution sources of the target water diversion project; according to the contribution value WQI of the target water diversion project and the preset grading rules for the contribution value of the target water diversion project, determine the pollution level of the target water diversion project; generate a distribution map of the N second sampling contribution values WQI of the target water diversion project (n) .

[0166] In a possible implementation manner, the initial pollution source weights of the source water, water conveyance along the line, and reservoir are preset as: 0.4, 0.4, 0.2; the initial pollutant weights of permanganate index, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, copper, zinc, fluoride, arsenic, lead, fecal coliforms, sulfate, chloride, nitrate, iron, and manganese are preset as: 0.06, 0.07, 0.06, 0.10, 0.09, 0.09, 0.04, 0.04, 0.03, 0.09, 0.09, 0.06, 0.04, 0.04, 0.06, 0.02, 0.02.

[0167] In a possible implementation manner, the risk assessment device further includes:

[0168] A feature vector generation module, configured to obtain the water area passing positions of the target water diversion project, the water flow, the scales of factories, residences, and public facilities along the line, and the scales of ecological protection areas, nature reserves, and park green spaces along the line, and generate corresponding feature vectors;

[0169] A clustering module, configured to use the K-means clustering method to cluster the target water diversion project and the water diversion projects that have completed treatment according to the feature vectors of the target water diversion project, the pollutant weights of pollution sources, the pollution source weights, the pollution source contribution values, and the contribution value of the target water diversion project;

[0170] A reference governance measure generation module is configured to generate reference governance measures for a target water diversion project based on the governance measures of the completed water diversion projects of the same category as the target water diversion project.

[0171] The water body composite pollution source risk assessment device based on the evidence weight method provided by the embodiments of the present application has strong adaptability and simple operation, and can improve the safety of water conveyance in water diversion projects.

[0172] See Figure 9 as shown in Figure 9 which is a schematic diagram of an electronic device provided by an embodiment of the present application. The electronic device 900 includes: a processor 901, a memory 902, and a bus 903. The memory 902 stores machine-readable instructions executable by the processor 901. When the electronic device runs, the processor 901 communicates with the memory 902 through the bus 903, and the processor 901 executes the machine-readable instructions to perform the steps of the water body composite pollution source risk assessment method based on the evidence weight method as described above.

[0173] Specifically, the above-mentioned memory 902 and processor 901 can be general memories and processors, which are not specifically limited here. When the processor 901 runs the computer program stored in the memory 902, it can execute the water body composite pollution source risk assessment method based on the evidence weight method as described above.

[0174] Corresponding to the above-mentioned water body composite pollution source risk assessment method based on the evidence weight method, an embodiment of the present application also provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, it executes the steps of the water body composite pollution source risk assessment method based on the evidence weight method as described above.

[0175] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems and devices described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated here. In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division, and there can be other division methods in actual implementation. For another example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the coupling or direct coupling or communication connection shown or discussed with each other can be through some communication interfaces, and the indirect coupling or communication connection of the devices or modules can be in an electrical, mechanical or other forms.

[0176] The module described as a separation component may or may not be physically separated. The component shown as a module may or may not be a physical module, that is, it may be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0177] In addition, each functional module in various embodiments of this application can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

[0178] If the above function is implemented in the form of a software functional module and sold or used as an independent product, it can be stored in a non-volatile computer-readable storage medium executable by a processor. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0179] Finally, it should be noted that the above-described embodiments are only specific implementation manners of this application, used to illustrate the technical solution of this application, rather than limiting it. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that any technician familiar with this technical field can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes, or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A water body composite pollution source risk assessment method based on the weight of evidence method, characterized in that: The risk assessment method includes: Obtain pollutant testing data for each pollution source along the target water diversion project; pollution sources include source water, water diversion along the route, and reservoirs; pollutants to be tested for each pollution source include permanganate index, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, copper, zinc, fluoride, arsenic, lead, fecal coliform bacteria, sulfate, chloride, nitrate, iron, and manganese; According to pollution source i Detection data and pollution sources of various pollutants i The first sampling weight of each pollutant to determine the pollution source i The first sampling contribution value, from the pollution source i of N Select the pollution source from the first sampling contribution value i The contribution value of pollution i pollutants j of N Select pollution sources from the first sampling weight i pollutants j The weight of According to the contribution value of each pollution source along the target water diversion project and the second sampling weight of each pollution source, the second sampling contribution value of the target water diversion project is determined. N The contribution value of the target water diversion project is selected from the second sampling contribution value, and the contribution value of the target water diversion project is selected from the pollution source. i of N The pollution source is selected from the second sampling weight i The weight of According to the pollutant weight, pollution source weight, pollution source contribution value and pollution source N The first sampling contribution value, the target water diversion project contribution value and the target water diversion project contribution value N The second sampling contribution value is used to generate a pollution risk assessment report for the target water diversion project; According to the pollution source i Detection data and pollution sources of various pollutants i The first sampling weight of each pollutant to determine the pollution source i The first sampling contribution value, from the pollution source i of N Select the pollution source from the first sampling contribution value i The contribution value of pollution i pollutants j of N Select pollution sources from the first sampling weight i pollutants j The weights include: Step 1.1: Sources of contamination for the first sampling i pollutants j The first sampling weight p ij(1) is the preset initial pollutant weight; n -1) Pollution sources of secondary sampling i pollutants j The first sampling weight p ij(n-1) and pollution sources i pollutants j Test data X ij The standardized result of the product of n Sub-sampling pollution sources i pollutants j The first sampling weight p ij(n) ; Step 1.2: According to n Sub-sampling pollution sources i pollutants j The first sampling weight p ij(n) and pollution sources i pollutants j Test data X ij ,use , calculate the n Sub-sampling pollution sources i The first sample contribution value WQI i(n) ,in, k is the total amount of pollutants, n =1,2,3,……, N , N To specify the number of sampling times; Step 1.3: Repeat steps 1.1 and 1.2 until the specified number of sampling times is completed. N ,get N pollution sources i The first sample contribution value WQI i(n) ; Step 1.4: According to the pollution source i The first sample contribution value of N samples WQI i(n) The frequency of occurrence of i Contribution value WQI i ; Step 1.5: Connect with the pollution source i Contribution value WQI i The same sampling times n Sub-sampling pollution sources i pollutants j The first sampling weight p ij(n) , identified as a pollution source i pollutants j Weight p ij .

2. The water body composite pollution source risk assessment method based on the weight of evidence method according to claim 1 is characterized in that: The acquisition of pollutant detection data of various pollution sources along the target water diversion project includes: At any testing time point, collect the concentration of the pollutants to be tested from each pollution source along the target water diversion project; Preprocessing the collected pollutant concentrations, converting the pollutant concentrations after removing invalid characters into floating point numbers for numerical calculation; The ratio of the pollutant concentration after pretreatment to the associated pollutant concentration standard value is used as the standardized pollutant concentration; The pollution source i pollutants j The average value of the standardized pollutant concentration at each detection time point is used as the pollution source i pollutants j 's detection data.

3. The water body composite pollution source risk assessment method based on the weight of evidence method according to claim 1 is characterized in that: The second sampling contribution value of the target water diversion project is determined according to the contribution value of each pollution source along the target water diversion project and the second sampling weight of each pollution source. N The contribution value of the target water diversion project is selected from the second sampling contribution value, and the contribution value of the target water diversion project is selected from the pollution source. i of N The pollution source is selected from the second sampling weight i The weights include: Step 2.1: Sources of contamination for the first sampling i The second sampling weight q i(1) is the preset initial pollution source weight; n -1) Pollution sources of secondary sampling i The second sampling weight q i(n-1) With the first n -1) Pollution sources of secondary sampling i The first sample contribution value WQI i(n-1) The standardized result of the average value is taken as the n Sub-sampling pollution sources i The second sampling weight q i(n) ; Step 2.2: According to n Sub-sampling pollution sources i The second sampling weight q i(n) and n Sub-sampling pollution sources i The first sample contribution value WQI i(n) ,use , calculate the n The second sampling contribution value of the target water diversion project WQI (n) ,in, g is the total number of pollution sources, n= 1,2,3,……, N , N To specify the number of sampling times; Step 2.3: Repeat steps 2.1 and 2.2 until the specified number of sampling times is completed. N ,get N The second sampling contribution value of the target water diversion project WQI (n) ; Step 2.4: Water diversion project according to target N The second sample contribution value of the subsample WQI (n) The frequency of occurrence of the target water diversion project is used to determine the contribution value of the target water diversion project. WQI ; Step 2.5: Compare the contribution value of the target water diversion project to the WQI The same sampling times n Sub-sampling pollution sources i The second sampling weight q i(n) , identified as a pollution source i Weight q i .

4. The water body composite pollution source risk assessment method based on the weight of evidence method according to claim 1 is characterized in that: The pollutant weight, pollution source weight, pollution source contribution value and pollution source N The first sampling contribution value, the target water diversion project contribution value and the target water diversion project contribution value N The second sampling contribution value is used to generate a pollution risk assessment report for the target water diversion project, including: According to pollution source i pollutants j Weight p ij , identify the pollution source i The main pollutants, secondary pollutants, and weakly related pollutants; according to the pollution source i Contribution value WQI i , and the preset pollution source contribution value classification rules to determine the pollution source i The pollution level; the pollution source i of N First sample contribution WQI i(n) Distribution map of According to pollution source i Weight q i , determine the main pollution sources, secondary pollution sources, and weakly related pollution sources of the target water diversion project; according to the contribution value of the target water diversion project WQI , and the preset target water diversion project contribution value classification rules to determine the pollution level of the target water diversion project; generate the target water diversion project N Second sampling contribution WQI (n) distribution map.

5. The water body composite pollution source risk assessment method based on the weight of evidence method according to claim 1 or claim 3 is characterized in that: The preset initial pollution source weights of source water, water transfer along the line, and reservoir are 0.4, 0.4, and 0.2 respectively; the preset initial pollutant weights of permanganate index, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, copper, zinc, fluoride, arsenic, lead, fecal coliform group, sulfate, chloride, nitrate, iron, and manganese are 0.06, 0.07, 0.06,0.10, 0.09, 0.09, 0.04, 0.04, 0.03, 0.09, 0.09, 0.06, 0.04, 0.04, 0.06, 0.02, and 0.02 respectively.

6. The water body composite pollution source risk assessment method based on the weight of evidence method according to claim 1 is characterized in that: The risk assessment method further comprises: Obtain the location of the water area through which the target water diversion project flows, the water area flow rate, the scale of factories, residences, and public facilities along the route, and the scale of ecological protection zones, nature reserves, and parks and green spaces along the route, and generate corresponding feature vectors; The K-means clustering method is used to cluster the target water diversion projects and the water diversion projects that have been completed according to the characteristic vector of the target water diversion project, the pollutant weight of the pollution source, the pollution source weight, the pollution source contribution value, and the contribution value of the target water diversion project; Based on the treatment measures of completed water diversion projects that belong to the same category as the target water diversion project, reference treatment measures for the target water diversion project are generated.

7. A water body composite pollution source risk assessment device based on the weight of evidence method, characterized in that: The risk assessment device comprises: The data acquisition module is used to obtain pollutant detection data from various pollution sources along the target water diversion project. Pollution sources include source water, water diversion along the route, and reservoirs. The pollutants to be detected from each pollution source include permanganate index, chemical oxygen demand, five-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, copper, zinc, fluoride, arsenic, lead, fecal coliform bacteria, sulfate, chloride, nitrate, iron, and manganese. The first selection module is used to select the pollution source i Detection data and pollution sources of various pollutants i The first sampling weight of each pollutant to determine the pollution source i The first sampling contribution value, from the pollution source i of N Select the pollution source from the first sampling contribution value i The contribution value of pollution i pollutants j of N Select pollution sources from the first sampling weight i pollutants j The weight of The second selection module is used to determine the second sampling contribution value of the target water diversion project according to the contribution value of each pollution source along the target water diversion project and the second sampling weight of each pollution source. N The contribution value of the target water diversion project is selected from the second sampling contribution value, and the contribution value of the target water diversion project is selected from the pollution source. i of N The pollution source is selected from the second sampling weight i The weight of Report generation module is used to generate reports based on the pollutant weight, pollution source weight, pollution source contribution value and pollution source N The first sampling contribution value, the target water diversion project contribution value and the target water diversion project contribution value N The second sampling contribution value is used to generate a pollution risk assessment report for the target water diversion project; The first selection module, based on the pollution source i Detection data and pollution sources of various pollutants i The first sampling weight of each pollutant to determine the pollution source i The first sampling contribution value, from the pollution source i of N Select the pollution source from the first sampling contribution value i The contribution value of pollution i pollutants j of N Select pollution sources from the first sampling weight i pollutants j The weights include: Step 1.1: Sources of contamination for the first sampling i pollutants j The first sampling weight p ij(1) is the preset initial pollutant weight; n -1) Pollution sources of secondary sampling i pollutants j The first sampling weight p ij(n-1) and pollution sources i pollutants j Test data X ij The standardized result of the product of n Sub-sampling pollution sources i pollutants j The first sampling weight p ij(n) ; Step 1.2: According to n Sub-sampling pollution sources i pollutants j The first sampling weight p ij(n) and pollution sources i pollutants j Test data X ij ,use , calculate the n Sub-sampling pollution sources i The first sample contribution value WQI i(n) ,in, k is the total amount of pollutants, n =1,2,3,……, N , N To specify the number of sampling times; Step 1.3: Repeat steps 1.1 and 1.2 until the specified number of sampling times is completed. N ,get N pollution sources i The first sample contribution value WQI i(n) ; Step 1.4: According to the pollution source i The first sample contribution value of N samples WQI i(n) The frequency of occurrence of i Contribution value WQI i ; Step 1.5: Connect with the pollution source i Contribution value WQI i The same sampling times n Sub-sampling pollution sources i pollutants j The first sampling weight p ij(n) , identified as a pollution source i pollutants j Weight p ij .

8. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate via the bus, and the processor executes the machine-readable instructions to perform the steps of the method for risk assessment of complex pollution sources in water bodies based on the weight of evidence method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the method for risk assessment of composite pollution sources in water bodies based on the weight of evidence method as described in any one of claims 1 to 6.

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