Pollution tracing method and system based on data analysis

Abstract

The invention relates to the technical field of river water pollution detection, and particularly discloses a pollution tracing method and system based on data analysis, and the system comprises a region division module which is used for dividing a river body into a plurality of regions with the same area, and dividing the river body into a plurality of detection regions according to a fixed depth interval, a data acquisition module acquires water body data information of different depths in a river body in different areas, and analyzes water body pollution conditions in the different areas according to the data, and parameters used in the analysis process are water body data obtained by detection of a plurality of detection areas at fixed depth intervals in the river body. According to the method and the system, the real pollution condition of the water body can be completely reflected, so that the accuracy of the analysis result of the pollution condition of the water body in different areas is ensured, the future pollution condition of the water body in different areas is analyzed, an early warning effect can be achieved, and environmental pollution is effectively prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of river water pollution detection, and specifically to a pollution source tracing method and system based on data analysis. Background Art

[0002] The main purpose of river water pollution monitoring is to timely and accurately grasp the water quality status of the river water, discover potential pollution sources, trace them in time, take corresponding treatment measures, prevent the water quality from deteriorating further, and thus protect water resources and the ecological environment.

[0003] Common water pollution detection and tracing systems in the prior art mainly rely on manual inspections and regular sampling and analysis. By collecting water body data information in various regions of the river body and analyzing and comparing the collected water body data information with the preset water body data information, the water pollution situation in the river body is analyzed. Then, combined with the monitoring situation of the river body water quality pollution, the sewage discharge inlets in the regions with higher pollution levels are checked to achieve traceability management.

[0004] When the common water pollution detection and tracing systems in the prior art are in use, generally, the water body data information in various regions of the river body is collected for analysis. However, there are differences in the water body data at different depths in the water body. On this premise, traditional water body data collection only collects the water body data information at a certain depth in the water body, and this data cannot fully reflect the true pollution situation of the water body, resulting in deviations in the subsequent judgment of the water pollution situation in the river body and affecting the accuracy of water pollution detection results and traceability. Summary of the Invention

[0005] The purpose of the present invention is to provide a pollution source tracing method and system based on data analysis, and solve the following technical problems:

[0006] How to improve the accuracy of water pollution detection results.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] A pollution source tracing method and system based on data analysis, the system includes:

[0009] A regional division module, used to divide the river body into multiple regions with the same area, and divide the river body into multiple detection regions at fixed depth intervals;

[0010] A data collection module, used to collect water body data information at different depths in the river body in different regions;

[0011] A data analysis module, used to analyze the water pollution situation in different regions by combining the water body data information at different depths in the river body in different regions collected by the data collection module;

[0012] A data prediction module, which is used to analyze the future pollution situation of water bodies in different regions by combining the analysis data of the data analysis module;

[0013] A pollution source tracing module, which is used to trace the pollution sources in the river body by combining the data analyzed by the data analysis module and the data prediction module.

[0014] Furthermore, the water body information collected by the data collection module includes: dissolved oxygen content, organic carbon content, ammonia nitrogen content, sediment thickness, and heavy metal content.

[0015] Furthermore, the analysis process of the data analysis module includes:

[0016] Through the formula Calculate the water body pollution index t of the a-th detection area in the i-th area of the river body during one data collection ai ;

[0017] Wherein, i is any area divided by the river body, a is any detection area in the river body, rjy ai Is the dissolved oxygen content of the a-th detection area in the i-th area of the river body, yjy y Is the preset dissolved oxygen content, yjt ai Is the organic carbon content of the a-th detection area in the i-th area of the river body, yjt y Is the preset organic carbon content, ad ai Is the ammonia nitrogen content of the a-th detection area in the i-th area of the river body, ad y Is the preset ammonia nitrogen content, zxh ai Is the heavy metal content of the a-th detection area in the i-th area, zxh y Is the preset heavy metal content, x1, x2, x3 and x4 are weight coefficients, rj i Is the total water volume of the i-th area of the river body, dn i Is the sediment thickness of the i-th area of the river body, dn y Is the preset sediment thickness, dn b Is dn i The standard value of, f m Is a defined function, if f m (x) ≥ x, then let f m (x) = x, otherwise, let f m (x) = 1.

[0018] Furthermore, the analysis process of the data analysis module also includes:

[0019] Through the formula Calculate the average water body pollution index r of the i-th area during one data collectioni ;

[0020] Among them, b is the total number of detection areas divided in the river body, and y a is the weight coefficient of the a-th detection area, which is set according to empirical fitting, is the average value of all t ai .

[0021] Furthermore, the analysis process of the data analysis module also includes:

[0022] By comparing the average water pollution index r i in the i-th area during the first data collection with the preset pollution index threshold r 01 ;

[0023] If r i ≥r 01 , the system determines that the water body in the i-th area is polluted, which means there is a sewage discharge phenomenon at the sewage outlet in the river body, and traceability inspections are carried out on several areas with the highest average water pollution index according to the size of the average water pollution index in all areas;

[0024] If r i <r 01 , the system determines that the water body in the i-th area has not yet reached the pollution standard temporarily, and no traceability inspection is carried out temporarily, and the data prediction module is used to further analyze the change of water pollution in different areas.

[0025] Furthermore, the prediction process of the data prediction module includes:

[0026] By continuously monitoring through the data analysis module, the average water pollution index r i in the i-th area during the first data collection is obtained, and a change curve δ i (t) of the average water pollution index in the i-th area is established;

[0027] And through the formula the average change amount ρ i of the average water pollution index in the i-th area during the continuous monitoring process is calculated;

[0028] Among them, t1 is the start time point of continuous monitoring by the data analysis module, t2 is the end time point of continuous monitoring by the data analysis module, g is a proportionality coefficient, which is set according to empirical fitting, is the maximum value among all r i , is the minimum value among all r i .

[0029] Furthermore, the prediction process of the data prediction module also includes:

[0030] By comparing the average change amount ρ of the average pollution index of the water body in the i-th area during continuous monitoring i with a preset change amount threshold ρ 01 for comparison;

[0031] If ρ i < ρ 01 , the system determines that during continuous monitoring, the average pollution index of the water body in the i-th area has not increased significantly, which means that the water body situation is stable and there will be no pollution situation in the future for a period of time;

[0032] If ρ i ≥ ρ 01 , the system determines that during continuous monitoring, the average pollution index of the water body in the i-th area has increased significantly, which means that the water body situation is unstable and there may be a pollution situation in the future for a period of time, and timely traceability inspections are carried out on several areas with relatively high average pollution indices of the water body.

[0033] A pollution traceability method based on data analysis, the method comprising:

[0034] S1: Divide the river body into multiple areas of the same area through a regional division module, and divide the river body into multiple detection areas at fixed depth intervals;

[0035] S2: Collect water body data information at different depths in the river body in different areas through a data collection module;

[0036] S3: Analyze the water body pollution situation in different areas through a data analysis module in combination with the water body data information at different depths in the river body collected by the data collection module;

[0037] S4: Analyze the future pollution situation of the water body in different areas through a data prediction module in combination with the analysis data of the data analysis module;

[0038] S5: Trace the pollution source in the river body through a pollution traceability module in combination with the data analyzed by the data analysis module and the data prediction module.

[0039] Advantages of the present invention:

[0040] (1) The present invention collects water body data information at different depths in the river bodies of different regions through a data collection module, and analyzes the water body pollution conditions in different regions based on this data. Since the parameters used in this analysis process are based on the water body data obtained from multiple detection regions at fixed depth intervals within the river body, the accuracy of this data is relatively high, which can fully reflect the true pollution situation of the water body, thereby ensuring the accuracy of the analysis results of the water body pollution conditions in different regions. Moreover, by analyzing the future pollution situation of the water bodies in different regions, it can also play a role in early warning and effectively prevent the occurrence of environmental pollution.

[0041] (2) The present invention compares the average pollution index r of the water body in the i-th region during the first data collection i with the preset pollution index threshold r 01 . Since this data is obtained by fusing and calculating the pollution indices of water bodies at different depths within the same region, through this comparison method, an accurate judgment can be made on whether there is pollution in the water body in the i-th region, thereby avoiding the situation where the true pollution situation of the water body cannot be reflected due to only collecting the water body data information at a certain depth within the water body, and further improving the accuracy of the subsequent analysis results of the water body pollution situation in the river body.

[0042] (3) The present invention compares the average change amount ρ of the average pollution index of the water body in the i-th region during continuous monitoring i with the preset change amount threshold ρ 01 . Through this comparison method, an accurate judgment can be made on whether there is a significant increase in the average pollution index of the water bodies in different regions during continuous monitoring. The analysis result can reflect the change in the content of pollutants in the water body over a period of time. Combining this data, a judgment can be made on whether pollution will occur in the future for a period of time, thereby achieving the effect of early warning and facilitating the development of traceability operations.

[0043] (4) The present invention analyzes the water body pollution conditions in different regions by combining the water body data information at different depths in the river bodies of different regions. Since the collected water body data information is based on the water bodies in different regions and at different depths, the obtained data can reflect the true pollution situation of the water bodies in different regions, thereby ensuring that when analyzing the water body pollution conditions in different regions based on this data, the accuracy of the analysis results can be improved, thereby improving the accuracy of the water body pollution detection results, and further ensuring the accuracy of the traceability results. Description of the Drawings

[0044] The present invention will be further described below with reference to the accompanying drawings.

[0045] Figure 1It is a schematic block diagram of a pollution source tracing system based on data analysis in the present invention;

[0046] Figure 2 It is a flowchart of a pollution source tracing method based on data analysis in the present invention. Specific embodiments

[0047] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0048] Please refer to Figure 1 As shown, in one embodiment, the present application provides a pollution source tracing method and system based on data analysis. The system includes:

[0049] A regional division module, configured to divide the river body into multiple regions with the same area, and divide the river body into multiple detection regions at fixed depth intervals;

[0050] A data acquisition module, configured to acquire water body data information at different depths in the river body of different regions;

[0051] A data analysis module, configured to analyze the water body pollution conditions in different regions by combining the water body data information at different depths in the river body of different regions acquired by the data acquisition module;

[0052] A data prediction module, configured to analyze the future pollution conditions of the water body in different regions by combining the analysis data of the data analysis module;

[0053] A pollution source tracing module, configured to trace the pollution sources in the river body by combining the data analyzed by the data analysis module and the data prediction module;

[0054] Through the above technical solution, this embodiment provides a regional division module, which is used to divide the river body into multiple regions with the same area and divide the river body into multiple detection regions at fixed depth intervals. When conducting water quality pollution detection, first, the data acquisition module collects water body data information at different depths in the river body in different regions, and the data analysis module combines the water body data information at different depths in the river body in different regions collected by the data acquisition module to analyze the water body pollution conditions in different regions. If it is determined that there is a water body pollution situation, the pollution source tracing module can trace the pollution source in the river body according to the severity of the water body pollution in different regions. If it is determined that there is no water body pollution situation, the data prediction module combines the analysis data of the data analysis module to analyze the future pollution situation of the water body in different regions. If it is determined that the water body may be polluted in the future, the pollution source tracing module can trace the pollution source in the river body according to the water body pollution situation in different regions;

[0055] Through the above technical solution, the data acquisition module collects water body data information at different depths in the river body in different regions, and analyzes the water body pollution conditions in different regions based on this data. Since the parameters used in this analysis process are based on the water body data obtained from the detection of multiple detection regions in the river body at fixed depth intervals, the accuracy of this data is relatively high, which can fully reflect the true pollution situation of the water body, thus ensuring the accuracy of the analysis results of the water body pollution conditions in different regions. And by analyzing the future pollution situation of the water body in different regions, it can also play a role in early warning and effectively prevent the occurrence of environmental pollution.

[0056] The water body information collected by the data acquisition module includes: dissolved oxygen content, organic carbon content, ammonia nitrogen content, sediment thickness, and heavy metal content;

[0057] Through the above technical solution, this example provides the water body information collected by the data acquisition module, including dissolved oxygen content, organic carbon content, ammonia nitrogen content, sediment thickness, and heavy metal content. By collecting and monitoring this data, it can provide accurate data for subsequent analysis of the water body pollution conditions in different monitoring regions in different regions of the river body, thereby improving the accuracy of subsequent analysis results.

[0058] The analysis process of the data analysis module includes:

[0059] Through the formula Calculate the water body pollution index t of the a-th detection region in the i-th region of the river body during one data collection ai ;

[0060] where, i is any region divided by the river body, a is any detection region in the river body, rjy aiis the dissolved oxygen content of the ath detection area in the ith area of the river body, rjy y is the preset dissolved oxygen content, yjt ai is the organic carbon content of the ath detection area in the ith area of the river body, yjt y is the preset organic carbon content, ad ai is the ammonia nitrogen content of the ath detection area in the ith area of the river body, ad y is the preset ammonia nitrogen content, zxh ai is the heavy metal content of the ath detection area in the ith area of the river body, zxh y is the preset heavy metal content, x1, x2, x3 and x4 are weight coefficients, rj i is the total amount of water in the ith area of the river body, dn i is the sediment thickness in the ith area of the river body, dn y is the preset sediment thickness, dn b is dn i is the standard value of dn. The above standard value can be selected and set according to the allowable error in the empirical data, f m is a defined function. If f m (x)≥x, then let f m (x)=x, otherwise, let f m (x)=1;

[0061] Through the above technical solution, this embodiment provides the water body pollution index t of the ath detection area in the ith area of the river body during one data collection ai , which can be obtained by the formula Obviously, when the dissolved oxygen content of the ath detection area in the ith area of the river body is lower, the organic carbon content, ammonia nitrogen content and heavy metal content are higher, and the sediment thickness in the ith area of the river body is thicker, then the water body pollution index t of the ath detection area in the ith area of the river body ai is higher, indicating that the water body in the current depth detection area of this area of the river body is polluted. On the contrary, when the dissolved oxygen content of the ath detection area in the ith area of the river body is higher, the organic carbon content, ammonia nitrogen content and heavy metal content are lower, and the sediment thickness in the ith area of the river body is thinner, then the water body pollution index t of the ath detection area in the ith area of the river body ai is lower, indicating that the water body in the current depth detection area of this area of the river body is not polluted;

[0062] By setting like this, based on the water body information collected by the data collection module and assigning different weights to the data parameters, the water body pollution index t of the ath detection area in the ith area of the river body during one data collection can be obtained aiMake an accurate calculation. This data can reflect the water body pollution situation in the a-th detection area within the i-th area of the river body, thus providing accurate data support for subsequent analysis of the overall pollution situation in the i-th area of the river body to ensure the accuracy of the analysis results.

[0063] The analysis process of the data analysis module further includes:

[0064] Through the formula Calculate the average water body pollution index r in the i-th area during one data collection i ;

[0065] Where b is the total number of detection areas divided in the river body, y a Is the weight coefficient of the a-th detection area, set according to empirical fitting, Is the average value of all t ai ;

[0066] Through the above technical solution, this embodiment provides the average water body pollution index r in the i-th area during one data collection i , which can be calculated through the formula By this calculation method, after combining the water body pollution indexes t of all detection areas in the i-th area of the river body during one data collection ai , the average water body pollution index r in the i-th area i Can be calculated. Since this data integrates the pollution indexes of water bodies at different depths in the same area, the accuracy of the calculation result of this data can be ensured.

[0067] The analysis process of the data analysis module further includes:

[0068] By comparing the average water body pollution index r in the i-th area during one data collection i With the preset pollution index threshold r 01 For comparison;

[0069] If r i ≥r 01 , the system determines that the water body in the i-th area is polluted, which means there is a sewage discharge phenomenon at the sewage outlet in the river body, and traceability inspections are carried out on the areas with the highest average water body pollution indexes according to the magnitudes of the average water body pollution indexes in all areas;

[0070] If r i <r 01 , the system determines that the water body in the i-th area has not yet reached the pollution standard temporarily, and no traceability inspection is carried out temporarily, and the data prediction module is used to further analyze the changes in water body pollution in different areas;

[0071] Through the above technical solution, in this embodiment, the average pollution index r of the water body in the i-th area during the first data collection i is compared with the preset pollution index threshold r 01 . Since this data is obtained by fusing the pollution indices of water bodies at different depths within the same area, through this comparison method, an accurate judgment can be made on whether the water body in the i-th area is polluted, thereby avoiding the inability to reflect the true pollution situation of the water body due to only collecting the water body data information at a certain depth in the water body, and further improving the accuracy of the subsequent analysis results of the water body pollution situation in the river.

[0072] The prediction process of the data prediction module includes:

[0073] Continuously monitor through the data analysis module to obtain the average pollution index r of the water body in the i-th area during the first data collection i , and establish the change curve δ i (t) of the average pollution index of the water body in the i-th area;

[0074] And calculate the average change amount ρ of the average pollution index of the water body in the i-th area during the continuous monitoring process through the formula i ;

[0075] wherein, t1 is the start time point of continuous monitoring by the data analysis module, t2 is the end time point of continuous monitoring by the data analysis module, g is a proportionality coefficient, set by empirical fitting, is the maximum value among all r i , is the minimum value among all r i ;

[0076] Through the above technical solution, this example provides the average change amount ρ i of the average pollution index of the water body in the i-th area during the continuous monitoring process, which can be calculated through the formula . Through this calculation method, by combining the average pollution index of the water body in the i-th area over a period of time, the change amount of this data can be calculated, and the calculation result can reflect the change situation of the average pollution index of the water body in the i-th area over a period of time, thereby providing data support for subsequent analysis of whether pollution will occur in the i-th area in the future, and further ensuring the accuracy of the analysis results.

[0077] The prediction process of the data prediction module further includes:

[0078] By comparing the average change amount ρ i of the average pollution index of the water body in the i-th area during the continuous monitoring process with the preset change amount threshold ρ01 Make a comparison;

[0079] If ρ i < ρ 01 , the system judges that during the continuous monitoring process, the average pollution index of the water body in the i-th area has not increased significantly, which means that the water body situation is stable and there will be no pollution situation in the future for a period of time;

[0080] If ρ i ≥ ρ 01 , the system judges that during the continuous monitoring process, the average pollution index of the water body in the i-th area has not increased significantly, which means that the water body situation is unstable and there may be a pollution situation in the future for a period of time, and timely traceability inspections are carried out on several areas with relatively high average pollution indices of the water body;

[0081] Through the above technical solution, in this embodiment, the average change amount ρ i of the average pollution index of the water body in the i-th area during the continuous monitoring process is 01 compared with the preset change amount threshold ρ. Through this comparison method, it is possible to accurately judge whether the average pollution index of the water body in different areas has increased significantly during the continuous monitoring process. The analysis result can reflect the change of the content of pollutants in the water body over a period of time. Combining this data, it is possible to judge whether there will be a pollution situation in the future for a period of time, so as to achieve the effect of early warning and facilitate the development of traceability operations.

[0082] Please refer to Figure 2 shown, a pollution traceability method based on data analysis, the method includes:

[0083] S1: Divide the river body into multiple areas with the same area through the area division module, and divide the river body into multiple detection areas at fixed depth intervals;

[0084] S2: Collect water body data information at different depths in the river body in different areas through the data collection module;

[0085] S3: Analyze the water body pollution situation in different areas through the data analysis module in combination with the water body data information at different depths in the river body collected by the data collection module;

[0086] S4: Analyze the future pollution situation of the water body in different areas through the data prediction module in combination with the analysis data of the data analysis module;

[0087] S5: Trace the pollution source in the river body through the pollution traceability module in combination with the data analyzed by the data analysis module and the data prediction module;

[0088] Through the above technical solution, this embodiment provides a pollution source tracing method based on data analysis. First, the river body is divided into multiple regions with the same area by the regional division module, and multiple detection regions are divided from the river body at fixed depth intervals. Then, the water body data information at different depths in the river body of different regions is collected by the data collection module. After that, the water body pollution conditions in different regions are analyzed by the data analysis module in combination with the water body data information at different depths in the river body of different regions collected by the data collection module. When it is determined that there is water body pollution, the pollution source in the river body is traced by the pollution source tracing module. Otherwise, the future pollution conditions of the water body in different regions are analyzed by the data prediction module in combination with the analysis data of the data analysis module, and it is decided whether a tracing inspection is required according to the analysis results;

[0089] Through the above technical solution, this example analyzes the water body pollution conditions in different regions by combining the water body data information at different depths in the river body of different regions. Since the collected water body data information is based on the water bodies in different regions and at different depths, the obtained data can reflect the real pollution conditions of the water bodies in different regions, thus ensuring that when analyzing the water body pollution conditions in different regions based on this data, the accuracy of the analysis results can be improved, thereby improving the accuracy of the water body pollution detection results, and further ensuring the accuracy of the tracing results.

[0090] The above has described a detailed description of an embodiment of the present invention, but the content described is only the preferred embodiment of the present invention and cannot be considered as used to limit the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A pollution source tracing system based on data analysis, characterized in that: The system comprises: The area division module is used to divide the river body into multiple areas of equal area, and divide the river body into multiple detection areas at fixed depth intervals; The data collection module is used to collect water data information at different depths in rivers in different areas; The data analysis module is used to analyze the water pollution situation in different areas by combining the water body data information of different depths in the river body in different areas collected by the data collection module; The data prediction module is used to analyze the future pollution of water bodies in different areas by combining the analysis data of the data analysis module; The pollution source tracing module is used to trace the pollution sources in the river body by combining the data analyzed by the data analysis module and the data prediction module.

2. A pollution source tracing system based on data analysis according to claim 1, characterized in that: The water body information collected by the data collection module includes: dissolved oxygen content, organic carbon content, ammonia nitrogen content, sediment thickness and heavy metal content.

3. A pollution source tracing system based on data analysis according to claim 2, characterized in that: The analysis process of the data analysis module includes: By formula Calculate the water pollution index t of the ath detection area in the i-th area of ​​the river during a data collection ai ; Among them, i is any area divided by the river, a is any detection area in the river, rjy ai is the dissolved oxygen content of the ath detection area in the ith area of ​​the river, rjy y is the preset dissolved oxygen content, yjt ai is the organic carbon content of the ath detection area in the ith area of ​​the river body, yjt y To preset the organic carbon content, ad ai is the ammonia nitrogen content in the ath detection area in the ith area of ​​the river body, ad y is the preset ammonia nitrogen content, zxh ai is the heavy metal content of the ath detection area in the ith area, zxh y is the preset heavy metal content, x1, x2, x3 and x4 are weight coefficients, rj i is the total amount of water in the ith area of ​​the river, dn i is the thickness of the sediment in the ith area of ​​the river, dn y is the preset sediment thickness, dn b dn i The standard value, f m To define a function, if f m (x)≥x, then let f m (x) = x, otherwise, let f m (x)=1.

4. A pollution source tracing system based on data analysis according to claim 3, characterized in that: The analysis process of the data analysis module also includes: By formula Calculate the average water pollution index r in the i-th area during a data collection i ; Among them, b is the total number of detection areas divided in the river, y a is the weight coefficient of the ath detection area, which is set according to empirical fitting. For all t ai The average value of .

5. A pollution source tracing system based on data analysis according to claim 4, characterized in that: The analysis process of the data analysis module also includes: The average water pollution index r in the ith area during a data collection is calculated i and the preset pollution index threshold r 01 Make a comparison; If r i ≥r 01 , the system determines that the water in the i-th area is polluted, which means that there is a sewage outlet in the river body, and according to the average water pollution index of all areas, the system conducts source tracing inspection on the areas with the highest average water pollution index; If r i <r 01 The system determines that the water in the i-th area has not yet reached the pollution standard, and does not conduct a source traceability inspection for the time being. It further analyzes the changes in water pollution in different areas through the data prediction module.

6. A pollution source tracing system based on data analysis according to claim 5, characterized in that: The prediction process of the data prediction module includes: The average water pollution index r in the i-th area during a data collection is obtained through continuous monitoring by the data analysis module i , establish the variation curve of the average water pollution index in the i-th region δ i (t); And through the formula Calculate the average change ρ of the average water pollution index in the i-th area during continuous monitoring i ; Among them, t1 is the start time point of continuous monitoring of the data analysis module, t2 is the end time point of continuous monitoring of the data analysis module, and g is the proportional coefficient, which is set according to empirical fitting. For all r i The maximum value in For all r i The minimum value in .

7. A pollution source tracing system based on data analysis according to claim 6, characterized in that: The prediction process of the data prediction module also includes: The average change of the average water pollution index in the i-th region during the continuous monitoring process is calculated as i The preset change threshold ρ 01 Make a comparison; If i < 01 ,The system judges that during the continuous monitoring process, the average pollution index of the water body in the ith area has not increased significantly, which means that the water body is stable and there will be no pollution in the future; If i ≥ρ 01 The system determines that during the continuous monitoring process, the average water pollution index in the i-th area has not increased significantly, which means that the water situation is unstable and pollution may occur in the future. It also promptly conducts source tracing inspections on several areas with relatively high average water pollution indexes.

8. A pollution source tracing method based on data analysis, characterized in that: The method adopts a pollution source tracing system based on data analysis as claimed in claim 1, and the method comprises: S1: The river body is divided into multiple regions of equal area through the region division module, and the river body is divided into multiple detection areas according to fixed depth intervals; S2: Collect water data information of different depths in rivers in different areas through the data acquisition module; S3: Analyze the water pollution situation in different areas by combining the water body data information of different depths in the river body in different areas collected by the data analysis module and the data collection module; S4: Analyze the future pollution of water bodies in different areas by combining the data prediction module with the analysis data of the data analysis module; S5: The pollution source tracing module is combined with the data analyzed by the data analysis module and the data prediction module to trace the pollution source in the river.

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