Surface water environment online monitoring method

Abstract

The invention relates to the technical field of water quality monitoring, in particular to a surface water environment online monitoring method which comprises the following steps: acquiring water quality monitoring data of urban pipe network nodes, establishing a pipe network topological structure, adjusting the topological structure in combination with a water flow direction, determining the water flow direction, performing time segmentation on the topological structure, and calculating topological change frequency. And establishing a pipe network topology evolution structure. According to the method, the topological change frequency is calculated in combination with time segments, pipe segments with obvious changes are screened, and the continuous diffusion condition of pollutants is judged by removing trend influence, extracting stable water quality characteristic information, screening continuous abnormal points and analyzing the pollution diffusion trend in combination with the topological relation in the screening of abnormal fluctuation pipeline connection. The pollution influence range is combined with concentration changes, key diffusion channels are marked, pollution duration is combined, and pollution source candidate points are screened, so that water quality monitoring can adapt to pipe network changes, and the real-time performance and the intelligent level of an urban pipe network water quality monitoring system are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of water quality monitoring, and particularly to an on-line monitoring method for surface water environment. Background Art

[0002] The technical field of water quality monitoring includes technologies for detecting and analyzing the physical, chemical, and biological characteristics of water bodies, aiming to obtain the water quality status and evaluate its safety, covering various application scenarios such as water source areas, water supply pipe networks, sewage treatment, and environmental water bodies. The main monitoring parameters include temperature, turbidity, pH value, dissolved oxygen, conductivity, heavy metal ions, organic pollutants, and microorganisms. Water quality monitoring can be carried out by on-line monitoring, laboratory analysis, and portable detection, and real-time or periodic detection of water quality can be achieved through means such as sensor detection, reagent analysis, spectroscopic technology, and chromatographic analysis. In recent years, with the development of information technology, the application of technologies such as data acquisition, remote monitoring, and automatic warning has made water quality monitoring more efficient and intelligent.

[0003] Among them, the on-line monitoring method for surface water environment refers to a method for monitoring the water quality of the pipe network water body in the water supply system to ensure the water quality safety during the transportation process. It mainly involves deploying water quality sensors at key nodes or specific positions in the pipe network, collecting data on physical and chemical indicators in water through means such as electrochemistry, electrode determination, optical analysis, or colorimetry, and transmitting the data to the monitoring center for analysis by means of wireless communication, optical fiber transmission, or wired network. Usually, combined with time series analysis or threshold judgment methods, the water quality change trend is analyzed, and the water quality anomaly is judged through a preset mathematical model or rule base. In addition, some methods also combine hydraulic simulation calculations, and use flow velocity, pressure, and flow direction data to infer the pollutant diffusion path to improve the comprehensiveness and accuracy of water quality monitoring.

[0004] There are various deficiencies in the current urban pipe network water quality monitoring process. The use of a fixed topological structure fails to reflect the real-time changes in the water flow direction, resulting in some water quality anomalies not being accurately identified due to insufficient adjustment of the flow direction. Water quality monitoring mainly relies on single-point or a small number of sampling points, making it difficult to comprehensively capture water quality fluctuations. The data fluctuations in a single sampling are prone to misjudgment or missed reports due to the lack of trend correction. Most water quality anomaly analyses are based on static threshold judgments and do not conduct dynamic analyses in combination with changes in the flow direction. Some short-term fluctuations may be misjudged as anomalies, or the water quality changes caused by pollutant diffusion cannot be effectively identified. The determination of pollution events usually relies on single anomaly data, without combining spatial distribution and time trends, missing continuous pollution phenomena and resulting in insufficient identification accuracy of pollution events. The analysis of pollution diffusion paths fails to fully combine the characteristics of pollutant concentration changes and lacks the screening of key diffusion paths, leading to deviations in the estimated diffusion range and affecting the accuracy of pollution control. The tracing of pollution sources relies on static models for calculation, without conducting comprehensive analyses in combination with dynamic flow directions and pollution duration, resulting in deviations in the positions of pollution sources, reducing the effectiveness of pollution source tracing, limiting the accuracy and real-time response capabilities of the water quality monitoring system, and making it difficult to provide efficient pollution diffusion prediction and pollution source location support during pollution events. Summary of the Invention

[0005] The object of the present invention is to solve the deficiencies existing in the prior art and to propose an on-line monitoring method for surface water environment.

[0006] To achieve the above object, the present invention adopts the following technical solutions: An on-line monitoring method for surface water environment, comprising the following steps: S1: Obtain the water quality monitoring data of urban pipe network nodes, establish a pipe network topological structure, adjust the topological structure in combination with the water flow direction, determine the water flow direction, segment the topological structure by time, calculate the topological change frequency, and establish a pipe network topological evolution structure; S2: According to the pipe network topological evolution structure, calculate the changes in the water quality monitoring data of each node, analyze the water quality change trend of the urban water supply pipe network, and compare whether the water quality changes between pipes conform to the water flow propagation relationship, and screen out the abnormal connections of fluctuating pipes to obtain detrended water quality characteristic information; S3: According to the detrended water quality characteristic information, screen out pollution abnormal points, calculate the occurrence frequency of abnormal points, analyze the water quality changes of the main water supply pipes and secondary pipes, calculate the pollutant diffusion trend, and statistically obtain the pollution impact range data; S4: According to the pollution impact range data, analyze the pollution propagation direction of the water quality, compare the pollutant concentrations of each node in the polluted area, mark the key diffusion channels, and obtain pollution diffusion analysis information; S5: According to the pollution diffusion analysis information, trace back the pollution occurrence location, calculate the earliest pipe network node where the pollutant appears, compare the pollution duration, screen the candidate pollution source points, and obtain the pollution source location result.

[0007] As a further solution of the present invention, the pipe network topology evolution structure includes the water flow direction, the topology change frequency, and the pipe segments with obvious changes. The detrended water quality characteristic information includes the water quality parameter fluctuation situation, the water quality change trend analysis result, and the pipe connections with abnormal fluctuations. The pollution influence range data includes pollution abnormal points, the abnormal point distribution situation, and the pollutant diffusion trend analysis result. The pollution diffusion analysis information includes the pollutant propagation path, the key diffusion channels, and the pollutant concentration change data. The pollution source location result includes the pollution occurrence location, the optimal pollution propagation tracing direction, and the candidate pollution source points.

[0008] As a further solution of the present invention, the specific steps for obtaining the water quality monitoring data of urban pipe network nodes, establishing the pipe network topology structure, adjusting the topology structure in combination with the water flow direction, determining the water flow direction, segmenting the topology structure by time, calculating the topology change frequency, and establishing the pipe network topology evolution structure are as follows: S111: Obtain the water quality monitoring data of urban pipe network nodes, establish the pipe network topology structure, regard the nodes as water quality monitoring points, the pipes as connection relationships, adjust the topology structure in combination with the water flow direction, compare the pressure differences between adjacent nodes, calculate the water flow direction, screen the pipe segments with changed water flow directions, and obtain the screening record of the water flow direction change pipe segments; S112: Based on the screening record of the water flow direction change pipe segments, segment the topology structure by time, count the frequency of water flow direction changes in each time period, calculate the change frequency of each pipe segment, and obtain the pipe segment change frequency distribution data; S113: Based on the pipe segment change frequency distribution data, screen the pipe segments with change frequencies greater than the set threshold, and use the formula: ; Calculate the topology evolution influence degree , and establish the pipe network topology evolution structure, where, represents the water pressure change value of the rd pipe segment, represents the length of the th pipe segment, represents the flow rate of the th pipe segment, represents the flow velocity of the th pipe segment, represents the water flow direction change frequency of the th pipe segment, represents the number of all screened pipe segments.

[0009] As a further solution of the present invention, according to the topological evolution structure of the pipe network, calculate the changes in water quality monitoring data at each node, analyze the water quality change trend of the urban water supply pipe network, and compare whether the water quality changes between pipes conform to the water flow propagation relationship. The specific steps to screen the abnormal pipeline connections with fluctuations and obtain the detrended water quality characteristic information are as follows: S211: Based on the topological evolution structure of the pipe network, calculate the changes in water quality monitoring data at each node, extract the temporal change trend of water quality parameters, compare the fluctuation amplitudes of water quality parameters at each node, screen the monitoring points exceeding the set water quality fluctuation threshold, and obtain the water quality abnormal monitoring points; S212: Based on the water quality abnormal monitoring points, analyze the water quality change trend of the water supply pipe network, combine with the water supply pipe network flow direction, compare the water quality changes of adjacent nodes, calculate the water quality parameter change rate of each adjacent node, and use the formula: ; Calculate the water quality change rate of the th node , and obtain the water quality change rate data of adjacent nodes. Among them, represents the water quality parameter value of the th node, represents the water quality parameter value of its adjacent upstream node, represents the monitoring time of the th node, represents the monitoring time of its adjacent upstream node, represents the flow rate of the th node, represents the flow velocity of the th node, represents the flow rate of its adjacent upstream node, represents the flow velocity of its adjacent upstream node, represents the water pressure of the th node, represents the water pressure of its adjacent upstream node, represents the th node and the length of the pipeline between it and its adjacent node; S213: Based on the water quality change rate data of adjacent nodes, compare whether the water quality changes between pipes conform to the water flow propagation relationship, screen the abnormal pipeline connections with fluctuations, and obtain the detrended water quality characteristic information.

[0010] As a further solution of the present invention, according to the detrended water quality characteristic information, screen the pollution abnormal points, calculate the occurrence frequency of the abnormal points, analyze the water quality changes of the main water supply pipes and secondary pipes, calculate the pollutant diffusion trend, and the specific steps to statistically obtain the pollution influence range data are as follows: S311: Based on the detrended water quality characteristic information, calculate the degree of water quality change at adjacent times, extract the water quality change rate, compare the change rate with the set abnormal range, screen out the pollution abnormal points of the urban water supply network that exceed the change range, calculate the occurrence frequency of each abnormal point, and obtain the pollution abnormal point frequency value; S312: Based on the pollution abnormal point frequency value, screen out the continuously changing abnormal data, calculate the continuity of the abnormal data on the time axis, screen out the data that meet the conditions as pollution events, and obtain the pollution event time series; S313: Based on the pollution event time series, analyze the water quality change situation of the main water supply pipes and secondary pipes, and use the formula: ; Calculate the pollutant diffusion trend value , combine the pipe network topology relationship to judge whether the pollutant continues to spread, and statistically obtain the pollution influence range data. Among them, represents the concentration of the pollutant in the pipeline section , represents the pollutant concentration in the previous time period, represents the flow velocity of the pipeline section , represents the cross-sectional area of the pipeline section , represents the th length of the pipeline, represents the total length of all polluted pipelines, represents the maximum value of the pollution event time interval, represents the total number of all pipelines, represents the number of polluted pipelines.

[0011] As a further solution of the present invention, according to the pollution influence range data, analyze the water quality pollution propagation direction, compare the pollutant concentrations at each node in the polluted area, and mark the key diffusion channels. The specific steps to obtain the pollution diffusion analysis information are as follows: S411: Based on the pollution influence range data, combine the pipe network topology structure, establish the propagation path of the pollutant, identify the connection relationship between each node, analyze the path and potential diffusion direction of the pollutant propagating along the pipe network, calculate the pollutant concentration change rate of each path, and obtain the pollutant propagation path data; S412: Based on the pollutant propagation path data, compare the pollutant concentrations at each node in the polluted area, calculate the pollutant concentration change rate of each node, and screen out the paths whose concentration change rate exceeds the set concentration increase threshold to obtain the key concentration change paths; S413: According to the key concentration change path, use the formula: ; Calculate the pollution path of the diffusion influence intensity and screen out the path with the greatest diffusion influence intensity to obtain pollution diffusion analysis information. Among them, represents the pollutant concentration of the path node , represents the average value of the pollutant concentrations of all nodes on this path, represents the pipe network length at the path node , represents the cumulative mass of pollutants at the path node , represents the residence time of pollutants at the path node , represents the total number of nodes on the path.

[0012] As a further solution of the present invention, according to the pollution diffusion analysis information, trace the pollution occurrence location and calculate the earliest pipe network node where the pollutant appears, compare the pollution duration, screen the candidate pollution source points, and the specific steps for obtaining the pollution source positioning result are as follows: S511: Based on the pollution diffusion analysis information, obtain the diffusion path data of pollutants in the pipe network, sort out the diffusion direction, concentration change and time series of pollutants, determine the key diffusion channels of pollutants in the pipe network, identify the pollution diffusion trend along this channel, and extract the pollutant appearance time and concentration change of each node to obtain pollution diffusion trend data; S512: According to the pollution diffusion trend data, calculate the earliest appearance time of pollutants at each pipe network node, analyze the time series of pollutants, determine the node with the longest pollution duration, and screen out the node with the longest pollution duration that conforms to the pollution propagation characteristics. Use the formula: ; Calculate the average appearance time of pollutants , and combine the time offset to calculate the pollution duration of each node to obtain candidate pollution source nodes. Among them, represents the pollutant concentration at the node , represents the first appearance time of pollutants, represents the total number of nodes on the pollution diffusion path, represents the th pollution duration of the node, represents the average value of the pollution durations of all nodes, represents the total number of all nodes; S513: According to the candidate pollution source nodes, compare the pollution durations of each node, and combine the pollution diffusion path to screen out the nodes that conform to the optimal traceability direction of pollution propagation to obtain the pollution source positioning result.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In the present invention, by combining time segmentation to calculate the topological change frequency and screening the pipe segments with obvious changes, the screening of abnormally fluctuating pipeline connections removes the trend influence to extract stable water quality characteristic information. The abnormal point detection combines the water quality change range, distribution and time dimension to screen continuous abnormal points, effectively improving the accuracy of pollution monitoring. The pollution diffusion trend analysis combines the topological relationship to judge the continuous diffusion situation of pollutants. The pollution influence range combines the concentration change to mark the key diffusion channels, making the tracking of the pollution propagation path more accurate. The earliest occurrence position of pollutants is obtained through data traceability, and combined with the pollution duration, the candidate pollution source points are screened to improve the reliability of pollution source location. Through means such as water flow direction adjustment, dynamic topological modeling, trend removal analysis, continuous anomaly extraction and key path tracking, the water quality monitoring can adapt to the changes in the pipe network, improve the monitoring accuracy, the ability to identify pollution events and the accuracy of pollution source location, and enhance the real-time and intelligent level of the water quality monitoring system. Brief Description of the Drawings

[0014] Figure 1 is the main step flow chart of the present invention; Figure 2 is the flow chart of step S1 of the present invention; Figure 3 is the flow chart of step S2 of the present invention; Figure 4 is the flow chart of step S3 of the present invention; Figure 5 is the flow chart of step S4 of the present invention; Figure 6 is the flow chart of step S5 of the present invention. Detailed Description of the Invention

[0015] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0016] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, in the description of the present invention, the meaning of "a plurality of" is two or more, unless otherwise specifically defined.

[0017] Please refer to Figure 1 , an on-line monitoring method for surface water environment, comprising the following steps: S1: Obtain the water quality monitoring data of urban pipe network nodes, establish the pipe network topology structure, regard the nodes as water quality monitoring points, the pipes as connection relationships, adjust the topology structure in combination with the water flow direction, compare the pressure differences between adjacent nodes to determine the water flow direction, segment the topology structure by time, calculate the topology change frequency, mark the pipe segments with obvious changes by screening those greater than the frequency change threshold, and establish the pipe network topology evolution structure; S2: According to the pipe network topology evolution structure, calculate the changes in the water quality monitoring data of each node, screen the monitoring points where the water quality parameters fluctuate beyond the fluctuation threshold, analyze the water quality change trend of the urban water supply pipe network, analyze the water quality changes of adjacent nodes in combination with the water supply pipe network flow direction, compare whether the water quality changes between pipes conform to the water flow propagation relationship, and screen the abnormally fluctuating pipe connections to obtain the detrended water quality characteristic information; S3: According to the detrended water quality characteristic information, analyze the degree of water quality change at adjacent times, compare the set abnormal range, screen the pollution abnormal points of the urban water supply pipe network that exceed the change range, count the distribution of the abnormal points, calculate the occurrence frequency of the abnormal points, screen the continuously changing abnormal data as pollution events, analyze the water quality changes of the main water supply pipes and secondary pipes, calculate the diffusion trend of pollutants, and judge whether the pollutants continue to spread in combination with the pipe network topology relationship, and statistically obtain the pollution impact range data; S4: According to the pollution impact range data, establish the pollutant propagation path in combination with the pipe network topology structure, analyze the propagation direction of water quality pollution, compare the pollutant concentrations of each node in the polluted area, and mark the path with a concentration increase greater than the increase threshold as the key diffusion channel to obtain the pollution diffusion analysis information; S5: According to the pollution diffusion analysis information, trace the pollution occurrence location, use the key diffusion channel as the optimal pollution propagation tracing direction, calculate the pipe network node where the pollutant first appears, compare the pollution duration, and screen the node with the longest pollution occurrence time as the pollution source candidate point to obtain the pollution source location result.

[0018] The pipe network topology evolution structure includes the water flow direction, the topology change frequency, and the pipe segments with obvious changes. The detrended water quality characteristic information includes the fluctuation of water quality parameters, the analysis results of water quality change trends, and the pipe connections with abnormal fluctuations. The pollution impact range data includes pollution abnormal points, the distribution of abnormal points, and the analysis results of pollutant diffusion trends. The pollution diffusion analysis information includes the pollutant propagation path, the key diffusion channels, and the pollutant concentration change data. The pollution source location result includes the pollution occurrence location, the optimal tracing direction of pollution propagation, and the candidate pollution sources.

[0019] Please refer to Figure 2 , and the S1 step is as follows: S111: Obtain the water quality monitoring data of the urban pipe network nodes, establish the pipe network topology structure, regard the nodes as water quality monitoring points, the pipes as connection relationships, adjust the topology structure in combination with the water flow direction, compare the pressure differences between adjacent nodes, calculate the water flow direction, screen the pipe segments with changed water flow directions, and obtain the screening records of the pipe segments with changed water flow directions; When obtaining the water quality monitoring data of the urban pipe network nodes, it is necessary to collect data in real time at multiple monitoring points. There are a large number of monitoring points in the urban pipe network. For example, 100 monitoring points can be set in a certain area, and each monitoring point collects water quality data once an hour. The collected content includes water pressure (unit: MPa), flow rate (unit: m³ / h), turbidity (unit: NTU), etc., and the time stamp is recorded at the same time to ensure the timeliness of the data. Store all the collected data and establish a topology structure. Regard each monitoring point as a network node and each pipe as an edge connecting adjacent nodes to form an initial pipe network topology structure. On this basis, it is necessary to further determine the water flow direction, call the water pressure data of adjacent nodes for comparison, and the water flow direction is from high pressure to low pressure. The calculation method is: ; Among them, represents the water flow direction state of the th pipe. 1 means flowing from node to node , and 0 means reverse flow. Suppose the water pressures at both ends of a pipe are 0.35 MPa and 0.28 MPa respectively, then the water flow direction of this pipe segment is 1, that is, flowing from the high-pressure end to the low-pressure end. After traversing all the pipes, the water flow direction information can be obtained, and the pipe segments with changed water flow directions are screened out to finally obtain the screening records of the pipe segments with changed water flow directions.

[0020] S112: Based on the screening records of the pipe segments with changed water flow directions, segment the topology structure by time, count the frequency of water flow direction changes in each time period, calculate the change frequency of each pipe segment, and obtain the distribution data of the pipe segment change frequencies; Based on the records of the pipe segments screened by the change of water flow direction, it is necessary to conduct a time-segmented analysis of the topological structure, set a time window, for example, with one day as a cycle, calculate the change frequency of each pipe segment in different time periods. Assuming the monitoring period is 24 hours and the data is recorded once an hour, if the water flow direction of a certain pipe segment changes 8 times within 24 hours, then its change frequency is: ; Among them, represents the change frequency of the th pipe segment, represents the number of changes of the pipe segment within the cycle . For example, if the water flow direction of a certain pipe segment changes 8 times, hours, then . Calculate the change frequencies of all pipe segments in this way, store them and generate the distribution data of the pipe segment change frequencies. Table 1.1 lists the change frequency data of 5 pipelines in a certain area.

[0021] Table 1.1 Pipe segment change frequency table: ; As shown in Table 1.1, the change frequencies of different pipe segments are different. Some pipe segments show relatively high change frequencies. These pipe segments may be affected by flow fluctuations or scheduling changes. Subsequently, it is necessary to screen the pipe segments with frequencies higher than the threshold and analyze their evolution characteristics.

[0022] S113: Based on the distribution data of the pipe segment change frequencies, screen the pipe segments with change frequencies greater than the set threshold, and use the formula: ; Calculate the influence degree of topological evolution , and establish the topological evolution structure of the pipe network. Among them, represents the water pressure change value of the th pipe segment, represents the length of the th pipe segment, represents the flow rate of the th pipe segment, represents the flow velocity of the th pipe segment, represents the change frequency of the water flow direction of the th pipe segment, represents the number of all screened pipe segments; Based on the distribution data of the pipe segment change frequencies, it is necessary to screen out the pipe segments with change frequencies greater than the set threshold. The standard for setting the threshold can be determined according to historical data or statistical methods. For example, take the average value of the change frequencies of all pipe segments and add 1.5 times the standard deviation as the screening threshold, and set: ; Among them, Represents the mean value of the change frequency of all pipe sections, Represents the standard deviation of the change frequency. Assuming that the average change frequency of all pipe sections in a certain area is 0.20 and the standard deviation is 0.07, the screening threshold is: ; That is, the pipe segments with a change frequency greater than 0.305 (such as pipe segments 3 and 4 in Table 1) are screened out. These pipe segments will be used to construct the topological evolution structure, and the topological evolution influence degree will be calculated using the formula.

[0023] in: is the water pressure change value (unit: MPa). The water pressure change value of a pipe section can be calculated through the monitoring point data. If the water pressure of a pipe section drops from 0.35MPa to 0.25MPa, then MPa; is the length of the pipe section (unit: m), the length of the pipe section is 300m; is the flow rate (unit: m³ / h). The monitoring data shows that the flow rate of this pipe section is 50 m³ / h. is the flow velocity (unit: m / s), which can be calculated from the flow rate and the pipe cross-sectional area: If the pipe diameter is 0.5m, the cross-sectional area is: , then the flow rate: ; is the frequency of water flow direction change. From Table 1.1, we can see that the pipe section .

[0024] Bring in data: ; ; ; The final calculated topological evolution influence of the pipe segment is 0.0806, which is compared with the influence threshold.

[0025] The influence threshold is usually determined by statistical methods, and the mean of the topological evolution influence of all pipe segments is calculated. and standard deviation , and then set a significance threshold : ; in The coefficient is set, and the common value range is 1.5 to 2 (1.5 indicates a moderate deviation, and 2 indicates a strong significant deviation).

[0026] Assume that for all pipe segments in the entire pipe network, it is calculated that: The mean value of the topological change influence degree , and the standard deviation ; Then set the threshold (take ): ; Because the of this pipe segment is greater than , it indicates that the influence of the water flow direction change of this pipe segment on the pipe network topological structure exceeds the normal fluctuation range in statistics, so it can be considered significant.

[0027] Please refer to Figure 3 , and the steps of S2 are as follows: S211: Based on the topological evolution structure of the pipe network, calculate the changes in water quality monitoring data at each node, extract the time series change trend of water quality parameters, compare the fluctuation ranges of water quality parameters at each node, screen the monitoring points that exceed the set water quality fluctuation threshold, and obtain the water quality abnormal monitoring points; In actual operation, the topological evolution structure of the pipe network can be established through long-term monitoring data. The water quality data of each node contains multiple water quality parameters, such as pH value, turbidity, dissolved oxygen (DO), etc. First, obtain the historical water quality monitoring data, and calculate the time series change trend for each monitoring node. Set a time series sliding window (such as 24 hours or 7 days) for data smoothing to reduce the influence of noise. For example, the pH values of a certain monitoring point in the past 24 hours are 7.1, 7.2, 7.0, 6.9, 7.3 in sequence. Then calculate the mean value within this window as 7.1 and calculate the standard deviation σ. Next, compare the water quality change ranges in adjacent time periods to determine whether they exceed the set water quality fluctuation threshold.

[0028] The setting basis of the water quality fluctuation threshold is as follows: The pH value fluctuation threshold : Refer to the common pH change range during the pipeline water conveyance process. According to the water quality monitoring data of multiple cities, the pH value fluctuation range of natural water bodies generally does not exceed 0.4 - 0.6, and the national drinking water standard stipulates that the pH value should be controlled between 6.5 - 8.5. Therefore, a change exceeding 0.5 can be regarded as abnormal. Set the water quality fluctuation threshold by referring to the mean value and standard deviation of historical data. For example, the mean value of the historical data of a certain water plant , and the standard deviation , then take as the threshold.

[0029] The turbidity fluctuation threshold :The change in turbidity reflects the pollution situation of the pipe network. If the fluctuation is too large, it may indicate that the pipe deposits are disturbed or there are external pollution sources. By analyzing historical turbidity monitoring data, the drinking water standard stipulates that the turbidity should be lower than 5 NTU, and the general water quality fluctuation should not exceed 2 - 4 NTU. Therefore, the threshold is set at 3 NTU. Calculate the set value: If the average turbidity in a certain area is 1.2 NTU and the standard deviation , then take as the threshold.

[0030] For the pH value, set , for the turbidity set NTU. If the pH value at a certain monitoring point drops from 7.2 to 6.5 within 6 hours, and the change amount is , then determine that this node is an abnormal monitoring point. Finally, screen all monitoring points that exceed the threshold.

[0031] S212: Based on the abnormal water quality monitoring points, analyze the water quality change trend of the water supply pipe network. Combine the flow direction of the water supply pipe network, compare the water quality change situations of adjacent nodes, calculate the water quality parameter change rates of each adjacent node, and use the formula: ; Calculate the water quality change rate of the th node, obtain the water quality change rate data of adjacent nodes. Among them, represents the water quality parameter value of the th node, represents the water quality parameter value of its adjacent upstream node, represents the monitoring time of the th node, represents the monitoring time of its adjacent upstream node, represents the flow rate of the th node, represents the flow velocity of the th node, represents the flow rate of its adjacent upstream node, represents the flow velocity of its adjacent upstream node, represents the water pressure of the th node, represents the water pressure of its adjacent upstream node, represents the th node and the length of the pipe between it and its adjacent node; The water quality parameter change rate needs to be calculated by combining multiple factors, such as water flow velocity, pipe section length, water pressure difference, etc. For example, if the water quality parameter change situation between nodes A2 and A3 is as follows: The pH value of the A2 monitoring point , the pH value of the A3 monitoring point , time interval , the flow rate of A2 , the flow rate of A3 , the flow velocities are respectively and , water pressure , , pipe section length .

[0032] The setting basis of the water quality change rate threshold is as follows: Data analysis: According to the statistics of different pipe network monitoring data, the water quality change rate of general water supply pipe networks fluctuates between 0.8 - 1.5. If it exceeds this range, it may indicate abnormal fluctuations in the water supply system or the input of pollution sources.

[0033] Calculate the set value: The water quality change rate threshold should be determined based on the mean value and standard deviation of historical change data. For example, for a certain city's water supply pipe network, the measured mean value is , and the standard deviation is , then take as the abnormal threshold.

[0034] Substitute the data into the formula: ; ; ; ; Calculate to obtain , indicating the water quality change rate between A2 - A3. Since , it can be determined that the water quality fluctuation of this pipe section is relatively large.

[0035] S213: Based on the water quality change rate data of adjacent nodes, compare whether the water quality change between pipes conforms to the water flow propagation relationship, screen the abnormally fluctuating pipe connections, and obtain the detrended water quality characteristic information; In the water quality monitoring of urban pipe networks, the water quality parameter changes of adjacent pipe sections should conform to the water flow propagation characteristics, that is, the water quality change trend should propagate along the water flow direction. If there is reverse propagation or irregular jumping, it indicates that there may be pollution backflow, abnormal infiltration or sensor failure in this pipe section. By calling the water quality change rate of adjacent nodes, compare its consistency with the water flow direction. Assume that the water quality change rates of A2 - A3 and A3 - A4 nodes are respectively and , then if , it indicates that the water quality change conforms to the water flow propagation relationship, otherwise screen this pipe section as an abnormal pipe section.

[0036] In actual operation, the calculated water quality change rate can be stored in the database and trend analysis can be performed using historical data. For example, if the pH value of A2 - A3 decreases while the pH value of A3 - A4 increases, further investigation of potential pollution sources in this pipeline section is required. Finally, pipeline connections with abnormal fluctuations are screened to obtain detrended water quality characteristic information.

[0037] Table 2.1 Water Quality Change Trend Screening Table: ; As shown in Table 2.1, the water quality propagation trend of the A4 - A5 pipeline section is abnormal, so it is screened as a pipeline connection with abnormal fluctuations and detrended water quality characteristic information is obtained.

[0038] Please refer to Figure 4 , step S3 is as follows: S311: Based on the detrended water quality characteristic information, calculate the degree of water quality change at adjacent times, extract the water quality change rate, compare the change rate with the set abnormal range, screen out the abnormal pollution points in the urban water supply network that exceed the change range, calculate the occurrence frequency of each abnormal point, and obtain the pollution abnormal point frequency value; Based on the detrended water quality characteristic information, it is necessary to calculate the degree of water quality change at adjacent times. First, determine the basic water quality data of each monitoring point in the water supply network. The selection range of monitoring points should cover different areas of the main pipeline and secondary pipelines to ensure the comprehensiveness of the data. For example, install water quality monitors at 10 key nodes in a certain area of the city and record the changes in water quality parameters per unit time (such as every 5 minutes). The water quality parameters include but are not limited to residual chlorine (mg / L), turbidity (NTU), pH value, conductivity (μS / cm), etc. For these data, calculate the water quality change rate at adjacent times and use to solve it, where is the water quality change rate at monitoring point i, and are the water quality parameter values at adjacent time points respectively, is the time interval between adjacent time points. For example, if the residual chlorine value at a certain point is 0.5 mg / L at 10:00 and drops to 0.3 mg / L at 10:05, the change rate is mg / L / min, and then compare the change rate with the set abnormal range. For example, the preset abnormal threshold of the change rate is ±0.02 mg / L / min. The setting basis of this threshold is the residual chlorine concentration requirement in the National Hygienic Standard for Drinking Water (GB5749-2006). This standard stipulates that the residual chlorine content in municipal water supply at the user's faucet shall not be lower than 0.05 mg / L and shall not be higher than 4 mg / L. Considering that the attenuation rate of residual chlorine in the actual water supply process is affected by factors such as temperature, pipe material, and hydraulic conditions, it is necessary to ensure that the water quality change rate will not pose a threat to water supply safety under normal water supply conditions. Therefore, the specific setting basis of this threshold range is the attenuation curve of residual chlorine in the pipe network under normal water supply flow rate (0.6~1.2 m / s). Combining the flow rate of typical urban water supply pipes and the residual chlorine residue attenuation model, it is calculated that the normal residual chlorine decline rate is about between 0.005 and 0.015 mg / L / min. Based on this, the abnormal change threshold is determined to be ±0.02 mg / L / min. This value fluctuates with the increase of water temperature, the acceleration of flow rate, or the increase of pipe aging degree. For example, in summer with high temperature, the water quality fluctuates faster, and the change threshold may be adjusted to ±0.025 mg / L / min. In the low-temperature environment in winter, this value can be appropriately reduced to ±0.015 mg / L / min to more accurately capture the abnormal water quality change trend. For example, if abnormal conditions continuously occur at 5 monitoring points in a certain area within 20 minutes, the pollution abnormal point frequency value of this area can be calculated as 5 / 20 = 0.25 points / minute to obtain the pollution abnormal point frequency value.

[0039] S312: Based on the pollution abnormal point frequency value, screen the abnormal data with continuous changes, calculate the continuity of the abnormal data on the time axis, screen the data that meet the conditions as pollution events, and obtain the pollution event time series; Based on the pollution abnormal point frequency value, it is necessary to screen the abnormal data with continuous changes and calculate the continuity of the abnormal data on the time axis. Assume that multiple monitoring points in a water supply pipe network show abnormal changes during a certain period. Then, it is necessary to record the time point and duration of the abnormal occurrence. If the abnormal data remains continuous within a specific time period, that is, the data change rates of adjacent monitoring points both exceed the set threshold, it is determined as a pollution event. For example, on a water supply pipe, the residual chlorine concentration is continuously detected to decrease at 5 consecutive time points from 10:00 to 10:10 and exceeds 0.02 mg / L / min. Then, it is necessary to calculate the time continuity of the abnormal data with a set minimum continuous time threshold, such as 10 minutes as the judgment standard. That is, if the abnormal time exceeds 10 minutes, it is considered a pollution event. For example, if an abnormal point appears at 10:00, 10:05, and 10:10 respectively and lasts until 10:20, it is determined as a pollution event to obtain the pollution event time series.

[0040] S313: Analyze the water quality changes of the main water supply pipes and secondary pipes based on the time series of pollution incidents, using the formula: ; Calculate the pollutant diffusion trend value , and combine the pipe network topology relationship to determine whether the pollutant continues to spread, and statistically obtain the data of the pollution impact range. Among them, represents the concentration of the pollutant in the pipeline segment , represents the pollutant concentration in the previous time period, represents the flow velocity of the pipeline segment , represents the cross-sectional area of the pipeline segment , represents the th pipeline length, represents the total length of all polluted pipelines, represents the maximum value of the pollution incident time interval, represents the total number of all pipelines, represents the number of polluted pipelines; Based on the time series of pollution incidents, analyze the water quality changes of the main water supply pipes and secondary pipes, calculate the diffusion trend of pollutants in the pipeline, and need to combine the water flow velocity, pipe diameter and pollutant concentration changes in the pipeline. For example, if the residual chlorine concentration at a certain point in the pipeline section is 0.5 mg / L at 10:00 and drops to 0.3 mg / L at 10:05, then its mg² / L², is the water flow velocity (unit: m / s). If the flow velocity of a certain pipeline section is set to 0.8 m / s, then m³ / s³, represents the cross-sectional area of the pipeline. If the pipeline diameter is 0.3 m, then m 4 , calculate the diffusion trend contribution value of this pipeline section as , and similarly calculate other pipeline sections and accumulate to obtain the pollutant diffusion trend. represents the total length of all polluted pipelines. Assuming the total length of the polluted pipelines is 100 m, is the maximum value of the pollution incident time interval. If the maximum time interval is 15 minutes, then m / min, and finally calculate the pollution diffusion trend value m² / min, and combine the pipe network topology relationship to determine whether the pollutant continues to spread, and statistically obtain the data of the pollution impact range to obtain the pollution diffusion trend value.

[0041] Table 3.1 Pollution Diffusion Trend Calculation Parameter Table: ; As shown in Table 3.1, the pollution diffusion trend calculation parameters at different monitoring points cover the water quality changes, pipeline flow velocity, and pipeline size, and the calculated pollution diffusion trend values m² / min indicate the diffusion rate of pollutants in the pipe network. In the management of the water supply system, based on this data, the pollution impact range can be determined and corresponding control measures can be taken.

[0042] Please refer to Figure 5 , and step S4 is as follows: S411: Based on the pollution impact range data, combined with the pipe network topology structure, establish the propagation path of pollutants, identify the connection relationships between nodes, analyze the path and potential diffusion direction of pollutants along the pipe network, calculate the pollutant concentration change rate of each path, and obtain the pollutant propagation path data; Based on the pollution impact range data, first, the propagation path of pollutants needs to be established. Suppose a water supply pipe network consists of 6 monitoring points, and the initial pollutant concentrations of each point are shown in the following table: Table 4.1 Initial pollutant concentrations at monitoring points (mg / L): ; After determining the pollutant concentrations at the monitoring points, it is necessary to analyze the flow direction of adjacent pipe segments according to the pipe network topology structure and calculate the path of pollutant propagation along the water flow. For example, P1→P2→P3 is a pollutant diffusion path, and P3→P4→P5 is another diffusion path. After the water flow direction is clear, it is necessary to further calculate the pollutant concentration change rate of each path. The pollutant concentration change rate can be defined as: ; where is the pollutant concentration at monitoring point , and is the length of the pipe network between this point and the next monitoring point. For example, the calculation of the pollutant concentration change rate of the P1→P2 pipe segment is as follows: ; Similarly, the pollutant change rates of other pipe segments can be calculated, and the pollutant diffusion paths can be screened to finally obtain the pollutant propagation path data.

[0043] S412: Based on the pollutant propagation path data, compare the pollutant concentrations of each node in the polluted area, calculate the pollutant concentration change rate of each node, screen out the paths with a concentration change rate exceeding the set concentration increase threshold, and obtain the key concentration change paths; Retrieve the pollutant propagation path data, calculate the change rate of pollutant concentration at each node within the polluted area, and compare the concentration increase at each monitoring point. If the pollutant concentration increase at a certain monitoring point exceeds the set concentration increase threshold, then this path is determined to be a critical pollution path. This threshold is set based on the pipe network flow rate, the fluctuation range of the water quality background concentration, and the pollutant diffusion rate, comprehensively considering the typical concentration increase in historical pollution events and the detection sensitivity. Specifically, this value is determined by adding the average change amplitude of the pollutant to three times the standard deviation to ensure coverage of more than 95% of pollution anomalies. The threshold setting is as follows: Assume that the historical pollutant background concentration variation range in a certain area is 0.5 - 1.0 mg / L, calculate its standard deviation , then the threshold can be taken as . Calculate the change of pollutant concentration at each monitoring point, as shown in Table 4.2

[0044] Table 4.2 Change of pollutant concentration at monitoring points: ; As shown in Table 4.2, the pollutant concentration changes at P3 and P5 exceed the threshold, so P2→P3 and P4→P5 are marked as critical concentration change paths

[0045] S413: According to the critical concentration change path, use the formula: ; Calculate the diffusion influence intensity of the pollution path , and screen out the path with the largest diffusion influence intensity to obtain the pollution diffusion analysis information, where represents the pollutant concentration at path node , represents the average value of pollutant concentrations at all nodes on this path, represents the pipe network length at path node , represents the cumulative mass of pollutants at path node , represents the residence time of pollutants at path node , represents the total number of nodes on the path; Based on the critical concentration change path, calculate the pollutant diffusion influence intensity to determine the critical diffusion channels. The diffusion influence intensity considers the degree of deviation of the pollutant concentration from the mean value, the pipe network length, and the pollutant residence time

[0046] Now assume that the pollutant concentration mean value, cumulative mass, and residence time of the two paths P2→P3 and P4→P5 are as shown in the following table: Table 4.3 Parameters of critical diffusion paths: ; Substitute into the formula for calculation: ; ; ; ; Compare the results, is the largest. Therefore, P4→P5 is determined as the key diffusion channel, and finally the pollution diffusion analysis information is obtained.

[0047] Please refer to Figure 6 , and the steps of S5 are as follows: S511: Based on the pollution diffusion analysis information, obtain the diffusion path data of pollutants in the pipe network, sort out the diffusion direction, concentration change and time series of pollutants, determine the key diffusion channels of pollutants in the pipe network, identify the pollution diffusion trend along this channel, and extract the pollutant appearance time and concentration change of each node to obtain the pollution diffusion trend data; Based on the pollution diffusion analysis information, first, it is necessary to obtain the diffusion path data of pollutants in the pipe network. The specific steps include monitoring the pollutant concentration in the pipe network at different time nodes and recording the pollutant concentration changes at each pipe network node. For example, in a certain sewage treatment pipe network, 10 monitoring points (such as 1, 2, 3, 4, etc.) are selected, and the pollutant concentration is recorded every 10 minutes and sorted into the data shown in Table 5.1.

[0048] Table 5.1 Pollutant Concentration Data at Monitoring Points (Unit: mg / L): ; It can be seen from Table 5.1 that the pollutant concentration first increases at point A and then spreads along the pipe network to points B, C, D, and E, indicating that the main direction of pollutant diffusion is from A to E. Combining the pollutant concentration changes at different nodes, the diffusion rate can be further calculated to judge the key diffusion channels. Assuming that the flow velocity of the pollutant is 0.5 m / s, the diffusion distance of the pollutant within 10 minutes is m. Combining the actual pipe network topology structure, the main diffusion path can be determined as 1→2→3→4→5, thereby identifying the key diffusion channel.

[0049] S512: According to the pollution diffusion trend data, calculate the earliest appearance time of pollutants at each pipe network node, analyze the time series of pollutants, determine the node with the longest pollution duration, and screen out the node with the longest pollution duration that conforms to the pollution propagation characteristics. Use the formula: ; Calculate the average appearance time of pollutants , and calculate the pollution duration of each node in combination with the time offset to obtain candidate source nodes, where represents the pollutant concentration at the node . represents the time of the first appearance of the pollutant, represents the total number of nodes on the pollution diffusion path, represents the th pollution duration of the node, represents the average value of the pollution duration of all nodes, represents the total number of all nodes; When calling the pollution diffusion trend data, it is necessary to calculate the earliest appearance time of pollutants at each pipe network node. For example, assuming the initial time is minutes, then the earliest appearance time of pollutants at point A is minutes, at point B is minutes, at point C is minutes, and so on. The time series of pollutants can be sorted as follows: Table 5.2 Pollutant appearance time data (unit: minutes): ; Based on the data in Table 5.2, calculate the node with the longest pollution duration and substitute the data for calculation:

[0050] ; ; ; The calculation results show that the node with the longest pollution duration appears at minutes. Combining with the pipe network topology, the most likely pollution source is screened out, that is, the candidate source node.

[0051] S513: According to the candidate source nodes, compare the pollution duration of each node, and combine with the pollution diffusion path to screen out the nodes that meet the optimal tracing direction of pollution propagation to obtain the pollution source location result; Based on the candidate source nodes, it is necessary to compare the pollution duration of each node, and combine with the pollution diffusion path to screen out the nodes that meet the optimal tracing direction of pollution propagation. Assume that the candidate source nodes are one of 1, 2, and 3, and it is necessary to further analyze the change of pollutant concentration. For example, if the pollutant concentration changes violently at point 2, while the concentration at point 1 changes relatively smoothly, it can be judged that point 1 is more likely to be the pollution source. Based on the monitoring data: ; ; ; Calculation shows that the pollutant concentration at point 1 increases the fastest. Therefore, it can be preliminarily determined that point 1 is the pollution source. Finally, the pollution source location result is obtained.

[0052] The above are only the preferred embodiments of the present invention and do not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as they do not depart from the technical solution content of the present invention, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. An on-line monitoring method for surface water environment, characterized in that, It includes the following steps: S1: Obtain the water quality monitoring data of urban pipe network nodes, establish the pipe network topological structure, adjust the topological structure in combination with the water flow direction, determine the water flow direction, segment the topological structure by time, calculate the topological change frequency, and establish the pipe network topological evolution structure; S2: According to the pipe network topological evolution structure, calculate the changes in the water quality monitoring data of each node, analyze the water quality change trend of the urban water supply pipe network, and compare whether the water quality changes between pipes conform to the water flow propagation relationship, screen the pipe connections with abnormal fluctuations, and obtain the detrended water quality characteristic information; S3: According to the detrended water quality characteristic information, screen the pollution abnormal points, calculate the occurrence frequency of the abnormal points, analyze the water quality changes of the main water supply pipes and secondary pipes, calculate the pollutant diffusion trend, and statistically obtain the pollution impact range data; S4: According to the pollution impact range data, analyze the water quality pollution propagation direction, compare the pollutant concentrations of each node in the polluted area, mark the key diffusion channels, and obtain the pollution diffusion analysis information; S5: According to the pollution diffusion analysis information, trace the pollution occurrence location and calculate the earliest pipe network node where the pollutant appears, compare the pollution duration, screen the candidate pollution source points, and obtain the pollution source location result.

2. The online monitoring method for surface water environment according to claim 1, characterized in that The pipe network topological evolution structure includes the water flow direction, the topological change frequency, and the pipe segments with obvious changes. The detrended water quality characteristic information includes the water quality parameter fluctuation situation, the water quality change trend analysis result, and the pipe connections with abnormal fluctuations. The pollution impact range data includes the pollution abnormal points, the distribution of abnormal points, and the pollutant diffusion trend analysis result. The pollution diffusion analysis information includes the pollutant propagation path, the key diffusion channels, and the pollutant concentration change data. The pollution source location result includes the pollution occurrence location, the optimal pollution propagation tracing direction, and the candidate pollution source points.

3. The online monitoring method for surface water environment according to claim 1, characterized in that, The specific steps for obtaining the water quality monitoring data of urban pipe network nodes, establishing the pipe network topological structure, adjusting the topological structure in combination with the water flow direction, determining the water flow direction, segmenting the topological structure by time, calculating the topological change frequency, and establishing the pipe network topological evolution structure are as follows: S111: Obtain the water quality monitoring data of urban pipe network nodes, establish the pipe network topological structure, regard the nodes as water quality monitoring points, regard the pipes as connection relationships, adjust the topological structure in combination with the water flow direction, compare the pressure differences between adjacent nodes, calculate the water flow direction, screen the pipe segments with changed water flow direction, and obtain the screening record of the pipe segments with changed water flow direction; S112: Based on the screening record of the pipe segments with changed water flow direction, segment the topological structure by time, count the frequency of water flow direction changes in each time period, calculate the change frequency of each pipe segment, and obtain the pipe segment change frequency distribution data; S113: Based on the pipe segment change frequency distribution data, screen the pipe segments with a change frequency greater than the set threshold, and use the formula: ； Calculate the influence degree of topological evolution , and establish the topological evolution structure of the pipe network, where represents the water pressure change value of the th pipe segment, represents the length of the th pipe segment, represents the flow rate of the th pipe segment, represents the flow velocity of the th pipe segment, represents the change frequency of the water flow direction of the th pipe segment, represents the number of all selected pipe segments.

4. The on-line monitoring method for surface water environment according to claim 1, wherein The specific steps for calculating the changes in the water quality monitoring data of each node according to the pipe network topological evolution structure, analyzing the water quality change trend of the urban water supply pipe network, comparing whether the water quality changes between pipes conform to the water flow propagation relationship, screening the pipe connections with abnormal fluctuations, and obtaining the detrended water quality characteristic information are as follows: S211: Based on the topological evolution structure of the pipe network, calculate the changes in water quality monitoring data at each node, extract the temporal variation trends of water quality parameters, compare the fluctuation amplitudes of water quality parameters at each node, screen out the monitoring points that exceed the set water quality fluctuation threshold, and obtain the water quality abnormal monitoring points; S212: Based on the water quality abnormal monitoring points, analyze the water quality change trend of the water supply pipe network, combine with the flow direction of the water supply pipe network, compare the water quality change conditions of adjacent nodes, calculate the change rate of water quality parameters between each adjacent node, and use the formula: ； Calculate the water quality change rate of the th node, obtain the water quality change rate data of adjacent nodes, where represents the water quality parameter value of the th node, represents the water quality parameter value of its adjacent upstream node, represents the monitoring time of the th node, represents the monitoring time of its adjacent upstream node, represents the flow rate of the th node, represents the flow velocity of the th node, represents the flow rate of its adjacent upstream node, represents the flow velocity of its adjacent upstream node, represents the water pressure of the th node, represents the water pressure of its adjacent upstream node, represents the length of the pipeline between the th node and its adjacent node;​ S213: Based on the data of the change rate of water quality between adjacent nodes, compare whether the water quality change between pipes conforms to the water flow propagation relationship, screen out the abnormally fluctuating pipe connections, and obtain the detrended water quality characteristic information.

5. The on-line monitoring method for surface water environment according to claim 1, characterized in that The specific steps for screening pollution abnormal points, calculating the occurrence frequency of abnormal points, analyzing the water quality change conditions of the main water supply pipes and secondary pipes, calculating the pollutant diffusion trend, and statistically obtaining the pollution impact range data according to the detrended water quality characteristic information are as follows: S311: Based on the detrended water quality characteristic information, calculate the degree of water quality change at adjacent times, extract the change rate of water quality, compare the change rate with the set abnormal range, screen out the pollution abnormal points of the urban water supply pipe network that exceed the change range, calculate the occurrence frequency of each abnormal point, and obtain the pollution abnormal point frequency value; S312: Based on the pollution abnormal point frequency value, screen out the continuously changing abnormal data, calculate the continuity of the abnormal data on the time axis, screen out the data that meet the conditions as pollution events, and obtain the pollution event time series; S313: Based on the pollution event time series, analyze the water quality change conditions of the main water supply pipes and secondary pipes, and use the formula: ； Calculate the pollutant diffusion trend value , determine whether the pollutant continues to spread by combining the pipe network topology relationship, and statistically obtain the data of the pollution influence range. Among them, represents the concentration of the pollutant in the pipe segment . represents the pollutant concentration in the previous time period, represents the flow velocity of the pipe segment . represents the cross-sectional area of the pipe segment . represents the length of the th pipe, represents the total length of all polluted pipes, represents the maximum value of the time interval of the pollution event, represents the total number of all pipes, represents the number of polluted pipes.

6. The on-line monitoring method for surface water environment according to claim 1, wherein, The specific steps for analyzing the water quality pollution propagation direction according to the pollution impact range data, comparing the pollutant concentrations at each node in the polluted area, marking the key diffusion channels, and obtaining the pollution diffusion analysis information are as follows: S411: Based on the pollution impact range data, combine with the pipe network topological structure, establish the propagation path of pollutants, identify the connection relationships between each node, analyze the path and potential diffusion direction of pollutants propagating along the pipe network, calculate the change rate of pollutant concentration of each path, and obtain the pollutant propagation path data; S412: Based on the pollutant propagation path data, compare the pollutant concentrations at each node in the polluted area, calculate the change rate of pollutant concentration at each node, screen out the paths whose change rate of concentration exceeds the set concentration increase threshold, and obtain the key concentration change paths; S413: According to the key concentration change paths, use the formula: ； Calculate the pollution path of the diffusion influence intensity , and screen out the path with the maximum diffusion influence intensity to obtain pollution diffusion analysis information. Among them, represents the pollutant concentration of the path node . represents the average value of the pollutant concentrations of all nodes on this path represents the pipe network length at the path node . represents the cumulative mass of pollutants at the path node . represents the residence time of pollutants at the path node . represents the total number of nodes on the path 7. The on-line monitoring method for surface water environment according to claim 1, characterized in that The specific steps for tracing the pollution occurrence location according to the pollution diffusion analysis information, calculating the earliest pipe network node where pollutants appear, comparing the pollution duration, screening out the candidate pollution sources, and obtaining the pollution source location result are as follows: S511: Based on the pollution diffusion analysis information, obtain the diffusion path data of pollutants in the pipe network, sort out the diffusion direction, concentration change and time series of pollutants, determine the key diffusion channels of pollutants in the pipe network, identify the pollution diffusion trend along this channel, and extract the pollutant appearance time and concentration change at each node to obtain the pollution diffusion trend data; S512: Calculate the earliest occurrence time of pollutants at each pipe network node based on the pollution diffusion trend data, analyze the time series of pollutants, determine the node with the longest pollution duration, and screen out the node with the longest pollution duration that conforms to the pollution propagation characteristics. Use the formula: ； Calculate the average occurrence time of pollutants , and calculate the pollution duration of each node in combination with the time offset to obtain candidate nodes of the pollution source, where represents the pollutant concentration at node . represents the first occurrence time of the pollutant represents the total number of nodes on the pollution diffusion path represents the pollution duration of the -th node represents the average value of the pollution duration of all nodes represents the total number of all nodes; S513: Based on the candidate pollution source nodes, compare the pollution duration of each node, and combine with the pollution diffusion path to screen out the nodes that conform to the optimal tracing direction of pollution propagation, and obtain the pollution source location result.

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