A method for monitoring pond water environment and biological community

Abstract

This invention provides a method for monitoring the aquatic environment and biological community of a pond, relating to the field of environmental monitoring technology. The method includes: determining the corresponding key water quality monitoring parameter types based on the real-time monitoring needs of the target pond; collecting the key water quality monitoring parameters of the target pond to obtain a first water quality parameter; determining a biological community sampling plan based on the real-time monitoring needs of the target pond; collecting samples to obtain a first sample; performing parameter analysis on the first water quality parameter, thereby visualizing the parameters based on the analysis results to obtain the real-time water quality trend of the target pond; simultaneously, performing sample analysis on the first sample to evaluate the analysis results and predict the biological community assessment results of the target pond; and comprehensively judging the monitoring optimization measures for the target pond based on the real-time water quality trend and the biological community assessment results, and performing dynamic optimization. This method enables more timely and accurate environmental monitoring of the target pond, thereby allowing for more precise management and protection.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring technology, and in particular to a method for monitoring the water environment and biological community of a pond. Background Technology

[0002] Currently, pond aquaculture, as an important aquaculture method, plays a vital role in ensuring food supply and promoting rural economic development. However, due to the limited self-purification capacity of pond water, pollutants such as feed residue and fish metabolites gradually accumulate, leading to water quality deterioration and affecting the survival of aquatic organisms and the profitability of aquaculture.

[0003] However, traditional monitoring methods are often limited to a single water quality indicator or biological species, making it difficult to fully reflect the true state of the pond's aquatic environment and biological community.

[0004] Therefore, the present invention provides a method for monitoring pond water environment and biological community. Summary of the Invention

[0005] This invention provides a method for monitoring pond aquatic environment and biological community. By monitoring water quality and biological community in real time, it can accurately acquire data and perform visual analysis to accurately assess the ecological status of the pond. Then, it can formulate precise and optimized monitoring measures and dynamically optimize them, effectively improving the management efficiency and protection level of the pond ecological environment, and ensuring the continuous stability of water quality and the healthy development of biological community.

[0006] This invention provides a method for monitoring pond aquatic environment and biological communities, including:

[0007] Step 1: Based on the real-time monitoring requirements of the target pond, determine the corresponding key water quality monitoring parameter types, thereby collecting key water quality monitoring parameters of the target pond in real time and processing the parameters to obtain the first water quality parameter;

[0008] Step 2: Determine the corresponding biological community sampling plan based on the real-time monitoring requirements of the target pond, and collect samples based on the biological community sampling plan to obtain the first sample.

[0009] Step 3: Perform parameter analysis on the first water quality parameter, visualize the parameter based on the parameter analysis results, obtain the real-time water quality trend of the target pond, and at the same time, perform sample analysis on the first collected sample to evaluate the analysis results, obtain the sample evaluation results of the target pond, and predict the biological community evaluation results of the target pond.

[0010] Step 4: Based on real-time water quality trends and biological community assessment results, comprehensively determine the monitoring and optimization measures for the target pond and carry out dynamic optimization.

[0011] The method for obtaining the first water quality parameter according to the present invention includes:

[0012] Step 11: Determine the real-time monitoring requirements of the target pond based on historical water quality data and external environmental factors, and then determine the types of key water quality parameters that need to be monitored in real time based on the real-time monitoring requirements;

[0013] Step 12: Collect key water quality monitoring parameters corresponding to the key water quality parameter types based on preset monitoring equipment;

[0014] Step 13: Perform data cleaning and standardization on key water quality monitoring parameters to obtain the first water quality parameters of the target pond.

[0015] According to the biological community-based sampling scheme provided by the present invention, a first sample is obtained by sampling, including:

[0016] Step 21: Develop a biological community sampling plan based on the historical biological community characteristics of the target pond, external environmental factors, and the real-time monitoring requirements of the target pond;

[0017] Step 22: Collect biological samples in the target pond based on the biological community sampling scheme to obtain the first sample.

[0018] The first sample provided by the present invention includes: plankton, benthic animals, and aquatic plants.

[0019] The method for obtaining real-time water quality trends of a target pond according to the present invention includes:

[0020] Step 31: Perform descriptive statistics on the first water quality parameter based on preset statistical tools to obtain the distribution of water quality parameters in the target pond;

[0021] Step 32: Obtain the first water quality parameter of the target pond at each moment in the current period, and obtain the water quality change curve of the target pond in the current period based on the time series;

[0022] Step 33: Obtain the average water quality parameters of the target pond in the previous period, and input the average water quality parameters into the water quality change curve of the current period to obtain the first water quality change curve of the target pond;

[0023] Step 34: Based on the preset correlation technology, analyze the parameter correlation between different water quality parameters in the first water quality parameter, and obtain the comprehensive parameter correlation matrix of the first water quality parameter based on the parameter correlation of different water quality parameters;

[0024] Step 35: Obtain the monitoring and analysis objectives for the target pond, and determine the corresponding visualization scheme based on the monitoring and analysis objectives;

[0025] Step 36: Adjust the initial visualization tool based on the visualization scheme, and input the first water quality change curve and the comprehensive parameter correlation matrix into the adjusted initial visualization tool to obtain the parameter visualization results of the target pond;

[0026] Step 37: Based on the parameter visualization results, comprehensively determine the real-time water quality trend corresponding to different water quality parameters of the target pond.

[0027] According to the present invention, the method for predicting the biological community assessment results of a target pond based on the sample assessment results of the target pond includes:

[0028] Step 01: Based on the preset technology, perform a first analysis on the biological species and quantity in the first collected sample to obtain the first evaluation result of the first collected sample;

[0029] Step 02: Determine the biomass of organisms contained in the first sample based on the preset measurement technology, and obtain the second evaluation result of the first sample by combining the collection area information of the first sample.

[0030] Step 03: Combine the first evaluation result and the second evaluation result to determine the sample evaluation result of the first collected sample. Based on the information of the collection area corresponding to the first collected sample and the area information of the target pond, combined with the sample evaluation result, make a comprehensive prediction of the biological community of the target pond to obtain the biological community evaluation result of the target pond.

[0031] According to the present invention, a comprehensive prediction of the biological community of a target pond is made based on the information of the collection area corresponding to the first collected sample and the regional information of the target pond, combined with the sample evaluation results, to obtain the biological community evaluation result of the target pond, including:

[0032] Step 031: Obtain the collection area information corresponding to the first sample and the area information of the target pond, and extract the first area volume from the collection area information and the second area volume from the area information of the target pond;

[0033] Step 032: Based on the ratio of the volume of the first region to the volume of the second region, and combined with the sample evaluation results of the first collected sample, a prediction is made to obtain the initial biological community evaluation results of the target pond.

[0034] Step 033: Optimize the initial biological community assessment results based on the seasonal cycle community change trend of the target pond and the real-time season of the target pond to obtain the first biological community assessment result.

[0035] Step 034: Compare the first biological community assessment results with the historical biological community assessment results of the target pond to obtain the community change trend of the biological community in the target pond;

[0036] Step 035: Based on the community change trend and the community prediction model, predict the biological community of the target pond, and optimize the first biological community assessment result based on the prediction result to obtain the biological community assessment result of the target pond.

[0037] According to the monitoring and optimization measures for target ponds based on real-time water quality trends and biological community assessment results provided by the present invention, dynamic optimization is performed, including:

[0038] Step 41: Combine real-time water quality trends and biological community assessment results to comprehensively judge the ecological environment status of the target pond;

[0039] Step 42: Based on the ecological environment status of the target pond, select monitoring optimization measures that match the current ecological environment status from the preset pond monitoring optimization database to obtain the first optimization measure;

[0040] Step 43: Combine the first optimization measures with the first water quality parameters of the target pond and the sample evaluation results to determine the monitoring optimization measures for the target pond;

[0041] Step 44: Based on monitoring and optimization measures, dynamically optimize the corresponding area of ​​the target pond, and monitor the real-time water quality and biological community of the target pond in real time, so as to adjust the optimization measures in a timely manner and achieve dynamic optimization and continuous improvement of the target pond.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention provides a method for monitoring pond water environment and biological community, which accurately acquires data and performs visualization analysis by real-time monitoring of water quality and biological community, accurately assesses the ecological status of pond, and then formulates precise and optimized monitoring measures and dynamically optimizes them, effectively improving the management efficiency and protection level of pond ecological environment, and ensuring the continuous stability of water quality and the healthy development of biological community. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0044] Figure 1 This is a flowchart of a method for monitoring pond water environment and biological community provided in an embodiment of the present invention. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0046] Example 1:

[0047] This invention provides a method for monitoring pond aquatic environment and biological communities, such as... Figure 1 As shown, it includes:

[0048] Step 1: Based on the real-time monitoring requirements of the target pond, determine the corresponding key water quality monitoring parameter types, thereby collecting key water quality monitoring parameters of the target pond in real time and processing the parameters to obtain the first water quality parameter;

[0049] Step 2: Determine the corresponding biological community sampling plan based on the real-time monitoring requirements of the target pond, and collect samples based on the biological community sampling plan to obtain the first sample.

[0050] Step 3: Perform parameter analysis on the first water quality parameter, visualize the parameter based on the parameter analysis results, obtain the real-time water quality trend of the target pond, and at the same time, perform sample analysis on the first collected sample to evaluate the analysis results, obtain the sample evaluation results of the target pond, and predict the biological community evaluation results of the target pond.

[0051] Step 4: Based on real-time water quality trends and biological community assessment results, comprehensively determine the monitoring and optimization measures for the target pond and carry out dynamic optimization.

[0052] In this embodiment, the target pond refers to the specific pond for which water quality and biological community monitoring are required.

[0053] In this embodiment, the real-time monitoring requirement is based on factors such as the species and density of aquaculture in the pond, historical water quality, geographical location, and climate conditions, to determine the key water quality parameters and biological community characteristics that need to be monitored.

[0054] In this embodiment, the key water quality monitoring parameter type refers to parameters that have a significant impact on the pond water quality, such as dissolved oxygen, pH value, water temperature, turbidity, ammonia nitrogen, nitrite, total phosphorus, and total nitrogen.

[0055] In this embodiment, the first water quality parameter refers to water quality parameter data collected by real-time monitoring equipment and preliminarily processed.

[0056] In this embodiment, the biological community sampling scheme is a scheme designed to collect biological samples of plankton, benthic organisms and aquatic plants in a pond based on real-time monitoring requirements. It includes sampling location, sampling time, sampling frequency and sampling method.

[0057] In this embodiment, the first sample collected refers to the biological sample collected according to the biological community sampling scheme, which is used for subsequent biological community analysis.

[0058] In this embodiment, parameter analysis involves statistical analysis, trend analysis, and anomaly detection of the first water quality parameter to reveal the changing patterns of water quality.

[0059] In this embodiment, parameter visualization is to visually display the results of parameter analysis in the form of charts, images, etc., so as to facilitate understanding and analysis.

[0060] In this embodiment, the real-time water quality trend is the trend of pond water quality changing over time, derived from the results of parameter analysis.

[0061] In this embodiment, sample analysis involves identifying species, counting quantities, and calculating diversity indices in the first collected sample to assess the condition of the biological community.

[0062] In this embodiment, the sample evaluation results are based on the biological community status assessment results obtained from sample analysis, including species composition, quantity distribution, diversity level, etc.

[0063] In this embodiment, the biological community assessment results are an assessment of the overall condition of the pond biological community based on the sample assessment results, including ecological health status, presence or absence of pollution indicator species, etc.

[0064] In this embodiment, the monitoring and optimization measures are measures formulated based on real-time water quality trends and biological community assessment results to improve pond water quality and biological community conditions, such as adjusting stocking density, optimizing feed formulation, adding aeration equipment, and carrying out ecological restoration.

[0065] In this embodiment, dynamic optimization involves continuously adjusting and optimizing the monitoring scheme, sampling scheme, and optimization measures based on real-time monitoring data and evaluation results to adapt to changes in pond water quality and biological community conditions.

[0066] The beneficial effects of the above technical solution are: by real-time monitoring of water quality and biological communities, accurate data acquisition and visualization analysis can be performed to accurately assess the ecological status of the pond, thereby formulating precise and optimized monitoring measures and dynamically optimizing them, effectively improving the management efficiency and protection level of the pond's ecological environment, and ensuring the continuous stability of water quality and the healthy development of the biological community.

[0067] Example 2:

[0068] Based on Example 1, the first water quality parameters are obtained, including:

[0069] Step 11: Determine the real-time monitoring requirements of the target pond based on historical water quality data and external environmental factors, and then determine the types of key water quality parameters that need to be monitored in real time based on the real-time monitoring requirements;

[0070] Step 12: Collect key water quality monitoring parameters corresponding to the key water quality parameter types based on preset monitoring equipment;

[0071] Step 13: Perform data cleaning and standardization on key water quality monitoring parameters to obtain the first water quality parameters of the target pond.

[0072] In this embodiment, the target pond refers to the specific pond that needs to be monitored in real time, and it is usually selected based on factors such as aquaculture needs, geographical location, and environmental conditions.

[0073] In this embodiment, historical water quality data refers to water quality parameter data recorded in the target pond over a period of time. This data helps to understand the long-term trend of water quality changes and potential problems in the pond.

[0074] In this embodiment, external environmental factors are external conditions that affect the pond water quality, such as climate conditions (temperature, rainfall), geographical location (soil type, water source), and human activities (breeding density, feed input).

[0075] In this embodiment, the real-time monitoring requirement is determined based on historical water quality data and external environmental factors, focusing on the current and future water quality monitoring priorities of the target pond to ensure water quality safety and optimize aquaculture management.

[0076] In this embodiment, the key water quality parameter type refers to the parameter category that has a significant impact on the pond water quality, such as dissolved oxygen, pH value, water temperature, ammonia nitrogen, nitrite, total phosphorus, and total nitrogen. These parameters can reflect the quality of the water and potential risks.

[0077] In this embodiment, the preset monitoring equipment refers to water quality monitoring devices pre-installed and configured in the target pond for real-time collection of water quality parameter data. These devices may include sensors, analyzers, etc., capable of automatically or manually collecting water quality data.

[0078] In this embodiment, the key water quality monitoring parameter refers to the specific water quality parameter value corresponding to the key water quality parameter type, which reflects the current status of the pond water quality.

[0079] In this embodiment, data cleaning involves processing the collected key water quality monitoring parameters to remove outliers, duplicates, missing values, etc., to ensure the accuracy and integrity of the data.

[0080] In this embodiment, data standardization processing involves converting the cleaned data into a unified standard format to facilitate subsequent data analysis and comparison. Standardization processing may include operations such as data normalization and data transformation.

[0081] In this embodiment, the first water quality parameter is a key water quality parameter value obtained after data cleaning and standardization. These parameter values ​​reflect the standardized and accurate state of the target pond's water quality, providing basic data for subsequent water quality analysis and optimization management.

[0082] The beneficial effects of the above technical solution are: by determining the types of key water quality monitoring parameters, collecting parameters, and processing parameters, the determined primary water quality parameters can be made more accurate and standardized, thereby making the water quality analysis and optimization management of the target pond more precise and efficient.

[0083] Example 3:

[0084] Based on Example 2, the first sample was obtained, including:

[0085] Step 21: Develop a biological community sampling plan based on the historical biological community characteristics of the target pond, external environmental factors, and the real-time monitoring requirements of the target pond;

[0086] Step 22: Collect biological samples in the target pond based on the biological community sampling scheme to obtain the first sample.

[0087] In this embodiment, the target pond refers to the specific pond for which biological community monitoring is required, and its biological community characteristics may vary depending on factors such as the species being farmed, the ecological environment, and historical changes.

[0088] In this embodiment, historical biological community characteristics refer to the characteristics of the biological community composition, quantity, distribution, and diversity recorded in the target pond over a period of time. These characteristics help to understand the long-term changing trends and potential problems of the biological community.

[0089] In this embodiment, external environmental factors are external conditions that also affect the pond's biological community, such as climate conditions (temperature, light, rainfall), geographical location (soil type, water source), and human activities (aquaculture management, drug use), etc.

[0090] In this embodiment, the real-time monitoring requirement is based on historical biological community characteristics and external environmental factors, combined with goals such as aquaculture management and ecological protection, to determine the current and future biological community monitoring focus of the target pond.

[0091] In this embodiment, the biological community sampling plan is formulated based on real-time monitoring requirements and is used to guide the specific plan for collecting biological samples in the target pond, including sampling location, sampling time, sampling method, sampling frequency, etc.

[0092] In this embodiment, biological sample collection is the process of collecting biological samples such as plankton, benthic organisms, and aquatic plants from the target pond according to a biological community sampling plan. Collection methods may include netting, trawls, and water filtration.

[0093] In this embodiment, the first sample is a collection of biological samples obtained through a biological sample collection process, used for subsequent biological community analysis. This includes plankton, benthic animals, and aquatic plants, used to assess the composition, quantity, distribution, and diversity of the biological community.

[0094] The beneficial effects of the above technical solution are: by combining the real-time monitoring requirements to determine the biological community sampling scheme, the determined collected samples can better meet the real-time monitoring needs of the pond, more accurately reflect the status of the pond's biological community, and thus obtain more precise optimization management measures for dynamic optimization.

[0095] Example 4:

[0096] Based on Example 3, the first sample collected included: plankton, benthic animals, and aquatic plants.

[0097] Example 5:

[0098] Based on Example 3, the real-time water quality trend of the target pond is obtained, including:

[0099] Step 31: Perform descriptive statistics on the first water quality parameter based on preset statistical tools to obtain the distribution of water quality parameters in the target pond;

[0100] Step 32: Obtain the first water quality parameter of the target pond at each moment in the current period, and obtain the water quality change curve of the target pond in the current period based on the time series;

[0101] Step 33: Obtain the average water quality parameters of the target pond in the previous period, and input the average water quality parameters into the water quality change curve of the current period to obtain the first water quality change curve of the target pond;

[0102] Step 34: Based on the preset correlation technology, analyze the parameter correlation between different water quality parameters in the first water quality parameter, and obtain the comprehensive parameter correlation matrix of the first water quality parameter based on the parameter correlation of different water quality parameters;

[0103] Step 35: Obtain the monitoring and analysis objectives for the target pond, and determine the corresponding visualization scheme based on the monitoring and analysis objectives;

[0104] Step 36: Adjust the initial visualization tool based on the visualization scheme, and input the first water quality change curve and the comprehensive parameter correlation matrix into the adjusted initial visualization tool to obtain the parameter visualization results of the target pond;

[0105] Step 37: Based on the parameter visualization results, comprehensively determine the real-time water quality trend corresponding to different water quality parameters of the target pond.

[0106] In this embodiment, the preset statistical tools refer to the statistical software or tools, such as SPSS, R language, Excel, etc., that are selected or installed in advance for data analysis, and are used to perform descriptive statistical analysis on water quality parameters.

[0107] In this embodiment, the first water quality parameter refers to the key water quality parameter value obtained after data cleaning and standardization.

[0108] In this embodiment, descriptive statistics is a data analysis method used to summarize and generalize the main characteristics of data, such as mean, median, mode, standard deviation, maximum value, minimum value, etc., so as to obtain the distribution of water quality parameters.

[0109] In this embodiment, the water quality parameter distribution refers to the distribution of the first water quality parameter in the target pond, reflecting the central tendency, dispersion, and distribution pattern of the water quality parameter.

[0110] In this embodiment, the current period refers to a specific time period for monitoring the water quality of the target pond, such as one day, one week, or one month.

[0111] In this embodiment, the water quality change curve is a time series curve formed by connecting the water quality parameter values ​​of the target pond at each moment in the current period, which is used to intuitively show the trend of water quality parameters changing over time.

[0112] In this embodiment, the average water quality parameter of the previous period refers to the average value of each water quality parameter of the target pond in the previous monitoring period, which is used to compare with the water quality changes in the current period.

[0113] In this embodiment, the first water quality change curve is formed by adding the average water quality parameters of the previous period to the water quality change curve of the current period, thus creating a water quality change curve that includes historical comparison information.

[0114] In this embodiment, the preset correlation technique refers to a statistical method or algorithm used to analyze the correlation between variables, such as Pearson correlation coefficient, Spearman rank correlation coefficient, etc.

[0115] In this embodiment, parameter correlation refers to the degree of correlation between different water quality parameters, reflecting their mutual influence and association.

[0116] In this embodiment, the comprehensive parameter correlation matrix is ​​a two-dimensional table, where rows and columns represent different water quality parameters, and the values ​​in the table represent the correlation coefficients between the corresponding parameters, which is used to comprehensively display the correlation between water quality parameters.

[0117] In this embodiment, the purpose of monitoring and analysis refers to the specific goals or needs of water quality monitoring and analysis, such as assessing water quality status, identifying potential problems, and optimizing aquaculture management.

[0118] In this embodiment, the visualization scheme is a data visualization method and strategy determined according to the monitoring and analysis objectives, used to present complex data information in an intuitive and easy-to-understand way.

[0119] In this embodiment, the initial visualization tool refers to software or platforms used for data visualization, such as Tableau, Power BI, ECharts, etc.

[0120] In this embodiment, the parameter visualization results are based on a visualization scheme. Information such as the first water quality change curve and the comprehensive parameter correlation matrix are input into the adjusted visualization tool to generate charts or reports that intuitively display the changes and correlations of water quality parameters.

[0121] In this embodiment, the real-time water quality trend is based on the parameter visualization results. The real-time change trend of different water quality parameters in the target pond is comprehensively analyzed and judged, such as rising, falling, or stabilizing, so as to provide a basis for subsequent water quality management and optimization.

[0122] The beneficial effects of the above technical solution are: by performing parameter analysis on the first water quality parameter and combining it with parameter correlation for comprehensive analysis, the analysis results can be visualized, making the water quality analysis of the target pond more accurate and enabling personalized result visualization, so that the target users can manage the pond water quality more accurately and in a timely manner.

[0123] Example 6:

[0124] Based on Example 5, the predicted biological community assessment results for the target pond include:

[0125] Step 01: Based on the preset technology, perform a first analysis on the biological species and quantity in the first collected sample to obtain the first evaluation result of the first collected sample;

[0126] Step 02: Determine the biomass of organisms contained in the first sample based on the preset measurement technology, and obtain the second evaluation result of the first sample by combining the collection area information of the first sample.

[0127] Step 03: Combine the first evaluation result and the second evaluation result to determine the sample evaluation result of the first collected sample. Based on the information of the collection area corresponding to the first collected sample and the area information of the target pond, combined with the sample evaluation result, make a comprehensive prediction of the biological community of the target pond to obtain the biological community evaluation result of the target pond.

[0128] In this embodiment, the preset technology refers to the specialized techniques or methods used for biological species and quantity analysis, which may include microscopic observation, DNA sequencing, flow cytometry, etc. These techniques can identify and count the species and quantity of organisms in a sample.

[0129] In this embodiment, the first sample collected refers to a biological sample collected from the target pond according to a preset plan, which is used for subsequent biological community analysis.

[0130] In this embodiment, the first analysis is a preliminary analysis of the first collected sample, the purpose of which is to determine the species and quantity of organisms in the sample.

[0131] In this embodiment, the first assessment result is based on the first analysis, which is an assessment of the species and quantity of organisms in the first collected sample.

[0132] In this embodiment, the preset measurement technology is a technology or method for measuring biomass, which may include dry weight method, wet weight method, spectral analysis, etc. These technologies can quantify the total mass or biomass of organisms in a sample.

[0133] In this embodiment, biomass refers to the total mass or quantity of all organisms in the sample, which is an important indicator for measuring the size of a biological community.

[0134] In this embodiment, the information about the collection area is specific information about the location of the first sample collection, such as water depth, substrate type, and distance from the shore. This information helps to understand the distribution and characteristics of the biological community.

[0135] In this embodiment, the second evaluation result is a comprehensive evaluation of the first collected sample, combining biomass and collection area information.

[0136] In this embodiment, the sample evaluation result is a comprehensive assessment of the first collected sample, combining the first and second evaluation results. This evaluation result includes information on both the species and quantity of organisms, as well as biomass information.

[0137] In this embodiment, the information on the collection area refers to the specific location of the first sample collection, while the information on the target pond refers to the geographical, ecological, and other characteristics of the entire pond. Combining these two types of information helps to more accurately understand the distribution and characteristics of the biological community throughout the pond.

[0138] In this embodiment, the comprehensive prediction of the biological community is based on the sample evaluation results and regional information, and is a holistic prediction of the biological community of the target pond, including predictions of biological species, quantity, distribution, ecological relationships, etc.

[0139] In this embodiment, the biological community assessment results of the target pond are a comprehensive assessment of the biological community status of the target pond, including information on the composition, structure, and function of the biological community, providing an important basis for subsequent pond management and ecological protection.

[0140] The beneficial effects of the above technical solution are: by analyzing and evaluating the first collected sample and combining it with the regional information of the target pond to comprehensively predict the biological community assessment results of the target pond, the assessment of the biological community of the target pond can be made more accurate.

[0141] Example 7:

[0142] Based on Example 6, the biological community assessment results of the target pond were obtained, including:

[0143] Step 031: Obtain the collection area information corresponding to the first sample and the area information of the target pond, and extract the first area volume from the collection area information and the second area volume from the area information of the target pond;

[0144] Step 032: Based on the ratio of the volume of the first region to the volume of the second region, and combined with the sample evaluation results of the first collected sample, a prediction is made to obtain the initial biological community evaluation results of the target pond.

[0145] Step 033: Optimize the initial biological community assessment results based on the seasonal cycle community change trend of the target pond and the real-time season of the target pond to obtain the first biological community assessment result.

[0146] Step 034: Compare the first biological community assessment results with the historical biological community assessment results of the target pond to obtain the community change trend of the biological community in the target pond;

[0147] Step 035: Based on the community change trend and the community prediction model, predict the biological community of the target pond, and optimize the first biological community assessment result based on the prediction result to obtain the biological community assessment result of the target pond.

[0148] In this embodiment, the information of the collection area corresponding to the first sample refers to the specific location information recorded when the first sample is collected, which may include water depth, latitude and longitude, substrate type, etc. This information helps to understand the distribution and characteristics of the biological community.

[0149] In this embodiment, the regional information of the target pond is geographical and ecological characteristics of the entire target pond, such as the total area of ​​the pond, water depth distribution, and ecological environment.

[0150] In this embodiment, the volume of the first region is the volume of the region where the first sample is located, calculated based on the information of the collection area. It may be calculated based on parameters such as water depth and area.

[0151] In this embodiment, the volume of the second region is the volume of the entire pond calculated based on the regional information of the target pond.

[0152] In this embodiment, the ratio is the proportional relationship between the volume of the first region and the volume of the second region, used to assess the representativeness of the collected samples in the target pond.

[0153] In this embodiment, the sample evaluation result is a comprehensive assessment of the first collected sample, including information such as species, quantity, and biomass of organisms.

[0154] In this embodiment, the initial biological community assessment result is a preliminary assessment of the target pond biological community based on ratios and sample assessment results.

[0155] In this embodiment, the seasonal periodic community change trend is the regular change trend of the target pond biological community with seasonal changes.

[0156] In this embodiment, optimization is based on seasonal cyclical community change trends and real-time seasons to adjust and improve the initial biological community assessment results in order to improve the accuracy of the assessment.

[0157] In this embodiment, the historical biological community assessment results are the results of past assessments of the biological community of the target pond, which may include data from multiple time points.

[0158] In this embodiment, the community change trend is the trend of the biological community changing over time by comparing the current (first biological community assessment result) and historical biological community assessment results.

[0159] In this embodiment, the community prediction model is a mathematical model or algorithm used to predict the future changing trends of a biological community, which may be constructed based on historical data, environmental factors, etc.

[0160] In this embodiment, the prediction results are the prediction results of the future change trend of the biological community of the target pond using a community prediction model.

[0161] In this embodiment, optimization is based on community change trends and prediction results, further adjusting and improving the first biological community assessment results to ultimately obtain the biological community assessment results for the target pond. This result integrates the current situation, historical trends, and future predictions, providing an important basis for pond management and ecological protection.

[0162] The beneficial effects of the above technical solution are: by analyzing and evaluating the first collected sample, and combining the regional information of the target pond and the seasonal cycle community change trend, the biological community assessment results of the target pond can be predicted more accurately.

[0163] Example 8:

[0164] Based on Example 6, the monitoring and optimization measures for the target pond are dynamically optimized by comprehensively judging the real-time water quality trends and biological community assessment results, including:

[0165] Step 41: Combine real-time water quality trends and biological community assessment results to comprehensively judge the ecological environment status of the target pond;

[0166] Step 42: Based on the ecological environment status of the target pond, select monitoring optimization measures that match the current ecological environment status from the preset pond monitoring optimization database to obtain the first optimization measure;

[0167] Step 43: Combine the first optimization measures with the first water quality parameters of the target pond and the sample evaluation results to determine the monitoring optimization measures for the target pond;

[0168] Step 44: Based on monitoring and optimization measures, dynamically optimize the corresponding area of ​​the target pond, and monitor the real-time water quality and biological community of the target pond in real time, so as to adjust the optimization measures in a timely manner and achieve dynamic optimization and continuous improvement of the target pond.

[0169] In this embodiment, the real-time water quality trend refers to the trend of change of the target pond water quality parameters over time, obtained through continuous monitoring and analysis, reflecting the real-time status of the pond water quality.

[0170] In this embodiment, the biological community assessment result is a comprehensive assessment of the biological community of the target pond, including information such as the species, quantity, distribution, and biomass of organisms, as well as the overall health status and stability of the biological community.

[0171] In this embodiment, the ecological environment status is a comprehensive evaluation of the overall ecological environment of the target pond, based on real-time water quality trends and biological community assessment results, reflecting the overall quality and potential problems of the pond's ecological environment.

[0172] In this embodiment, the preset pond monitoring optimization database is a database that stores a variety of pond monitoring optimization measures. These measures may be designed for different types of ponds, different ecological environment conditions, and different management objectives.

[0173] In this embodiment, the monitoring optimization measures are specific measures aimed at improving the efficiency of pond monitoring and improving the pond's ecological environment. These measures may include adjusting the monitoring frequency, increasing monitoring indicators, and optimizing sampling locations.

[0174] In this embodiment, the first optimization measure is the monitoring optimization measure that best matches the current ecological environment status of the target pond, selected from a preset pond monitoring optimization database.

[0175] In this embodiment, the first water quality parameter is a key water quality parameter value after data cleaning and standardization, which is used to reflect the real-time status of the pond water quality.

[0176] In this embodiment, the sample evaluation result is a comprehensive assessment of the first collected sample, including information such as species, quantity, and biomass of organisms.

[0177] In this embodiment, the determination of monitoring optimization measures involves combining the first optimization measures with the first water quality parameters and sample evaluation results, taking into account the ecological environment, water quality, and biological community characteristics of the pond, and finally determining the monitoring optimization measures to be implemented for the target pond.

[0178] In this embodiment, dynamic optimization is a process of flexibly adjusting and improving the monitoring and optimization measures for the pond based on real-time monitoring data and changes in the ecological environment.

[0179] In this embodiment, the corresponding area refers to the specific area in the target pond where monitoring and optimization measures need to be implemented, which may be determined based on factors such as water quality and biological community distribution.

[0180] In this embodiment, real-time monitoring involves continuously monitoring the water quality and biological community of the target pond to obtain the latest ecological and environmental data.

[0181] In this embodiment, timely adjustment and optimization measures are made based on real-time monitoring data and changes in the ecological environment to ensure their relevance and effectiveness.

[0182] In this embodiment, dynamic optimization and continuous improvement are achieved by continuously improving the ecological environment of the target pond through real-time monitoring, dynamic adjustment and optimization measures, thereby realizing continuous improvement in environmental quality and ecological protection.

[0183] The beneficial effects of the above technical solution are: by monitoring the target pond in real time and dynamically optimizing the monitoring optimization measures based on the monitoring results, the management and protection of the target pond can be made more timely and accurate.

[0184] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring the aquatic environment and biological community of a pond, characterized in that, include: Step 1: Based on the real-time monitoring requirements of the target pond, determine the corresponding key water quality monitoring parameter types, thereby collecting key water quality monitoring parameters of the target pond in real time and processing the parameters to obtain the first water quality parameter; Step 2: Determine the corresponding biological community sampling plan based on the real-time monitoring requirements of the target pond, and collect samples based on the biological community sampling plan to obtain the first sample. Step 3: Perform parameter analysis on the first water quality parameter, visualize the parameter based on the parameter analysis results, obtain the real-time water quality trend of the target pond, and at the same time, perform sample analysis on the first collected sample to evaluate the analysis results, obtain the sample evaluation results of the target pond, and predict the biological community evaluation results of the target pond. Step 4: Based on real-time water quality trends and biological community assessment results, comprehensively determine the monitoring and optimization measures for the target pond, and conduct dynamic optimization; Based on the real-time monitoring requirements of the target pond, the corresponding key water quality monitoring parameter types are determined, thereby collecting key water quality monitoring parameters of the target pond in real time and processing the parameters to obtain the first water quality parameters, including: Step 11: Determine the real-time monitoring requirements of the target pond based on historical water quality data and external environmental factors, and then determine the types of key water quality parameters that need to be monitored in real time based on the real-time monitoring requirements; Step 12: Collect key water quality monitoring parameters corresponding to the key water quality parameter types based on preset monitoring equipment; Step 13: Perform data cleaning and standardization on key water quality monitoring parameters to obtain the first water quality parameters of the target pond; Parameter analysis is performed on the first water quality parameter, and parameter visualization is performed based on the analysis results to obtain the real-time water quality trend of the target pond, including: Step 31: Perform descriptive statistics on the first water quality parameter based on preset statistical tools to obtain the distribution of water quality parameters in the target pond; Step 32: Obtain the first water quality parameter of the target pond at each moment in the current period, and obtain the water quality change curve of the target pond in the current period based on the time series; Step 33: Obtain the average water quality parameters of the target pond in the previous period, and input the average water quality parameters into the water quality change curve of the current period to obtain the first water quality change curve of the target pond; Step 34: Based on the preset correlation technology, analyze the parameter correlation between different water quality parameters in the first water quality parameter, and obtain the comprehensive parameter correlation matrix of the first water quality parameter based on the parameter correlation of different water quality parameters; Step 35: Obtain the monitoring and analysis objectives for the target pond, and determine the corresponding visualization scheme based on the monitoring and analysis objectives; Step 36: Adjust the initial visualization tool based on the visualization scheme, and input the first water quality change curve and the comprehensive parameter correlation matrix into the adjusted initial visualization tool to obtain the parameter visualization results of the target pond; Step 37: Based on the parameter visualization results, comprehensively determine the real-time water quality trend corresponding to different water quality parameters of the target pond.

2. The method for monitoring pond water environment and biological community according to claim 1, characterized in that, Based on the real-time monitoring requirements of the target pond, a corresponding biological community sampling plan was determined, and samples were collected based on the biological community sampling plan to obtain the first sample, including: Step 21: Develop a biological community sampling plan based on the historical biological community characteristics of the target pond, external environmental factors, and the real-time monitoring requirements of the target pond; Step 22: Collect biological samples in the target pond based on the biological community sampling scheme to obtain the first sample.

3. The method for monitoring pond water environment and biological community according to claim 2, characterized in that, The first batch of samples collected included: plankton, benthic animals, and aquatic plants.

4. The method for monitoring pond water environment and biological community according to claim 3, characterized in that, The first collected sample is analyzed to evaluate the results, yielding an evaluation of the target pond's sample community and predicting its biological community assessment, including: Step 01: Based on the preset technology, perform a first analysis on the biological species and quantity in the first collected sample to obtain the first evaluation result of the first collected sample; Step 02: Determine the biomass of organisms contained in the first sample based on the preset measurement technology, and obtain the second evaluation result of the first sample by combining the collection area information of the first sample. Step 03: Combine the first evaluation result and the second evaluation result to determine the sample evaluation result of the first collected sample. Based on the information of the collection area corresponding to the first collected sample and the area information of the target pond, combined with the sample evaluation result, make a comprehensive prediction of the biological community of the target pond to obtain the biological community evaluation result of the target pond.

5. The method for monitoring pond water environment and biological community according to claim 4, characterized in that, Based on the information of the collection area corresponding to the first sample and the regional information of the target pond, combined with the sample evaluation results, a comprehensive prediction of the biological community of the target pond is made, resulting in the biological community evaluation results of the target pond, including: Step 031: Obtain the collection area information corresponding to the first sample and the area information of the target pond, and extract the first area volume from the collection area information and the second area volume from the area information of the target pond; Step 032: Based on the ratio of the volume of the first region to the volume of the second region, and combined with the sample evaluation results of the first collected sample, a prediction is made to obtain the initial biological community evaluation results of the target pond. Step 033: Optimize the initial biological community assessment results based on the seasonal cycle community change trend of the target pond and the real-time season of the target pond to obtain the first biological community assessment result. Step 034: Compare the first biological community assessment results with the historical biological community assessment results of the target pond to obtain the community change trend of the biological community in the target pond; Step 035: Based on the community change trend and the community prediction model, predict the biological community of the target pond, and optimize the first biological community assessment result based on the prediction result to obtain the biological community assessment result of the target pond.

6. The method for monitoring pond water environment and biological community according to claim 4, characterized in that, Based on real-time water quality trends and biological community assessment results, a comprehensive assessment of monitoring and optimization measures for the target pond is conducted, and dynamic optimization is implemented, including: Step 41: Combine real-time water quality trends and biological community assessment results to comprehensively judge the ecological environment status of the target pond; Step 42: Based on the ecological environment status of the target pond, select monitoring optimization measures that match the current ecological environment status from the preset pond monitoring optimization database to obtain the first optimization measure; Step 43: Combine the first optimization measures with the first water quality parameters of the target pond and the sample evaluation results to determine the monitoring optimization measures for the target pond; Step 44: Based on monitoring and optimization measures, dynamically optimize the corresponding area of ​​the target pond, and monitor the real-time water quality and biological community of the target pond in real time, so as to adjust the optimization measures in a timely manner and achieve dynamic optimization and continuous improvement of the target pond.

Images