Flood season river pollution early warning system and method

Abstract

The invention discloses a flood season river pollution early warning system and method, and relates to the technical field of environmental monitoring, the system comprises a microbial electrochemical sensor module, a current monitoring and data analysis module, a multistage early warning trigger module, a chemical detection auxiliary module, and a data transmission and storage module, through the microbial electrochemical sensor network, water samples on the surface layer, the middle layer and the bottom layer of a river can be collected at the same time, the toxicity index of composite pollutants is analyzed in real time by means of metabolic activity changes of electroactive flora, the comprehensiveness of monitoring of the river pollution condition is greatly improved, meanwhile, the current pulse frequency is monitored in real time, and the toxicity index is rapidly analyzed; and by matching with a preset accurate threshold value of the early warning trigger module, an early warning mechanism can be quickly triggered once the pollution condition reaches an early warning standard, so that the early warning timeliness is greatly improved, the time interval from pollution occurrence to early warning sending is shortened, and precious time is won for taking pollution prevention and control measures in time.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and specifically provides a river pollution early warning system and method during the flood season. Background Art

[0002] During the flood season, the hydrodynamic conditions of rivers change significantly, with a sharp increase in flow rate and velocity. A large amount of precipitation not only washes various pollutants on land into the river, but also causes the pollutants originally deposited on the river bottom to resuspend and spread. At the same time, the rainstorm scouring causes a large amount of agricultural pollutants, industrial wastewater, and sediment endogenous pollution to be released in a short time, forming a composite pollution mass, which poses a serious threat to the drinking water safety and ecological system of the downstream.

[0003] At present, there are many limitations in the existing technologies for river pollution monitoring. In terms of detecting pollution in different water layers, most traditional monitoring systems only arrange monitoring equipment on the river surface, making it difficult to obtain pollution information in the middle and bottom layers. Moreover, conventional water quality detection methods rely on chemical reagents, which are not only cumbersome to operate but also have a long detection cycle, making it difficult to meet the monitoring requirements for the rapid changes in pollution during the flood season. This single detection method lacks an effective dual-mode response mechanism. Once a detection error occurs, it cannot be verified and corrected in a timely manner.

[0004] To sum up, the existing river pollution monitoring technologies cannot comprehensively, accurately, and timely give early warnings of river pollution under the complex environment of the flood season. This not only increases the difficulty of pollution control but also leads to serious ecological pollution. Therefore, it is extremely urgent to develop a new system and method that can monitor the pollution of rivers in real time and comprehensively during the flood season and give early warnings in a timely manner. Summary of the Invention

[0005] The purpose of the present invention is to make up for the deficiencies of the existing technologies and provide a river pollution early warning system and method during the flood season. It can collect water samples from the surface, middle, and bottom layers of the river through a microbial electrochemical sensor network, and use the change in the metabolic activity of electroactive bacteria to analyze the toxicity index of composite pollutants in real time. This unique detection method greatly improves the comprehensiveness of monitoring river pollution compared with the traditional technology that only targets surface water quality detection. At the same time, it monitors the current pulse frequency in real time and quickly analyzes the toxicity index, and combines with the precise threshold preset by the early warning trigger module. Once the pollution situation reaches the early warning standard, it can quickly trigger the early warning mechanism, greatly improving the timeliness of the early warning and significantly shortening the time interval from the occurrence of pollution to the issuance of the early warning.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: On the one hand, a river pollution early warning system during the flood season, the composition of the system includes: a microbial electrochemical sensor module, a current monitoring and data analysis module, a multi-level early warning trigger module, a chemical detection assistance module, and a data transmission and storage module;

[0007] The microbial electrochemical sensor module is composed of three groups of sensor units, namely the surface layer, the middle layer, and the bottom layer. Electroactive microbial communities are encapsulated within each layer of sensor units. When detecting corresponding pollutants, the three groups of sensor units synchronously output current pulse signals through a phase difference detection circuit.

[0008] The current monitoring and data analysis module continuously monitors the current pulse frequency generated by the microbial fuel cell, analyzes and processes the current data, and resolves the current change into a composite pollutant toxicity index.

[0009] The multi-level warning trigger module is equipped with a three-level warning response mechanism and a cross-level interlock mechanism. It compares the composite pollutant toxicity index with a dynamic warning threshold, and triggers the three-level warning response mechanism according to the composite pollutant toxicity index output by the current monitoring and data analysis module.

[0010] The chemical detection auxiliary module analyzes the chemical composition of the collected water sample according to the warning signal of the warning trigger module, and mutually verifies and supplements it with the bioelectric signal warning generated by the microbial fuel cell.

[0011] The data transmission and storage module is responsible for storing the data collected by the microbial electrochemical sensor module, the data processed by the current monitoring and data analysis module, and the detection data of the chemical detection auxiliary module, and real-time transmitting them to the monitoring terminal for viewing.

[0012] Furthermore, a microbial fuel cell is integrated inside each layer of sensor units of the microbial electrochemical sensor module. The microbial fuel cell encapsulates electroactive microbial communities, which include sulfate-reducing bacteria sensitive to sulfide, iron-oxidizing bacteria sensitive to iron-containing pollutants, and nitrifying bacteria sensitive to nitrogen-containing pollutants. When the corresponding pollutants appear, the metabolic activity of the microbial communities increases sharply, and electrochemical reactions occur inside the microbial fuel cell, thus generating specific current pulse signals.

[0013] Even further, the current monitoring and data analysis module is used to continuously collect the current pulse frequency data generated by the microbial fuel cells in the sensor unit group, capture the change in the current pulse frequency, and resolve the current change into a composite pollutant toxicity index. The composite pollutant toxicity index is calculated by where T represents the composite pollutant toxicity index, f i is the real-time current pulse frequency of the i-th layer of sensor units, where i = 1, 2, 3 respectively correspond to the surface layer, the middle layer, and the bottom layer, F i,base is the reference pulse frequency of the i-th layer of sensor units in the pollution-free state, and Δφ max is the absolute value of the maximum phase difference between the three layers of sensor units and Δφ max= max(|φ1 - φ2|, |φ2 - φ3|, |φ1 - φ3|), where α and β are weighting coefficients, with the value ranges α ∈ [0.8, 0.9] and β ∈ [0.1, 0.3] respectively, and α + β = 1.

[0014] Furthermore, the three - level early warning response mechanism in the multi - level early warning trigger module includes a threshold dynamic calculation unit, a three - level response unit, and a false - alarm suppression unit, where:

[0015] The threshold dynamic calculation unit sets a dynamic early warning threshold T according to the historical pollution data and the pollutant benchmark T0 of the hydrological characteristics k , and sets three early warning levels, namely the first - level early warning, the second - level early warning, and the third - level early warning, that is T k is the k - th level dynamic threshold, k = 1, 2, 3 corresponding to the three - level early warning, v is the real - time water flow velocity of the current section, v max is the historical maximum flow velocity, SC is the pollutant concentration, SC crit is the critical turbidity value of the pollutant;

[0016] The three - level response unit continuously compares the composite pollutant toxicity index T output by the current - monitoring and data - analysis module with the thresholds of each level determined by the threshold dynamic calculation unit, so as to respond to different early warning levels;

[0017] When the same - layer sensor unit triggers an early warning more than 3 times within 1 hour, and the matching degree between the water sample detection result of the chemical detection auxiliary module for this node and the bio - electrical signal early warning is < 50%, the false - alarm suppression unit performs a false - alarm suppression operation. The false - alarm suppression operation adjusts the composite pollutant toxicity index threshold of the current early warning level, and increases the dynamic early warning threshold T k by 20%, that is to avoid frequent false alarms caused by abnormal interference existing in this node.

[0018] Furthermore, the specific response principle of the three - level response unit is:

[0019] Normal monitoring: When T < T1, no early warning is triggered, and the system is in the normal monitoring state;

[0020] First - level early warning: When the composite pollutant toxicity index T satisfies T ≥ T1 and the continuous duration Δt ≥ 5 min, start collecting water samples with 3 times the standard volume and continuously detect;

[0021] Second - level early warning: When either T ≥ T2 or the first - level early warning lasts for Δt ≥ 15 min, send an early warning message to the monitoring platform and activate the chemical detection auxiliary module for analysis;

[0022] Third - level early warning: When T ≥ T3 and detected When any one of the conditions is met, an emergency alarm is issued, and at the same time, the chemical detection assistance module is linked to increase the detection frequency and scope, and the components and sources of pollutants are analyzed in detail.

[0023] Furthermore, the cross-level interlock mechanism in the multi-level early warning trigger module is as follows: when is satisfied, it is determined as a sudden major pollution, and it directly jumps to the third-level early warning. Among them, is the T gradient change rate along the water flow direction, and v is the real-time water flow velocity of the current section.

[0024] Furthermore, when a pollution event suddenly occurs during the flood season, the chemical detection assistance module separately detects different early warning signals through the priority control parameter W. The priority control parameter W is dynamically calculated from the composite pollutant toxicity index T, that is, where Δφ is the phase difference of the sensor unit in the bioelectrochemical sensor module. When W > 0.8, the mass spectrometry detection unit is immediately started to analyze the components and concentrations of pollutants. When 0.5 ≤ W < 0.8, the spectral rapid screening is started to quickly conduct a preliminary investigation and judgment on the pollutants in the water sample.

[0025] Furthermore, the mass spectrometry detection unit quantitatively analyzes the target pollutants in the water sample to generate a concentration vector c = [c1, c2,..., c 32 , where c i represents the concentration of the i-th target pollutant, and the matching degree between the bioelectric signal and the chemical detection is calculated where, T i refers to the composite pollutant toxicity index of the i-th layer of the microbial electrochemical sensor module, c i is the concentration of the corresponding pollutant detected chemically, and w i is the matching degree coefficient, which is used to reflect the importance of different layers of sensors in the comprehensive matching degree calculation. Among them, the surface layer is 0.4, the middle layer is 0.5, and the bottom layer is 0.1. When M ≥ 0.85, the pollution event is confirmed; otherwise, the false alarm suppression operation is triggered.

[0026] On the other hand, a method for early warning of river pollution during the flood season, the specific steps of this method are as follows:

[0027] S100. Deploy a microbial electrochemical sensor network in the river area during the flood season, so that the sensor nodes can collect water samples from the surface, middle and bottom layers of the river and transmit current pulse signals;

[0028] S200. The current monitoring and data analysis module monitors the current pulse signals in real time and conducts analysis to calculate the composite pollutant toxicity index;

[0029] S300. The early warning trigger module continuously compares the calculated composite pollutant toxicity index with the dynamic early warning threshold.

[0030] S400. After the early warning is triggered, the chemical detection auxiliary module is automatically activated to analyze the chemical components of the water sample and transmit the results to the data transmission and storage module.

[0031] S500. The data transmission and storage module stores all data and transmits it to the monitoring terminal in real time for decision-making and processing based on the data.

[0032] Compared with the prior art, the flood season river pollution early warning system and method have the following beneficial effects:

[0033] First, through the microbial electrochemical sensor network, the present invention can simultaneously collect water samples from the surface, middle, and bottom layers of the river, and use the changes in the metabolic activity of electroactive microbial communities to analyze the composite pollutant toxicity index in real time, greatly improving the comprehensiveness of river pollution monitoring. At the same time, the current pulse frequency is monitored in real time and the toxicity index is quickly analyzed. Coupled with the precise threshold preset by the early warning trigger module, once the pollution situation reaches the early warning standard, the early warning mechanism can be quickly triggered, greatly improving the timeliness of early warning and shortening the time interval from pollution occurrence to early warning issuance, thus winning precious time for taking pollution prevention and control measures in a timely manner.

[0034] Second, the present invention adopts a dual-mode response mechanism of bioelectric signals and chemical detection. When the power generation of the microbial fuel cell triggers an early warning, the chemical detection auxiliary module is automatically activated to conduct an in-depth chemical component analysis of the water sample. The two verify and complement each other. If the bioelectric signal early warning and the chemical detection results are highly matched, the pollution event is further confirmed, effectively avoiding false alarms that may occur with a single detection method. In addition, with the support of the data transmission and storage module, all monitoring data can be completely saved and transmitted in real time, facilitating the staff to comprehensively master the pollution information and make more scientific and accurate decisions, thereby significantly improving the reliability of the entire early warning system.

[0035] Other advantages, objectives, and features of the present invention will be described to some extent in the subsequent specification, and to some extent, will be obvious to those skilled in the art based on the study of the following text, or can be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0037] Figure 1 It is an operation flow chart of a river pollution early warning system during the flood season;

[0038] Figure 2 It is a step diagram of a river pollution early warning method during the flood season;

[0039] Figure 3 It is a schematic diagram of the module composition of a river pollution early warning system during the flood season. Specific implementation manners

[0040] To further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following combines the accompanying drawings and preferred embodiments to detail the specific implementation manners, structures, features and their effects according to the present invention as follows.

[0041] Embodiment 1

[0042] As Figure 1 shown, this embodiment focuses on the actual application of a river pollution early warning system during the flood season. By deploying the system in the river area during the flood season, the working principles of each module (microbial electrochemical sensor module, current monitoring and data analysis module, multi-level early warning trigger module, chemical detection auxiliary module, data transmission and storage module) are elaborated in detail, showing how the system realizes comprehensive, timely and accurate early warning of river pollution and provides strong support for the prevention and control of river pollution during the flood season.

[0043] In the selected river area, a microbial electrochemical sensor network is deployed. The microbial electrochemical sensor module consists of three groups of sensor units on the surface layer, middle layer and bottom layer. Each sensor unit integrates a microbial fuel cell internally and encapsulates electroactive microbial communities, including sulfur-reducing bacteria sensitive to sulfides, iron-oxidizing bacteria sensitive to iron-containing pollutants, and nitrifying bacteria sensitive to nitrogen-containing pollutants. These microbial communities maintain a certain metabolic activity under normal conditions and maintain a stable basic current pulse frequency generated by the microbial fuel cell. As the water flow in the river continuously flows through the sensor, when target pollutants such as sulfides, iron-containing pollutants or nitrogen-containing pollutants exist in the water, the metabolic activity of the corresponding electroactive microbial communities (sulfur-reducing bacteria, iron-oxidizing bacteria, nitrifying bacteria) will increase sharply. For example, if sulfides appear, sulfur-reducing bacteria will use sulfides for metabolic activities and electrochemical reactions will occur in the microbial fuel cell, thereby generating specific current pulse signals. The microbial fuel cells in each group of sensor units convert the chemical energy generated by the microbial metabolism into electrical energy and output current pulses. Since the pollution situations in the surface layer, middle layer and bottom layer may be different, the three groups of sensor units will synchronously output current pulse signals with different frequencies and phases through a phase difference detection circuit. These signals not only reflect the presence of pollutants in different water layers, but also provide more information about pollution distribution and transmission for subsequent analysis through the change of phase difference.

[0044] The current monitoring and data analysis module continuously collects the current pulse frequency data generated by the microbial fuel cells in the sensor unit group. This module is connected to the output end of the microbial fuel cell through a high-precision current sensor and can accurately capture the minute changes in the current pulse frequency. After collecting the real-time current pulse frequency data, it uses the formula to analyze and process the current change and calculate the composite pollutant toxicity index T. Among them, f i is the real-time current pulse frequency of the i-th layer of sensor units (i = 1, 2, 3 corresponding to the surface layer, middle layer, and bottom layer respectively), F i,base is the reference pulse frequency of the i-th layer of sensor units in the pollution-free state, which reflects the electrical activities of the sensors themselves and the bacterial communities under normal conditions. Δφ max is the absolute value of the maximum phase difference between the three layers of sensor units. It is calculated by Δφ max = max(|φ1 - φ2|, |φ2 - φ3|, |φ1 - φ3|). The change in the phase difference reflects the time difference and intensity difference in the response of sensors in different water layers to pollutants, which helps to more accurately judge the distribution and spread of pollution. α and β are weight coefficients, and their value ranges are α ∈ [0.8, 0.9] and β ∈ [0.1, 0.3] respectively, and α + β = 1. They are used to balance the influence degrees of the current frequency change and the phase difference change on the composite pollutant toxicity index. Through this formula, the current monitoring and data analysis module converts the collected current pulse frequency data and phase difference data into a comprehensive composite pollutant toxicity index T. This index can intuitively reflect the degree of composite pollution in the river and provide an important basis for subsequent early warning judgments.

[0045] After receiving the composite pollutant toxicity index T output by the current monitoring and data analysis module, the multi-level early warning trigger module starts the early warning judgment. This module is equipped with a three-level early warning response mechanism and a cross-level interlock mechanism. In the three-level early warning response mechanism, the threshold dynamic calculation unit determines the pollutant benchmark T0 based on historical pollution data and hydrological characteristics, and combines parameters such as the real-time water flow velocity v and pollutant concentration SC at the current cross-section. Through set the dynamic early warning threshold T k , where T k is the k-th level dynamic threshold (k = 1, 2, 3 corresponding to the three-level early warning). The real-time water flow velocity v is obtained through a flow velocity sensor installed in the river, which reflects the current hydrodynamic conditions of the river. The historical maximum flow velocity v max is obtained by long-term monitoring of the flow velocity data of this river during the flood season and non-flood season and is used to measure the relative magnitude of the current flow velocity. SC is the pollutant concentration, and SC critis the critical turbidity value of pollutants, used to evaluate the potential impact degree of pollutants on river ecology; the three-level response unit continuously compares the composite pollutant toxicity index T with the thresholds at all levels determined by the threshold dynamic calculation unit. When T < T1, the system is in the normal monitoring state and does not trigger an early warning, which means that the pollution degree in the current river is relatively low and has not reached the level that requires an alarm to be issued; when the composite pollutant toxicity index T satisfies T ≥ T1 and the duration Δt ≥ 5 min, the first-level early warning is activated. At this time, the system will start collecting water samples with 3 times the standard volume and continuously detect. This is because in the first-level early warning stage, although the pollution degree is relatively low, in order to more accurately evaluate the pollution situation, increasing the amount of water sample collection can obtain more comprehensive pollution information, and continuous detection helps to observe the pollution trend and judge whether the pollution is further developing; when either T ≥ T2 or the first-level early warning lasts for Δt ≥ 15 min is satisfied, a warning message is sent to the monitoring platform to activate the chemical detection auxiliary module for analysis. The second-level early warning indicates that the river pollution situation has been relatively serious and timely measures need to be taken. Activating the chemical detection auxiliary module can conduct a more in-depth chemical composition analysis of the water sample, mutually verify with the bioelectric signal early warning generated by the microbial fuel cell, and further determine the specific composition and degree of the pollution; when either T ≥ T3 and is satisfied, the third-level early warning is issued. The third-level early warning represents that the river pollution has reached a serious level and immediate emergency measures need to be taken. At this time, the system will issue an emergency alarm and at the same time link the chemical detection auxiliary module to increase the detection frequency and scope, and analyze the composition and source of pollutants in detail. represents the change rate of the composite pollutant toxicity index over time, which reflects the change speed of the pollution degree. When this change rate is greater than 0.5 / min, it indicates that the pollution is deteriorating rapidly, and immediate action must be taken to reduce the impact of the pollution on the river ecology and the surrounding environment. In addition, the multi-level early warning trigger module is also equipped with a cross-level interlock mechanism. When is satisfied, it is determined as a sudden major pollution and directly jumps to the third-level early warning. Among them, is the T gradient change rate along the water flow direction, obtained through spatial analysis of the composite pollutant toxicity index detected by sensors at different positions. This parameter reflects the propagation speed and concentration change of the pollution in the river. When is satisfied, it means that the pollution may spread rapidly in a short time and pose a serious threat to the downstream. Therefore, the highest-level early warning is directly activated so as to take corresponding measures in time. During the early warning process, the false alarm suppression unit plays an important role. When the same-layer sensor unit triggers an early warning more than 3 times within 1 hour and the matching degree between the detection result of the chemical detection auxiliary module for the water sample at this node and the bioelectric signal early warning is < 50%, the false alarm suppression operation is executed. The false alarm suppression operation will adjust the composite pollutant toxicity index threshold of the current early warning level, increasing the dynamic early warning threshold T k by 20%, that is This can avoid frequent false alarms caused by abnormal interference existing in this node, and ensure the accuracy and reliability of the early warning system.

[0046] The chemical detection auxiliary module starts to work after receiving the early warning signal sent by the early warning trigger module. When a pollution incident occurs suddenly during the flood season, it dynamically calculates the priority control parameter W according to the composite pollutant toxicity index T. The formula is where Δφ is the phase difference of the sensor unit in the bioelectrochemical sensor module. When W>0.8, the mass spectrometry detection unit is immediately activated to analyze the components and concentrations of pollutants. The mass spectrometry detection unit can perform high-sensitivity and high-resolution quantitative analysis on the target pollutants in the water sample, and generate a concentration vector c = c1, c2,..., c 32 , where c i represents the concentration of the i-th target pollutant. By accurately measuring the concentrations of these pollutants, the specific situation of river pollution can be understood more accurately. When 0.5≤W<0.8, spectral rapid screening is activated. Spectral rapid screening utilizes the absorption and emission characteristics of different pollutants for specific spectra to quickly conduct a preliminary investigation and judgment on the pollutants in the water sample. This method can obtain a large amount of information in a short time and provide a direction for accurate detection. After the mass spectrometry detection is completed, the matching degree M between the bioelectric signal and the chemical detection is calculated. The formula is where T i refers to the composite pollutant toxicity index of the i-th layer of the microbial electrochemical sensor module, C i is the concentration of the corresponding pollutant in the chemical detection, and w i is the matching degree coefficient, which is used to reflect the importance of different layers of sensors in the comprehensive matching degree calculation. The value for the surface layer is 0.4, the middle layer is 0.5, and the bottom layer is 0.1. When M≥0.85, the pollution incident is confirmed, indicating that the bioelectric signal early warning is highly consistent with the chemical detection result, further verifying the authenticity of the pollution situation. Otherwise, the false alarm suppression operation is triggered to re-evaluate and process the early warning result.

[0047] The data transmission and storage module is responsible for collecting the data collected by the microbial electrochemical sensor module, the data processed by the current monitoring and data analysis module, and the detection data of the chemical detection auxiliary module. This module transmits these data to the monitoring terminal in real time through wireless transmission. During the transmission process, encryption technology is used to ensure the security and integrity of the data, preventing the data from being tampered with or lost during transmission. At the same time, the data transmission and storage module stores all data in the local database. The stored data includes not only real-time monitoring data but also historical data for subsequent data analysis and trend research. Staff can view the current pollution monitoring data, early warning information, and historical data at any time through the monitoring terminal, and make scientific decisions based on these data, such as formulating pollution prevention and control measures and adjusting the sewage treatment plan.

[0048] In summary, in this embodiment, by implementing the warning system of the present invention in the river area during the flood season, each module works in coordination to achieve comprehensive, timely, and accurate monitoring and warning of river pollution. The microbial electrochemical sensor module can collect water samples from different water layers simultaneously, and utilize the metabolic changes of electroactive bacteria to generate specific current pulse signals, providing rich information for subsequent analysis. The current monitoring and data analysis module analyzes the current changes into the toxicity index of composite pollutants through precise algorithms, providing a quantitative basis for warning judgment. The multi-level warning trigger module can issue warnings at different levels in a timely manner according to the pollution degree and change trend through dynamic threshold calculation, three-level response mechanism, and cross-level interlock mechanism, and improves the accuracy of warning through the false alarm suppression unit. The chemical detection auxiliary module conducts chemical composition analysis after warning is triggered, verifying with the bioelectric signal warning to further clarify the pollution situation. The data transmission and storage module ensures the real-time transmission and secure storage of data, providing convenient means for staff to view and analyze data, and providing an innovative solution for flood season river pollution prevention and control.

[0049] Embodiment 2

[0050] As Figure 2 shown, this embodiment elaborates in detail the specific steps of a method for warning of river pollution during the flood season when analyzing river pollution during the flood season. Through orderly operations of each link of the system, the river pollution situation can be comprehensively and accurately analyzed, and warnings can be issued in a timely manner. The specific steps are as follows:

[0051] S100. Data collection and preprocessing

[0052] Before the flood season arrives, according to the terrain, hydrological characteristics of the river and the distribution of surrounding pollution sources, deploy a microbial electrochemical sensor network. These sensors should be able to collect water sample information from the surface, middle, and bottom layers of the river simultaneously to comprehensively reflect the pollution situation of different water layers of the river; during the flood season, the microbial electrochemical sensors continuously work to monitor the metabolic changes of electroactive bacteria in the river in real time. When there are pollutants such as sulfide, iron-containing pollutants, and nitrogen-containing pollutants in the river, the metabolic activities of the corresponding electroactive bacteria will change, that is, further detect the change values of the metabolic amounts of pollutants such as sulfide, iron-containing pollutants, and nitrogen-containing pollutants through sulfur-reducing bacteria, iron-oxidizing bacteria, and nitrifying bacteria in the microbial electrochemical sensor, so as to make the microbial fuel cell generate specific current pulse signals. The sensors convert these current pulse signals into digital data and integrate and record them as the judgment basis for composite pollutants;

[0053] S200. Pollution feature extraction

[0054] The current monitoring and data analysis module deeply analyzes the recorded data, extracts the characteristics of the current pulse signal, calculates the composite pollutant toxicity index through the learning and analysis of historical data. The composite pollutant toxicity index comprehensively reflects the potential harm degree of various pollutants in the river to the ecological environment and organisms.

[0055] S300, Pollution degree assessment

[0056] According to historical data and actual situations, corresponding warning thresholds are set for different pollution levels. Using the calculated composite pollutant toxicity index, the pollution degree of the river is divided into different levels, and each level corresponds to a different warning level and corresponding countermeasures. By clarifying the pollution level, it provides a clear basis for subsequent warnings and decision-making. The calculated composite pollutant toxicity index is compared with the set warning threshold. When the toxicity index exceeds the corresponding threshold, a warning of the corresponding level is triggered. Once the warning is triggered, the corresponding decision-making process is immediately started, and different countermeasures are formulated according to different warning levels.

[0057] S400, Chemical detection for auxiliary judgment

[0058] After the warning is triggered, the chemical detection auxiliary module is started to analyze the chemical components of the collected water samples. Through chemical detection methods, the types and concentrations of various pollutants in the river are accurately determined. The chemical detection results are compared and verified with the results monitored by the microbial electrochemical sensor, so that it can better adapt to the pollution situation of the river during different flood seasons.

[0059] S500, Data storage and analysis

[0060] All the data collected, the calculated results, warning information, and countermeasures taken during the entire pollution analysis process are comprehensively stored for easy data management and query. The stored data includes not only the real-time data of the current flood season but also historical data, providing rich materials for subsequent research and analysis. The stored data is regularly analyzed and mined to summarize the laws and trends of river pollution during the flood season.

[0061] In summary, through the above specific steps, the flood season river pollution warning method can effectively conduct a comprehensive analysis and warning of the pollution status of the flood season river. From data collection and preprocessing, pollution feature extraction, pollution degree assessment, warning trigger and decision-making, to verification and feedback, and data storage and analysis, a complete closed loop is formed. Each step is interrelated and mutually influential, jointly ensuring the accuracy and reliability of the warning system.

[0062] The above are only the preferred embodiments of the present invention, and there is no limitation to the present invention in any form. Although the present invention has been disclosed above with the preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments of equivalent changes within the scope of the technical solution of the present invention by using the technical content disclosed above. However, as long as it does not depart from the content of the technical solution of the present invention, any brief modifications, equivalent changes and modifications made to the above embodiments according to the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A river pollution early warning system during the flood season, characterized in that, The system consists of: a microbial electrochemical sensor module, a current monitoring and data analysis module, a multi-level early warning trigger module, a chemical detection assistance module, and a data transmission and storage module; The microbial electrochemical sensor module is composed of three groups of sensor units, namely the surface layer, the middle layer, and the bottom layer. Electroactive microbial communities are encapsulated within each layer of sensor units. When corresponding pollutants are detected, the three groups of sensor units synchronously output current pulse signals through a phase difference detection circuit; The current monitoring and data analysis module continuously monitors the current pulse frequency generated by the microbial fuel cell and analyzes and processes the current data, resolving the current change into a composite pollutant toxicity index; The multi-level early warning trigger module is equipped with a three-level early warning response mechanism and a cross-level interlock mechanism. It compares the composite pollutant toxicity index with a dynamic early warning threshold and triggers the three-level early warning response mechanism based on the composite pollutant toxicity index output by the current monitoring and data analysis module; The chemical detection assistance module conducts a chemical composition analysis of the collected water samples according to the early warning signal from the early warning trigger module, mutually verifying and complementing the bioelectric signal early warning generated by the microbial fuel cell; The data transmission and storage module is responsible for storing the data collected by the microbial electrochemical sensor module, the data processed by the current monitoring and data analysis module, and the detection data of the chemical detection assistance module, and real-time transmitting them to the monitoring terminal for viewing.

2. The flood season river pollution warning system according to claim 1, wherein Each layer of sensor units within the microbial electrochemical sensor module integrates a microbial fuel cell, which encapsulates electroactive microbial communities. The electroactive microbial communities include sulfate-reducing bacteria sensitive to sulfides, iron-oxidizing bacteria sensitive to iron-containing pollutants, and nitrifying bacteria sensitive to nitrogen-containing pollutants. When the corresponding pollutants appear, the metabolic activity of the microbial communities increases sharply, and electrochemical reactions occur within the microbial fuel cell, thereby generating specific current pulse signals.

3. The pollution warning system for rivers during flood season according to claim 1, characterized in that, The current monitoring and data analysis module is used to continuously collect the current pulse frequency data generated by the microbial fuel cells in the sensor unit group, capture the changes in the current pulse frequency, and resolve the current changes into a composite pollutant toxicity index. The composite pollutant toxicity index is calculated by where T represents the composite pollutant toxicity index, f i is the real-time current pulse frequency of the i-th layer of sensor units, where i = 1, 2, 3 correspond to the surface layer, middle layer, and bottom layer respectively, and F i,base is the reference pulse frequency of the i-th layer of sensor units in a pollution-free state, and Δφ max is the absolute value of the maximum phase difference between the three layers of sensor units and Δφ max = max(|φ1 - φ2|, |φ2 - φ3|, |φ1 - φ3|), and α and β are weighting coefficients, with the value ranges of α ∈ [0.8, 0.9] and β ∈ [0.1, 0.3] respectively, and α + β = 1.

4. The flood season river pollution warning system according to claim 1, wherein, The three-level early warning response mechanism in the multi-level early warning trigger module includes a threshold dynamic calculation unit, a three-level response unit, and a false alarm suppression unit, where: The threshold dynamic calculation unit sets a dynamic early warning threshold T according to the historical pollution data and the pollutant benchmark T0 of the hydrological characteristics k , and sets three early warning levels, namely, level 1 early warning, level 2 early warning, and level 3 early warning, that is T k is the k-th level dynamic threshold, k = 1, 2, 3 corresponding to the three-level early warning, v is the real-time water flow velocity of the current section, v max is the historical maximum flow velocity, SC is the pollutant concentration, SC crit is the critical turbidity value of the pollutant; The three-level response unit continuously compares the composite pollutant toxicity index T output by the current monitoring and data analysis module with the thresholds at each level determined by the threshold dynamic calculation unit, thereby responding to different early warning levels; When the false alarm suppression unit detects that the same - layer sensor unit triggers a warning more than 3 times within 1 hour, and the matching degree between the water sample detection result of the chemical detection auxiliary module for this node and the bio - electrical signal warning is less than 50%, it will perform a false alarm suppression operation. The false alarm suppression operation adjusts the threshold of the composite pollutant toxicity index at the current warning level, and increases the dynamic warning threshold T k by 20%, that is to avoid frequent false alarms caused by abnormal interference existing in this node.

5. The flood season river pollution warning system according to claim 3, characterized in that, The specific response principle of the three-level response unit is as follows: Normal monitoring: When T < T1, no early warning is triggered, and the system is in a normal monitoring state; Level 1 early warning: When the composite pollutant toxicity index T satisfies T ≥ T1 and the duration Δt ≥ 5 min, initiate the collection of 3 times the standard volume of water samples and continuously detect; Level 2 early warning: When either T ≥ T2 or the level 1 early warning lasts for Δt ≥ 15 min, send an early warning message to the monitoring platform and activate the chemical detection assistance module for analysis; Level 3 warning: When T≥T3 and either of the following conditions is met, an emergency alarm is issued, and at the same time, the chemical detection auxiliary module is linked to increase the detection frequency and scope, and the components and sources of pollutants are analyzed in detail.

6. The flood season river pollution early warning system according to claim 1, characterized in that, The cross-level interlock mechanism in the multi-level early warning trigger module is as follows: When is satisfied, it is determined as a sudden major pollution, and it directly jumps to the third-level early warning. Among them, is the T gradient change rate along the water flow direction, and v is the real-time water flow velocity of the current section.

7. The flood season river pollution early warning system according to claim 1, characterized in that When a pollution incident occurs during the flood season, the chemical detection assistance module separately detects different warning signals through the priority control parameter W, and the priority control parameter W is dynamically calculated from the composite pollutant toxicity index T, that is where Δφ is the phase difference of the sensor unit in the bioelectrochemical sensor module. When W > 0.8, the mass spectrometry detection unit is immediately activated to analyze the pollutant components and concentrations. When 0.5 ≤ W < 0.8, the spectral rapid screening is activated to quickly conduct a preliminary investigation and judgment on the pollutants in the water sample.

8. A flood-season river pollution early warning system according to claim 7, characterized in that, The mass spectrometry detection unit quantitatively analyzes the target pollutants in the water sample to generate a concentration vector c = [c1, c2,..., c 32 , where c i represents the concentration of the i-th target pollutant, and calculates the matching degree between the bioelectric signal and the chemical detection where, T i refers to the composite pollutant toxicity index of the i-th layer of the microbial electrochemical sensor module, c i is the concentration of the corresponding pollutant detected chemically, w i is the matching degree coefficient, which is used to reflect the importance of different layers of sensors in the comprehensive matching degree calculation. The top layer is 0.4, the middle layer is 0.5, and the bottom layer is 0.

1. When M≥0.85, the pollution event is confirmed; otherwise, the false alarm suppression operation is triggered.

9. A method for warning of river pollution during flood season, applicable to a river pollution warning system according to any one of claims 1-8, characterized in that, The specific steps of this method are as follows: S100. Deploy a microbial electrochemical sensor network in the river area during the flood season, enabling the sensor nodes to collect water samples from the surface layer, middle layer, and bottom layer of the river and transmit current pulse signals; S200. The current monitoring and data analysis module continuously monitors the current pulse signals and conducts analysis to calculate the composite pollutant toxicity index; S300. The early warning trigger module continuously compares the calculated composite pollutant toxicity index with the dynamic early warning threshold; S400. The chemical detection assistance module is automatically activated after the early warning is triggered, analyzes the chemical components of the water sample, and transmits the results to the data transmission and storage module; S500. The data transmission and storage module stores all data and transmits it to the monitoring terminal in real time, and makes decisions and processes according to the data.

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