Water quality pollution monitoring system and method

Abstract

The invention discloses a water quality pollution monitoring system and method, and relates to the field of water quality pollution monitoring. The system comprises a region division and sampling point layout module, a deviation analysis module, a first monitoring region analysis module and a second monitoring region analysis module, the region division and sampling point layout module analyzes the pollution source characteristics of the to-be-monitored region, reasonably divides the monitoring region and arranges sampling points; the deviation analysis module is used for performing deviation analysis on data of adjacent sampling points after water quality samples are collected, so as to ensure the accuracy and consistency of the data; the first monitoring area analysis module is combined with a water quality fluorescence fingerprint analysis technology to carry out matching and tracing on a known pollution source and accurately identify the position of the pollution source; and the second monitoring area analysis module gradually confirms the specific position of the pollution source by analyzing the water sample flowing path.

Description

Technical Field

[0001] The present invention relates to the field of water pollution monitoring, and in particular to a water pollution monitoring system and method. Background Art

[0002] Current water pollution monitoring technology mainly relies on the detection of traditional water quality indicators (such as chemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, etc.). Although these indicators can identify basic pollution conditions in water quality in some cases, in the monitoring of organic pollutants, traditional technologies are often unable to accurately distinguish the types of pollution sources, thereby limiting the effectiveness of pollution source tracing.

[0003] To address this issue, water quality fingerprinting technology has gradually become an important monitoring tool. However, existing technologies still face two key challenges in practical application: first, the placement of sampling points. Especially in complex environments such as sewage treatment plant inlets and river sections, how to rationally arrange sampling points to ensure that the collected water samples truly reflect the actual pollution source; second, the problem of water sample analysis. How to accurately identify pollution sources through data analysis remains a difficult problem facing current technologies. Summary of the Invention

[0004] The purpose of the present invention is to provide a water pollution monitoring system and method to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: The water pollution monitoring method comprises the following steps: Step S100: Acquire location information of the area to be monitored, extract pollution source characteristics from the location information, and divide the area to be monitored into a first monitoring area and a second monitoring area based on the pollution source characteristics; and arrange sampling points for water quality monitoring based on the classification of the area to be monitored; Step S200. Collect water samples in sequence according to the arranged water quality monitoring sampling points to obtain corresponding water quality monitoring data; perform deviation analysis on the water quality monitoring data of two adjacent sampling points, and adjust the sampling point density according to the deviation analysis results; Step S300: For the first monitoring area, the water samples at the corresponding sampling points are subjected to water quality fluorescence fingerprint analysis and matched with the water quality fluorescence fingerprints of known pollution sources in the pollution source database; based on the matching results, the suspected pollution source is identified and the location of the suspected pollution source is sent to relevant personnel; Step S400. For the second monitoring area, perform water sample flow path analysis, compare the water quality fluorescent fingerprints of cross-section water samples at different sampling points, and gradually confirm the location of the suspected pollution source based on the comparison results, and send the suspected pollution source location to relevant personnel.

[0006] Furthermore, step S100 includes: S101. Divide the area to be monitored into several sub-areas according to a preset minimum area. Obtain location information of the area to be monitored. For each sub-area, extract pollution source characteristics from the corresponding location information. Determine the category of the corresponding sub-area based on the pollution source characteristics. If a known pollution source is found in the pollution source characteristics of the sub-area, the sub-area is divided into a first monitoring area. If an unknown pollution source is found in the pollution source characteristics of the sub-area, the sub-area is divided into a second monitoring area. The first monitoring area has known pollution sources, such as sewage treatment plants and factory discharge points. The second monitoring area has unknown pollution sources, such as rivers, lakes, and other natural water bodies. S102. For the first monitoring area, obtain the corresponding drainage network structure diagram, identify the sewage outlet and the intersection point of the drainage pipe according to the drainage network structure diagram; obtain the historical sewage discharge data of the first monitoring area, and calculate the pollutant concentration Cp of each sewage outlet in combination with the historical sewage discharge data, and Cp = Mp / Qp, where Mp represents the total amount of pollutants discharged from the sewage outlet, and Qp represents the discharge flow of the sewage outlet; summarize the pollutant concentration Cp of all sewage outlets, and compare the pollutant concentration Cp of all sewage outlets with the preset pollutant concentration threshold C1 in turn, and select the sewage outlets with a pollutant concentration Cp greater than or equal to the pollutant concentration Cp. The sewage outlet with the pollutant concentration threshold C1 is recorded as the sampling point; the pollutant concentration Cj of each drainage pipe intersection is calculated, and Cj=∑ni=1(Qi×Ci) / ∑ni=1Qi, where Qi represents the flow rate of the i-th pipe, Ci represents the pollutant concentration of the i-th pipe, and n represents the number of pipes connected at the intersection; the pollutant concentration Cj of all drainage pipe intersections is summarized, and the pollutant concentration Cj of all drainage pipe intersections is compared with the preset pollutant concentration threshold C2 in turn, and the drainage pipe intersection with the pollutant concentration Cj greater than or equal to the pollutant concentration threshold C2 is recorded as the sampling point; S103. For the second monitoring area, obtain the flow direction and confluence relationship of all tributaries in the second monitoring area, so as to identify the confluence points in the second monitoring area, and use the confluence points as sampling points for the second monitoring area; according to the location of each confluence point and in combination with the flow direction of the corresponding tributary, follow the flow direction of the tributary and set the sampling points in sections according to the preset minimum sampling point distance.

[0007] Furthermore, step S200 includes: S201. For the first monitoring area and the second monitoring area, water samples are collected in sequence according to the arranged water quality monitoring sampling points, thereby obtaining corresponding water quality monitoring data. The collected water quality monitoring data are processed in sequence according to the monitoring areas and sampling points, thereby obtaining a first monitoring data set A and a second monitoring data set B, where A={a1,a2,...,au} and B={b1,b2,...,bv}, where a1 represents the water quality monitoring data of the first sampling point in the first monitoring area, a2 represents the water quality monitoring data of the second sampling point in the first monitoring area, and so on, au represents the water quality monitoring data of the u-th sampling point in the first monitoring area; similarly, b1 represents the water quality monitoring data of the first sampling point in the second monitoring area, b2 represents the water quality monitoring data of the second sampling point in the second monitoring area, and bv represents the water quality monitoring data of the v-th sampling point in the second monitoring area; u and v represent the number of sampling points in the first monitoring area and the second monitoring area, respectively. S202. Calculate, for each of the first monitoring dataset A and the second monitoring dataset B, a deviation index R of the water quality monitoring data of two adjacent sampling points. The corresponding calculation formula is: R = |f_k - f_k+1| / d_k, where f_k represents the water quality monitoring data of the kth sampling point in the first monitoring dataset A or the second monitoring dataset B, f_k+1 represents the water quality monitoring data of the k+1th sampling point in the first monitoring dataset A or the second monitoring dataset B, and d_k represents the distance between adjacent sampling points f_k and f_k+1 in the first monitoring dataset A or the second monitoring dataset B. Compare the deviation index R of the water quality monitoring data of the two adjacent sampling points with a threshold RT. If the deviation index R is greater than the threshold RT, insert a new sampling point between the two adjacent sampling points, output the location of the area between the two adjacent sampling points to relevant personnel, and have the relevant personnel increase the sampling point density in the current area. If the deviation index R is less than the threshold RT, merge the adjacent sampling points, output the location of the area between the two adjacent sampling points to relevant personnel, and have the relevant personnel reduce the sampling point density in the current area.

[0008] Furthermore, step S300 includes: S301. For the first monitoring area, perform water quality fluorescence fingerprint analysis on the corresponding sampling points to obtain water quality fluorescence fingerprint data corresponding to each sampling point; calculate the similarity between the water quality fluorescence fingerprint data of each sampling point and the water quality fluorescence fingerprint data of known pollution sources in the database; if the similarity result is greater than or equal to the similarity threshold, mark the corresponding sampling point as a suspected pollution source; S302. For sampling points with similarity less than the similarity threshold, obtain the water quality fluorescence fingerprint data of the sampling point upstream of this sampling point and perform similarity calculation. If the similarity is greater than or equal to the similarity threshold, the upstream sampling point is used as the target sampling point; calculate the similarity between the water quality fluorescence fingerprint data of the target sampling point and the sampling point upstream of it until the similarity is less than the similarity threshold, and mark the target sampling point as a suspected pollution source; output the location coordinates of the suspected pollution source to relevant personnel, who will perform corresponding processing. Among them, for sampling points with similarity less than the similarity threshold, it is necessary to continue tracing the source to the upstream sampling point, so the upstream sampling point is used as the target sampling point. This step is essentially to gradually eliminate irrelevant sampling points through similarity calculation until an area with water quality characteristics similar to the known pollution source is found; when the similarity is less than the similarity threshold, it means that continuing upstream tracing is invalid, and the pollution source may have been located in the target sampling point area, so the target sampling point is marked as a suspected pollution source.

[0009] Furthermore, step S400 includes: S401. For each sampling point in the second monitoring area, perform a water sample flow path analysis. Name the sampling section at the sampling point Section X, and name the sampling section at the upstream sampling point of the current sampling point Section Y. Analyze the similarity between the water quality fluorescence fingerprint data of the water samples corresponding to Sections X and Y. If the similarity is greater than or equal to a similarity threshold, it indicates that the suspected pollution source may be upstream of Section Y. Name the sampling section at the upstream sampling point of Section Y Section Z1. Analyze the similarity between the water quality fluorescence fingerprint data of the water samples corresponding to Sections X and Z1. If the similarity is greater than or equal to the similarity threshold, continue analyzing the similarity between Section X and the water quality fluorescence fingerprint data of the water samples corresponding to the sampling section at the upstream sampling point of Section Z1 until the similarity is less than the similarity threshold. Finally, identify the sampling points corresponding to Sections Y and Z1 as suspected pollution sources. S402. Analyze the similarity between the water quality fluorescence fingerprint data of the water samples corresponding to Section X and Section Z1. If the similarity is less than the similarity threshold, it indicates that the suspected pollution source may be between Sections Y and X. The sampling points corresponding to Sections X and Y are regarded as suspected pollution sources; the location coordinates of the suspected pollution source are output to relevant personnel for appropriate processing.

[0010] The water pollution monitoring system includes: an area division and sampling point layout module, a deviation analysis module, a first monitoring area analysis module, and a second monitoring area analysis module; The area division and sampling point layout module obtains the location information of the area to be monitored, extracts the pollution source characteristics from the location information, and divides the area to be monitored into a first monitoring area and a second monitoring area based on the pollution source characteristics; based on the classification of the area to be monitored, it layouts the sampling points for water quality monitoring; The deviation analysis module collects water samples in sequence according to the arranged water quality monitoring sampling points to obtain the corresponding water quality monitoring data; it performs deviation analysis on the water quality monitoring data of two adjacent sampling points and adjusts the sampling point density according to the deviation analysis results; The first monitoring area analysis module performs water quality fluorescence fingerprint analysis on water samples from the corresponding sampling points in the first monitoring area and matches them with the water quality fluorescence fingerprints of known pollution sources in the pollution source database; based on the matching results, the suspected pollution source is identified and the location of the suspected pollution source is sent to relevant personnel; The second monitoring area analysis module analyzes the flow path of water samples by comparing the water quality fluorescent fingerprints of cross-section water samples at different sampling points, and gradually confirms the location of suspected pollution sources based on the comparison results, and sends the location of suspected pollution sources to relevant personnel.

[0011] Furthermore, the region division and sampling point layout module includes a region division unit and a sampling point layout unit; The area division unit divides the area to be monitored into multiple sub-areas according to the preset minimum area, obtains the location information of each sub-area, and extracts the pollution source characteristics; based on the pollution source characteristics, it determines whether there is a known pollution source in each sub-area and classifies it as the first monitoring area or the second monitoring area; the sampling point layout unit layouts the sampling points for water quality monitoring based on the division category of the area to be monitored.

[0012] Furthermore, the deviation analysis module includes a data deviation calculation unit and a sampling point density adjustment unit; The data deviation calculation unit calculates the deviation index of the water quality monitoring data of two adjacent sampling points and compares it with the preset threshold; the sampling point density adjustment unit determines whether the sampling point density needs to be increased or decreased based on the deviation analysis results; if the deviation index is greater than the set threshold, the sampling points are increased; if the deviation index is less than the set threshold, the sampling points are reduced.

[0013] Furthermore, the first monitoring area analysis module includes a water quality fluorescence fingerprint analysis unit and a first pollution source identification unit; The water quality fluorescence fingerprint analysis unit performs fluorescence fingerprint analysis on the water samples at the sampling points in the first monitoring area and obtains the corresponding water quality fluorescence fingerprint data; the pollution source identification unit matches the water quality fluorescence fingerprint data of each sampling point with the water quality fluorescence fingerprint data of known pollution sources in the database, and identifies the suspected pollution source based on the matching results, and sends the location of the pollution source to relevant personnel.

[0014] Furthermore, the second monitoring area analysis module includes a water quality flow path analysis unit and a second pollution source identification unit; The water quality flow path analysis unit performs water sample flow path analysis on the second monitoring area; the second pollution source identification unit compares the water quality fluorescent fingerprints of cross-section water samples at different sampling points, and gradually confirms the location of the pollution source based on the comparison results, and sends the pollution source location to relevant personnel.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention divides the area to be monitored into a first monitoring area and a second monitoring area according to the characteristics of the pollution source, and adopts different sampling point layout methods for different areas to ensure the pertinence and accuracy of the monitoring work; for the known pollution sources in the first monitoring area, accurate monitoring is carried out by combining the sewage outlet and the pipe network structure diagram; and for the second monitoring area, the monitoring points are laid out according to the flow direction and confluence relationship, so as to fully cover the potential pollution source area. Through deviation analysis and data processing, the sampling point density can be dynamically adjusted according to the deviation of the monitoring data; the deviation index between adjacent sampling points is compared, and the number of sampling points is increased or decreased in time according to the results, thereby optimizing the layout of the sampling points and the monitoring accuracy; through the comparison of water quality fluorescent fingerprint data with known pollution sources, similarity calculation and other methods, the suspected pollution source can be effectively traced, and irrelevant sampling points can be gradually eliminated to finally locate the precise location of the pollution source; this step-by-step tracing method is more comprehensive than traditional single-point sampling or local area analysis, and can better deal with complex water pollution sources. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a module schematic diagram of the water pollution monitoring system of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0018] See also Figure 1 , the present invention provides a technical solution: The water pollution monitoring system includes: an area division and sampling point layout module, a deviation analysis module, a first monitoring area analysis module, and a second monitoring area analysis module; The area division and sampling point layout module obtains the location information of the area to be monitored, extracts the pollution source characteristics from the location information, and divides the area to be monitored into a first monitoring area and a second monitoring area based on the pollution source characteristics; based on the classification of the area to be monitored, it layouts the sampling points for water quality monitoring; The deviation analysis module collects water samples in sequence according to the arranged water quality monitoring sampling points to obtain the corresponding water quality monitoring data; it performs deviation analysis on the water quality monitoring data of two adjacent sampling points and adjusts the sampling point density according to the deviation analysis results; The first monitoring area analysis module performs water quality fluorescence fingerprint analysis on water samples from the corresponding sampling points in the first monitoring area and matches them with the water quality fluorescence fingerprints of known pollution sources in the pollution source database; based on the matching results, the suspected pollution source is identified and the location of the suspected pollution source is sent to relevant personnel; The second monitoring area analysis module analyzes the flow path of water samples by comparing the water quality fluorescent fingerprints of cross-section water samples at different sampling points, and gradually confirms the location of suspected pollution sources based on the comparison results, and sends the location of suspected pollution sources to relevant personnel.

[0019] The area division and sampling point layout module includes an area division unit and a sampling point layout unit; The area division unit divides the area to be monitored into multiple sub-areas according to the preset minimum area, obtains the location information of each sub-area, and extracts the pollution source characteristics; based on the pollution source characteristics, it determines whether there is a known pollution source in each sub-area and classifies it as the first monitoring area or the second monitoring area; the sampling point layout unit layouts the sampling points for water quality monitoring based on the division category of the area to be monitored.

[0020] The deviation analysis module includes a data deviation calculation unit and a sampling point density adjustment unit; The data deviation calculation unit calculates the deviation index of the water quality monitoring data of two adjacent sampling points and compares it with the preset threshold; the sampling point density adjustment unit determines whether the sampling point density needs to be increased or decreased based on the deviation analysis results; if the deviation index is greater than the set threshold, the sampling points are increased; if the deviation index is less than the set threshold, the sampling points are reduced.

[0021] The first monitoring area analysis module includes a water quality fluorescence fingerprint analysis unit and a first pollution source identification unit; The water quality fluorescence fingerprint analysis unit performs fluorescence fingerprint analysis on the water samples at the sampling points in the first monitoring area and obtains the corresponding water quality fluorescence fingerprint data; the pollution source identification unit matches the water quality fluorescence fingerprint data of each sampling point with the water quality fluorescence fingerprint data of known pollution sources in the database, and identifies the suspected pollution source based on the matching results, and sends the location of the pollution source to relevant personnel.

[0022] The second monitoring area analysis module includes a water quality flow path analysis unit and a second pollution source identification unit; The water quality flow path analysis unit performs water sample flow path analysis on the second monitoring area; the second pollution source identification unit compares the water quality fluorescent fingerprints of cross-section water samples at different sampling points, and gradually confirms the location of the pollution source based on the comparison results, and sends the pollution source location to relevant personnel.

[0023] The water pollution monitoring method comprises the following steps: Step S100: Acquire location information of the area to be monitored, extract pollution source characteristics from the location information, and divide the area to be monitored into a first monitoring area and a second monitoring area based on the pollution source characteristics; and arrange sampling points for water quality monitoring based on the classification of the area to be monitored; Step S200. Collect water samples in sequence according to the arranged water quality monitoring sampling points to obtain corresponding water quality monitoring data; perform deviation analysis on the water quality monitoring data of two adjacent sampling points, and adjust the sampling point density according to the deviation analysis results; Step S300: For the first monitoring area, the water samples at the corresponding sampling points are subjected to water quality fluorescence fingerprint analysis and matched with the water quality fluorescence fingerprints of known pollution sources in the pollution source database; based on the matching results, the suspected pollution source is identified and the location of the suspected pollution source is sent to relevant personnel; Step S400. For the second monitoring area, perform water sample flow path analysis, compare the water quality fluorescent fingerprints of cross-section water samples at different sampling points, and gradually confirm the location of the suspected pollution source based on the comparison results, and send the suspected pollution source location to relevant personnel.

[0024] Step S100 includes: S101. Divide the area to be monitored into several sub-areas according to a preset minimum area. Obtain location information of the area to be monitored. For each sub-area, extract pollution source characteristics from the corresponding location information. Determine the category of the corresponding sub-area based on the pollution source characteristics. If a known pollution source is found in the pollution source characteristics of the sub-area, the sub-area is divided into a first monitoring area. If an unknown pollution source is found in the pollution source characteristics of the sub-area, the sub-area is divided into a second monitoring area. The first monitoring area has known pollution sources, such as sewage treatment plants and factory discharge points. The second monitoring area has unknown pollution sources, such as rivers, lakes, and other natural water bodies. S102. For the first monitoring area, obtain the corresponding drainage network structure diagram, identify the sewage outlet and the intersection point of the drainage pipe according to the drainage network structure diagram; obtain the historical sewage discharge data of the first monitoring area, and calculate the pollutant concentration Cp of each sewage outlet in combination with the historical sewage discharge data, and Cp = Mp / Qp, where Mp represents the total amount of pollutants discharged from the sewage outlet, and Qp represents the discharge flow of the sewage outlet; summarize the pollutant concentration Cp of all sewage outlets, and compare the pollutant concentration Cp of all sewage outlets with the preset pollutant concentration threshold C1 in turn, and select the sewage outlets with a pollutant concentration Cp greater than or equal to the pollutant concentration Cp. The sewage outlet with the pollutant concentration threshold C1 is recorded as the sampling point; the pollutant concentration Cj of each drainage pipe intersection is calculated, and Cj=∑ni=1(Qi×Ci) / ∑ni=1Qi, where Qi represents the flow rate of the i-th pipe, Ci represents the pollutant concentration of the i-th pipe, and n represents the number of pipes connected at the intersection; the pollutant concentration Cj of all drainage pipe intersections is summarized, and the pollutant concentration Cj of all drainage pipe intersections is compared with the preset pollutant concentration threshold C2 in turn, and the drainage pipe intersection with the pollutant concentration Cj greater than or equal to the pollutant concentration threshold C2 is recorded as the sampling point; S103. For the second monitoring area, obtain the flow direction and confluence relationship of all tributaries in the second monitoring area, so as to identify the confluence points in the second monitoring area, and use the confluence points as sampling points for the second monitoring area; according to the location of each confluence point and in combination with the flow direction of the corresponding tributary, follow the flow direction of the tributary and set the sampling points in sections according to the preset minimum sampling point distance.

[0025] Step S200 includes: S201. For the first monitoring area and the second monitoring area, water samples are collected in sequence according to the arranged water quality monitoring sampling points, thereby obtaining corresponding water quality monitoring data. The collected water quality monitoring data are processed in sequence according to the monitoring areas and sampling points, thereby obtaining a first monitoring data set A and a second monitoring data set B, where A={a1,a2,...,au} and B={b1,b2,...,bv}, where a1 represents the water quality monitoring data of the first sampling point in the first monitoring area, a2 represents the water quality monitoring data of the second sampling point in the first monitoring area, and so on, au represents the water quality monitoring data of the u-th sampling point in the first monitoring area; similarly, b1 represents the water quality monitoring data of the first sampling point in the second monitoring area, b2 represents the water quality monitoring data of the second sampling point in the second monitoring area, and bv represents the water quality monitoring data of the v-th sampling point in the second monitoring area; u and v represent the number of sampling points in the first monitoring area and the second monitoring area, respectively. S202. Calculate, for each of the first monitoring dataset A and the second monitoring dataset B, a deviation index R of the water quality monitoring data of two adjacent sampling points. The corresponding calculation formula is: R = |f_k - f_k+1| / d_k, where f_k represents the water quality monitoring data of the kth sampling point in the first monitoring dataset A or the second monitoring dataset B, f_k+1 represents the water quality monitoring data of the k+1th sampling point in the first monitoring dataset A or the second monitoring dataset B, and d_k represents the distance between adjacent sampling points f_k and f_k+1 in the first monitoring dataset A or the second monitoring dataset B. Compare the deviation index R of the water quality monitoring data of the two adjacent sampling points with a threshold RT. If the deviation index R is greater than the threshold RT, insert a new sampling point between the two adjacent sampling points, output the location of the area between the two adjacent sampling points to relevant personnel, and have the relevant personnel increase the sampling point density in the current area. If the deviation index R is less than the threshold RT, merge the adjacent sampling points, output the location of the area between the two adjacent sampling points to relevant personnel, and have the relevant personnel reduce the sampling point density in the current area.

[0026] In this embodiment, it is assumed that for a water quality monitoring indicator in the second monitoring area, the following calculation process is performed: The first pair of sampling points: b1 and b2; Calculate the corresponding deviation index R1 = |b1-b2| / d1 = |6.0-6.7| / 1.5 = 0.7 / 1.5 = 0.467; compare R1 with the threshold RT = 1.5. Since 0.467 < 1.5, it is necessary to merge the two sampling points to reduce the sampling point density; the determination of RT requires professional analysis. The second pair of sampling points: b2 and b3; The deviation index R2=|b2-b3| / d2=|6.7-8.5| / 1.0=1.8; comparing R2 and the threshold RT=1.5: 1.8>1.51, so it is necessary to insert new sampling points to increase the sampling point density.

[0027] Step S300 includes: S301. For the first monitoring area, perform water quality fluorescence fingerprint analysis on the corresponding sampling points to obtain water quality fluorescence fingerprint data corresponding to each sampling point; calculate the similarity between the water quality fluorescence fingerprint data of each sampling point and the water quality fluorescence fingerprint data of known pollution sources in the database; if the similarity result is greater than or equal to the similarity threshold, mark the corresponding sampling point as a suspected pollution source; S302. For sampling points with similarity less than the similarity threshold, obtain the water quality fluorescence fingerprint data of the sampling point upstream of this sampling point and perform similarity calculation. If the similarity is greater than or equal to the similarity threshold, the upstream sampling point is used as the target sampling point; calculate the similarity between the water quality fluorescence fingerprint data of the target sampling point and the sampling point upstream of it until the similarity is less than the similarity threshold, and mark the target sampling point as a suspected pollution source; output the location coordinates of the suspected pollution source to relevant personnel, who will perform corresponding processing. Among them, for sampling points with similarity less than the similarity threshold, it is necessary to continue tracing the source to the upstream sampling point, so the upstream sampling point is used as the target sampling point. This step is essentially to gradually eliminate irrelevant sampling points through similarity calculation until an area with water quality characteristics similar to the known pollution source is found; when the similarity is less than the similarity threshold, it means that continuing upstream tracing is invalid, and the pollution source may have been located in the target sampling point area, so the target sampling point is marked as a suspected pollution source.

[0028] In this embodiment, a traceability water sample analysis is performed on each sampling point in the first monitoring area, and the sample is compared with the existing pollution source water quality fluorescent fingerprint database. The water sample to be traced is compared with the water quality fluorescent fingerprint of the known pollution sources in the database, and the suspected pollution source with the highest similarity and its similarity are given; when no similar pollution source is found in the pollution source water quality fluorescent fingerprint database, the sampling points can be increased, and the water quality fluorescent fingerprint of the water sample to be traced is compared one by one with the water quality fluorescent fingerprint of the collected pollution source water sample; for example, a pollution source with a similarity ≥ 60% can be regarded as a suspected pollution source. After the suspected pollution source is determined, water samples of the suspected pollution source and its surrounding areas should be collected as soon as possible to determine the pollution source; for water areas with large changes in water quality fluorescent fingerprints, as many water samples as possible from relevant points should be collected for investigation.

[0029] Step S400 includes: S401. For each sampling point in the second monitoring area, perform a water sample flow path analysis. Name the sampling section at the sampling point Section X, and name the sampling section at the upstream sampling point of the current sampling point Section Y. Analyze the similarity between the water quality fluorescence fingerprint data of the water samples corresponding to Sections X and Y. If the similarity is greater than or equal to a similarity threshold, it indicates that the suspected pollution source may be upstream of Section Y. Name the sampling section at the upstream sampling point of Section Y Section Z1. Analyze the similarity between the water quality fluorescence fingerprint data of the water samples corresponding to Sections X and Z1. If the similarity is greater than or equal to the similarity threshold, continue analyzing the similarity between Section X and the water quality fluorescence fingerprint data of the water samples corresponding to the sampling section at the upstream sampling point of Section Z1 until the similarity is less than the similarity threshold. Finally, identify the sampling points corresponding to Sections Y and Z1 as suspected pollution sources. S402. Analyze the similarity between the water quality fluorescence fingerprint data of the water samples corresponding to Section X and Section Z1. If the similarity is less than the similarity threshold, it indicates that the suspected pollution source may be between Sections Y and X. The sampling points corresponding to Sections X and Y are regarded as suspected pollution sources; the location coordinates of the suspected pollution source are output to relevant personnel for appropriate processing.

[0030] In this embodiment, a water flow path analysis is performed for each sampling point within the second monitoring area. The water sample at the sampling point is used as the source-tracing water sample. The section where the source-tracing water sample is collected is named Section X. If the water quality fluorescence fingerprint similarity between the source-tracing water sample and the water sample at an upstream section (named Section Y) is ≥60%, it indicates that the suspected pollution source may be upstream of Section Y. The source-tracing water sample is then compared with the water quality fluorescence fingerprint of the water sample at the upstream section of Section Y (named Section Z1). If the river section where the pollution occurred can be determined, Section Y is set approximately halfway between the confirmed polluted river section. If the polluted river section cannot be determined, the upstream section Y is set approximately halfway between the river source and Section X. If the similarity between the source-tracing water sample and the water sample at Section Y is less than 60%, it indicates that the suspected pollution source may be between Sections Y and X. Collect water samples from the section about 1 / 2 of the distance between the two sections (named as section Z2), and then compare the water quality fluorescence fingerprint of the water sample to be traced with that of the water sample from section Z2.

[0031] Based on the similarity results, the aforementioned method is used to continuously narrow the investigation scope. When the investigation scope is reduced to approximately 1 km, relevant personnel should collect water samples from rainwater outlets, pollution source outlets into rivers (lakes, reservoirs), and tributary outlets into rivers (lakes, reservoirs), and use water quality fluorescence fingerprint comparison to locate the location where the pollution entered the river (lake, reservoir).

[0032] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0033] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A water pollution monitoring method, characterized in that: The method comprises the following steps: Step S100: Acquire location information of the area to be monitored, extract pollution source characteristics from the location information, and divide the area to be monitored into a first monitoring area and a second monitoring area based on the pollution source characteristics; and arrange sampling points for water quality monitoring based on the classification of the area to be monitored; Step S200. Collect water samples in sequence according to the arranged water quality monitoring sampling points to obtain corresponding water quality monitoring data; perform deviation analysis on the water quality monitoring data of two adjacent sampling points, and adjust the sampling point density according to the deviation analysis results; Step S300: For the first monitoring area, the water samples at the corresponding sampling points are subjected to water quality fluorescence fingerprint analysis and matched with the water quality fluorescence fingerprints of known pollution sources in the pollution source database; based on the matching results, the suspected pollution source is identified and the location of the suspected pollution source is sent to relevant personnel; Step S400. For the second monitoring area, perform water sample flow path analysis, compare the water quality fluorescent fingerprints of cross-section water samples at different sampling points, and gradually confirm the location of the suspected pollution source based on the comparison results, and send the suspected pollution source location to relevant personnel.

2. The water pollution monitoring method according to claim 1, characterized in that: The step S100 includes: S101. Divide the area to be monitored into several sub-areas according to a preset minimum area. Obtain location information of the area to be monitored. For each sub-area, extract pollution source characteristics from the corresponding location information. Determine the category of the corresponding sub-area based on the pollution source characteristics. If the pollution source characteristics of the sub-area contain known pollution sources, then the sub-area is classified as a first monitoring area. If the pollution source characteristics of the sub-area contain unknown pollution sources, then the sub-area is classified as a second monitoring area. S102. For the first monitoring area, obtain the corresponding drainage network structure diagram, identify the sewage outlet and the intersection point of the drainage pipe according to the drainage network structure diagram; obtain the historical sewage discharge data of the first monitoring area, and calculate the pollutant concentration Cp of each sewage outlet in combination with the historical sewage discharge data, and Cp = Mp / Qp, where Mp represents the total amount of pollutants discharged from the sewage outlet, and Qp represents the discharge flow of the sewage outlet; summarize the pollutant concentration Cp of all sewage outlets, and compare the pollutant concentration Cp of all sewage outlets with the preset pollutant concentration threshold C1 in turn, and select the sewage outlets with a pollutant concentration Cp greater than or equal to the pollutant concentration Cp. The sewage outlet with the pollutant concentration threshold C1 is recorded as the sampling point; the pollutant concentration Cj of each drainage pipe intersection is calculated, and Cj=∑ni=1(Qi×Ci) / ∑ni=1Qi, where Qi represents the flow rate of the i-th pipe, Ci represents the pollutant concentration of the i-th pipe, and n represents the number of pipes connected at the intersection; the pollutant concentration Cj of all drainage pipe intersections is summarized, and the pollutant concentration Cj of all drainage pipe intersections is compared with the preset pollutant concentration threshold C2 in turn, and the drainage pipe intersection with the pollutant concentration Cj greater than or equal to the pollutant concentration threshold C2 is recorded as the sampling point; S103. For the second monitoring area, obtain the flow direction and confluence relationship of all tributaries in the second monitoring area, so as to identify the confluence points in the second monitoring area, and use the confluence points as sampling points for the second monitoring area; according to the location of each confluence point and in combination with the flow direction of the corresponding tributary, follow the flow direction of the tributary and set the sampling points in sections according to the preset minimum sampling point distance.

3. The water pollution monitoring method according to claim 2, characterized in that: The step S200 includes: S201. For the first monitoring area and the second monitoring area, water samples are collected in sequence according to the arranged water quality monitoring sampling points, thereby obtaining corresponding water quality monitoring data. The collected water quality monitoring data are processed in sequence according to the monitoring areas and sampling points, thereby obtaining a first monitoring data set A and a second monitoring data set B, where A={a1,a2,...,au} and B={b1,b2,...,bv}, where a1 represents the water quality monitoring data of the first sampling point in the first monitoring area, a2 represents the water quality monitoring data of the second sampling point in the first monitoring area, and so on, au represents the water quality monitoring data of the u-th sampling point in the first monitoring area; similarly, b1 represents the water quality monitoring data of the first sampling point in the second monitoring area, b2 represents the water quality monitoring data of the second sampling point in the second monitoring area, and bv represents the water quality monitoring data of the v-th sampling point in the second monitoring area; u and v represent the number of sampling points in the first monitoring area and the second monitoring area, respectively. S202. Calculate, for each of the first monitoring dataset A and the second monitoring dataset B, a deviation index R of the water quality monitoring data of two adjacent sampling points. The corresponding calculation formula is: R = |f_k-f_k+1| / d_k, where f_k represents the water quality monitoring data of the kth sampling point in the first monitoring dataset A or the second monitoring dataset B, f_k+1 represents the water quality monitoring data of the k+1th sampling point in the first monitoring dataset A or the second monitoring dataset B, and d_k represents the distance between adjacent sampling points f_k and f_k+1 in the first monitoring dataset A or the second monitoring dataset B. Compare the deviation index R of the water quality monitoring data of the two adjacent sampling points with a threshold RT. If the deviation index R is greater than the threshold RT, output the location of the area between the two adjacent sampling points to relevant personnel, who will increase the sampling point density in the current area. If the deviation index R is less than the threshold RT, output the location of the area between the two adjacent sampling points to relevant personnel, who will decrease the sampling point density in the current area.

4. The water pollution monitoring method according to claim 3, characterized in that: The step S300 includes: S301. For the first monitoring area, perform water quality fluorescence fingerprint analysis on the corresponding sampling points to obtain water quality fluorescence fingerprint data corresponding to each sampling point; calculate the similarity between the water quality fluorescence fingerprint data of each sampling point and the water quality fluorescence fingerprint data of known pollution sources in the database; if the similarity result is greater than or equal to the similarity threshold, mark the corresponding sampling point as a suspected pollution source; S302. For sampling points with similarity less than the similarity threshold, obtain the water quality fluorescence fingerprint data of the sampling point upstream of this sampling point and perform similarity calculation. If the similarity is greater than or equal to the similarity threshold, then use the upstream sampling point as the target sampling point; calculate the similarity between the water quality fluorescence fingerprint data of the target sampling point and the sampling point upstream of it until the similarity is less than the similarity threshold, and mark the target sampling point as a suspected pollution source; output the location coordinates of the suspected pollution source to relevant personnel, who will perform corresponding processing.

5. The water pollution monitoring method according to claim 4, characterized in that: The step S400 includes: S401. For each sampling point in the second monitoring area, perform a water sample flow path analysis. Name the sampling section at the sampling point as Section X, and the collection section at the upstream sampling point of the current sampling point as Section Y. Analyze the similarity between the water quality fluorescence fingerprint data of the water samples corresponding to Sections X and Y. If the similarity is greater than or equal to a similarity threshold, name the collection section at the upstream sampling point of Section Y as Section Z1. Analyze the similarity between the water quality fluorescence fingerprint data of the water samples corresponding to Sections X and Z1. If the similarity is greater than or equal to the similarity threshold, continue analyzing the similarity between the water quality fluorescence fingerprint data of Section X and the water samples collected at the upstream sampling point of Section Z1 until the similarity is less than the similarity threshold. Then, identify the sampling points corresponding to Sections Y and Z1 as suspected pollution sources. S402. Analyze the similarity between the water quality fluorescence fingerprint data of the water samples corresponding to Section X and Section Z1. If the similarity is less than the similarity threshold, it indicates that the suspected pollution source may be between Sections Y and X. The sampling points corresponding to Sections X and Y are regarded as suspected pollution sources; the location coordinates of the suspected pollution source are output to relevant personnel for appropriate processing.

6. A water pollution monitoring system, applied to the water pollution monitoring method according to any one of claims 1 to 5, characterized in that: The system includes: an area division and sampling point layout module, a deviation analysis module, a first monitoring area analysis module, and a second monitoring area analysis module; The area division and sampling point layout module obtains the location information of the area to be monitored, extracts the pollution source characteristics from the location information, and divides the area to be monitored into a first monitoring area and a second monitoring area according to the pollution source characteristics; and arranges sampling points for water quality monitoring based on the classification of the area to be monitored; The deviation analysis module collects water samples in sequence according to the arranged water quality monitoring sampling points, thereby obtaining corresponding water quality monitoring data; performs deviation analysis on the water quality monitoring data of two adjacent sampling points, and adjusts the sampling point density according to the deviation analysis results; The first monitoring area analysis module performs water quality fluorescence fingerprint analysis on water samples at corresponding sampling points in the first monitoring area and matches the water quality fluorescence fingerprints of known pollution sources in the pollution source database; based on the matching results, the suspected pollution source is identified and the location of the suspected pollution source is sent to relevant personnel; The second monitoring area analysis module performs water sample flow path analysis by comparing the water quality fluorescent fingerprints of cross-section water samples at different sampling points, and gradually confirms the location of the suspected pollution source based on the comparison results, and sends the suspected pollution source location to relevant personnel.

7. The water pollution monitoring system according to claim 6, characterized in that: The region division and sampling point layout module includes a region division unit and a sampling point layout unit; The area division unit divides the area to be monitored into multiple sub-areas based on a preset minimum area, obtains the location information of each sub-area, and extracts the pollution source characteristics; based on the pollution source characteristics, it determines whether there is a known pollution source in each sub-area and classifies it as a first monitoring area or a second monitoring area; the sampling point layout unit layouts sampling points for water quality monitoring based on the division category of the area to be monitored.

8. The water pollution monitoring system according to claim 6, characterized in that: The deviation analysis module includes a data deviation calculation unit and a sampling point density adjustment unit; The data deviation calculation unit calculates the deviation index of the water quality monitoring data of two adjacent sampling points and compares it with a preset threshold; the sampling point density adjustment unit determines whether it is necessary to increase or decrease the sampling point density based on the deviation analysis result; if the deviation index is greater than the set threshold, the sampling points are increased; if the deviation index is less than the set threshold, the sampling points are reduced.

9. The water pollution monitoring system according to claim 6, characterized in that: The first monitoring area analysis module includes a water quality fluorescence fingerprint analysis unit and a first pollution source identification unit; The water quality fluorescence fingerprint analysis unit performs fluorescence fingerprint analysis on the water samples at the sampling points in the first monitoring area and obtains corresponding water quality fluorescence fingerprint data; The pollution source identification unit matches the water quality fluorescence fingerprint data of each sampling point with the water quality fluorescence fingerprint data of known pollution sources in the database, and identifies the suspected pollution source based on the matching result, and sends the location of the pollution source to relevant personnel.

10. The water pollution monitoring system according to claim 6, characterized in that: The second monitoring area analysis module includes a water quality flow path analysis unit and a second pollution source identification unit; The water quality flow path analysis unit performs water sample flow path analysis on the second monitoring area; the second pollution source identification unit compares the water quality fluorescent fingerprints of cross-sectional water samples at different sampling points, and gradually confirms the location of the pollution source based on the comparison results, and sends the location of the pollution source to relevant personnel.

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