Water quality monitoring system and method

Abstract

The embodiment of the present application relates to the technical field of water quality monitoring, and discloses a water quality monitoring system and method. The system includes: a water quality monitoring model determination module, which is used to determine a target water quality monitoring model based on first detection data and second detection data, and send the target water quality monitoring model to a cloud database; wherein the first detection data is determined by a portable monitoring instrument, and the second detection data is determined by a preset fixed monitoring site; a cloud database, which is used to send the target water quality monitoring model to the fixed monitoring site; a water quality monitoring model update module, which is used to update and upgrade the original water quality monitoring model of the fixed monitoring site according to the target water quality monitoring model. It can at least be used to solve the technical problem that the water quality monitoring method in the related technology cannot meet the needs of modern water body management.

Description

Technical Field

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

[0002] In order to achieve supervision and protection of the aquatic environment, the key is to accurately and efficiently monitor the water quality of rivers and lakes.

[0003] At present, river and lake management mainly relies on traditional empirical observation methods, such as "eyes, ears, and nose" to assess water quality, or regularly uses reagent box testing or manual sampling and then sends it to the laboratory for analysis.

[0004] However, the inventors found that there are at least the following technical problems in the related art:

[0005] Traditional empirical observation methods are affected by the experience and subjective judgment of inspectors, resulting in unstable monitoring quality, many loopholes, and low efficiency, and it is difficult to form continuous, complete, and dynamic visual data. The method of regularly using reagent box testing or manual sampling and sending to the laboratory for analysis has low detection efficiency and cannot meet the needs of modern water management. Summary of the invention

[0006] One purpose of the present application is to provide a method to at least solve the technical problem that the water quality monitoring method in the related art cannot meet the needs of modern water management.

[0007] To achieve the above objectives, some embodiments of the present application provide the following aspects:

[0008] In the first aspect, some embodiments of the present application also provide a water quality monitoring system, the system comprising: a water quality monitoring model determination module, used to determine a target water quality monitoring model based on first detection data and second detection data, and send the target water quality monitoring model to a cloud database; wherein the first detection data is determined by a portable monitoring instrument, and the second detection data is determined by a preset fixed monitoring site; a cloud database, used to send the target water quality monitoring model to the fixed monitoring site; a water quality monitoring model update module, used to update and upgrade the original water quality monitoring model of the fixed monitoring site according to the target water quality monitoring model.

[0009] In a second aspect, some embodiments of the present application further provide a water quality monitoring method, which is applied to the system as described above, and the method at least comprises:

[0010] According to the first detection data and the second detection data, a target water quality monitoring model is determined, and the target water quality monitoring model is sent to a cloud database; wherein the first detection data is determined by a portable monitoring instrument, and the second detection data is determined by a preset fixed monitoring site; the target water quality monitoring model is sent to the fixed monitoring site; according to the target water quality monitoring model, the original water quality monitoring model of the fixed monitoring site is updated and upgraded.

[0011] Compared with the related art, in the solution provided in the embodiment of the present application, by determining the target water quality monitoring model based on the first detection data and the second detection data, the flexibility of portable monitoring instruments and the continuous monitoring advantages of fixed monitoring sites are cleverly utilized to ensure the reliability of water quality monitoring data, while also optimizing the maintenance process of water quality monitoring; it can solve the technical problems in the related art that the traditional empirical observation method is affected by the experience and subjective judgment of inspectors, resulting in unstable monitoring quality, many loopholes, and low efficiency, and it is difficult to form continuous, complete, and dynamic visual data, as well as the method of regularly using reagent box detection or manual sampling and sending to the laboratory for analysis, which has low detection efficiency and cannot meet the needs of modern water body management. It helps to realize the intelligence and precision of water quality monitoring, and provide more powerful technical support for water resource management and protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0013] Figure 1 An exemplary structural diagram of a water quality monitoring system provided according to some embodiments of the present application;

[0014] Figure 2 An exemplary flow chart of a water quality monitoring system provided according to some embodiments of the present application;

[0015] Figure 3 An exemplary schematic diagram of a water quality monitoring system provided according to some embodiments of the present application;

[0016] Figure 4 is another exemplary schematic diagram of a water quality monitoring system provided according to some embodiments of the present application;

[0017] Figure 5 An exemplary schematic diagram of linear modeling in a water quality monitoring system provided according to some embodiments of the present application;

[0018] Figure 6An exemplary schematic diagram of nonlinear modeling in a water quality monitoring system provided according to some embodiments of the present application;

[0019] Figure 7 This is an exemplary flow chart of a water quality monitoring method provided according to some embodiments of the present application. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0021] First embodiment

[0022] The first embodiment of the present application relates to a water quality monitoring system. Figure 1 and Figure 2 As shown, the system may include: a water quality monitoring model determination module, a cloud database and a water quality monitoring model update module.

[0023] Specifically, the water quality monitoring model determination module is used to determine the target water quality monitoring model based on the first detection data and the second detection data, and send the target water quality monitoring model to the cloud database; wherein, the first detection data is determined by a portable monitoring instrument, and the second detection data is determined by a preset fixed monitoring site.

[0024] Exemplarily, the first detection data can be obtained by using a portable monitoring instrument to measure the water body in real time on site. In some examples, the water quality monitoring system can be as follows: Figure 3As shown, in this example, the portable monitoring instrument is mainly in the form of a portable instrument box. The portable monitoring instrument has the characteristics of high precision, multi-parameters and strong portability. It can quickly and accurately detect various indicators of water quality in various complex environments, and provide reliable data support for water quality safety. In some examples, the portable monitoring instrument can be designed with a high-strength PVC engineering plastic suitcase, which has high hardness and a solid structure and is suitable for field operations; in some other examples, the portable monitoring instrument can combine spectral detection and sensor detection technology to quickly detect multiple water quality indicators. This method is simple and fast to operate, does not cause reagent pollution, and the detection process can be completed in a few seconds. In addition, there is also an integrated digestion and detection technology, which decomposes the pollutants in the sample for detection, and the whole process takes about 30 minutes. In actual operation, if abnormal water quality data is found in the on-site rapid detection, it can be quickly sampled and taken back to the laboratory for more accurate determination using chemical methods to ensure the accuracy of the monitoring results. In addition, the built-in digestion module has a dual-temperature zone function, which can effectively digest the sample under different temperature conditions, optimize the chemical reaction process, and ensure the accuracy of the monitoring results.

[0025] In some embodiments, the water quality monitoring system can refer to Figure 4 As shown, the system may also include a handheld Bluetooth communication device, a portable monitoring instrument (sensor) and a mobile phone application. Among them, the handheld Bluetooth communication device is a stick-shaped device designed to be directly connected to the sensor; the handheld Bluetooth communication device has a built-in lithium battery and a power supply module, which can provide the required power for the sensor; the handheld Bluetooth communication device has a built-in Bluetooth module for establishing a wireless connection with a smartphone application app, replacing the form of a portable instrument box, which is flexible and portable; through the Bluetooth connection, the handheld Bluetooth communication device can transmit the data collected by the sensor to the mobile phone application app in real time. It can be seen that through this design, the water quality monitoring system is both flexible and portable, and relevant personnel can easily view and analyze the data collected by the sensor through the mobile phone application app.

[0026] Exemplarily, the second detection data can be determined by data uploaded by monitoring instruments at a preset fixed monitoring site. Generally speaking, the second detection data can be uploaded to a laboratory. Among them, several fixed monitoring sites can form a water quality monitoring network.

[0027] Exemplarily, the first detection data and the second detection data may respectively include but are not limited to: pH value, dissolved oxygen, chemical oxygen demand (COD), ammonia nitrogen, etc., which is not specifically limited in the embodiment of the present application.

[0028] It can be understood that for the water quality monitoring network, the monitoring instruments (such as sensors) at fixed monitoring sites need to operate for a long time. Therefore, the monitoring instrument may have technical problems of drift and decreased accuracy due to long-term work. In the related art, in order to solve the technical problems of drift and decreased accuracy of the monitoring instruments at the aforementioned fixed monitoring sites due to long-term work, relevant personnel are often required to regularly maintain and calibrate the monitoring instruments at the fixed monitoring sites to ensure the normal operation of the monitoring instruments, which is a time-consuming and laborious process. In an embodiment of the present application, based on the portability of the portable monitoring instrument, an accuracy test can be performed in the laboratory with a standard solution before using the portable monitoring instrument to ensure that the portable monitoring instrument is in a normal measurement state; and because the portable monitoring instrument is used on site for water quality detection, the data obtained shows the real-time water quality status. Therefore, by comparing the first detection data detected by the portable monitoring instrument with the second detection data of the monitoring instrument at the fixed monitoring site, it is possible to effectively determine whether there is an abnormality in the monitoring instrument at the fixed monitoring site, and ensure the authenticity and validity of the monitoring data. Through this comparison, the daily maintenance workload of monitoring instruments at fixed monitoring sites can be reduced, which can reduce maintenance costs and improve maintenance efficiency.

[0029] It can be seen that in the embodiment of the present application, by determining the target water quality monitoring model based on the first detection data and the second detection data, the flexibility of the portable monitoring instrument and the continuous monitoring advantage of the fixed monitoring site are cleverly utilized to ensure the reliability of the water quality monitoring data, while also optimizing the maintenance process of water quality monitoring. In other words, in the embodiment of the present application, by introducing a portable monitoring instrument to conduct collaborative measurements with the monitoring instruments at the fixed monitoring site, it is helpful to discover and correct possible measurement errors, and the authenticity and reliability of the water quality monitoring data can be ensured.

[0030] Specifically, the cloud database is used to send the target water quality monitoring model to the fixed monitoring site. The water quality monitoring model update module is used to update the original water quality monitoring model of the monitoring instrument of the fixed monitoring site according to the target water quality monitoring model.

[0031] Exemplarily, after obtaining the target water quality monitoring model, the water quality monitoring model determination module may integrate the target water quality monitoring model into a cloud database, and send the target water quality monitoring model to fixed monitoring sites in the water quality monitoring network through the cloud database.

[0032] Furthermore, the established river channel model can be integrated and deployed to the fixed monitoring sites of the water quality monitoring network through cloud technology. In this way, the monitoring instruments at the fixed monitoring sites can update and upgrade their original water quality monitoring models according to the issued river channel model, thereby improving the water quality analysis capabilities of the fixed monitoring sites, improving the accuracy of the monitoring data of the monitoring instruments and their adaptability to complex water environments, and improving the accuracy of the monitoring results.

[0033] It can be understood that by upgrading the original water quality monitoring model update module of the monitoring instrument at the fixed monitoring site according to the river model, the monitoring instrument can more accurately reflect the water quality conditions, improve the efficiency and accuracy of monitoring, and enhance the response capability to sudden water quality incidents.

[0034] It can be seen that in the embodiments of the present application, by synchronizing the monitoring data of portable monitoring instruments and fixed monitoring sites, a more accurate water quality monitoring model can be established, and these models can be applied to fixed monitoring sites through cloud technology, thereby improving the overall efficiency of water quality monitoring. This method helps to realize the intelligence and precision of water quality monitoring and provide more powerful technical support for water resource management and protection.

[0035] For example, the preliminary assessment of water quality network construction: quickly assess water quality safety with the help of portable monitoring instruments. It can be understood that portable monitoring instruments have the advantages of portability, ease of operation, and rapid response. They can quickly detect water quality at different locations and keep abreast of water quality conditions.

[0036] Furthermore, a river archive can be established based on the monitoring results of the portable monitoring instrument, wherein the river archive can provide timely and accurate water quality information and provide a scientific basis for the construction of a water quality monitoring and management network.

[0037] For example, the river archive may record basic information about the river, including but not limited to: river name, length, width, water depth, flow rate, etc.; water quality parameters, such as pH value, dissolved oxygen, chemical oxygen demand, ammonia nitrogen, total phosphorus, etc.; surrounding environment information, such as pollution sources, land use type, etc. This can provide a basis for the planning and design of the water quality monitoring and management network.

[0038] Based on the assessment results, the location, number and frequency of monitoring points are determined to ensure that the network can monitor water quality comprehensively and accurately.

[0039] It is not difficult to find that compared with the related art, in the solution provided in the embodiment of the present application, by determining the target water quality monitoring model based on the first detection data and the second detection data, the flexibility of the portable monitoring instrument and the continuous monitoring advantage of the fixed monitoring site are cleverly utilized to ensure the reliability of the water quality monitoring data, and at the same time optimize the maintenance process of the water quality monitoring; it can solve the technical problems in the related art that the traditional empirical observation method is affected by the experience and subjective judgment of the inspectors, resulting in unstable monitoring quality, many loopholes, and low efficiency, and it is difficult to form continuous, complete, and dynamic visual data, as well as the method of regularly using reagent box detection or manual sampling and sending to the laboratory for analysis, which has low detection efficiency and cannot meet the needs of modern water body management. It helps to realize the intelligence and precision of water quality monitoring, and provide more powerful technical support for water resources management and protection.

[0040] Second embodiment

[0041] The second embodiment of the present application relates to a water quality monitoring system. The second embodiment is an improvement on the first embodiment, and the specific improvement is: in the second embodiment of the present application, a specific implementation method of a water quality monitoring model determination module is provided.

[0042] Specifically, the water quality monitoring model determination module may further include a time synchronization unit and a model determination unit;

[0043] The time synchronization unit is used to synchronize the detection time of the first detection data with the assay time of the second detection data to obtain a synchronization result;

[0044] The water quality monitoring model determination module is used to determine the target water quality monitoring model according to the synchronization result.

[0045] Specifically, in the related art, for long-term water quality monitoring, relevant personnel need to collect water samples at different water collection points for testing at irregular intervals, and this sampling method is random. At the same time, the monitoring instruments at the fixed monitoring site are installed at fixed monitoring positions for continuous measurement. Due to the differences in time and space, there are differences in the data obtained by these two monitoring methods, resulting in monitoring errors. Therefore, in the related art, the first detection data and the second detection data are usually only suitable for analyzing the trend of water quality changes, but not for establishing a target water quality monitoring model. That is to say, in the related art, the second monitoring data of the fixed monitoring site cannot be used to improve the performance of the original water quality monitoring model of the fixed monitoring site itself, thereby failing to improve the water quality monitoring capability of the original water quality monitoring model of the fixed monitoring site itself. In order to solve this problem, in an embodiment of the present application, the target water quality monitoring model is established by synchronizing the detection time of the portable monitoring instrument with the test time of the sampled water sample test, and synchronizing the results.

[0046] Optionally, in some embodiments, the water quality monitoring model determination module is specifically used to determine the difference value between the first detection data and the second detection data at the same time according to the synchronization result; and determine the target water quality monitoring model according to the difference value.

[0047] Exemplarily, if the difference value is less than or equal to a preset threshold, the first detection data and the second detection data are used as input data of a water quality prediction model, and the water quality prediction model can automatically call the water quality prediction algorithm in the cloud database to correct and optimize the current water quality monitoring model to obtain the target water quality monitoring model (wherein the current water quality monitoring model here corresponds to the original water quality monitoring model of the fixed monitoring site); otherwise, if the difference value is greater than the preset threshold, it means that the error is large, and the system can issue an alarm message or prompt message.

[0048] It is not difficult to find that in the embodiment of the present application, the portable monitoring instrument can be used as a supplement and verification tool for the second detection data of the fixed monitoring site. By comparing the data of the two, possible measurement errors can be discovered and corrected in time, thereby improving the reliability of the monitoring data.

[0049] Third embodiment

[0050] The third embodiment of the present application relates to a water quality monitoring system. The third embodiment is an improvement on the second embodiment, and the specific improvement is that: in the second embodiment of the present application, the target water quality monitoring model can be a universal water quality monitoring model; while in the third embodiment of the present application, the target water quality monitoring model is a water quality monitoring model determined based on river archives.

[0051] Specifically, the water quality monitoring model determination module may further include a river channel archive determination unit.

[0052] The river course archive determination unit is used to determine the river course archive according to the first detection data and the second detection data; wherein the river course archive includes water quality history information and water quality status information for characterizing the target river course;

[0053] The water quality monitoring model determination module is used to determine the target water quality monitoring model according to the synchronization result and the river archive.

[0054] For example, a series of data can be collected by using portable monitoring instruments to test water quality regularly or irregularly, and a river archive on water quality can be established based on these data. Since the river archive includes historical water quality information and current water quality information used to characterize the target river, it is helpful to understand the historical changes in water quality and the current water quality status of the target river, and provide basic data for the current formulation of effective water management measures and emergency response plans.

[0055] Optionally, in some embodiments, before the water quality monitoring model determination module determines the target water quality monitoring model based on the synchronization result and the river archive, the system can obtain the actual value and the predicted value based on the universal water quality monitoring model, and calculate the mean square error between the actual value and the predicted value, and evaluate the prediction accuracy of the universal water quality monitoring model based on the mean square error. It can be understood that the mean square error refers to the expected value of the square of the difference between the estimated value of the parameter and the true value of the parameter. In the embodiment of the present application, it can be used to characterize the prediction accuracy of the universal water quality monitoring model. Exemplarily, the smaller the value of the mean square error, the higher the prediction accuracy of the universal water quality monitoring model.

[0056] Exemplarily, the method for determining the mean square error can be implemented by the following formula:

[0057]

[0058] Among them, the represents the mean square error, the represents the total number of observations, Represents the index of each observation, from 1 to , Indicates The actual value of the observations, Indicates The predicted value of the observed value.

[0059] Furthermore, in some examples, a pre-set mean square error threshold can be obtained; if the calculated mean square error value is less than or equal to the mean square error threshold, it can be indicated that the water quality of the current river can be predicted using the general water quality monitoring model; if the mean square error value is greater than the mean square error threshold, it can be indicated that the water quality components of the river are relatively complex, and the use of the general water quality monitoring model cannot provide accurate predictions. In this case, it is necessary to establish a separate target water quality monitoring model for the river to improve the accuracy of the prediction. Specifically, the river archive determination unit is used to determine the river archive based on the first detection data and the second detection data; wherein the river archive includes water quality historical information and water quality status information for characterizing the target river; the water quality monitoring model determination module is used to obtain the target water quality monitoring model determination module based on the synchronization result and the river archive, which is used to determine the target water quality monitoring model based on the synchronization result and the river archive.

[0060] Optionally, in some embodiments, the system may further include the fixed monitoring site determination unit, which is used to determine at least one of the following based on the river channel file provided by the river channel file determination unit: the layout of several fixed monitoring sites in the water quality monitoring management network, the monitoring frequency of each fixed monitoring site, and the location of each fixed monitoring site.

[0061] Optionally, in some embodiments, the fixed monitoring site determination unit is further specifically used to receive the planned number of the fixed monitoring sites; based on the river archive of the target river and the planned number, determine the layout of several fixed monitoring sites in the water quality monitoring management network, the monitoring frequency of each fixed monitoring site, and the location of each fixed monitoring site. Exemplarily, relevant personnel can specify the planned number of fixed monitoring sites that can be established for the target river in the system, and then the fixed monitoring site determination unit can determine the layout of several fixed monitoring sites in the water quality monitoring management network, the monitoring frequency of each fixed monitoring site, and the location of each fixed monitoring site based on the river archive of the target river and the planned number. Doing so will help optimize the monitoring network, ensure the effective use of resources, and help improve the efficiency and coverage of the water quality monitoring network.

[0062] Specifically, in some examples, the system can obtain specific index requirements for each type of water quality based on the current definition of water categories 1 to 5. Then, the system can compare the collected water quality measurement indicators of different rivers with these standard indicators, calculate the relative error of each indicator, and obtain a numerical value used to characterize the degree of pollution in the river by accumulation or weighted calculation. The numerical values ​​used to characterize the degree of pollution in the river will be sorted to obtain a sorting result; based on the sorting result, relevant personnel can refer to and evaluate the pollution status of the river, thereby determining the layout of several fixed monitoring stations in the water quality monitoring management network, the monitoring frequency of each fixed monitoring station, and the location of each fixed monitoring station.

[0063] In some examples, the system can also establish a corresponding decision-making intelligent model to determine the layout of several fixed monitoring stations in the water quality monitoring management network, the monitoring frequency of each fixed monitoring station, and the location of each fixed monitoring station based on the decision-making intelligent model.

[0064] Exemplarily, the decision intelligence model may specifically be, but is not limited to, a TS fuzzy neural network model.

[0065] Specifically, corresponding to the step of determining the layout of several fixed monitoring sites in the water quality monitoring and management network, the monitoring frequency of each fixed monitoring site, and the location of each fixed monitoring site according to the TS fuzzy neural network model, the system may include: a data collection and preprocessing module, a first determination module for determining input and output variables, a construction module for constructing the TS fuzzy neural network model, a model training module, and a second determination module for determining the layout, monitoring frequency and location of monitoring sites.

[0066] In some examples, the data collection and preprocessing module can be used to collect factor data of the target area, and the factor data refers to relevant data that may affect changes in water quality and the layout of monitoring sites. For example, the factor data may include at least one of the following: geographic information, water system distribution, population density, and industrial distribution. The data collection and preprocessing module is also used to collect historical water quality monitoring data, including various water quality parameters at different locations and time points, such as pH, dissolved oxygen, chemical oxygen demand, etc. The data collection and preprocessing module is also used to clean and preprocess the collected data to remove outliers and noise to ensure the accuracy and reliability of the data.

[0067] In some examples, the first determination module can be used to determine the input variables of the TS fuzzy neural network in combination with the factor data. Exemplarily, the input variables may include at least one of the following: geographic location coordinates (latitude and longitude), surrounding environmental characteristics (such as the distance from the industrial area, the distance from the residential area, etc.), water system flow, season, etc. The first determination module is also used to determine the output variable. Exemplarily, the output variable may include at least one of the following: the layout of the monitoring site (a Boolean value of whether to set the monitoring site), the monitoring frequency (such as once a day, once a week, etc.), and the location (latitude and longitude coordinates).

[0068] In some examples, the construction module is specifically used to fuzzify the input variables, divide them into several fuzzy sets according to the value range of the input variables, and obtain a fuzzy layer. For example, the value range of the input variables can be divided into: "low", "medium", "high", etc. The construction module is also used to generate several fuzzy rules according to the fuzzified input variables to obtain a rule layer. For example, the generated fuzzy rules may include: if the distance to the industrial area is close and the water flow is large, the monitoring frequency is high. The construction module is also used to defuzzify the output of the rule layer to obtain a defuzzified layer. The defuzzified layer is used to generate specific output values, namely the layout, monitoring frequency and location of the monitoring site.

[0069] In some examples, the model training module is used to train and evaluate the TS fuzzy neural network model constructed by the construction module. Specifically, the collected historical data can be divided into a training set and a test set, usually in a certain proportion, such as 70% of the data as a training set and 30% of the data as a test set. Then the training set is used to train the TS fuzzy neural network, and by adjusting the weights and parameters of the network, the TS fuzzy neural network model can accurately predict the layout, monitoring frequency and location of the monitoring site. Exemplarily, an optimization algorithm such as a back propagation algorithm can be used for training. The trained TS fuzzy neural network model can be evaluated using a test set to calculate indicators such as the accuracy and recall rate of the TS fuzzy neural network model. By evaluating the performance of the TS fuzzy neural network model, the target TS fuzzy neural network model can be obtained.

[0070] In some examples, the second determination module is used to input the geographic information, environmental characteristics, etc. of the area to be monitored into the trained target TS fuzzy neural network model. The target TS fuzzy neural network model can predict the layout, monitoring frequency and location of the monitoring sites in the area based on the input information. In addition, the system can also analyze the results predicted by the target TS fuzzy neural network model to determine whether the results are reasonable, and can adjust the results according to actual conditions. For example, if the predicted monitoring frequency is too high, a prompt message can be issued to reduce the monitoring frequency to save costs; if the predicted location is not convenient for monitoring, a prompt message can be issued to adjust the location to other alternative areas.

[0071] Furthermore, after obtaining the layout, monitoring frequency and location of the monitoring site, the system can also regularly update and optimize the target TS fuzzy neural network model as time goes by and new data accumulates, so as to improve the accuracy and adaptability of the target TS fuzzy neural network model. In addition, the system can also adjust and optimize the layout, monitoring frequency and location of the monitoring site according to the actual monitoring results and feedback information to ensure the effectiveness and reliability of the water quality monitoring management network.

[0072] For example, the river can be divided into several areas according to the geographical information of the river. A clustering algorithm, such as the K-means clustering algorithm, can be used. The river is divided into (the planned number of) clusters using geographical features such as the length, width, and surrounding environment of the river as clustering attributes. The center of each cluster or a representative location (such as a point close to the point with the largest water quality change within the cluster) is preliminarily determined as a candidate location for a fixed monitoring site. Furthermore, the changes in the historical water quality data within each cluster can be analyzed, including the fluctuation range and change frequency of water quality parameters.

[0073] If the water quality changes within a cluster are large and uneven, add more candidate monitoring points to the cluster, or adjust the location of the candidate monitoring points to make them closer to the area with complex water quality changes.

[0074] Furthermore, for each initially determined fixed monitoring station location, analyze the fluctuation of the water quality parameters of the corresponding river area in the historical data. Calculate the standard deviation or coefficient of variation of the water quality parameters (the ratio of the standard deviation to the mean). If the water quality parameters of a certain area fluctuate greatly (the standard deviation or coefficient of variation exceeds a certain threshold), the monitoring frequency of the fixed monitoring station corresponding to the area is set to a higher value. For example, for areas with large water quality fluctuations, monitoring can be performed every hour or every half hour; for areas with relatively stable water quality, monitoring can be set 4 to 6 times a day. For areas where there are pollution sources such as sewage treatment plant outlets, continuous monitoring at the minute level can be performed. At the same time, the potential impact of the surrounding environment of each fixed monitoring station on water quality can also be considered. If there are many pollution sources (such as factories, sewage treatment plants, etc.) or areas susceptible to pollution (such as agricultural irrigation areas, residential areas, etc.) in the surrounding area, the monitoring frequency of the station should be appropriately increased.

[0075] Furthermore, the locations of fixed monitoring stations are finally optimized by comprehensively considering the preliminary results of the layout and monitoring frequency. Specifically, the expected values ​​of coverage and accuracy of water quality monitoring of the entire river can be calculated for each combination of the initially determined monitoring station layout and monitoring frequency. A simulation algorithm can be used to evaluate the detectable changes in water quality and the ability to respond to the overall river water quality conditions, assuming water quality monitoring under different layouts and frequencies. According to the expected values ​​of coverage and accuracy, the locations of monitoring stations are adjusted to ensure the best water quality monitoring effect within the limits of the planned number. Furthermore, the finalized locations of fixed monitoring stations can be verified using field visits or geographic information system (GIS) technology. If it is found that some locations have practical operational difficulties (such as difficulty in reaching, safety issues, etc.) or inaccurate geographic information, the locations are appropriately adjusted, and the rationality of the layout and monitoring frequency are re-evaluated.

[0076] It can be understood that in the related art, the method for selecting fixed monitoring sites is to determine the monitoring indicators in the early stage of building the fixed monitoring sites, and to manually monitor and evaluate the water quality. Among them, the monitoring indicators are used to characterize the water quality parameters that need to be monitored for a long time at the fixed monitoring sites. And the layout, monitoring frequency and location of the fixed monitoring sites are determined manually based on the results of water quality monitoring and evaluation. This method results in a large workload for relevant personnel and low efficiency. The technical solution provided by the embodiment of the present application can effectively solve the technical problems of large workload and low efficiency for relevant personnel.

[0077] It should be noted that the third embodiment of the present application may also be an improvement based on the first embodiment.

[0078] It is not difficult to find that in the embodiment of the present application, the target water quality monitoring model is a water quality monitoring model determined based on river archives, which is conducive to understanding the historical changes in the water quality of the target river and the current water quality status, and providing basic data for the current formulation of effective water management measures and emergency response plans.

[0079] Fourth embodiment

[0080] The fourth embodiment of the present application relates to a water quality monitoring system. The fourth embodiment is an improvement on the third embodiment, and the specific improvement is that: in the third embodiment of the present application, the target water quality monitoring model can be constructed based on the entire target river; and in the fourth embodiment of the present application, in the process of constructing the target water quality monitoring model, the tributary information of the target river can also be considered.

[0081] Optionally, in some embodiments, the system further includes an emergency response module; the river archive further includes tributary information for characterizing the target river;

[0082] The water quality monitoring model determination module is specifically used to determine whether there is an abnormality in the tributary information of the target river channel through the second detection data provided by the fixed monitoring station deployed on the tributary side; and when it is determined that there is an abnormality in the tributary information of the target river channel, issue a prompt message; the prompt message is used to prompt the deployment of the portable monitoring instrument on the tributary side so that the portable monitoring instrument issues the first detection data based on the tributary side;

[0083] The emergency response module is used to determine the diffusion range and diffusion trend of the pollutants based on the first detection data and the second detection data.

[0084] Specifically, fixed monitoring stations can be used to comprehensively monitor the water quality of upstream and downstream tributaries of the target river, so as to obtain tributary information of the target river, such as historical water quality information and current water quality information based on the tributaries. For example, the tributaries upstream of the water source of the target river can be monitored, and if abnormalities are detected in the tributaries upstream of the water source, it indicates that pollution may have entered.

[0085] Furthermore, when it is determined that there is an abnormality in the tributary information of the target river, the system can issue a prompt message so that relevant personnel can immediately deploy portable monitoring instruments to relevant areas, and use the portable monitoring instruments to conduct rapid water quality testing to obtain the first test data. It can be understood that fixed monitoring sites can generally only monitor limited water quality parameters and cannot detect newly emerging pollutants. In the embodiment of the present application, since the monitoring indicators of the fixed monitoring site are relatively fixed, by cleverly coordinating the fixed monitoring site and the portable monitoring instrument, it is possible to achieve multi-parameter detection using portable monitoring instruments, and adjust or modify the corresponding parameters according to actual needs, so as to detect more water quality parameters, which helps to discover new pollution indicators and provide data support for the upgrade of the water quality monitoring network.

[0086] Optionally, in some embodiments, multiple water quality parameters can be detected according to the portable monitoring instrument to obtain monitoring results; a water quality classification and discrimination model can be constructed according to the monitoring results; wherein the water quality classification and discrimination model is used to adaptively identify different water quality categories. The water quality monitoring model can include several water quality classification and discrimination models. In this way, the system can intelligently select a suitable water quality classification and discrimination model for water quality monitoring.

[0087] Exemplarily, the multiple water quality parameters may include, but are not limited to: at least one of the following water quality parameters: water temperature, pH value, dissolved oxygen, salinity, turbidity, chemical oxygen demand (COD), ammonia nitrogen, etc. The above parameters are key indicators for evaluating water quality. For example, pH value and dissolved oxygen are basic indicators for measuring the health of water bodies; chemical oxygen demand (COD) and ammonia nitrogen are important parameters for evaluating the degree of organic pollution in water bodies. By detecting these parameters, the pollution status and ecological health status of water bodies can be quickly understood.

[0088] Furthermore, the emergency response module can analyze the types and concentration changes of pollutants by comparing and integrating the first detection data and the second detection data, trace the specific pollution source, further determine the diffusion range and trend of pollutants, and form a complete water quality monitoring report to obtain monitoring results. This is conducive to quickly taking corresponding emergency measures, such as notifying relevant departments and launching emergency plans, so as to reduce the impact of pollution on water quality.

[0089] Furthermore, this incident can also be used to evaluate and optimize the water quality monitoring network, increase the necessary monitoring points at fixed monitoring stations, and improve the coverage and response speed of the monitoring network.

[0090] It is understandable that the existing water quality monitoring network, based on construction cost considerations, generally only monitors the key nodes of the main rivers, while ignoring the tributaries and failing to effectively monitor the tributaries. Through the technical solution provided by the embodiment of the present application, the technical problem that the monitoring water quality parameters of the fixed monitoring stations that have been built are limited and cannot perceive new pollutants is cleverly solved with the help of portable monitoring instruments. In this way, multi-parameter detection of water quality can be performed, and the pollution indicators that need to be added can be determined, which can assist in improving the upgrade of the existing water quality monitoring network, and the existing water quality monitoring network can be expanded relatively quickly, the network monitoring nodes can be refined, and the pollutants can be analyzed more accurately, and the source and flow of pollutants can be tracked, which helps to determine the location of the pollution source and the propagation path of the pollutants in the water body, providing a basis for pollution control and governance.

[0091] It should be noted that the fourth embodiment of the present application may also be an improvement based on the first embodiment and / or the second embodiment.

[0092] It is not difficult to find that in the embodiment of the present application, by taking into account the tributary information of the target river, the water quality monitoring network can be refined to help quickly locate the source of pollution, achieve accurate tracking of the pollution source, and ensure that the source and destination of the pollution are known and traceable. It can effectively improve the timeliness and accuracy of water quality monitoring, which is of great significance for protecting water resources and responding to water pollution incidents in a timely manner.

[0093] Fifth embodiment

[0094] The fifth embodiment of the present application relates to a water quality monitoring system. The fifth embodiment is an improvement on the third embodiment, and the specific improvement is: in the fifth embodiment of the present application, a specific implementation method for determining the target water quality monitoring model is provided.

[0095] Optionally, in some embodiments, the water quality monitoring model determination module is specifically used to establish a first water quality monitoring model corresponding to a single target river channel according to the single target river channel when the amount of data is less than a preset threshold, and use the first water quality monitoring model as the target water quality monitoring model.

[0096] Optionally, in some embodiments, the water quality monitoring model determination module is also specifically used to establish a second water quality monitoring model corresponding to a certain area range based on multiple target rivers within the area range when the data amount is greater than or equal to the preset threshold, and use the second water quality monitoring model as the target water quality monitoring model.

[0097] For example, when the amount of data is insufficient, a model can be established for each river separately to obtain a first target water quality monitoring model. In this way, the parameters of the corresponding first target water quality monitoring model can be adjusted according to the specific conditions of each river to adapt to its unique hydrological characteristics. In practical applications, the first water quality monitoring model that matches the relevant conditions of the target river can be selected first to ensure the accuracy of monitoring.

[0098] Furthermore, when enough data is collected and the amount of data is greater than or equal to the preset threshold, a universal model applicable to the entire area, namely, a second water quality monitoring model, can be established. At this time, the second water quality monitoring model can replace the first water quality monitoring model as the target water quality monitoring model. Among them, the target river channel can also be classified according to the regional scope, and the second target water quality monitoring model can be obtained by training based on the classification results. Doing so will help improve the versatility of the second target water quality monitoring model, reduce the workload of establishing the first target water quality monitoring model for each river channel separately, and can also ensure the accuracy of monitoring to a certain extent.

[0099] It should be noted that the fifth embodiment of the present application may also be an improvement based on any one or more of the first embodiment, the second embodiment and the fourth embodiment.

[0100] It is not difficult to find that in the embodiment of the present application, a specific implementation method for determining the target water quality monitoring model is provided.

[0101] Sixth embodiment

[0102] The sixth embodiment of the present application relates to a water quality monitoring system. The sixth embodiment is an improvement on the fifth embodiment, and the specific improvement is: providing another implementation of the water quality monitoring model determination module.

[0103] Specifically, in some embodiments, it is specifically used to perform linear modeling and nonlinear modeling based on target parameters according to the first detection data and the second detection data, as well as the target river channel and different parameters, to obtain the first water quality monitoring model and the second water quality monitoring model.

[0104] Optionally, in some embodiments, the target parameter is a parameter used to characterize the synergistic effect between different parameters. For example, dissolved oxygen and pH both affect water quality, so a target parameter "dissolved oxygen × pH" can be constructed to capture the possible synergistic effect between dissolved oxygen and pH. In actual applications, relevant personnel can select different parameters according to actual needs, so that the system can obtain the target parameter after interacting with different parameters.

[0105] Exemplarily, the target parameter may be a single parameter or multiple parameters, which is not specifically limited in the embodiments of the present application.

[0106] For ease of understanding, the present application embodiment is described by taking a single parameter, specifically chemical oxygen demand (COD), as an example.

[0107] Exemplarily, a linear regression algorithm may be used to perform linear modeling, establish a regression model for the target river channel, and obtain the first model. The reference formula may be:

[0108] ;

[0109] in, represents the predicted value of COD, Indicates the true value of COD, represents the slope coefficient of the regression model, represents the intercept of the regression model.

[0110] For example, after comparing the first detection data detected by the portable monitoring instrument with the second detection data of the monitoring instrument at the fixed monitoring site, if it is determined that there is no abnormality in the monitoring instrument at the fixed monitoring site, the original water quality monitoring model of the monitoring instrument at the fixed monitoring site can be updated and upgraded according to the target water quality monitoring model. Specifically, the COD predicted value of the water sample can be directly collected on-site using a portable monitoring instrument. At the same time, the COD true value of the water sample is obtained, and these true values ​​are usually obtained through laboratory analysis. Then, based on the COD predicted value and the COD true value, a database containing the COD predicted value and the COD true value for characterizing the portable monitoring instrument is established. The least squares method, Newton's method or other optimization algorithms can be used to fit the data to determine the best Value and In this way, the difference between the COD predicted value and the COD true value can be minimized, so that the parameters of the first model can be obtained.

[0111] Furthermore, if Figure 5 As shown, the coefficient of determination of the first model can be calculated by To evaluate the goodness of fit of the first model. The closer the value of is to 1, the better the prediction effect of the first model is. Figure 4 In the example shown, the first model The value is 0.42783, The value is -0.84056, and the coefficient of determination The value of reaches 0.99939, indicating that the first model has a fairly high prediction accuracy. In this way, by using the first model to update and upgrade the original water quality monitoring model of the monitoring instrument of the fixed monitoring station, the fixed monitoring station can obtain a more accurate COD value according to the first model even without manual detection in the future.

[0112] Exemplarily, a nonlinear regression algorithm may be used to perform nonlinear modeling, establish a nonlinear regression model for the target river channel, and obtain a second model. The reference formula may be:

[0113] ;

[0114] in, represents the predicted value of COD, Indicates the true value of COD, , ,and are parameters respectively.

[0115] For example, after comparing the first detection data detected by the portable monitoring instrument with the second detection data of the monitoring instrument at the fixed monitoring site, if it is determined that there is no abnormality in the monitoring instrument at the fixed monitoring site, the original water quality monitoring model of the monitoring instrument at the fixed monitoring site can be updated and upgraded according to the target water quality monitoring model. Specifically, the COD predicted value of the water sample can be directly collected on-site using a portable monitoring instrument. At the same time, the COD true value of the water sample is obtained, and these true values ​​are usually obtained through laboratory analysis. Then, based on the COD predicted value and the COD true value, a database containing the COD predicted value and the COD true value for characterizing the portable monitoring instrument is established. The least squares method, Newton's method or other optimization algorithms can be used to fit the data to determine the best value, Value and In this way, the difference between the COD predicted value and the COD true value can be minimized, so that the parameters of the second model can be obtained.

[0116] Furthermore, if Figure 6 As shown, the coefficient of determination can be The values ​​of and other statistical indicators are used to evaluate the goodness of fit of the second model. Figure 5 In the example shown, the parameters of the second model are: =15.0044, =0.17658, =0.00191, and the coefficient of determination of the second model The value of reached 0.99362. This is a relatively high value, indicating that the second model can explain the variation in the data very well and has a good fitting effect. In other words, the second model can more accurately predict and analyze water quality parameters, thereby providing more powerful data support for water quality management and protection.

[0117] Furthermore, the system can select between the first model and the second model according to actual needs, and the selected model is the first water quality monitoring model. The method for determining the second water quality monitoring model is roughly the same as the method for determining the first water quality monitoring model, and will not be repeated here to avoid repetition.

[0118] It can be known from the above description that, considering that the difference in the organic matter composition of different water bodies will affect the accuracy of the monitoring results, therefore, in the embodiment of the present application, by setting up the regression model of different target rivers, it can be ensured that the sensor is suitable for different water quality conditions. In this way, by setting up a customized first water quality monitoring model for the target river, the monitoring accuracy of the fixed monitoring site can be significantly improved. In addition, it is worth emphasizing that the above example is only exemplified by COD value to illustrate how to improve the accuracy under different water quality conditions by setting up the first water quality monitoring model. However, in actual applications, the method provided by the embodiment of the present application can also be extended to the monitoring of other water quality parameters, such as ammonia nitrogen, total phosphorus, etc., to further improve the overall effectiveness of the water quality monitoring network.

[0119] Optionally, in some embodiments, the target water quality monitoring model may specifically be a target water quality monitoring model constructed based on multiple parameters.

[0120] Specifically, in actual water quality monitoring, since water is a complex mixture of multiple components, different parameters may affect each other, thereby affecting the accuracy of the monitoring results. For example, the monitoring results of ammonia nitrogen in water may be affected by the pH value, because the existence form of ammonia nitrogen changes with the change of pH value. Under acidic conditions, ammonia nitrogen mainly exists in molecular form, while under neutral or alkaline conditions, ammonia nitrogen gradually converts into ionic form. This change in form directly affects the removal efficiency and monitoring results of ammonia nitrogen. Therefore, in order to obtain accurate ammonia nitrogen concentration, pH compensation is generally required to ensure the reliability of the monitoring results. Similarly, the detection of COD may also be interfered by other parameters such as turbidity and chromaticity. Therefore, in a complex water environment, the monitoring of a single parameter may not effectively reflect the true water quality conditions.

[0121] In order to solve this problem, in some embodiments, the target water quality monitoring model can be constructed based on multiple parameters, that is, taking multiple water quality parameters as input, and constructing a target water quality monitoring model that can integrate the influence of multiple parameters through machine learning algorithms such as neural networks. For example, a neural network model can be established that takes multiple water quality parameters such as turbidity, chlorophyll, COD as input and outputs a predicted COD value. Such a model can better adapt to complex water environments and improve the accuracy and adaptability of water quality detection.

[0122] Furthermore, with the continuous accumulation of monitoring data, the target water quality monitoring model can be continuously optimized and upgraded, so that the target water quality monitoring model can better learn and adapt to the laws of water quality changes. For example, by constructing a target water quality monitoring model based on a composite neural network to predict multivariate water quality indicators, water quality parameters such as pH, dissolved oxygen (DO), permanganate index (CODMn), and ammonia nitrogen (NH3-N) can be predicted, providing scientific, reasonable, and effective support for water quality assurance and water management.

[0123] It should be noted that the sixth embodiment of the present application may also be an improvement based on any one or more embodiments of the first to fourth embodiments.

[0124] It is not difficult to find that in the embodiment of the present application, another specific implementation method for determining the target water quality monitoring model is provided.

[0125] It is worth mentioning that the modules involved in the above embodiments are all logic modules. In practical applications, a logic unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, in order to highlight the innovative part of the present application, the present embodiment does not introduce units that are not closely related to solving the technical problems proposed by the present application, but this does not mean that there are no other units in the present embodiment.

[0126] Seventh embodiment

[0127] The seventh embodiment of the present application relates to a water quality monitoring method. Figure 7 shown.

[0128] Specifically, the water quality monitoring method can be applied to the system described in any one or more of the first to sixth embodiments, such as Figure 7 As shown, the method may at least include the following steps:

[0129] Step S101, determining a target water quality monitoring model according to the first detection data and the second detection data, and sending the target water quality monitoring model to a cloud database; wherein the first detection data is determined by a portable monitoring instrument, and the second detection data is determined by a preset fixed monitoring site;

[0130] Step S102, sending the target water quality monitoring model to the fixed monitoring site;

[0131] Step S103: updating and upgrading the original water quality monitoring model of the fixed monitoring site according to the target water quality monitoring model.

[0132] It is not difficult to find that this embodiment is a method embodiment corresponding to the first embodiment, and this embodiment can be implemented in conjunction with the first embodiment. The relevant technical details mentioned in the first embodiment are still valid in this embodiment, and in order to reduce repetition, they are not repeated here. Accordingly, the relevant technical details mentioned in this embodiment can also be applied in the first embodiment.

[0133] The step division of the above methods is only for clear description. When implemented, they can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they include the same logical relationship, they are all within the scope of protection of this application; adding insignificant modifications to the algorithm or process or introducing insignificant designs without changing the core design of the algorithm and process are all within the scope of protection of this application.

[0134] The flow chart or block diagram in the accompanying drawings shows the possible architecture, function and operation of the equipment, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated system for hardware that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0135] The scope of the present application is defined by the appended claims rather than the above description, and it is intended that all changes that fall within the meaning and scope of the equivalent elements of the claims are included in the present application. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the device claim may also be implemented by one unit or device through software or hardware. The words "first", "second", etc. are only used to distinguish the description, and do not indicate any particular order, nor can they be understood as indicating or implying relative importance.

[0136] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily mention changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims, and the above embodiments should be regarded as exemplary and non-restrictive.

Claims

1. A water quality monitoring system, characterized in that: The system comprises: A water quality monitoring model determination module, used to determine a target water quality monitoring model according to the first detection data and the second detection data, and send the target water quality monitoring model to a cloud database; wherein the first detection data is determined by a portable monitoring instrument, and the second detection data is determined by a preset fixed monitoring site; A cloud database, used to send the target water quality monitoring model to the fixed monitoring site; A water quality monitoring model updating module, used to update and upgrade the original water quality monitoring model of the fixed monitoring site according to the target water quality monitoring model; The water quality monitoring model determination module includes a time synchronization unit and a model determination unit; the time synchronization unit is used to synchronize the detection time of the first detection data and the test time of the second detection data to obtain a synchronization result; the water quality monitoring model determination module is used to determine the target water quality monitoring model according to the synchronization result; The water quality monitoring model determination module also includes a river channel archive determination unit; the river channel archive determination unit is used to determine the river channel archive based on the first detection data and the second detection data; wherein the river channel archive includes water quality historical information and water quality current information for characterizing the target river channel; the water quality monitoring model determination module is used to determine the target water quality monitoring model based on the synchronization result and the river channel archive.

2. The system according to claim 1, characterized in that The water quality monitoring model determination module is specifically used to determine the difference value between the first detection data and the second detection data at the same time according to the synchronization result; and determine the target water quality monitoring model according to the difference value.

3. The system according to claim 1, characterized in that The system also includes a fixed monitoring site determination unit; The fixed monitoring site determination unit is used to determine at least one of the following based on the river channel archive provided by the river channel archive determination unit: the layout of several fixed monitoring sites, the monitoring frequency of each fixed monitoring site, and the location of each fixed monitoring site.

4. The system according to claim 3, characterized in that The fixed monitoring site determination unit is also specifically used to receive the planned number of the fixed monitoring sites; determine the layout of several fixed monitoring sites in the water quality monitoring management network, the monitoring frequency of each fixed monitoring site, and the location of each fixed monitoring site based on the river channel file of the target river and the planned number.

5. The system according to claim 1, characterized in that The system further includes an emergency response module; the river archive further includes tributary information for characterizing the target river; The water quality monitoring model determination module is specifically used to determine whether there is an abnormality in the tributary information of the target river channel through the second detection data provided by the fixed monitoring station deployed on the tributary side; and when it is determined that there is an abnormality in the tributary information of the target river channel, issue a prompt message; the prompt message is used to prompt the deployment of the portable monitoring instrument on the tributary side so that the portable monitoring instrument issues the first detection data based on the tributary side; The emergency response module is used to determine the diffusion range and diffusion trend of the pollutants based on the first detection data and the second detection data.

6. The system according to claim 1, characterized in that The water quality monitoring model determination module is specifically used to establish a first water quality monitoring model corresponding to a single target river channel when the data volume is less than a preset threshold value, and use the first water quality monitoring model as the target water quality monitoring model; The water quality monitoring model determination module is also specifically used to establish a second water quality monitoring model corresponding to a certain area range based on multiple target rivers within the area when the data volume is greater than or equal to the preset threshold, and use the second water quality monitoring model as the target water quality monitoring model.

7. The system according to claim 6, characterized in that The water quality monitoring model determination module is specifically used to perform linear modeling and nonlinear modeling based on target parameters according to the first detection data and the second detection data, as well as the target river channel and different parameters, to obtain the first water quality monitoring model and the second water quality monitoring model.

8. The system according to claim 7, characterized in that The target parameter is a parameter used to characterize the synergistic effect between different parameters.

9. The system according to claim 1, characterized in that Before the water quality monitoring model determination module determines the target water quality monitoring model according to the synchronization result and the river archive, the system is further used to: Obtaining an actual value and a predicted value based on a universal water quality monitoring model, and calculating a mean square error between the actual value and the predicted value, and evaluating the prediction accuracy of the universal water quality monitoring model according to the mean square error; If the value of the mean square error is less than or equal to the mean square error threshold, the water quality of the current river is predicted using the universal water quality monitoring model; If the value of the mean square error is greater than the mean square error threshold, the target water quality monitoring model is determined.

10. A water quality monitoring method, characterized in that: The method is applied to the system according to any one of claims 1 to 9, and the method at least comprises: Determine a target water quality monitoring model according to the first detection data and the second detection data, and send the target water quality monitoring model to a cloud database; wherein the first detection data is determined by a portable monitoring instrument, and the second detection data is determined by a preset fixed monitoring site; Sending the target water quality monitoring model to the fixed monitoring site; According to the target water quality monitoring model, the original water quality monitoring model of the fixed monitoring site is updated and upgraded.

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