Evaluation method based on water ecological environment monitoring

Abstract

The invention discloses an evaluation method based on water ecological environment monitoring, and relates to the technical field of water ecological environment evaluation. Comprising the steps of data collection: obtaining a river basic information data set, a monitoring equipment information data set and a historical monitoring information data set, and building a cloud server to store the river basic information data set, the monitoring equipment information data set and the historical monitoring information data set. According to the method, each region is accurately monitored through region division of river landforms and a targeted monitoring method, the timeliness of monitoring data is ensured, the water quality condition can be evaluated in real time and the water quality of the corresponding region under unique weather can be evaluated by acquiring a region monitoring data set and a weather information data set in real time to cooperate with an evaluation model, and the water quality evaluation accuracy is improved. In addition, weather changes can be monitored and early warned, timely support is provided for dealing with emergencies, and by summarizing the method, related departments can formulate more reasonable treatment schemes, the water quality management efficiency and effect are improved, and the water quality problem is found and solved in time.

Description

Technical Field

[0001] The present invention relates to the technical field of water ecological environment assessment, and in particular to an assessment method based on water ecological environment monitoring. Background Art

[0002] Water ecology refers to the impact of environmental water factors on organisms and the adaptation of organisms to various water conditions. Life originated in water, and water is an important component of all living things. Organisms continuously exchange water with the environment. The quality and quantity of water in the environment are important factors that determine the distribution of organisms, species composition and quantity, and lifestyle.

[0003] A water ecological environment assessment system with patent publication number CN114330858A can perform data and statistical standardization, and then compare it with historical data through a comparison model to obtain the assessment results of the water ecological environment. The assessment results and historical data can also be used to predict environmental changes in the future. It not only achieves environmental assessment, but also environmental prediction, bringing more scientific and intelligent assessment results to ecological assessment.

[0004] However, the above-mentioned technology and similar technologies focus on the demarcation and reclassification of sampling areas, and compare them with historical data through comparative models to obtain the assessment results of the water ecological environment. If the sampling area of ​​the river is photographed by remote sensing technology, the collected data will have a certain time difference due to the long river area, which will ultimately lead to inaccurate assessment results. Therefore, this type of technology cannot be applied to scenes with long river waters and large differences in conditions in various river areas, and it is difficult to accurately assess the river water quality. Summary of the invention

[0005] The purpose of the present invention is to provide an evaluation method based on water ecological environment monitoring to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: an evaluation method based on water ecological environment monitoring, the method comprising:

[0007] Data collection: Obtain river basic information data set, monitoring equipment information data set and historical monitoring information data set, and build a cloud server to store the river basic information data set, monitoring equipment information data set and historical monitoring information data set. The river basic information data set includes a topographic data set, a geological data set, a hydrological data set, an ecological data set and a river vector data set. The historical monitoring information data set includes a pollution source data set;

[0008] Regional division monitoring: Based on the river basic information data set, the river landform is divided into regions according to the regional division method to obtain the river regional information data set, and basic monitoring equipment is laid in each region based on the river regional information data set, and corresponding monitoring equipment is laid in each region according to the targeted monitoring method to obtain the regional monitoring data set, which includes the real-time regional monitoring data set and the historical regional monitoring data set;

[0009] Weather monitoring: Based on the river area information data set, meteorological monitoring stations are set up in various regions to obtain weather information data sets, and monitor and warn the weather in various regions. The weather information data sets include real-time weather information data sets and historical weather information data sets;

[0010] Model creation: establishing an evaluation model based on the monitoring information dataset, the weather information dataset and the regional monitoring dataset, wherein the evaluation model is used to evaluate the water quality of each region;

[0011] Monitoring and evaluation: Based on the regional division of rivers and the cooperation of targeted monitoring methods, conventional areas and key areas in each region can be accurately monitored to ensure the accuracy of regional monitoring data sets and regional evaluations. Meteorological monitoring stations in each region can accurately obtain the weather in each region, and can timely use real-time weather information data sets in conjunction with evaluation models to evaluate the water quality of the corresponding region, so as to make accurate decisions;

[0012] The method for creating the evaluation model includes:

[0013] S1: Data integration and standardization: preprocessing and integration based on historical monitoring information datasets, weather information datasets and regional monitoring datasets, and standardizing the historical monitoring information datasets, weather information datasets and regional monitoring datasets to obtain standard data, and dividing the standard data into training set, validation set and test set;

[0014] S2: Feature extraction and model selection: feature extraction is performed based on the training set, and a random forest model is selected based on the training set for training to obtain an initial model;

[0015] S3: Model training, optimization and update. The evaluation model is obtained based on the initial model training and optimization, and the evaluation model is updated regularly.

[0016] Furthermore, the area division method includes:

[0017] A1: Identification of topographic and geomorphic types: based on the topographic and geomorphic dataset, terrain parameters are calculated through DEM data in ArcGIS, and different landform types are identified accordingly;

[0018] A2: Identification of geological structure and lithology distribution: Based on the geological dataset, the spatial analysis and symbolization functions in ArcGIS are used to identify the main geological structures and lithology distribution along the river.

[0019] A3: Identification of rapid and slow flow areas: Based on the hydrological dataset, the rapid and slow flow areas are identified through the hydrological analysis toolset of ArcGIS;

[0020] A4: Ecological type regional division: Different ecological type regions are divided based on ecological data sets through NDVI calculation tools and cluster analysis calculation tools in ArcGIS;

[0021] A5: Pollution risk area division: Based on the pollution source dataset, the distribution and pollution degree of pollution sources are determined through ArcGIS symbolization, spatial query, statistical and reclassification tools, and pollution risk areas are divided;

[0022] A6: Construction of river area information dataset: Integrate the contents of A1 to A5 through ArcGIS and draw the river ArcGIS map, finally divide the upstream, midstream and downstream areas of the river, determine the key areas, ecological type areas and pollution risk areas in each area, and obtain the river area information dataset.

[0023] Furthermore, the river ArcGIS map creation method includes:

[0024] B1: Import and prepare basic data: import the river basic information dataset, monitoring equipment information dataset and historical monitoring information dataset into ArcGIS, establish a projection coordinate system and match it with the river vector dataset to obtain the basis of the map;

[0025] B2: Overlay analysis and preliminary map drawing: Using the overlay analysis function of ArcGIS, the results of the content analysis in A1 to A5 are overlaid and integrated to obtain the analysis results, and the boundaries are drawn in ArcGIS based on the analysis results to obtain a preliminary map;

[0026] B3: Map annotation, optimization and visualization: annotation and optimization are performed based on the preliminary map, and the preliminary map is visualized through ArcGIS symbolization tools to finally obtain the river ArcGIS map;

[0027] B4: Map export and storage, based on the river ArcGIS map is exported to the required format and stored in the cloud server.

[0028] Furthermore, the targeted monitoring method includes:

[0029] C1: First-level classification, based on the analysis of topographic and geomorphic data sets and geological data sets, key areas, environmental risk areas and groundwater pollution areas are screened out, and first-level monitoring points are set up for key areas, environmental risk areas and groundwater pollution areas respectively;

[0030] C2: Secondary classification: based on the analysis of hydrological data sets, rapid flow areas, slow flow areas and areas with complex hydrological conditions are screened out, and secondary monitoring points are set up for rapid flow areas, slow flow areas and areas with complex hydrological conditions respectively;

[0031] C3: Three-level classification, based on the analysis of ecological data sets, ecologically sensitive areas and ecologically diverse areas are screened out, and three-level monitoring points are set for the decibels in ecologically sensitive areas and ecologically diverse areas;

[0032] C4: Four-level classification, based on the analysis of pollution source data sets, the factory emission areas and pollution risk areas are screened out, and four-level monitoring points are set for the factory emission areas and pollution risk areas;

[0033] C5: Monitoring point marking: marking the first-level monitoring points, second-level monitoring points, third-level monitoring points and fourth-level monitoring points to distinguish the areas corresponding to the same-level monitoring points;

[0034] C6: Configuration of monitoring equipment and parameters. Based on the marked first-level monitoring points, second-level monitoring points, third-level monitoring points and fourth-level monitoring points, set the corresponding monitoring equipment, corresponding monitoring parameters and monitoring frequency respectively.

[0035] Furthermore, the targeted monitoring method also includes:

[0036] D1: Specific monitoring: based on the pollution risk area, the monitoring items and monitoring frequency of specific pollutants can be increased;

[0037] D2: Threshold setting: Set corresponding preset thresholds for each water quality monitoring data and meteorological parameter in each region based on the regional monitoring data set, weather information data set and historical monitoring information data set, and formulate emergency response plans based on the preset thresholds and the changing trends of the regional monitoring data set.

[0038] Furthermore, the training, optimization and updating methods of the evaluation model include:

[0039] Y1: Model evaluation: Use the validation set to evaluate the trained initial model and obtain the evaluation results. The evaluation results are used to analyze the performance of the model and identify possible problems and improvements.

[0040] Y2: Model optimization, optimize the model based on the evaluation results, and tune the parameters through the grid search method;

[0041] Y3: Model verification, using the test set to verify the optimized model to ensure the generalization ability of the model on unknown data;

[0042] Y4: Model update: regularly update the evaluation model and use incremental learning methods to update the model in real time.

[0043] Furthermore, the laying method of the basic monitoring equipment is:

[0044] T1: Monitoring equipment selection: determine the monitoring needs of each area based on the river area information data set, and select basic monitoring equipment based on the monitoring needs;

[0045] T2: Determine the number of equipment, based on the monitoring range of the basic monitoring equipment and the river area information data set and topographic and geomorphic data set;

[0046] T3: Determine the laying location, based on the historical monitoring information dataset and the river basic information dataset, determine the laying location of the basic monitoring equipment.

[0047] Furthermore, the multiple basic monitoring devices and the multiple corresponding monitoring devices in each area of ​​the river area information data set and the meteorological monitoring stations set up in each area are connected to the cloud server through a private local area network. The method for creating the private local area network is as follows:

[0048] C1: Information acquisition, obtaining basic network information of basic monitoring equipment, corresponding monitoring equipment, meteorological monitoring stations and cloud servers, the basic network information including equipment IP;

[0049] C2: Device connection, the cloud server automatically allocates communication channels to match the IP of the basic monitoring device, the IP of the corresponding monitoring device and the IP of the meteorological monitoring station with the IP of the cloud server;

[0050] C3: Configure the network. The cloud server configures the corresponding network services and security measures for the communication channel to create a private LAN.

[0051] Furthermore, the basic monitoring equipment and corresponding monitoring equipment include floating water quality online monitoring stations, water quality sensors, river and lake water level monitors, river and lake flow rate monitors, pipe network water quality monitors and pollution source monitoring equipment.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] Through the regional division of river landforms and targeted monitoring methods, accurate monitoring is implemented in each area to ensure the timeliness of monitoring data. By real-time acquisition of regional monitoring data sets and weather information data sets in conjunction with evaluation models, water quality conditions and corresponding regional water quality assessments under unique weather conditions can be evaluated in real time. Weather changes can also be monitored and warned to provide timely support for responding to emergencies. The above summary will help relevant departments to formulate more reasonable governance plans, improve the efficiency and effectiveness of water quality management, promptly discover and solve water quality problems, and provide strong guarantees for the sustainable use of water resources and the sustainable development of the ecological environment.

[0054] Through comprehensive analysis of topography, geological structure, hydrological characteristics, ecological types and pollution risks, the river area can be divided into fine divisions, which is helpful to formulate differentiated monitoring and governance strategies for different types of regions, and improve the efficiency and pertinence of water resources management and water environment governance. The creation of ArcGIS maps provides an intuitive visual expression tool for river ecological environment monitoring and evaluation, and integrates river basic information datasets, monitoring equipment information datasets and historical monitoring information datasets in ArcGIS maps to facilitate unified data management, query and analysis. ArcGIS maps can be dynamically updated according to real-time monitoring data to reflect the real-time status of the river ecological environment, which helps to promptly discover and deal with potential problems and provide real-time and accurate decision-making support for water resources management and water environment governance.

[0055] Through targeted monitoring methods, we can accurately identify key areas, risk areas, areas with complex hydrological conditions, ecological sensitivity and diversity, and pollution sources in rivers. By grading and configuring monitoring points, we can optimize the configuration of monitoring equipment and parameters to ensure the accuracy and reliability of monitoring data. We can also reasonably allocate monitoring resources and improve resource utilization efficiency based on the characteristics and needs of different regions. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a schematic diagram of the principle structure of the present invention;

[0057] Figure 2 It is a schematic diagram of the principle structure of the area division method of the present invention;

[0058] Figure 3 This is a schematic diagram of the principle structure of the evaluation model of the present invention:

[0059] Figure 4 It is a structural schematic diagram of a floating type water quality online monitoring station of the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] The assessment of the existing water ecological environment requires the collection of various monitoring data of a certain section of water, and the accuracy and comprehensiveness of each monitoring data must be ensured. The present invention collects comprehensive data sets such as river basic data, monitoring equipment information and historical monitoring information to ensure the real-time and traceability of the data, divide the river into regions and conduct targeted monitoring, achieve precise regional monitoring, and obtain accurate and comprehensive monitoring data. Finally, combined with weather data, the assessment model can be used to evaluate the water quality of each region in real time, providing strong support for decision-making. When evaluating the river water quality through this method, a stable network environment and power supply are required to ensure real-time transmission of data and continuous operation of the equipment. In terms of operation, the device requires the operator to have certain data processing and analysis capabilities in order to accurately interpret the monitoring data and make corresponding decisions. At the same time, the operator must strictly abide by the safety operating procedures to ensure the safe operation of the equipment.

[0062] like Figure 1-Figure 4 As shown, the present invention provides a technical solution: an evaluation method based on water ecological environment monitoring, the method comprising:

[0063] Data collection: Obtain river basic information data sets, monitoring equipment information data sets and historical monitoring information data sets, and build a cloud server to store river basic information data sets, monitoring equipment information data sets and historical monitoring information data sets. The river basic information data sets include topographic data sets, geological data sets, hydrological data sets, ecological data sets and river vector data sets. The historical monitoring information data sets include pollution source data sets;

[0064] It should be noted that the monitoring equipment information data set includes "Basic equipment information: equipment name / model / manufacturer information / equipment serial number / unique identifier / installation location (latitude and longitude or other geographical identifiers), technical parameters: monitoring range / capability (such as temperature range, pressure range, etc.) / resolution / accuracy (such as the accuracy of the measured value) / sampling frequency / cycle (such as collecting data once per second, every minute or every hour), working status information: current working status (such as online, offline, fault, etc.) / last maintenance / calibration date / battery / power status, data interface information: data transmission method (such as wired, wireless, 4G / 5G, Wi-Fi, etc.) / data format (such as JSON, XML, CS V, etc.) / data access rights / security settings", the historical monitoring information dataset also includes "environmental parameter dataset: air quality parameters (such as PM2.5, PM10, O3, NO2, SO2, etc.) / water quality parameters (such as pH value, dissolved oxygen, turbidity, heavy metal content, etc.) / soil parameters (such as soil moisture, temperature, salinity, pH value, etc.), meteorological parameter dataset: temperature / humidity / air pressure / wind speed / wind direction / precipitation, snowfall, radiation, etc., biological parameter dataset (if ecological monitoring is involved): biodiversity indicators / number / distribution of specific species / ecosystem health indicators, other related datasets: historical concentration / distribution of specific pollutants (such as specific chemicals, heavy metals, etc.)".

[0065] Regional division monitoring: Based on the river basic information data set, the river landform is divided into regions according to the regional division method to obtain the river regional information data set, and basic monitoring equipment is laid in each region based on the river regional information data set, and corresponding monitoring equipment is laid in each region according to the targeted monitoring method to obtain the regional monitoring data set. The regional monitoring data set includes real-time regional monitoring data set and historical regional monitoring data set;

[0066] Weather monitoring: Based on the river area information data set, meteorological monitoring stations are set up in various regions to obtain weather information data sets, and monitor and warn the weather in various regions. The weather information data sets include real-time weather information data sets and historical weather information data sets;

[0067] It should be noted that the meteorological monitoring stations need to monitor the following: Temperature: measuring air temperature to understand climate change trends and weather forecasts; Humidity: measuring air humidity, which has an important impact on climate and weather forecasts; Air pressure: measuring the pressure of the atmosphere on a unit area, which is one of the important indicators of meteorological changes; Wind speed and direction: measuring wind speed and direction, which is crucial for climate research and weather forecasts; Precipitation, monitoring and warning of extreme weather events.

[0068] Model creation: An evaluation model is established based on the monitoring information dataset, weather information dataset, and regional monitoring dataset. The evaluation model is used to evaluate the water quality of each region.

[0069] Monitoring and evaluation: Based on the regional division of rivers and the cooperation of targeted monitoring methods, conventional areas and key areas in each region can be accurately monitored to ensure the accuracy of regional monitoring data sets and regional evaluations. Meteorological monitoring stations in each region can accurately obtain the weather in each region, and can timely use real-time weather information data sets in conjunction with evaluation models to evaluate the water quality of the corresponding region, so as to make accurate decisions;

[0070] It should be noted that river basic information datasets, monitoring equipment information datasets and historical monitoring information datasets can be collected in a variety of ways, including but not limited to on-site surveys, public data sources, government reports, data sharing by research institutions, etc. The construction of cloud servers can utilize existing cloud service providers. The establishment of meteorological monitoring stations can draw on the existing meteorological monitoring network layout principles and be optimized in combination with the specific characteristics of the river area. Accurate monitoring may rely on high-precision sensors and instruments, as well as regular on-site sampling and analysis. Weather data can be used as an input parameter and updated in real time to the assessment model to dynamically adjust the water quality assessment results. Decision support may be based on real-time water quality assessment and weather data, through preset rules or algorithms. The method can be used to automatically generate response strategies and suggestions (a series of thresholds for water quality parameters and weather parameters can be set. When the real-time regional monitoring dataset and the real-time weather information dataset exceed or fall below these thresholds, specific response strategies or suggestions will be triggered. Different response strategies can also be generated according to different input conditions (such as water quality parameters, weather parameters, etc.) through decision trees or a series of predefined rules. These rules can be based on expert experience, historical cases or data analysis. Finally, different weather and water quality scenarios can be simulated by adjusting the real-time regional monitoring dataset and the real-time weather information dataset in conjunction with the evaluation model, and the potential impact of each scenario can be evaluated. Based on the simulation results, response strategies and suggestions for different scenarios can be generated).

[0071] like Figure 3 As shown, the method for creating an evaluation model includes: S1: data integration and standardization, preprocessing and integration based on historical monitoring information datasets, weather information datasets and regional monitoring datasets, and standardizing the historical monitoring information datasets, weather information datasets and regional monitoring datasets to obtain standard data, and dividing the standard data into training set, validation set and test set, S2: feature extraction and model selection, feature extraction based on the training set, and selecting a random forest model based on the training set for training to obtain an initial model, S3: model training, optimization and updating, obtaining an evaluation model based on the initial model training and optimization, and regularly updating the evaluation model.

[0072] It should be noted that missing value processing: check the missing values ​​in the historical monitoring information dataset, weather information dataset and regional monitoring dataset, and fill them according to the actual situation (such as using the mean, median, mode, or interpolation method); outlier processing: identify and process outliers in the dataset, and identify outliers by setting thresholds, IQR (interquartile range) methods or methods based on statistical distribution, and perform appropriate processing (such as deletion, replacement or scaling to the normal range); data cleaning: remove duplicate data, irrelevant data or erroneous data, and sort the historical monitoring information dataset, weather information dataset and regional monitoring dataset according to certain rules (such as time). The merged data set is standardized using the Z-score standardization method, that is, the value of each feature is scaled to a uniform range (such as between 0 and 1) to eliminate the differences between different features due to different dimensions or units. The training set is used to train the model, the validation set is used to adjust the model parameters and prevent overfitting, and the test set is used to evaluate the performance of the model. The features related to the evaluation target are extracted from the training set through statistical analysis methods. Random forest is an ensemble learning method based on decision trees. It improves the stability and accuracy of the model by constructing multiple decision trees and integrating their prediction results.

[0073] like Figure 2 As shown in the figure, the regional division method includes: A1: identification of topographic and geomorphic types. Based on the topographic and geomorphic dataset, the terrain parameters are calculated through the DEM data in ArcGIS, and different landform types are identified accordingly. A2: identification of geological structure and lithology distribution. Based on the geological dataset, the spatial analysis function and symbolization function in ArcGIS are used to identify the main geological structure and lithology distribution along the river. A3: identification of rapid and slow flow areas. Based on the hydrological dataset, the hydrological analysis toolset in ArcGIS is used to identify the rapid and slow flow areas. A4: regional division of ecological types. Based on the ecological dataset, the ND in ArcGIS is used to identify the main geological structures and lithology distribution along the river. VI calculation tools and cluster analysis calculation tools are used to divide different ecological type areas. A5: Pollution risk area division. Based on the pollution source dataset, the distribution and pollution degree of pollution sources are determined through ArcGIS's symbolization function, spatial query function, statistical function and reclassification tool to divide the pollution risk areas. A6: River area information dataset construction. The contents of A1 to A5 are integrated through ArcGIS, and the river ArcGIS map is drawn. Finally, the upstream, midstream and downstream areas of the river are divided, and the key areas, ecological type areas and pollution risk areas in each area are determined to obtain the river area information dataset.

[0074] It should be noted that ArcGIS software is used to load DEM (digital elevation model) data, and terrain parameters are calculated through terrain analysis tools in ArcGIS, such as slope analysis and elevation analysis. Based on the calculated terrain parameters, such as slope and elevation, different landform types (such as mountains, hills, plains, etc.) are identified by setting thresholds or using classification algorithms. Geological datasets are imported into ArcGIS, including geological exploration data and stratigraphic data. ArcGIS spatial analysis functions, such as overlay analysis and buffer zone analysis, are used to identify the main geological structures along the river (such as faults and folds). Different lithologies are visualized using symbolization functions to facilitate identification of lithology distribution. Hydrological datasets are imported into ArcGIS, including flow velocity, water depth and other data. The hydrological analysis toolset of ArcGIS, such as flow direction analysis and flow accumulation, is used to identify rapids and slow-flow areas based on hydrological data. Rapids and slow-flow areas are defined by setting thresholds for flow velocity or hydraulic gradient. Ecological datasets are imported, including vegetation type, biodiversity and other data. The NDVI (Normalized Difference Vegetation Index) calculation tool in ArcGIS is used to analyze vegetation coverage. Combined with cluster analysis calculation tools (such as K-means clustering), the area is divided into different ecological types (such as forests, wetlands, grasslands, etc.) according to ecological data. The pollution source dataset, including industrial emissions, agricultural emissions and other data, is loaded in ArcGIS. The pollution sources are visualized using the symbolization function to facilitate observation of distribution. The distribution density and pollution degree of pollution sources are analyzed using spatial query and statistical functions. The pollution risk is divided into different levels through the reclassification tool to determine the pollution risk area. The integration function of ArcGIS is used to overlay and integrate the various regional information identified in steps A1 to A5. The upstream, midstream and downstream areas of the river are clearly marked on the ArcGIS map through drawing and editing functions. The key areas (such as terrain change points, important ecological areas, etc.), ecological type areas and pollution risk areas in each area are determined. Finally, the integrated river area information dataset is exported, which may include maps, tables or reports.

[0075] The river ArcGIS map creation method includes: B1: basic data import and preparation, importing the river basic information dataset, monitoring equipment information dataset and historical monitoring information dataset into ArcGIS, establishing a projection coordinate system and matching the river vector dataset to obtain the basis of the map, B2: overlay analysis and preliminary map drawing, using the overlay analysis function of ArcGIS in ArcGIS, overlaying and integrating the results of the content analysis in A1 to A5 to obtain the analysis results, and drawing the boundaries in ArcGIS based on the analysis results to obtain a preliminary map, B3: map annotation, optimization and visualization, annotating and optimizing the preliminary map, and realizing the visualization expression of the preliminary map through the symbolization tool of ArcGIS, and finally obtaining the river ArcGIS map, B4: map export and storage, exporting the river ArcGIS map to the required format and storing it in the cloud server.

[0076] It should be noted that to import the river basic information dataset, monitoring equipment information dataset and historical monitoring information dataset into ArcGIS, you can create a new folder through ArcCatalog, create a new dataset in it, and then import the required layer data to view the coordinate information of the layer. By using the Define Projection tool in ArcToolbox to define the projection for the layer, the river vector data is imported into the ArcGIS map. As the basis of the map, the overlay analysis function of ArcGIS is used to overlay and integrate the results obtained in steps A1 to A5. The results of the overlay analysis are integrated to obtain the final analysis result layer. Based on the analysis result layer, the boundaries of various river areas are drawn in ArcGIS to obtain a preliminary map. Necessary annotations are made to the preliminary map, such as river name, geographic coordinates, monitoring sites, etc. The map is adjusted and optimized in color, line, font and other styles as needed to improve the readability and aesthetics of the map. The symbolization tools of ArcGIS (such as Unique Values, Classified, etc.) to visualize the map to make it more intuitive and easy to understand. In ArcGIS, select the "File" menu, click the "Export Map" option, select the desired export format (such as JPEG, PDF, SVG, etc.), and set related parameters (such as resolution, page margins, etc.). Click the "Save" button to export the map to a file in the specified format, and store the exported map file in the cloud server for subsequent use or sharing.

[0077] Targeted monitoring methods include: C1: primary classification, based on the analysis of topographic and geomorphic data sets and geological data sets, key areas, environmental risk areas and groundwater pollution areas are screened out, and primary monitoring points are set up for key areas, environmental risk areas and groundwater pollution areas respectively; C2: secondary classification, based on the analysis of hydrological data sets, rapid flow areas, slow flow areas and areas with complex hydrological conditions are screened out, and secondary monitoring points are set up for rapid flow areas, slow flow areas and areas with complex hydrological conditions respectively; C3: tertiary classification, based on the analysis of ecological data sets, ecologically sensitive areas and ecologically diverse areas are screened out, and ecologically sensitive areas are screened out. C4: Four-level classification, based on the analysis of the pollution source data set, screen out the factory emission areas and pollution risk areas, and set up four-level monitoring points for the factory emission areas and pollution risk areas. C5: Monitoring point marking, mark the first-level monitoring points, second-level monitoring points, third-level monitoring points and fourth-level monitoring points to distinguish the areas corresponding to the same level of monitoring points. C6: Configuration of monitoring equipment and parameters, based on the marked first-level monitoring points, second-level monitoring points, third-level monitoring points and fourth-level monitoring points, set the corresponding monitoring equipment, corresponding monitoring parameters and monitoring frequencies.

[0078] It should be noted that the spatial analysis function of ArcGIS is used to analyze and screen the various areas of C1-C4, and the annotation function of ArcGIS is used to annotate the primary, secondary, tertiary and quaternary monitoring points. The annotation information is used to clearly distinguish the areas corresponding to the monitoring points of the same level. Based on the annotated monitoring points, according to the characteristics and monitoring needs of each area, appropriate monitoring equipment is selected, and corresponding monitoring parameters and monitoring frequencies are configured for each monitoring point to ensure the accuracy and timeliness of the monitoring data.

[0079] The targeted monitoring method also includes, D1: specific monitoring, based on the pollution risk area, the monitoring items and monitoring frequency of specific pollutants can be increased, D2: threshold setting, based on the regional monitoring data set, weather information data set and historical monitoring information data set, corresponding preset thresholds are set for each water quality monitoring data and meteorological parameter in each region, and emergency response plans are formulated based on the preset thresholds and the changing trends of the regional monitoring data set.

[0080] It should be noted that based on the characteristics and potential risks of pollution risk areas, specific pollutants that require special attention are identified. These specific pollutants may include heavy metals, toxic chemicals, radioactive substances, etc. For the identified specific pollutants, corresponding monitoring items are added and a higher monitoring frequency is set to ensure that changes in pollutants can be detected in a timely manner and responded to in a timely manner. According to the nature of specific pollutants, appropriate monitoring technologies are selected. For example, for some pollutants that are difficult to measure directly, the bioindicator method is used to integrate regional monitoring data sets, weather information data sets and historical monitoring information data sets. These data sets can provide information on water quality, meteorological conditions, historical pollution events, etc. Based on data analysis and expert judgment, corresponding preset thresholds are set for each water quality monitoring data and meteorological parameters in each region. These thresholds should be able to reflect changes in water quality and meteorological conditions. The setting of thresholds can be based on comprehensive consideration of historical data, environmental standards, expert opinions and other factors. The regional monitoring data set is evaluated in real time to check whether any data exceeds the preset threshold. This can be achieved through regular manual inspections. Based on the preset thresholds and the changing trends of the regional monitoring data set, an emergency response plan is formulated. The plan should clearly state the emergency measures and response procedures to be taken when the monitoring data exceeds the threshold. The emergency response plan may include emergency closure of pollution sources, activation of temporary treatment facilities, notification of relevant departments and the public, and evacuation of residents in affected areas. With the continuous accumulation and updating of monitoring data and changes in environmental conditions, the emergency response plan also needs to be updated and optimized accordingly. The effectiveness and applicability of the plan are regularly evaluated, and it is revised and improved according to actual conditions and expert advice to ensure its pertinence and effectiveness.

[0081] The training, optimization and update methods of the evaluation model include: Y1: Model evaluation, using the validation set to evaluate the trained initial model to obtain the evaluation results. The evaluation results are used to analyze the performance of the model and find out possible problems and improvements. Y2: Model optimization, optimizing the model based on the evaluation results, and tuning the parameters through the grid search method. Y3: Model verification, using the test set to verify the optimized model to ensure the generalization ability of the model on unknown data. Y4: Model update, regularly update the evaluation model, and use the incremental learning method to update the model in real time.

[0082] It should be noted that feature extraction is performed based on the training set, and features that have an important impact on water quality assessment are selected. The trained initial model is evaluated using the validation set. The accuracy is calculated to measure the proportion of correct predictions of the model as a whole, the recall is calculated to measure the ability of the model to find positive examples (such as water quality exceeding the standard), the precision is calculated to measure the proportion of samples predicted by the model as positive examples that are truly positive examples, and the F1 score is calculated to comprehensively evaluate the performance of the model. Definition of accuracy: Accuracy is the ratio of the number of samples correctly classified by the model to the total number of samples. The formula is: Accuracy = (TP + TN) / (TP + TN +FP + FN), where TP is a true positive example, TN is a true negative example, FP is a false positive example, and FN is a false negative example. Definition of recall: Recall is the ratio of the number of samples correctly predicted by the model as positive examples to the number of samples that are actually positive examples. The formula is: Recall = TP / (TP + FN), recall reflects the sensitivity of the model to positive examples, precision definition: precision is the proportion of samples predicted by the model as positive examples that are actually positive examples, formula: Precision = TP / (TP + FP), precision reflects the reliability of the model's prediction of positive examples, F1 score definition: F1 score is the harmonic mean of precision and recall, which is used to balance the importance of precision and recall, formula: F1 = 2 (Precision Recall) / (Precision + Recall), use grid search or random search methods to explore different parameter combinations, for each set of parameters, use the training set to retrain the model, and use the validation set to evaluate its performance, record the evaluation indicators of each set of parameters, and select the parameter combination with the best performance, use the optimized model to predict the test set, and calculate the accuracy, recall, precision and F1 score indicators based on the prediction results and actual labels. By comparing with the performance on the validation set, verify the generalization ability of the model on unknown data. After collecting new data, use the incremental learning method to update the model, use a part of the new data or an independent validation set to verify the performance of the updated model, calculate the accuracy, recall, precision and F1 score indicators, and compare them with the model performance before the update.

[0083] Laying method of basic monitoring equipment: T1: Monitoring equipment selection, determine the monitoring needs of each area based on the river area information data set, and select basic monitoring equipment based on the monitoring needs. T2: Equipment quantity determination, determine the quantity of basic monitoring equipment based on the monitoring range of the basic monitoring equipment and the river area information data set and the topography data set. T3: Laying location determination, determine the laying location of the basic monitoring equipment based on the historical monitoring information data set and the river basic information data set.

[0084] It should be noted that the length, width, flow, water quality, hydrological characteristics, etc. of the rivers in the river regional information dataset are analyzed to determine the monitoring needs of each area, such as the water quality parameters that need to be monitored (such as dissolved oxygen, pH value, turbidity, etc.), water level changes, flow rate, etc. According to the monitoring needs, appropriate basic monitoring equipment is selected, such as water quality monitors, water level meters, flow meters, etc., the monitoring range of basic monitoring equipment is studied, the monitoring area that each device can cover is understood, the complementarity and overlap between equipment are considered, and monitoring is ensured to have no blind spots. Based on the river regional information dataset, each area is ensured to be fully monitored, and the area, shape, monitoring needs and monitoring range of each area are determined according to the equipment. The scope of the project should be calculated, the number of basic monitoring equipment required should be calculated, historical monitoring information data sets should be analyzed, the hydrological changes and water quality conditions of the river at different times and locations should be understood, areas or key monitoring points prone to problems should be identified, and basic river information data sets should be studied, including the direction, tributaries, curvature, and riverbed morphology of the river, and factors such as flow characteristics and riverbed stability should be considered to determine the appropriate laying location. Before actual laying, on-site surveys should be conducted to understand the actual situation, and the laying location should be adjusted according to the survey results to ensure the best monitoring effect of the equipment. According to the monitoring results and actual needs, the layout and number of monitoring equipment should be continuously optimized to ensure that the monitoring network can cover the entire river area and meet the monitoring needs.

[0085] Multiple basic monitoring devices and multiple corresponding monitoring devices in each area of ​​the river area information data set and the meteorological monitoring stations established in each area are connected to the cloud server through a private LAN. The method for creating a private LAN is as follows: C1: Information acquisition, obtaining basic networking information of basic monitoring devices, corresponding monitoring devices, meteorological monitoring stations and cloud servers. The basic networking information includes device IP. C2: Device connection. The cloud server automatically allocates communication channels to match the IP of basic monitoring devices, the IP of corresponding monitoring devices and the IP of meteorological monitoring stations with the IP of cloud servers. C3: Network configuration. The cloud server configures corresponding network services and security measures for the communication channel to create a private LAN.

[0086] It is important to install and configure firewalls on cloud servers, restrict unauthorized access to the LAN, and monitor network traffic to detect and block potential attacks. Use authentication mechanisms such as usernames and passwords, fingerprints, or smart cards to ensure that only authorized users can log in and use LAN resources. Assign each user the minimum necessary permissions to prevent users from abusing permissions or accessing unauthorized resources. Use encryption technologies such as TLS / SSL during data transmission to ensure data confidentiality and integrity. Enable the security logging function, and monitor and analyze logs to promptly discover and respond to potential security incidents. Regularly back up key data and configuration information within the LAN to prevent data loss or damage. For key devices on cloud servers and LANs, take physical security measures, such as setting up secure areas, installing anti-theft locks and cameras, to prevent equipment from being stolen or damaged.

[0087] like Figure 4 As shown, the basic monitoring equipment and corresponding monitoring equipment include floating water quality online monitoring stations, water quality sensors, river and lake water level monitors, river and lake flow rate monitors, pipe network water quality monitors and pollution source monitoring equipment.

[0088] It should be noted that there are monitoring equipment for specific pollutants, such as heavy metal monitors, toxic organic matter monitors, etc. Floating water quality online monitoring stations can monitor various water quality indicators in real time, such as pH value, dissolved oxygen, turbidity, conductivity, ammonia nitrogen, total phosphorus, total nitrogen, etc. Water quality sensors are used to monitor specific parameters of water bodies, such as water temperature, conductivity, pH value, etc., to provide key data for water quality assessment, River and lake water level monitor: using small beam angle long-range millimeter wave radar ranging technology and built-in temperature compensation mechanism to achieve real-time and accurate monitoring of water levels of rivers, lakes, reservoirs, etc. River and lake flow rate monitor: with the help of high-precision FMCW millimeter wave radar detection technology, it can realize all-weather monitoring of core parameters such as river and lake water level and flow rate. Pipeline network water quality monitor: provides flexible and changeable multi-parameter indicator monitoring options to track and monitor key environmental quality indicators in real time.

[0089] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is limited by the attached embodiments and their equivalents.

Claims

1. An assessment method based on water ecological environment monitoring, characterized in that: The method comprises: Data collection: Obtain river basic information data set, monitoring equipment information data set and historical monitoring information data set, and build a cloud server to store the river basic information data set, monitoring equipment information data set and historical monitoring information data set. The river basic information data set includes a topographic data set, a geological data set, a hydrological data set, an ecological data set and a river vector data set. The historical monitoring information data set includes a pollution source data set; Regional division monitoring: Based on the river basic information data set, the river landform is divided into regions according to the regional division method to obtain the river regional information data set, and basic monitoring equipment is laid in each region based on the river regional information data set, and corresponding monitoring equipment is laid in each region according to the targeted monitoring method to obtain the regional monitoring data set, which includes the real-time regional monitoring data set and the historical regional monitoring data set; Weather monitoring: Based on the river area information data set, meteorological monitoring stations are set up in various regions to obtain weather information data sets, and monitor and warn the weather in various regions. The weather information data sets include real-time weather information data sets and historical weather information data sets; Model creation: Establish an evaluation model based on historical monitoring information data sets, weather information data sets and regional monitoring data sets, and the evaluation model is used to evaluate the water quality of each region; Monitoring and evaluation: Based on the regional division of rivers and the cooperation of targeted monitoring methods, conventional areas and key areas in each region can be accurately monitored to ensure the accuracy of regional monitoring data sets and regional evaluations. Meteorological monitoring stations in each region can accurately obtain the weather in each region, and can timely use real-time weather information data sets in conjunction with evaluation models to evaluate the water quality of the corresponding region, so as to make accurate decisions; The method for creating the evaluation model includes: S1: Data integration and standardization: preprocessing and integration based on historical monitoring information datasets, weather information datasets and regional monitoring datasets, and standardizing the historical monitoring information datasets, weather information datasets and regional monitoring datasets to obtain standard data, and dividing the standard data into training set, validation set and test set; S2: Feature extraction and model selection: feature extraction is performed based on the training set, and a random forest model is selected based on the training set for training to obtain an initial model; S3: Model training, optimization and update. The evaluation model is obtained based on the initial model training and optimization, and the evaluation model is updated regularly.

2. The evaluation method based on water ecological environment monitoring according to claim 1 is characterized in that: The regional division method includes: A1: Identification of topographic and geomorphic types: based on the topographic and geomorphic dataset, terrain parameters are calculated through DEM data in ArcGIS, and different landform types are identified accordingly; A2: Identification of geological structure and lithology distribution: Based on the geological dataset, the spatial analysis and symbolization functions in ArcGIS are used to identify the main geological structures and lithology distribution along the river. A3: Identification of rapid and slow flow areas: Based on the hydrological dataset, the rapid and slow flow areas are identified through the hydrological analysis toolset of ArcGIS; A4: Ecological type regional division: Different ecological type regions are divided based on ecological data sets through NDVI calculation tools and cluster analysis calculation tools in ArcGIS; A5: Pollution risk area division: Based on the pollution source dataset, the distribution and pollution degree of pollution sources are determined through ArcGIS symbolization, spatial query, statistical and reclassification tools, and pollution risk areas are divided; A6: Construction of river area information dataset: Integrate the contents of A1 to A5 through ArcGIS and draw the river ArcGIS map, finally divide the upstream, midstream and downstream areas of the river, determine the key areas, ecological type areas and pollution risk areas in each area, and obtain the river area information dataset.

3. The evaluation method based on water ecological environment monitoring according to claim 2 is characterized in that: The river ArcGIS map creation method includes: B1: Import and prepare basic data: import the river basic information dataset, monitoring equipment information dataset and historical monitoring information dataset into ArcGIS, establish a projection coordinate system and match it with the river vector dataset to obtain the basis of the map; B2: Overlay analysis and preliminary map drawing: Using the overlay analysis function of ArcGIS, the results of the content analysis in A1 to A5 are overlaid and integrated to obtain the analysis results, and the boundaries are drawn in ArcGIS based on the analysis results to obtain a preliminary map; B3: Map annotation, optimization and visualization: annotation and optimization are performed based on the preliminary map, and the preliminary map is visualized through ArcGIS symbolization tools to finally obtain the river ArcGIS map; B4: Map export and storage, based on the river ArcGIS map is exported to the required format and stored in the cloud server.

4. The evaluation method based on water ecological environment monitoring according to claim 1 is characterized in that: The targeted monitoring approach includes: C1: First-level classification, based on the analysis of topographic and geomorphic data sets and geological data sets, key areas, environmental risk areas and groundwater pollution areas are screened out, and first-level monitoring points are set up for key areas, environmental risk areas and groundwater pollution areas respectively; C2: Secondary classification: based on the analysis of hydrological data sets, rapid flow areas, slow flow areas and areas with complex hydrological conditions are screened out, and secondary monitoring points are set up for rapid flow areas, slow flow areas and areas with complex hydrological conditions respectively; C3: Three-level classification, based on the analysis of ecological data sets, ecologically sensitive areas and ecologically diverse areas are screened out, and three-level monitoring points are set for the decibels in ecologically sensitive areas and ecologically diverse areas; C4: Four-level classification, based on the analysis of pollution source data sets, the factory emission areas and pollution risk areas are screened out, and four-level monitoring points are set for the factory emission areas and pollution risk areas; C5: Monitoring point marking: marking the first-level monitoring points, second-level monitoring points, third-level monitoring points and fourth-level monitoring points to distinguish the areas corresponding to the same-level monitoring points; C6: Configuration of monitoring equipment and parameters. Based on the marked first-level monitoring points, second-level monitoring points, third-level monitoring points and fourth-level monitoring points, set the corresponding monitoring equipment, corresponding monitoring parameters and monitoring frequency respectively.

5. The evaluation method based on water ecological environment monitoring according to claim 4 is characterized in that: The targeted monitoring approach also includes: D1: Specific monitoring: based on the pollution risk area, the monitoring items and monitoring frequency of specific pollutants can be increased; D2: Threshold setting: Set corresponding preset thresholds for each water quality monitoring data and meteorological parameter in each region based on the regional monitoring data set, weather information data set and historical monitoring information data set, and formulate emergency response plans based on the preset thresholds and the changing trends of the regional monitoring data set.

6. The evaluation method based on water ecological environment monitoring according to claim 1 is characterized in that: The training, optimization and updating methods of the evaluation model include: Y1: Model evaluation: Use the validation set to evaluate the trained initial model and obtain the evaluation results. The evaluation results are used to analyze the performance of the model and identify possible problems and improvements. Y2: Model optimization, optimize the model based on the evaluation results, and tune the parameters through the grid search method; Y3: Model verification, using the test set to verify the optimized model to ensure the generalization ability of the model on unknown data; Y4: Model update: regularly update the evaluation model and use incremental learning methods to update the model in real time.

7. The evaluation method based on water ecological environment monitoring according to claim 1 is characterized in that: The laying method of the basic monitoring equipment: T1: Monitoring equipment selection: determine the monitoring needs of each area based on the river area information data set, and select basic monitoring equipment based on the monitoring needs; T2: Determine the number of equipment, based on the monitoring range of the basic monitoring equipment and the river area information data set and topographic and geomorphic data set; T3: Determine the laying location, based on the historical monitoring information dataset and the river basic information dataset, determine the laying location of the basic monitoring equipment.

8. The evaluation method based on water ecological environment monitoring according to claim 1 is characterized in that: The multiple basic monitoring devices and multiple corresponding monitoring devices in each area of ​​the river area information data set and the meteorological monitoring stations set up in each area are connected to the cloud server through a private local area network. The method for creating the private local area network is as follows: C1: Information acquisition, obtaining basic network information of basic monitoring equipment, corresponding monitoring equipment, meteorological monitoring stations and cloud servers, the basic network information including equipment IP; C2: Device connection, the cloud server automatically allocates communication channels to match the IP of the basic monitoring device, the IP of the corresponding monitoring device and the IP of the meteorological monitoring station with the IP of the cloud server; C3: Configure the network. The cloud server configures the corresponding network services and security measures for the communication channel to create a private LAN.

9. The evaluation method based on water ecological environment monitoring according to claim 1 is characterized in that: The basic monitoring equipment and corresponding monitoring equipment include floating water quality online monitoring stations, water quality sensors, river and lake water level monitors, river and lake flow rate monitors, pipe network water quality monitors and pollution source monitoring equipment.

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