A floating water environment monitoring and early warning method and device

Abstract

The present invention relates to the technical field of water quality monitoring and early warning, specifically to a floating water environment monitoring and early warning method and device, the method comprising the following steps: using a floating water environment monitoring and early warning device to obtain initial water environment monitoring information, optimizing the initial water environment monitoring information, and obtaining water environment monitoring target information; establishing a water environment monitoring system based on the water environment monitoring target information; establishing a water environment pH prediction model based on the target information and the monitoring system to obtain pH prediction results; constructing a water environment turbidity analysis model based on the target information and the monitoring system to obtain turbidity analysis results; obtaining a comprehensive monitoring report of the water environment through the pH prediction results, turbidity analysis results and the evaluation results of the monitoring system, and matching an environmental early warning plan. The present invention conducts comprehensive monitoring and analysis of the water environment by constructing a mathematical model and a monitoring system, and matches appropriate early warning measures and emergency protection plans, thereby ensuring the healthy and sustainable development of the water environment.

Description

Technical Field

[0001] The present invention relates to the technical field of water environment monitoring and early warning, and in particular to a floating water environment monitoring and early warning method and device. Background Art

[0002] With the rapid development of industrialization and urbanization, the security and sustainable use of water resources are facing tremendous pressure. Traditional water environment monitoring methods mainly rely on manual sample collection and laboratory analysis, which are not only inefficient and costly, but also significantly lag behind the dynamic changes of the water environment, making it difficult to capture, analyze and effectively warn of water environment changes in real time. In addition, when dealing with complex and changeable environmental data, existing water environment monitoring methods are difficult to ensure the accurate matching of multivariate data and time series, resulting in insufficient accuracy of monitoring data, and it is even more impossible to comprehensively and systematically analyze and evaluate the overall status of the water environment.

[0003] Therefore, a water environment monitoring and early warning method and supporting device that integrates real-time, precision, and comprehensiveness is needed. The water environment monitoring and early warning method can automatically and in real time collect environmental data, accurately monitor and optimize water environment data through advanced data processing and analysis technology, ensure the accuracy of monitoring information, comprehensively detect water environment conditions, timely discover and warn potential water pollution risks, quickly match corresponding early warning plans, and provide timely and effective technical support for water environment protection and management decisions, thereby promoting the healthy and sustainable development of the water environment. Summary of the invention

[0004] In view of the shortcomings of existing methods and the needs of practical applications, the present invention uses a floating water environment monitoring and early warning device to obtain real-time water environment data, establishes a mathematical model to optimize, analyze and evaluate the environmental data, so as to obtain a comprehensive and accurate comprehensive water environment monitoring report. The present invention realizes the intelligent matching of water environment early warning schemes based on the comprehensive monitoring report, improves the response speed, decision-making efficiency and accuracy of water environment protection, and provides technical support for the sustainable development of water environment. On the one hand, the present invention provides a floating water environment monitoring and early warning method, which includes the following steps: using a floating water environment monitoring and early warning device to obtain water environment monitoring initial information, optimizing the water environment monitoring initial information to obtain water environment monitoring target information; establishing a water environment monitoring system based on the water environment monitoring target information; establishing a water environment pH prediction model based on the water environment monitoring target information and the water environment monitoring system, and obtaining the prediction result of the water environment pH; constructing a water environment turbidity analysis model based on the water environment monitoring target information and the water environment monitoring system, and obtaining the analysis result of the water environment turbidity; obtaining a comprehensive monitoring report of the water environment through the pH prediction result, the turbidity analysis result and the evaluation result of the water environment monitoring system, and matching the water environment early warning scheme according to the comprehensive monitoring report. The present invention not only improves the real-time, accuracy and comprehensiveness of water environment monitoring data, but also enhances the timeliness and effectiveness of early warning measures, and provides technical support for the sustainable utilization and protection of the water environment.

[0005] Optionally, the floating water environment monitoring and early warning method further comprises: the floating water environment monitoring and early warning method sets the monitoring frequency, arranges the monitoring sites and adjusts the monitoring instruments based on the floating water environment monitoring and early warning device and the water environment conditions. The present invention sets the detection instruments according to the specific conditions of the water environment and the monitoring requirements, which can improve the monitoring efficiency, optimize the resource allocation, enhance the monitoring accuracy and enhance the early warning capability of the method.

[0006] Optionally, the optimizing the initial water environment monitoring information to obtain the water environment monitoring target information includes: establishing a time series-data optimization model according to the initial water environment monitoring information; optimizing the initial water environment monitoring information using the time series-data optimization model to obtain the water environment monitoring target information. The data optimization model of the present invention can optimize the water environment monitoring information, thereby improving the accuracy and reliability of the data, providing a more scientific and accurate information basis, and helping to formulate more reasonable and effective water environment protection measures.

[0007] Optionally, the time series-data optimization model satisfies the following relationship:

[0008] s t+1 ′=hφ t +μg t+1 +ρB t+1

[0009] Among them, S t+1 ′ represents the data matrix at time point t+1 after optimization, h represents the state transfer matrix, φ t represents the data matrix state variable at time point t, μ represents the gain of the input data at time point t+1, and g t+1 represents the input data at time t+1, ρ represents the noise driving matrix at time t+1, B t+1 Represents the white noise information in the data input process at time point t+1. The time series-data optimization model of the present invention can capture the dynamic characteristics of data changing over time, thereby more accurately predicting the data state at future time points, and further improving the accuracy and real-time performance of monitoring data.

[0010] Optionally, the establishment of a water environment monitoring system based on the water environment monitoring target information includes: obtaining water environment parameter information according to the water environment monitoring target information, wherein the water environment parameter information includes hydrological parameter information and water quality parameter information of the water environment; and establishing a water environment monitoring system according to the hydrological parameter information and the water quality parameter information. The present invention obtains meteorological parameter information, hydrological parameter information, and water quality parameter information of the water environment, which can realize comprehensive monitoring of the water environment and more accurately reflect the overall condition of the water environment.

[0011] Optionally, establishing a water environment pH prediction model based on water environment monitoring target information and a water environment monitoring system includes:

[0012] The water environment pH prediction model satisfies the following relationship:

[0013]

[0014] Among them, pH represents the predicted pH value of the water environment, pH c represents the pH value of the standard water quality sample, f represents the Faraday constant, e1 represents the electromotive force of the measured water environment, e2 represents the electromotive force of the standard water quality sample, R represents the gas constant, and T represents the absolute temperature of the water environment. The present invention combines physical parameters such as the Faraday constant, the gas constant and the absolute temperature to scientifically predict the pH value of the water environment. This prediction model has a solid theoretical basis and scientific basis.

[0015] Optionally, constructing a water environment turbidity analysis model according to water environment monitoring target information and a water environment monitoring system includes:

[0016] The water environment turbidity analysis model satisfies the following relationship:

[0017]

[0018] Wherein, K represents the turbidity coefficient of the water environment, δ represents a constant coefficient, I0 represents the incident light intensity, α represents the scattering angle, l represents the maximum length of light passing through the water body, λ represents the wavelength of the incident light, and w represents the scattered light intensity. The model of the present invention is based on the principle of optical scattering, and calculates the turbidity coefficient of the water environment through parameters such as the incident light intensity, the scattered light intensity, and the scattering angle. It has high accuracy and reliability and can more accurately reflect the turbidity of the water environment.

[0019] Optionally, the floating water environment monitoring and early warning method further comprises: obtaining biochemical index evaluation results based on the water environment monitoring system. The biochemical index evaluation results obtained by the present invention based on the water environment monitoring system are more comprehensive and accurate than single parameter evaluation, and are helpful for discovering potential water environment problems.

[0020] Optionally, the pH prediction model of the water environment is used to obtain the pH prediction value of the water environment; the turbidity coefficient of the water environment is obtained using the water environment turbidity analysis model; a comprehensive monitoring report of the water environment is obtained based on the pH prediction value, the turbidity coefficient and the biochemical index evaluation results; and a water environment early warning plan is matched according to the comprehensive monitoring report. The present invention combines the pH prediction value, the turbidity coefficient and the biochemical index evaluation results to more comprehensively analyze the actual situation of the water environment, and more accurately issue early warning signals and take control measures.

[0021] In the second aspect, in order to efficiently execute a floating water environment monitoring and early warning method provided by the present invention, the present invention also provides a floating water environment monitoring and early warning device, the device includes a monitoring device, a processor, an output device, an early warning device and a memory, the monitoring device, the processor, the output device, the early warning device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the floating water environment monitoring and early warning method as described in the first aspect of the present invention. The floating water environment monitoring and early warning device of the present invention has a compact structure and stable performance, and can stably execute the floating water environment monitoring and early warning method provided by the present invention, thereby improving the overall applicability and practical application ability of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of the floating water environment monitoring and early warning method of the present invention;

[0023] Figure 2 A schematic diagram of the monitoring process of meteorological parameter information of the floating water environment monitoring and early warning method of the present invention;

[0024] Figure 3 It is a schematic diagram of the floating water environment monitoring, analysis and early warning process of the present invention;

[0025] Figure 4 It is a structural diagram of the floating water environment monitoring and early warning device of the present invention. DETAILED DESCRIPTION

[0026] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0027] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0028] See also Figure 1 In order to achieve accurate analysis of water environment conditions and scientific matching of early warning schemes, the present invention acquires water environment monitoring data in real time based on a monitoring device, establishes a mathematical model to perform in-depth optimization, systematic analysis and scientific evaluation of water environment monitoring data, obtains a comprehensive and accurate water environment comprehensive monitoring report, provides technical support for the protection and management of water environment resources, and effectively promotes the sustainable development of water environment. The present invention provides a floating water environment monitoring and early warning method, which comprises the following steps:

[0029] S1. Use the floating water environment monitoring and early warning device to obtain the initial water environment monitoring information, and optimize the initial water environment monitoring information to obtain the water environment monitoring target information. The specific implementation steps and contents are as follows:

[0030] In this embodiment, the floating water environment monitoring and early warning method needs to set the device monitoring frequency, layout monitoring sites and adjust monitoring instruments based on the floating water environment monitoring and early warning device and the actual water environment conditions. The specific implementation contents are as follows:

[0031] In the embodiment, the floating water environment monitoring and early warning device is a modern water quality monitoring device that integrates multiple technologies, and is mainly used to monitor water conditions in real time, collect environmental monitoring data, and store data information. The floating platform in the floating water environment monitoring and early warning device is the carrier of the entire device system, which can be made of materials such as plastic or fiberglass, and needs to have good buoyancy, corrosion resistance, and stability, and can carry other equipment and sensors to move freely on the water surface to monitor the water quality of different regions or ecological environments. At the same time, the design of the floating platform should take into account the stability and durability under different water flow speeds and water depths.

[0032] The data acquisition equipment in the floating water environment monitoring and early warning device mainly includes various high-precision sensors and detection instruments, among which the flow meter is used to detect the water flow velocity and water flow in the water environment, including but not limited to water flow rate detectors, flow meters, flow meters, etc.

[0033] The turbidity monitor is used to collect natural water turbidity data of the water environment, the conductivity monitor is used to collect conductivity data of the water environment, the odor monitor is used to collect odor data of the water environment, the water temperature sensor is used to collect the temperature value of the water environment, the pH sensor is used to collect the pH value of the water environment, and the water level monitor is used to collect the water level value of the water environment.

[0034] The floating water environment monitoring and early warning device of the present invention can collect, process and manage monitoring data in real time, and integrate the equipment and technology in the fields of atmospheric environment monitoring, hydrological monitoring and water quality monitoring. The device in the embodiment can float on the water surface, can adapt to various water environments, and realize all-round, multi-dimensional real-time monitoring of water environment data to obtain initial information of water environment monitoring.

[0035] In an optional embodiment, the floating water environment monitoring and early warning device is equipped with a high-precision water quality monitor that can accurately capture key water quality parameters such as turbidity, pH value, dissolved oxygen, and conductivity in the water body; at the same time, the integrated COD water quality monitor can further analyze the chemical oxygen demand in the water body, providing a scientific basis for water quality assessment.

[0036] Furthermore, the floating water environment monitoring and early warning device adds monitoring sensors for core water quality indicators such as flow rate, DO (dissolved oxygen), COD (chemical oxygen demand), total nitrogen, ammonia nitrogen, total phosphorus, chlorophyll a, and heavy metals. The above sensors and their applications are as follows:

[0037] Flow velocity sensors usually use mechanical, electromagnetic or optical principles to measure the flow velocity of fluids in water environments. They can use ultrasonic or laser Doppler effect to measure water flow velocity. They can be widely used in flow velocity monitoring of rivers, lakes, oceans and other water bodies. They have the advantages of miniaturization, intelligence, low energy consumption and a wide range of applications.

[0038] DO (dissolved oxygen) sensors mainly utilize electrochemical principles. They infer the concentration of dissolved oxygen by measuring the current of the electrode in the solution. They can be used to monitor the dissolved oxygen content in water bodies. They are of great significance for evaluating the self-purification capacity of water bodies and biological respiration. DO sensors can monitor the concentration of dissolved oxygen in real time and continuously, and have high sensitivity and stability.

[0039] COD (Chemical Oxygen Demand) sensors mainly use chemical reactions to oxidize organic matter in water into carbon dioxide, and indirectly determine the COD content in water by measuring the amount of oxygen consumed in the oxidation process. They play a key role in water environment monitoring and management. They can monitor the COD content in water in real time and continuously, warn of pollution incidents and evaluate water quality. They can also quickly and accurately sample and conduct laboratory tests, saving time and labor costs.

[0040] The total nitrogen sensor uses spectrophotometry or chemiluminescence to measure the total nitrogen content in water bodies. It can be used to evaluate the eutrophication status of the water environment and is of great significance to water environment protection and ecological restoration. It can provide accurate, continuous and stable measurement data and can be used in floating water environment monitoring and early warning systems.

[0041] Ammonia nitrogen sensors are mainly based on the measurement principle of ammonia gas sensitive electrodes or ammonium ion electrodes. They measure the ammonia gas or ammonium ion concentration in water to infer the ammonia nitrogen content. They can be used to monitor ammonia nitrogen pollution in water bodies, can achieve in-situ rapid measurement, and have high sensitivity and accuracy.

[0042] The total phosphorus sensor also uses spectrophotometry or chemiluminescence to measure the total phosphorus content in the water body. Similar to the total nitrogen sensor, it can be used to assess the eutrophication status of the water body, provide continuous and stable measurement data, and can be integrated into the floating water environment monitoring and early warning system.

[0043] Chlorophyll a sensor mainly measures the chlorophyll A content in water based on fluorescence or absorption spectroscopy. Chlorophyll a is an important indicator of algae biomass in water environment and can be used to monitor the growth of algae in water. It is of great significance to prevent and control eutrophication of water bodies. It can achieve fast and accurate measurement without damaging the water environment.

[0044] Heavy metal sensors measure heavy metal content based on color changes or electrochemical signals produced by the reaction of heavy metal ions with specific reagents. They can be used to monitor heavy metal pollution in water bodies and are of great significance to ensuring the safety of drinking water and the health of the ecological environment. They have high sensitivity and high selectivity and can detect multiple heavy metal ions at the same time.

[0045] In terms of data collection, the floating water environment monitoring and early warning device uses highly sensitive sensors and intelligent collection equipment to ensure the accuracy and real-time nature of the data. The collected initial information is instantly cleaned, verified and integrated through the built-in data processing module to form structured water environment monitoring initial information. This device not only supports local storage, but can also be transmitted to the remote data center in real time through wireless communication technology, realizing remote monitoring and information sharing of the initial monitoring information.

[0046] The floating water environment monitoring and early warning device of the present invention has efficient data collection capability, intelligent data processing mechanism and integrated management mode, which provides strong technical support for real-time monitoring and early warning of water environment and contributes to the practical application of the floating water environment monitoring and early warning method.

[0047] Furthermore, the floating water environment monitoring and early warning device used in the present embodiment is only an optional condition of the present invention. In one or some other embodiments, the floating water environment monitoring and early warning device can be adjusted according to the actual water environment conditions and data monitoring requirements. The water environment characteristics, pollution source types and pollution levels of different waters are different. By increasing or reducing monitoring equipment, optimizing sensor layout, etc., the detection device can be ensured to adapt to the monitoring needs of different water environments and improve the accuracy and feasibility of information monitoring results.

[0048] In an optional embodiment, the monitoring frequency of the device is set based on the floating water environment monitoring and early warning device and the water environment conditions.

[0049] In order to efficiently capture the initial information of water environment monitoring, under the conditions of limited resources and monitoring capabilities, optimizing the monitoring frequency and sampling frequency of the device will help obtain the most representative water quality data, thereby achieving a comprehensive and objective understanding of the water environment status and its dynamic changes.

[0050] From the perspective of time series analysis, the setting of water quality monitoring frequency mainly depends on the characteristics and data attributes of key water environment parameters, including but not limited to trend characteristics, periodicity, variance, autocorrelation, and serial correlation or repeatability between water environment monitoring samples. The above characteristics and attributes jointly determine the performance of water environment monitoring information in time series.

[0051] In this embodiment, the time series of water quality monitoring can be composed of multiple components, including but not limited to trend components, periodic components, correlated random components and independent residual components. The trend component reflects the long-term trend of water quality changes over time; the periodic component reflects the periodic law of water quality changes; the correlated random component describes the random fluctuations in water quality data, which are related to various environmental factors, including but not limited to weather, human activities and natural changes; and the independent residual component represents the part that cannot be explained by the above components. On the other hand, different water quality parameters, such as dissolved oxygen, pH value, temperature, turbidity, heavy metal content, etc., have different change speeds and importance. For parameters that change faster or have a greater impact on water quality, a higher monitoring frequency can be set; and for relatively stable or less influential parameters, the monitoring frequency can be appropriately reduced.

[0052] When setting the monitoring frequency of the device, it is necessary to fully consider the influence of different key parameters or components. On the one hand, it is necessary to avoid missing important water quality change information due to too low a monitoring frequency; on the other hand, it is also necessary to avoid information redundancy and increased monitoring costs due to too high a monitoring frequency. Therefore, a reasonable monitoring frequency should be able to balance the integrity of information capture and the economy of monitoring costs, so as to achieve a comprehensive, objective and dynamic grasp of the water environment status and its dynamic changes.

[0053] Furthermore, in the present embodiment, the monitoring frequency of the floating water environment monitoring and early warning device is only an optional condition of the present invention. In one or some other embodiments, the monitoring frequency of the device can be adjusted according to the actual conditions of the water environment and the actual conditions of the device. Reasonable adjustment of the monitoring frequency under different circumstances can avoid unnecessary waste of resources. The device can better adapt to changes in the water environment, capture key information in a timely manner and make scientific adjustments.

[0054] In an optional embodiment, monitoring sites are arranged based on the floating water environment monitoring and early warning device and the water environment conditions.

[0055] In order to fully and accurately capture the most representative dynamic changes in water quality in the tested water environment, it is necessary to implement a scientific and reasonable monitoring site layout strategy, including but not limited to planning the location and number of monitoring sites, to ensure the comprehensive and accurate capture of the dynamic changes in water quality in the target waters, which can not only improve the accuracy and comprehensiveness of water quality monitoring data, but also effectively control data monitoring costs and optimize resource allocation.

[0056] In the embodiment, based on the characteristics of the floating water environment monitoring and early warning device, and taking full account of the actual situation of the target water environment, the geographical characteristics, water flow patterns, distribution of potential pollution sources and historical water quality data of the target water environment are analyzed, and the preliminary candidate locations of the monitoring sites are determined based on this; then, the most suitable site locations are further selected in combination with the technical characteristics and monitoring capabilities of the floating water environment monitoring and early warning device. In this process, the distribution balance of the monitoring sites also needs to be considered to ensure that the monitoring equipment can cover all key areas of the water area and realize all-round monitoring of water quality changes in the environment. At the same time, it is also necessary to flexibly adjust the layout of the monitoring sites according to factors such as seasonal changes in the water environment and sudden pollution incidents to ensure the timeliness and accuracy of the monitoring data.

[0057] In the embodiment, the geographical characteristics of the water area, water flow dynamics, distribution of pollution sources, and historical water quality data are comprehensively considered to determine the optimal location and number of monitoring sites. The above scientific and reasonable monitoring site layout method helps to improve the accuracy and integrity of water quality monitoring data, effectively control monitoring costs while ensuring data monitoring effects, and achieve optimal resource allocation. On the other hand, it can maximize the advantages of the floating water environment monitoring and early warning device, so that it can efficiently and accurately monitor the water quality change information of the target water area, ensuring the timeliness and representativeness of the monitoring data.

[0058] Furthermore, in the present embodiment, the layout of the monitoring points of the floating water environment monitoring and early warning device is only an optional condition of the present invention. In one or some other embodiments, the layout of the monitoring points of the device can be optimized according to the device equipment conditions and data collection requirements, so that key areas or potential risk points can be monitored more accurately, unnecessary monitoring blind spots can be reduced, monitoring efficiency can be improved, waste of resources can be avoided, and the comprehensiveness and accuracy of the initial information of water environment monitoring can be ensured.

[0059] A time series-data optimization model is established based on the above initial water environment monitoring information, and the time series-data optimization model is used to optimize the initial water environment monitoring information to obtain the water environment monitoring target information. The specific contents are as follows:

[0060] Water environment monitoring involves multiple parameters or variables, such as dissolved oxygen, pH value, temperature, turbidity, heavy metal content, etc. The above parameters influence each other, making different time series data more complicated. When processing such multidimensional and nonlinear data, it is often difficult to accurately capture the dynamic relationship between the variables, resulting in low prediction accuracy.

[0061] Traditional data processing models cannot adapt well to the complexity and variability of water environment monitoring data. As water environment conditions change, data distribution and correlation also change, and existing models cannot be adjusted in time to adapt to the above changes. Current data processing methods lack accurate identification of the correlation between monitoring data and time. Water environment monitoring data is long-term and cyclical. Current methods focus more on short-term fluctuations and ignore the analysis of long-term trends, resulting in the inability to guarantee the accuracy of monitoring data and fail to meet the minimum standards of modern data accuracy.

[0062] In the embodiment, a time series-data optimization model is established based on the monitoring frequency, monitoring sites and monitoring instruments in the floating water environment monitoring and early warning device, and combined with the initial water environment monitoring information. In the embodiment, advanced technologies such as machine learning and deep learning can be used to improve the prediction accuracy and processing capabilities of multivariate time series data, and data mining and statistical analysis methods are used to deeply explore the correlation between the initial water environment monitoring information and the monitoring frequency and collection time, thereby revealing the inherent laws of water environment changes and establishing a real-time data update mechanism to ensure the timeliness and accuracy of the initial water environment monitoring information. At the same time, data quality control and cleaning work are strengthened to improve the quality and reliability of the initial water environment monitoring information.

[0063] The above time series-data optimization model satisfies the following relationship:

[0064] s t+1 ′=hφ t +μg t+1 +ρB t+1

[0065] Among them, S t+1 ′ represents the data matrix at time point t+1 after optimization, h represents the state transfer matrix, φ t represents the data matrix state variable at time point t, μ represents the gain of the input data at time point t+1, and g t+1 represents the input data at time t+1, ρ represents the noise driving matrix at time t+1, B t+1 Represents the white noise information during the data input process at time point t+1.

[0066] Among them, the state transfer matrix can be used to describe the change law of the state of the data matrix over time. Specifically, the state transfer matrix is ​​a function of time and initial time, which can map the state vector of time to the state vector of a certain moment in the future. The stability of the initial data can be analyzed through the state transfer matrix, based on which the stability of the monitoring device can be analyzed and the working state of the observer can be adjusted.

[0067] The above state transfer matrix satisfies the following relationship:

[0068] ht =e yt

[0069] Among them, h t represents the state transfer matrix at time point t, y t is the state vector of the monitoring device at time point t. The state vectors of the monitoring device at different time points above satisfy the following relationship:

[0070] y t =h0ρ0+h t ρ t

[0071] Among them, y t is the state vector of the monitoring device at time t, h0 represents the initial matrix of the monitoring device, ρ0 represents the state vector of the monitoring device, and h t represents the input matrix of the monitoring device at time point t, ρ t Represents the state vector of the monitoring device at time point t.

[0072] In the field of control systems or data processing, the data matrix state variables at different time points refer to the quantitative representation of the internal state of the device at a specific time point. The above state variables can fully reflect the dynamic characteristics and behaviors of the monitoring device at different time points. The state variables change over time and can reflect the dynamic change process of the monitoring device state.

[0073] In order to improve the optimization capability of multivariate time series data, the data matrix state variables at different time points in the embodiment need to satisfy the following relationship:

[0074]

[0075] Among them, φ t Represents the data matrix state variable at time t, C t represents the monitoring variable at time point t, O t represents the white noise information of the monitoring process at time point t, and h′ represents the monitoring data matrix at time point t.

[0076] The gain of input data at different time points in a data monitoring device refers to the positive impact or value increase of the new input data on the monitoring device, data analysis process or decision making at a specific time point. t usually represents a base time point or any moment in the data collection cycle, while t+1 represents the next time point, moment or cycle immediately following it.

[0077] In data monitoring devices, input data at different time points are crucial to the accuracy and real-time nature of the monitoring process. The above input data not only reflects the current status of the monitoring device or the water environment, but also provides trends and patterns that change over time, which helps in in-depth analysis and decision-making. It is crucial for early warning signals and emergency incident handling in the water environment, and can reflect the working condition of the device or the dynamic changes of the water environment.

[0078] In the data monitoring device, the noise driving matrix at different time points can be used to describe the influence of other factors on the monitoring device. In the process of collecting data, the monitoring device will be interfered by various noises, including but not limited to the accuracy limitation of the sensor itself, the interference of environmental factors, errors in the data transmission process, etc. The above noise will affect the accuracy and reliability of the data, and thus affect the performance of the data monitoring device.

[0079] In the data monitoring device, the white noise information in the data input process at different time points refers to the interference of internal mechanisms, external environment and other factors in the data collection process of the monitoring device, which will generate certain noise, thereby affecting the accuracy of the detection data. When establishing a data optimization model, the influence of noise is taken into account, and the impact of noise on the monitoring results is reduced through model correction.

[0080] In an optional embodiment, the time series-data optimization model is used to optimize the initial water environment monitoring information to obtain the water environment monitoring target information, and the specific contents are as follows:

[0081] In the embodiment, a total of t time points are provided to monitor and record the initial water environment monitoring information, and the initial water environment monitoring information is recorded at different time points s1, s2, s3, ..., s t The corresponding monitoring data constitutes a data information matrix;

[0082] The relevant data are represented as a t×n data matrix, where t is the number of time points, that is, the different time points recorded, and n is the specific variables or characteristic information monitored at each time point. Each row of the matrix represents a monitoring record at a time point t, and each column represents the monitoring information of a specific variable at all time points.

[0083]

[0084] Among them, S represents the monitoring data matrix of water environment, s 11 Indicates the monitoring data of water environment parameter 1 at the first time point, s 12 Indicates the monitoring data of water environment parameter 2 at the first time point, s 1n represents the monitoring data of water environment parameter n at the first time point, s 21 represents the monitoring data of water environment parameter 1 at the second time point, s 22Indicates the monitoring data of water environment parameter 2 at the second time point, s 2n represents the monitoring data of water environment parameter n at the second time point, s t1 represents the monitoring data of water environment parameter 1 at time point t, s t2 represents the monitoring data of water environment parameter 2 at time point t, s tn Represents the monitoring data of water environment parameter n at time point t.

[0085] Through the time series-data optimization model, data at different time points are iteratively optimized:

[0086] s t+1 ′=hφ t +μg t+1 +ρB t

[0087] Among them, S t+1 ′ represents the data matrix at time point t+1 after optimization, h represents the state transfer matrix, φ t represents the data matrix state variable at time point t, μ represents the gain of the input data at time point t+1, and g t+1 represents the data input at time t+1, ρ represents the noise driving matrix at time t+1, B t+1 Represents the white noise information during the data input process at time point t+1.

[0088] Through the time series-data optimization model, the data matrix information at different time points can be deeply analyzed. Through recursive iteration, the time series-data optimization model can not only effectively track the subtle changes in the water environment, but also accurately capture the long-term trends and periodic fluctuations of the water environment, thereby achieving effective optimization of the target information of water environment monitoring.

[0089] The time series-data optimization model has excellent time series processing capabilities. Whether it is stable sequence data or complex and changeable non-stationary series, it can show extremely high adaptability and flexibility, and efficiently process and analyze data, effectively reducing the computational complexity and ensuring the timeliness and accuracy of the optimization results.

[0090] In practical applications, the time series-data optimization model has good practicality. It can optimize and update future water environment data information based on historical data, and provide a scientific decision-making basis for water environment management. At the same time, through real-time monitoring and dynamic adjustment, the model can quickly respond to emergencies and provide strong support for the protection and management of the water environment.

[0091] The data information after the above optimization, i.e., the water environment monitoring target information of this embodiment, satisfies the following relationship:

[0092]

[0093] Furthermore, the method for optimizing the initial monitoring information in the present embodiment is only an optional condition of the present invention. In one or some other embodiments, the data optimization method can be adjusted according to the data optimization target and the actual data situation. Since the data optimization method can be adjusted according to the data optimization target and the actual data situation, the present invention can be widely applied to water environment monitoring tasks of different types and complexities, and can ensure the accuracy and reliability of the data optimization results.

[0094] S2. Establish a water environment monitoring system based on the above water environment monitoring target information. The specific implementation steps and contents are as follows;

[0095] The water environment parameter information is obtained according to the water environment monitoring target information. The water environment parameter information in the embodiment mainly includes the water environment hydrological parameter information and water quality parameter information. The water environment monitoring system is established according to the hydrological parameter information and the water quality parameter information. The specific contents are as follows:

[0096] Based on the water environment monitoring target information, multi-dimensional parameter information of the water environment is systematically obtained and integrated. The above parameter information mainly includes hydrological parameters and water quality parameters.

[0097] Hydrological parameter information mainly describes the physical movement characteristics of water bodies and the dynamic changes of water volume, and is the key to understanding the behavior and changes of water environment. Among them, wave height, wave direction and wave period can reflect the characteristics of waves in the ocean or lake, and have a direct impact on water operations, shipping safety and coastal erosion; flow velocity and flow direction can be used to describe the speed and direction of water flow, and play an important role in water mixing, pollutant diffusion and ecosystem distribution; tides are particularly important in coastal areas, and they mainly affect the periodic changes of water levels, which have a far-reaching impact on port operations, fishery activities and marine engineering construction.

[0098] Water quality parameter information can directly reflect the chemical, physical and biological characteristics of water bodies, and is an important basis for evaluating water conditions and pollution levels. Among them, water temperature mainly affects the chemical reaction rate and biological metabolic activities in water bodies; pH value can measure the acidity and alkalinity of water bodies, which has an important impact on the survival of aquatic organisms and the form of chemical substances in water bodies; dissolved oxygen mainly reflects the oxygen content in water bodies, and is an important indicator for evaluating the self-purification capacity of water bodies and biological respiration; nutrients in the water environment, such as chlorophyll a, total nitrogen, total phosphorus, phosphate, nitrate, nitrite, ammonia nitrogen, etc., can reflect the eutrophication of water bodies and have a direct impact on algae growth and water quality deterioration; salinity is particularly important in marine and saltwater environments, affecting the physical properties and biological distribution of water bodies; turbidity can reflect the content of suspended particles in water bodies, affecting the transparency and photosynthesis of water bodies; COD (chemical oxygen demand) can be used to measure the content of oxidizable organic matter in water bodies, and is an important indicator for evaluating the degree of organic pollution in water bodies.

[0099] In summary, by comprehensively monitoring meteorological, hydrological and water quality parameter information, we can obtain comprehensive information on water environment conditions, changing trends and potential risks, and provide a scientific basis for water environment monitoring, early warning, protection and rational utilization.

[0100] Based on the multi-dimensional parameter information of the water environment mentioned above, a multi-dimensional and comprehensive water environment monitoring system is constructed. The above system integrates parameter information in the three core areas of meteorology, hydrology and water quality. Based on this system, it can not only capture and analyze the changing dynamics of the atmospheric environment in real time, such as light intensity, radiation characteristics, wind speed and direction, rainfall patterns, temperature, humidity conditions and other meteorological parameters, to provide basic data for predicting weather changes and evaluating energy potential; at the same time, it can explore the physical movement laws of water bodies, including but not limited to monitoring of hydrological parameters such as wave characteristics, flow velocity and direction, and tidal fluctuations, so as to reveal key information such as water flow, water volume changes and coastal dynamics; further, the system is used to pay close attention to the chemical, physical and biological characteristics of water quality, and by monitoring water quality parameters such as water temperature, pH value, dissolved oxygen, nutrients, salinity, turbidity and COD, it helps to comprehensively evaluate water conditions, pollution levels and ecological risks.

[0101] In this embodiment, the water environment monitoring system of the floating water environment monitoring and early warning method mainly includes three types of key parameters. For specific information, please refer to Table 1:

[0102] Table 1

[0103]

[0104] Water environment monitoring system information form

[0105] The above-mentioned water environment monitoring system covers many key aspects of water environment monitoring and evaluation, from hydrological dynamics to water quality conditions, ensuring the comprehensiveness of monitoring results and data feasibility, and helping to more accurately grasp the changing trends and potential risks of the water environment. By collecting and analyzing system data in real time, it can quickly feedback the changes in the water environment, provide timely early warning information, and help to take early warning measures in a timely manner.

[0106] Furthermore, the method of establishing a water environment monitoring system in the present embodiment is only an optional condition of the present invention. In one or some other embodiments, the method of constructing the monitoring system can be adjusted according to actual conditions and environmental detection requirements, so that the monitoring method has a high degree of adaptability and flexibility. Different regions, different water body types or different monitoring targets require different monitoring parameters, sampling frequencies or analysis methods. The present invention can ensure that the monitoring system is more in line with actual needs and improve the effectiveness and pertinence of the monitoring results.

[0107] S3. Establish a water environment pH prediction model based on the water environment monitoring target information and the water environment monitoring system, and obtain the prediction results of the water environment pH. The specific implementation steps and contents are as follows:

[0108] The floating water environment monitoring device can monitor the pH value of the water body in real time, transmit the data to the monitoring center through the sensor, and realize the real-time update of the data. In order to ensure the accuracy of the pH monitoring value, in this embodiment, the pH value of the water body in the future period of time can be predicted in combination with the prediction model. When it is predicted that the pH value will exceed the normal range, the floating water environment monitoring device can issue an early warning, which helps to take protective measures in time to prevent water quality deterioration or pollution incidents.

[0109] The sensor in the floating water environment monitoring device can realize real-time measurement of the pH value of the water body. However, in order to further ensure the accuracy of the pH value, the embodiment establishes a water environment pH prediction model based on advanced technologies such as big data analysis and machine learning. The above prediction model can comprehensively consider multiple influencing factors, such as meteorological conditions, hydrological dynamics, water quality conditions, etc., and make scientific and reasonable predictions on the pH value of the water body, so that the prediction results are more in line with the actual situation, which is helpful to formulate effective water environment management measures and early warning plans.

[0110] The above water environment pH prediction model satisfies the following relationship:

[0111]

[0112] Among them, pH represents the predicted pH value of the water environment, pH crepresents the pH value of the standard water quality sample, f represents the Faraday constant, e1 represents the electromotive force of the water environment being measured, e2 represents the electromotive force of the standard water quality sample, R represents the gas constant, and T represents the absolute temperature of the water environment.

[0113] In an optional embodiment, relevant parameter information is obtained based on the sensor in the monitoring device. The pH sensor is an electrochemical device specifically used to measure the acidity and alkalinity of a solution (i.e., pH value), which is mainly composed of two key parts: a glass electrode also called a measuring electrode or an indicator electrode and a reference electrode.

[0114] The glass electrode is the core part of the sensor. It has a highly selective response to hydrogen ions (H+) in the solution. When the glass electrode is immersed in the water to be tested, its surface will interact with the hydrogen ions in the solution, resulting in an electric potential on the electrode surface that is closely related to the activity of hydrogen ions in the solution. The above electric potential is negative and has a linear and predictable relationship with the negative logarithm of the hydrogen ion activity (i.e., pH value). Therefore, by measuring the electric potential on the glass electrode, the pH value of the water can be indirectly determined.

[0115] The reference electrode plays a vital role in the pH sensor. It provides a stable and known reference potential, which remains unchanged throughout the measurement process. As a benchmark for measuring the potential of the glass electrode, common reference electrodes include silver-silver chloride electrode, calomel electrode, etc., which make their potential remain relatively stable under a wide range of conditions, thereby ensuring the accuracy and reliability of pH measurement.

[0116] When a forward current flows out of the pH sensor, the electrode potential satisfies the following relationship:

[0117]

[0118] Among them, e + represents the forward current potential of the pH sensor, e0 represents the standard electrode potential, R represents the gas constant, T represents the absolute temperature of the water environment, n represents the number of measuring points of the pH sensor, f represents the Faraday constant, σ represents the activity index of the hydrogen ion, x(H + ) indicates H + The charge number of the ion.

[0119] When negative current flows out of the pH sensor, the electrode potential satisfies the following relationship:

[0120]

[0121] Among them, e -represents the negative current potential of the pH sensor, e0 represents the standard electrode potential, R represents the gas constant, T represents the absolute temperature of the water environment, n represents the number of measuring points of the pH sensor, f represents the Faraday constant, x(OH - ) indicates OH - The ion charge number, σ represents the activity index of the hydrogen ion.

[0122] Furthermore, in order to obtain relevant information of the standard water quality sample, the specific contents of the embodiment are as follows:

[0123] In order to accurately detect the pH value of the water environment samples actually collected, it is first necessary to prepare standard water quality samples as a comparison benchmark. The content of obtaining standard water quality samples is as follows: Prepare raw materials based on the historical data of the water environment to be tested: First, obtain the water quality standard sample through the water environment, and slowly and evenly pour the water quality standard sample into the same clean container with a capacity of at least 250ML to avoid excessive bubbles during the mixing process. In order to ensure the uniformity and consistency of the water quality standard sample, you can use the test tube or the lid of the container to gently shake the container several times. Be careful to avoid excessive shaking to avoid introducing unnecessary air bubbles or splashing the solution. Place the water quality standard sample at room temperature (about 25℃±3℃) and let it stand for about 24 hours to allow the suspended particles in the sample to fully settle and reach a stable state, thereby ensuring the accuracy of the pH measurement results. After the standing is over, check whether the sample is uniform and there is no obvious stratification or precipitation. If everything is normal, the same pH sensor can be used to obtain relevant information of the standard water quality sample, providing a reliable reference for the detection of actual water environment samples.

[0124] The pH prediction model of water environment was established by combining the pH measurement information of the floating water environment monitoring device and the relevant information of the standard water quality samples, which satisfies the following relationship:

[0125]

[0126] Among them, pH represents the predicted pH value of the water environment, pH c represents the pH value of the standard water quality sample, f represents the Faraday constant, e1 represents the electromotive force of the water environment being measured, e2 represents the electromotive force of the standard water quality sample, R represents the gas constant, and T represents the absolute temperature of the water environment.

[0127] The Faraday constant represents the charge carried by each mole of electrons, that is, the amount of charge carried by each mole of electrons.

[0128] The electromotive force of the measured water environment refers to the electromotive force information of the water environment measured by the sensor in the device.

[0129] The gas constant is a fundamental constant in thermodynamics that is used to describe the behavior of gases in thermodynamic processes and to link temperature and energy in water environment pH prediction models.

[0130] The absolute temperature of a water environment is the standard way to express thermodynamic temperature.

[0131] The water environment pH prediction model can timely detect abnormal conditions of water environment pH and provide early warning information for water environment prevention and control. Based on the prediction results, water quality early warning plans and protection measures can be formulated more scientifically and accurately to improve the sustainable development of the water environment.

[0132] Furthermore, the method for constructing a water environment pH prediction model in the present embodiment is only an optional condition of the present invention. In one or some other embodiments, the water environment pH prediction model can be reasonably adjusted according to the environmental parameter characteristics and the specific conditions of the water environment, which can not only improve the accuracy of the prediction and the applicability of the model, but also more effectively prevent and control the occurrence of water pollution incidents and protect the sustainable use of water resources.

[0133] S4. Construct a water environment turbidity analysis model based on the water environment monitoring target information and the water environment monitoring system, and obtain the analysis results of the water environment turbidity. The specific implementation steps and contents are as follows:

[0134] Turbidity, as a core parameter in water quality assessment, not only reflects the degree of obstruction of suspended matter in water to light transmission, but also reflects the complex situation of suspended particles in the water and the pollutants they carry. In the field of water environment monitoring, changes in turbidity are often early warning signs of water quality problems, which are closely related to the growth of microorganisms, accumulation of soluble impurities, and the content of suspended matter such as silt. In an optional embodiment, if the turbidity is significantly reduced, it indicates that the suspended particles in the water and the organic pollutants attached to them have been effectively removed, thereby improving the water quality.

[0135] Turbidity not only affects the clarity of water, but also indirectly regulates the structure and activity of microbial communities. In low-turbidity water, the nutrients attached to the surface of suspended particles are reduced, which in turn limits the growth and reproduction of microorganisms and reduces the risk of pathogenic microorganisms in the water. On the contrary, a high-turbidity environment provides a rich habitat and nutrient source for microorganisms, promotes the reproduction of microorganisms, and increases the risk of water pollution.

[0136] In addition, turbidity can also be used as a warning indicator for the deterioration of the water environment. When the turbidity in the water body increases abnormally, it indicates that there may be problems such as microbial contamination, organic matter accumulation or inorganic matter precipitation in the water body. By monitoring the changes in turbidity, potential problems in the water environment can be discovered and dealt with in a timely manner to prevent the spread and aggravation of water pollution.

[0137] Turbidity is one of the important parameters of water environment conditions. It can comprehensively reflect the content and characteristics of suspended particles in water and the pollutants they carry. By monitoring and controlling turbidity indicators, the safety and sustainable development of the water environment can be effectively guaranteed.

[0138] Therefore, in this embodiment, based on the water environment monitoring target information and the water environment monitoring system, the measurement results are recorded and analyzed to obtain the incident light angle, illuminance, radiation intensity and other numerical information, change trends and monitoring conditions of the water environment to be monitored. For the monitoring process of meteorological parameter information in the embodiment, please refer to Figure 2 .

[0139] In an optional embodiment, through the continuous operation and data collection of the water environment monitoring system, the key optical parameter change information of the water environment to be detected within a specific time period is comprehensively recorded, so that detailed numerical information of the water environment to be detected in terms of incident light angle, illuminance, radiation intensity, etc. can be quickly obtained. The changing trend of the above parameters and their intrinsic connection with environmental conditions are also deeply revealed, which provides an important basis for the physical properties and ecological processes of the water environment, and also lays a data foundation for the water environment turbidity analysis model.

[0140] According to the data characteristics of the optical parameters and the monitoring situation, a suitable turbidity analysis model is selected, which may include statistical models, physical models, chemical models, etc. The collected data is cleaned, sorted, converted, and processed again to ensure the integrity and consistency of the data, and then the key factors affecting turbidity are extracted as the input variables of the model.

[0141] The above water environment turbidity analysis model satisfies the following relationship:

[0142]

[0143] Among them, K represents the turbidity coefficient of the water environment, δ represents the constant coefficient, I0 represents the incident light intensity, α represents the scattering angle, l represents the maximum length of the light passing through the water body, λ represents the wavelength of the incident light, and w represents the scattered light intensity.

[0144] Among them, the constant coefficient is the product of the incident light wavelength and the particle distribution coefficient, which satisfies the following relationship:

[0145] δ=λω

[0146] The above scattered light intensity satisfies the following relationship:

[0147]

[0148] Among them, w represents the scattered light intensity, τ represents the proportional constant, I0 represents the incident light intensity, n represents the number of particles per unit volume of water, and v represents the unit volume of particles.

[0149] The proportionality constant in light scattering can be used to describe the quantitative relationship between the scattered light intensity and the incident light intensity, the properties of the scattering particles, the medium conditions and other factors. In practical applications, the scattered light intensity is affected by many factors. Therefore, the influence of relevant factors on the results should be fully considered. The introduction of the proportionality constant can reduce errors and improve accuracy.

[0150] Furthermore, in the present embodiment, the analysis method of the turbidity coefficient of the water environment is only an optional condition of the present embodiment. In one or some other embodiments, the analysis method of the turbidity degree of the water body can be optimized according to the actual situation and the prediction target. The method can be optimized for specific water body characteristics and monitoring targets, which can more accurately reflect the turbidity condition of the water body and improve the accuracy of the turbidity measurement results.

[0151] S5. Obtain a comprehensive monitoring report of the water environment through the pH prediction results, turbidity analysis results and the biochemical index evaluation results of the water environment monitoring system, and match the water environment early warning plan according to the comprehensive monitoring report. The specific implementation steps and contents are as follows:

[0152] In this embodiment, the floating water environment monitoring, analysis and early warning process is specifically referred to in Figure 3 .

[0153] The biochemical index evaluation results are obtained based on the water environment monitoring system; the hydrological evaluation results are obtained based on the hydrological parameter information; and the water quality evaluation results are obtained based on the water quality parameter information.

[0154] 1. Obtain biochemical indicator evaluation results based on the water environment monitoring system.

[0155] Based on physical indicators in the water environment monitoring system such as water temperature, transparency, water pressure, etc.; chemical indicators such as pH value, dissolved oxygen, chemical oxygen demand COD, biological oxygen demand BOD, etc. based on biological indicators such as aquatic biodiversity, biological activity, etc., the biochemical indicator evaluation results of the water environment to be monitored are obtained.

[0156] The biochemical indicators in the embodiments mainly refer to COD and BOD, which reflect the content and biodegradability of organic pollutants in water.

[0157] The water environment monitoring system in the embodiment includes comprehensive information for evaluating the water environment, including but not limited to physical, chemical and biological indicators, so as to fully understand the status of the water environment to be monitored. The above physical indicators such as water temperature, transparency and water pressure not only reflect the basic physical properties of the water body, but are also closely related to the living conditions of aquatic organisms and the stability of the ecosystem. Changes in water temperature will affect the metabolic rate and distribution range of aquatic organisms, while a decrease in transparency is often a sign of eutrophication of water bodies and excessive algae growth.

[0158] Chemical indicators, especially pH, dissolved oxygen, chemical oxygen demand (COD) and biological oxygen demand (BOD), are important parameters for assessing the degree of water pollution and self-purification capacity. The pH value determines the direction and rate of chemical reactions in the water, which is crucial to the survival of aquatic organisms. Dissolved oxygen is closely related to the respiration of aquatic organisms, and its low content indicates serious water pollution or an imbalance in the ecosystem. COD and BOD, as the core of biochemical indicators, directly reveal the load and biodegradation potential of organic pollutants in water, and are an important basis for judging the degree of water pollution and formulating treatment measures.

[0159] Biological indicators, such as aquatic biodiversity and biological activity, can directly provide feedback on the health of aquatic ecosystems. The richness of biodiversity reflects the stability and complexity of aquatic ecosystems, and the level of biological activity directly reveals the adaptability and survival status of aquatic organisms to the environment. Biological indicators are more sensitive than physical and chemical indicators and can provide early warning of water pollution and ecosystem degradation.

[0160] COD and BOD are used as key biochemical indicators in the assessment process. COD is an indicator for measuring the total amount of organic pollutants in water bodies, and its value directly reflects the degree of water pollution. BOD further reveals the ease with which organic pollutants are degraded by microorganisms, thereby reflecting the biodegradability and self-purification potential of water bodies. By comprehensively evaluating the values ​​of COD and BOD and their changing trends, we can more accurately judge the pollution status of water bodies, predict pollution trends, and formulate corresponding water environment protection and management measures.

[0161] In addition, it is also necessary to pay attention to the interaction and mutual influence between various indicators. In an optional embodiment, the reduction of dissolved oxygen will inhibit the activity of microorganisms, thereby reducing the degradation rate of BOD; and the excessive reproduction of algae caused by eutrophication of water bodies will consume a large amount of dissolved oxygen and nutrients, further deteriorating water quality. Therefore, in the evaluation process, it is necessary to comprehensively consider the changes in various indicators in order to obtain a more comprehensive and accurate evaluation result.

[0162] Ultimately, the evaluation results of biochemical indicators based on the water environment monitoring system provide strong support for water environment monitoring, protection and management. It not only helps to understand the current status of water bodies, but also predicts future trends, providing an important basis for the formulation of scientific and reasonable environmental protection policies and management measures. At the same time, through the feedback mechanism of monitoring and evaluation results, the water environment monitoring system can be continuously optimized and improved, the accuracy and reliability of the evaluation can be improved, and a strong guarantee can be provided for the sustainable use of water resources and the healthy development of the ecosystem.

[0163] 2. Obtain hydrological assessment results based on hydrological parameter information.

[0164] Hydrological parameter information mainly focuses on the physical characteristics and dynamic changes of water bodies, such as water level, flow velocity, flow, water depth, riverbed morphology, etc. By monitoring and analyzing the above hydrological parameters, hydrological assessment results can be obtained, which is helpful for understanding the flow patterns of water bodies, the availability of water resources, and the risk assessment of natural disasters such as floods and droughts.

[0165] 3. Obtain water quality assessment results based on water quality parameter information.

[0166] Water quality parameter information directly reflects the chemical, physical and biological characteristics of water bodies and is an important basis for evaluating the water environment. By monitoring and analyzing water quality parameters such as dissolved oxygen, COD, total nitrogen, ammonia nitrogen, phosphate, heavy metal concentration, microbial content, etc., water quality assessment results can be obtained, which is helpful to identify the source of pollutants in water bodies, assess the degree of pollution, and formulate corresponding water quality improvement measures.

[0167] The water environment monitoring system in the embodiment is a comprehensive system. Through various monitoring sites and sensors, various data about the water environment are collected in real time or regularly, including but not limited to water temperature, pH value, dissolved oxygen, turbidity, nutrient concentration, etc. Based on the evaluation results of the monitoring system, feedback and comprehensive evaluation can also be provided on the operating status of each monitoring site, data collection quality, data transmission stability, and data integrity. The evaluation results of the water environment monitoring system can ensure the reliability and accuracy of the water environment analysis results.

[0168] The comprehensive use of meteorological parameter information, hydrological parameter information and water quality parameter information in the water environment monitoring system can provide a comprehensive and in-depth understanding of the overall status of the water environment. The multi-dimensional assessment method not only improves the accuracy and reliability of the assessment, but also provides strong information support for subsequent water resources management, protection and early warning.

[0169] Then, the pH prediction value of the water environment is obtained through the water environment pH prediction model; and the turbidity coefficient of the water environment is obtained using the water environment turbidity analysis model.

[0170] In an optional embodiment, a water environment pH prediction model is first used to accurately predict the changes in the pH value of the water body within a specific time in the future, that is, the pH prediction value, which can capture the complex relationship between relevant factors and the pH value of the water body and achieve accurate prediction of the pH value of the water environment.

[0171] Secondly, the turbidity coefficient of the water environment is obtained by using the water environment turbidity analysis model. Through the water environment turbidity analysis model, the turbidity coefficient of the current water body can be accurately calculated to quantify the content of suspended particles in the water. The turbidity analysis model in the embodiment is mainly based on optical principles. The turbidity of the water body is inferred by measuring the attenuation of light when it passes through the water body. In this process, water quality parameters such as suspended particle concentration, particle size distribution, water flow characteristics such as flow rate, flow direction, and possible interference factors such as algae growth, water body color, etc. need to be considered to ensure the accuracy and reliability of the analysis results. The turbidity coefficient can be used to intuitively understand the clarity of the water body, and the degree of water pollution and ecological health can be evaluated accordingly.

[0172] In summary, by comprehensively utilizing the water environment pH prediction model and the water environment turbidity analysis model, comprehensive monitoring and prediction of water pH and turbidity can be achieved, which not only helps to timely discover and solve relevant problems in the water environment, but also provides an important scientific basis for environmental early warning, management and protection.

[0173] Next, a comprehensive monitoring report of the water environment is obtained based on the above-mentioned pH prediction value, turbidity coefficient and the evaluation results of the biochemical indicators of the monitoring system.

[0174] In the embodiment, based on the predicted pH value, turbidity coefficient and the evaluation results of the biochemical indicators of the monitoring system, the water environment conditions are comprehensively analyzed, and a comprehensive monitoring report of the water environment is obtained. The above comprehensive monitoring report is not only a comprehensive reflection of the current state of the water environment, but also a predictive insight into future trends. It deeply analyzes the changing trend of pH value and its possible ecological impact, and explains the pollution status of suspended particulate matter in the water body revealed by the turbidity coefficient and its source analysis. In addition, an objective evaluation of the operating status of the monitoring system is also conducted, which provides a scientific basis for the monitoring and early warning tasks of the water environment, and is conducive to promoting the continuous improvement and sustainable development of the water environment.

[0175] Finally, match the water environment early warning plan based on the above comprehensive monitoring report.

[0176] In this embodiment, a floating water environment monitoring and early warning device also includes a water environment early warning device.

[0177] Based on the above comprehensive water environment monitoring report, the corresponding water environment early warning plan can be accurately matched and implemented to ensure the safety of the water environment, respond to potential threats in a timely manner and effectively protect water resources.

[0178] In an optional embodiment, the data in the comprehensive monitoring report will be compared and analyzed with the preset warning thresholds. The above-mentioned warning thresholds are formulated based on historical data, scientific research and policy standards, and can identify abnormal conditions or potential risks that may exist in the water environment. Once the monitoring data exceeds or approaches the threshold, the water environment warning device in the floating water environment monitoring and early warning device will automatically trigger the warning mechanism, and immediately prompt relevant personnel to start the corresponding warning plan.

[0179] Early warning plans usually include response measures at multiple levels and dimensions. First, early warning information will be quickly issued to relevant departments, institutions and the public to remind relevant personnel to pay attention to the water environment and take necessary preventive measures. Secondly, according to the early warning level and specific circumstances, the corresponding emergency plan will be activated, such as increasing the monitoring frequency, expanding the monitoring scope, and implementing emergency treatment measures. Specific measures include adjusting the water intake depth of the water plant, closing the polluted water intake, cross-regional water diversion to dilute the pollutant concentration, adding coagulants and active adsorption of pollutants, etc. The early warning plan measures can timely control the pollution source, reduce the degree of pollution and protect the ecological environment.

[0180] In addition, the embodiments will also continuously track and evaluate the implementation effect of the early warning plan, continuously optimize and improve the early warning mechanism, and by summarizing lessons learned, adjusting early warning thresholds and improving emergency response capabilities, it can ensure that the floating water environment monitoring and early warning method and device of the present invention can respond to various challenges and risks more efficiently and accurately in future water environment monitoring.

[0181] In the embodiment, the water environment early warning plan is matched based on the comprehensive monitoring report, and the monitoring data and parameter analysis results are fully utilized. Warning signals can be issued in time through water environment early warning equipment, and response measures can be effectively implemented, which helps to maintain ecological balance and promote the sustainable development of the water environment.

[0182] Furthermore, the method of water environment monitoring and early warning in the present embodiment is only an optional condition of the present embodiment. In one or some other embodiments, the method of environmental monitoring and early warning can be adjusted according to the actual water environment conditions and early warning needs. Different water bodies such as rivers, lakes, reservoirs, oceans, etc. face different challenges and risks. Therefore, adjusting monitoring indicators, early warning thresholds and response strategies according to specific circumstances can improve the pertinence and effectiveness of early warning and response, and can further enhance the ability and level of water environment monitoring and early warning.

[0183] See also Figure 4In an optional embodiment, in order to efficiently execute the floating water environment monitoring and early warning method provided by the present invention, the present invention also provides a floating water environment monitoring and early warning device, the device includes a monitoring device, a processor, an output device, an early warning device and a memory, the monitoring device, the processor, the output device, the early warning device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, the processor is configured to call the program instructions, and execute the specific steps of the relevant embodiments of the floating water environment monitoring and early warning method provided by the present invention. The floating water environment monitoring and early warning device of the present invention has a complete structure, objective stability, and can efficiently execute the floating water environment monitoring and early warning method of the present invention, thereby improving the overall applicability and practical application ability of the present invention.

[0184] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A floating water environment monitoring and early warning method, characterized in that: The steps include: Using a floating water environment monitoring and early warning device to obtain initial water environment monitoring information, and optimizing the initial water environment monitoring information to obtain water environment monitoring target information; Establishing a water environment monitoring system based on the water environment monitoring target information; Establish water environment monitoring system based on water environment monitoring target information and water environment monitoring system Predictive model and obtain water environment The prediction results; Construct a water environment turbidity analysis model based on water environment monitoring target information and water environment monitoring system, and obtain the analysis results of water environment turbidity; pass The prediction results, turbidity analysis results and the evaluation results of the water environment monitoring system are used to obtain a comprehensive monitoring report of the water environment, and a water environment early warning plan is matched according to the comprehensive monitoring report; The optimizing the initial water environment monitoring information to obtain the water environment monitoring target information includes: Establishing a time series-data optimization model based on the initial water environment monitoring information; Optimizing the initial water environment monitoring information using the time series-data optimization model to obtain water environment monitoring target information; The time series-data optimization model satisfies the following relationship: ， in, After optimization The data matrix of time points, represents the state transfer matrix, express The data matrix state variables at the time points, express The gain of the input data at a time point, express Input data at a time point, express The noise driving matrix at a time point, express White noise information during the time point data input process; The water environment monitoring target information and water environment monitoring system are used to establish a water environment Predictive models include: The water environment The prediction model satisfies the following relationship: ， in, Represents water environment Predicted value, Indicates the standard water quality sample value, is the Faraday constant, Represents the electromotive force of the measured water environment, represents the electromotive force of the standard water sample, is the gas constant, Indicates the absolute temperature of the water environment; The water environment turbidity analysis model constructed according to the water environment monitoring target information and the water environment monitoring system includes: The water environment turbidity analysis model satisfies the following relationship: ， in, Indicates the turbidity coefficient of the water environment, represents a constant coefficient, represents the incident light intensity, represents the scattering angle, represents the maximum length of light passing through the water body, is the wavelength of incident light, Indicates the intensity of scattered light.

2. The floating water environment monitoring and early warning method according to claim 1 is characterized in that: The floating water environment monitoring and early warning method also includes: The floating water environment monitoring and early warning method sets the monitoring frequency, arranges the monitoring sites and adjusts the monitoring instruments based on the floating water environment monitoring and early warning device and the water environment conditions.

3. The floating water environment monitoring and early warning method according to claim 1 is characterized in that: The water environment monitoring system established based on the water environment monitoring target information includes: Obtaining water environment parameter information according to the water environment monitoring target information, wherein the water environment parameter information includes hydrological parameter information and water quality parameter information of the water environment; A water environment monitoring system is established based on the hydrological parameter information and the water quality parameter information.

4. The floating water environment monitoring and early warning method according to claim 3 is characterized in that: The floating water environment monitoring and early warning method also includes: The biochemical index evaluation results are obtained according to the water environment monitoring system.

5. The floating water environment monitoring and early warning method according to claim 4 is characterized in that: The floating water environment monitoring and early warning method also includes: Through the water environment The prediction model obtains the water environment Predicted value; Obtaining the turbidity coefficient of the water environment using the water environment turbidity analysis model; Based on the The predicted value, the turbidity coefficient and the biochemical index evaluation results are used to obtain a comprehensive monitoring report of the water environment; Match the water environment early warning plan according to the comprehensive monitoring report.

6. A floating water environment monitoring and early warning device, characterized in that: The device includes a monitoring device, a processor, an output device, an early warning device and a memory, wherein the monitoring device, the processor, the output device, the early warning device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the floating water environment monitoring and early warning method according to any one of claims 1 to 5.

Images