Pond water body environment and biocenosis monitoring method

Abstract

The invention provides a pond water body environment and biocenosis monitoring method, and relates to the technical field of environment monitoring, and the method comprises the steps: determining a corresponding key water quality monitoring parameter type based on the real-time monitoring demand of a target pond, collecting the key water quality monitoring parameter of the target pond, and obtaining a first water quality parameter; determining a biocenosis sampling scheme based on the real-time monitoring requirement of the target pond, and carrying out sample collection to obtain a first collected sample; performing parameter analysis on the first water quality parameter, performing parameter visualization based on a parameter analysis result to obtain a real-time water quality trend of the target pond, performing sample analysis on the first collected sample, evaluating the analysis result, and predicting a biocenosis evaluation result of the target pond; and comprehensively judging monitoring optimization measures of the target pond based on the real-time water quality trend and the biocenosis evaluation result, and performing dynamic optimization. The environment monitoring of the target pond can be more timely and accurate, so that management and protection can be more accurately carried out.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and particularly to a method for monitoring the pond water environment and biological community. Background Art

[0002] At present, pond farming, as an important aquaculture method, plays an important role in ensuring food supply and promoting rural economic development. However, due to the limited self-purification ability of pond water, pollutants such as feed residues and fish metabolites will gradually accumulate, leading to water quality deterioration and affecting the survival of aquatic organisms and aquaculture benefits.

[0003] However, traditional monitoring methods are often limited to single water quality indicators or biological species and are difficult to comprehensively reflect the true situation of the pond water environment and biological community.

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

[0005] The present invention provides a method for monitoring the pond water environment and biological community, which is used to accurately obtain data and perform visual analysis by real-time monitoring of water quality and biological community, accurately evaluate the pond ecological status, and then formulate precise optimization 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 the biological community.

[0006] The present invention provides a method for monitoring the pond water environment and biological community, including: Step 1: Determine the corresponding key water quality monitoring parameter types based on the real-time monitoring requirements of the target pond, thereby collecting the key water quality monitoring parameters of the target pond in real time and performing parameter processing 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 collected sample; Step 3: Analyze the first water quality parameter, perform parameter visualization based on the parameter analysis result to obtain the real-time water quality trend of the target pond. At the same time, analyze the first collected sample, evaluate the analysis result to obtain the sample evaluation result of the target pond, and predict the biological community evaluation result of the target pond; Step 4: Comprehensively judge the monitoring optimization measures of the target pond based on the real-time water quality trend and biological community evaluation result, and perform dynamic optimization.

[0007] According to the present invention, obtaining the first water quality parameter includes: Step 11: Determine the real-time monitoring requirements of the target pond based on the historical water quality data and external environmental factors of the target pond, and thus 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 types of key water quality parameters based on preset monitoring equipment; Step 13: Perform data cleaning and data standardization processing on the key water quality monitoring parameters to obtain the first water quality parameters of the target pond.

[0008] Collect samples according to the biological community sampling scheme provided by the present invention to obtain the first collected samples, including: Step 21: Develop a biological community sampling scheme according to the historical biological community characteristics and external environmental factors of the target pond in combination with 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 collected samples.

[0009] The first collected samples provided by the present invention include: plankton, benthic animals, and aquatic plants.

[0010] Obtain the real-time water quality trend of the target pond provided by the present invention, including: Step 31: Perform descriptive statistics on the first water quality parameters based on preset statistical tools to obtain the distribution of water quality parameters of the target pond; Step 32: Obtain the first water quality parameters at each moment in the current period of the target pond, 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: Analyze the parameter correlations between different water quality parameters in the first water quality parameters based on preset correlation techniques, and obtain the comprehensive parameter correlation matrix of the first water quality parameters based on the parameter correlations of different water quality parameters; Step 35: Obtain the monitoring and analysis purpose of the target pond, and determine the corresponding visualization scheme based on the monitoring and analysis purpose; 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 result of the target pond; Step 37: Comprehensively determine the real-time water quality trends corresponding to different water quality parameters of the target pond based on the parameter visualization results.

[0011] Based on the sample evaluation result of the target pond provided by the present invention, predicting the biological community evaluation result of the target pond, including: Step 01: Perform a first analysis on the biological species and biological quantity in the first collected sample based on a preset technology to obtain a first evaluation result of the first collected sample; Step 02: Determine the biomass of the organisms contained in the first collected sample based on a preset measurement technology, and combine it with the collection area information of the first collected sample to obtain a second evaluation result of the first collected sample; Step 03: Integrate the first evaluation result and the second evaluation result to determine the sample evaluation result of the first collected sample, and comprehensively predict the biological community of the target pond by combining the sample evaluation result with the collection area information corresponding to the first collected sample and the area information of the target pond to obtain the biological community evaluation result of the target pond.

[0012] Based on the comprehensive prediction of the biological community of the target pond by combining the collection area information corresponding to the first collected sample and the area information of the target pond with the sample evaluation result provided by the present invention to obtain the biological community evaluation result of the target pond, including: Step 031: Obtain the collection area information corresponding to the first collected sample and the area information of the target pond, and extract the first area volume of the collection area information and the second area volume in the area information of the target pond; Step 032: Based on the ratio of the first area volume to the second area volume, combine the sample evaluation result of the first collected sample for prediction, so as to obtain the initial biological community evaluation result of the target pond; Step 033: Optimize the initial biological community evaluation result 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 evaluation result; Step 034: Compare the first biological community evaluation result with the historical biological community evaluation result of the target pond to obtain the community change trend of the biological community in the target pond; Step 035: Predict the biological community of the target pond based on the community change trend and the community prediction model, and optimize the first biological community evaluation result based on the prediction result to obtain the biological community evaluation result of the target pond.

[0013] Based on the real-time water quality trend and the biological community evaluation result provided by the present invention, comprehensively judge the monitoring optimization measures of the target pond and perform dynamic optimization, including: Step 41: Comprehensively judge the ecological environment status of the target pond by combining the real-time water quality trend and the biological community evaluation result; Step 42: Based on the ecological environment status of the target pond, screen out the 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: Integrate the first optimization measure with the first water quality parameters and sample evaluation results of the target pond to determine the monitoring optimization measures for the target pond; Step 44: Dynamically optimize the corresponding area of the target pond based on the monitoring optimization measures, and real-time monitor the real-time water quality and biological community situation of the target pond, so as to timely adjust the optimization measures and achieve the dynamic optimization and continuous improvement of the target pond.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: A method for monitoring the water environment and biological community of a pond provided by the present invention accurately obtains data through real-time monitoring of water quality and biological community and performs visual analysis, accurately evaluates the ecological status of the pond, and then formulates precise optimization monitoring measures and dynamically optimizes 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 the biological community. Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a flowchart of a method for monitoring the water environment and biological community of a pond provided by an embodiment of the present invention. Detailed Embodiments

[0017] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention with reference to the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention.

[0018] Example 1: An embodiment of the present invention provides a method for monitoring the water environment and biological community of a pond, as Figure 1 shown, including: Step 1: Based on the real-time monitoring requirements of the target pond, determine the corresponding key water quality monitoring parameter types, so as to collect the key water quality monitoring parameters of the target pond in real time and perform parameter processing to obtain the first water quality parameters; Step 2: Determine the corresponding biotic community sampling plan based on the real-time monitoring requirements of the target pond, and collect samples according to the biotic community sampling plan to obtain the first collected samples; Step 3: Conduct parameter analysis on the first water quality parameters, perform parameter visualization based on the parameter analysis results to obtain the real-time water quality trend of the target pond. At the same time, analyze the first collected samples, evaluate the analysis results, obtain the sample evaluation results of the target pond, and predict the biotic community evaluation results of the target pond; Step 4: Comprehensively judge the monitoring optimization measures of the target pond based on the real-time water quality trend and biotic community evaluation results, and conduct dynamic optimization.

[0019] In this embodiment, the target pond refers to the specific pond that needs to be monitored for water quality and biotic community.

[0020] In this embodiment, the real-time monitoring requirements are to determine the water quality parameters and biotic community characteristics that need to be key monitored according to factors such as the aquaculture species, aquaculture density, historical water quality conditions, geographical location, and climate conditions of the pond.

[0021] In this embodiment, the key water quality monitoring parameter types refer to the parameters that have an important impact on the water quality conditions of the pond, such as dissolved oxygen, pH value, water temperature, turbidity, ammonia nitrogen, nitrite, total phosphorus, total nitrogen, etc.

[0022] In this embodiment, the first water quality parameters refer to the water quality parameter data collected by real-time monitoring equipment and preliminarily processed.

[0023] In this embodiment, the biotic community sampling plan is a plan designed according to the real-time monitoring requirements for collecting biological samples of plankton, benthos, and aquatic plants in the pond, including sampling locations, sampling times, sampling frequencies, sampling methods, etc.

[0024] In this embodiment, the first collected samples refer to the biological samples collected according to the biotic community sampling plan for subsequent biotic community analysis.

[0025] In this embodiment, parameter analysis is to conduct statistical analysis, trend analysis, anomaly detection, etc. on the first water quality parameters to reveal the change rules of water quality conditions.

[0026] In this embodiment, parameter visualization is to visually display the results of parameter analysis in the form of charts, images, etc. for easy understanding and analysis.

[0027] In this embodiment, the real-time water quality trend is the trend of the water quality conditions of the pond changing over time based on the parameter analysis results.

[0028] In this embodiment, the sample analysis is to conduct species identification, quantity statistics, calculation of diversity index, etc. on the first collected sample to evaluate the status of the biological community.

[0029] In this embodiment, the sample evaluation result is the evaluation result of the biological community status obtained based on the sample analysis, including species composition, quantity distribution, diversity level, etc.

[0030] In this embodiment, the biological community evaluation result is the evaluation of the overall status of the pond biological community based on the sample evaluation result, including ecological health status, presence or absence of pollution indicator species, etc.

[0031] In this embodiment, the monitoring optimization measures are measures formulated based on the real-time water quality trend and biological community evaluation result to improve the pond water quality and biological community status, such as adjusting the aquaculture density, optimizing the feed formula, increasing aeration equipment, conducting ecological restoration, etc.

[0032] In this embodiment, the dynamic optimization is to continuously adjust and optimize the monitoring plan, sampling plan, and optimization measures according to the real-time monitoring data and evaluation results to adapt to the changes in the pond water quality and biological community status.

[0033] The beneficial effects of the above technical solution are: By real-time monitoring the water quality and biological community, accurately obtaining data and conducting visual analysis, accurately evaluating the pond ecological status, and then formulating precise optimization monitoring measures and dynamically optimizing, it effectively improves the management efficiency and protection level of the pond ecological environment, and ensures the continuous stability of the water quality and the healthy development of the biological community.

[0034] Embodiment 2: Based on Embodiment 1, the first water quality parameters are obtained, including: Step 11: Determine the real-time monitoring requirements of the target pond according to the historical water quality data and external environmental factors of the target pond, and thus 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 types of key water quality parameters based on preset monitoring equipment; Step 13: Conduct data cleaning and data standardization processing on the key water quality monitoring parameters to obtain the first water quality parameters of the target pond.

[0035] In this embodiment, the target pond refers to the specific pond that needs to be monitored in real time, usually selected based on factors such as aquaculture requirements, geographical location, and environmental conditions.

[0036] In this embodiment, the historical water quality data refers to the water quality parameter data recorded by the target pond over a past period of time, and these data help to understand the long-term change trend and potential problems of the pond water quality.

[0037] In this embodiment, the external environmental factors are the external conditions that affect the water quality of the pond, such as climatic conditions (temperature, rainfall), geographical location (soil type, water source), human activities (aquaculture density, feed input), etc.

[0038] In this embodiment, the real-time monitoring requirements are the current and future key points of water quality monitoring for the target pond determined based on historical water quality data and external environmental factors, so as to ensure water quality safety and optimize aquaculture management.

[0039] In this embodiment, the types of key water quality parameters are the parameter categories that have an important impact on the water quality status of the pond, such as dissolved oxygen, pH value, water temperature, ammonia nitrogen, nitrite, total phosphorus, total nitrogen, etc. These parameters can reflect the quality and potential risks of the water quality.

[0040] In this embodiment, the preset monitoring equipment is the water quality monitoring equipment pre-installed and configured in the target pond for real-time collection of water quality parameter data. These devices may include sensors, analyzers, etc., which can collect water quality data automatically or manually.

[0041] In this embodiment, the key water quality monitoring parameters refer to the specific water quality parameter values corresponding to the types of key water quality parameters, which reflect the current status of the water quality of the pond.

[0042] In this embodiment, data cleaning is to process the collected key water quality monitoring parameters, remove outliers, duplicate values, missing values, etc., to ensure the accuracy and integrity of the data.

[0043] In this embodiment, data standardization processing is to convert the cleaned data into a unified standard format for subsequent data analysis and comparison. Standardization processing may include operations such as data normalization and data conversion.

[0044] In this embodiment, the first water quality parameters are the key water quality parameter values obtained after data cleaning and standardization processing. These parameter values reflect the standardized and accurate state of the water quality of the target pond, providing basic data for subsequent water quality analysis and optimization management.

[0045] 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 first water quality parameters can be made more accurate and standardized, so that the water quality analysis and optimization management of the target pond are more accurate and efficient.

[0046] Embodiment 3: Based on Embodiment 2, the first collected sample is obtained, including: Step 21: Develop a biological community sampling plan according to the historical biological community characteristics and external environmental factors of the target pond in combination with the real-time monitoring requirements of the target pond; Step 22: Collect biological samples in the target pond based on the biocoenosis sampling plan to obtain the first collection sample.

[0047] In this embodiment, the target pond refers to the specific pond that needs to be monitored for biocoenosis, and its biocoenosis characteristics may vary due to factors such as aquaculture species, ecological environment, and historical changes.

[0048] In this embodiment, the historical biocoenosis characteristics refer to the composition, quantity, distribution, diversity, etc. of the biocoenosis recorded in the target pond over a period of time in the past. These characteristics help to understand the long-term change trend and potential problems of the biocoenosis.

[0049] In this embodiment, the external environmental factors are also the external conditions that affect the pond biocoenosis, such as climatic conditions (temperature, light, rainfall), geographical location (soil type, water source), human activities (aquaculture management, drug use), etc.

[0050] In this embodiment, the real-time monitoring requirement is the current and future key points of biocoenosis monitoring for the target pond determined based on the historical biocoenosis characteristics and external environmental factors, combined with goals such as aquaculture management and ecological protection.

[0051] In this embodiment, the biocoenosis sampling plan is formulated according to the real-time monitoring requirement and is a specific plan for guiding the collection of biological samples in the target pond, including sampling locations, sampling times, sampling methods, sampling frequencies, etc.

[0052] In this embodiment, the collection of biological samples is a process of collecting biological samples such as plankton, benthos, and aquatic plants in the target pond according to the biocoenosis sampling plan. The collection methods may include net fishing, trawling, water sample filtration, etc.

[0053] In this embodiment, the first collection sample is a set of biological samples obtained through the process of collecting biological samples and is used for subsequent biocoenosis analysis. It includes plankton, benthic animals, and aquatic plants, and is used to evaluate the composition, quantity, distribution, and diversity of the biocoenosis.

[0054] The beneficial effects of the above technical solution are: By determining the biocoenosis sampling plan in combination with the real-time monitoring requirement, the determined collection sample can better meet the real-time monitoring requirement of the pond, can more accurately reflect the situation of the pond biocoenosis, and thus obtain more accurate optimization management measures for dynamic optimization.

[0055] Example 4: Based on Example 3, the first collection sample includes: plankton, benthic animals, and aquatic plants.

[0056] Example 5: Based on Example 3, the real-time water quality trend of the target pond is obtained, including: Step 31: Conduct descriptive statistics on the first water quality parameter based on a preset statistical tool to obtain the distribution of water quality parameters in the target pond; Step 32: Obtain the first water quality parameter at each moment within the current period of the target pond, and based on the time series, obtain the water quality change curve of the target pond in the current period; Step 33: Obtain the average water quality parameter of the target pond in the previous period, and input the average water quality parameter 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 a preset correlation technique, analyze the parameter correlation between different water quality parameters in the first water quality parameter, and based on the parameter correlation of different water quality parameters, obtain the comprehensive parameter correlation matrix of the first water quality parameter; Step 35: Obtain the monitoring and analysis purpose of the target pond, and determine the corresponding visualization scheme based on the monitoring and analysis purpose; 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 result of the target pond; Step 37: Comprehensively determine the real-time water quality trend corresponding to different water quality parameters of the target pond based on the parameter visualization result.

[0057] In this embodiment, the preset statistical tool refers to a statistical software or tool pre-selected or installed for data analysis, such as SPSS, R language, Excel, etc., which is used to conduct descriptive statistical analysis on water quality parameters.

[0058] In this embodiment, the first water quality parameter refers to the key water quality parameter value obtained after data cleaning and standardization processing.

[0059] In this embodiment, descriptive statistics is a data analysis method used to summarize and summarize 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.

[0060] In this embodiment, the water quality parameter distribution refers to the distribution of the first water quality parameter in the target pond, which reflects the central tendency, dispersion degree, and distribution form of the water quality parameter.

[0061] In this embodiment, the current period refers to a specific time period for water quality monitoring of the target pond, such as one day, one week, one month, etc.

[0062] In this embodiment, the water quality change curve is a line graph formed by connecting the water quality parameter values of the target pond at each moment within the current cycle based on a time series, and is used to visually display the change trend of water quality parameters over time.

[0063] In this embodiment, the average water quality parameters of the previous cycle refer to the average values of various water quality parameters of the target pond within the previous monitoring cycle, and are used to compare with the water quality changes in the current cycle.

[0064] In this embodiment, the first water quality change curve is formed by adding the average water quality parameters of the previous cycle to the water quality change curve of the current cycle to form a water quality change curve containing historical comparison information.

[0065] 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.

[0066] In this embodiment, parameter correlation refers to the degree of correlation between different water quality parameters, reflecting their mutual influence and association.

[0067] In this embodiment, the comprehensive parameter correlation matrix is a two-dimensional table, where the rows and columns respectively represent different water quality parameters, and the values in the table represent the correlation coefficients between the corresponding parameters, and are used to comprehensively display the correlation between water quality parameters.

[0068] In this embodiment, the monitoring and analysis purpose refers to the specific goals or requirements for water quality monitoring and analysis, such as evaluating water quality status, discovering potential problems, optimizing aquaculture management, etc.

[0069] In this embodiment, the visualization scheme is a data visualization method and strategy determined according to the monitoring and analysis purpose, and is used to present complex data information in an intuitive and easy-to-understand manner.

[0070] In this embodiment, the initial visualization tool refers to software or platforms used for data visualization, such as Tableau, Power BI, ECharts, etc.

[0071] In this embodiment, the parameter visualization result is a chart or report that intuitively displays the changes and correlations of water quality parameters, generated by inputting information such as the first water quality change curve and the comprehensive parameter correlation matrix into the adjusted visualization tool based on the visualization scheme.

[0072] In this embodiment, the real-time water quality trend is to comprehensively analyze and judge the real-time change trends of different water quality parameters of the target pond, such as rising, falling, stable, etc., based on the parameter visualization result, providing a basis for subsequent water quality management and optimization.

[0073] The beneficial effects of the above technical solution are as follows: By analyzing the first water quality parameter and comprehensively analyzing it in combination with parameter correlation, and then visualizing the analysis results, the water quality analysis of the target pond can be made more accurate, and the result visualization can be personalized, enabling the target user to manage the pond water quality in a more accurate and timely manner.

[0074] Example 6: Based on Example 5, predict the biological community assessment result of the target pond, including: Step 01: Perform a first analysis on the biological species and quantity in the first collected sample based on a preset technology to obtain the first assessment result of the first collected sample; Step 02: Determine the biomass of the organisms contained in the first collected sample based on a preset measurement technology, and combine the collection area information of the first collected sample to obtain the second assessment result of the first collected sample; Step 03: Combine the first assessment result and the second assessment result to determine the sample assessment result of the first collected sample, and comprehensively predict the biological community of the target pond based on the collection area information corresponding to the first collected sample and the area information of the target pond in combination with the sample assessment result to obtain the biological community assessment result of the target pond.

[0075] In this example, the preset technology refers to professional technologies or methods for biological species and quantity analysis, which may include microscopic observation, DNA sequencing, flow cytometry, etc. These technologies can identify and count the biological species and quantity in the sample.

[0076] In this example, the first collected sample refers to a biological sample collected from the target pond according to a preset plan for subsequent biological community analysis.

[0077] In this example, the first analysis is a preliminary analysis of the first collected sample, aiming to determine the biological species and quantity in the sample.

[0078] In this example, the first assessment result is based on the first analysis and is an assessment result regarding the biological species and quantity in the first collected sample.

[0079] In this example, 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 the organisms in the sample.

[0080] In this example, biomass refers to the total mass or quantity of all organisms in the sample and is an important indicator for measuring the scale of the biological community.

[0081] In this embodiment, the collection area information is specific information about the collection location of the first collection sample, such as water depth, sediment type, distance from the shore, etc. This information helps to understand the distribution and characteristics of the biological community.

[0082] In this embodiment, the second evaluation result is a comprehensive evaluation result of the first collection sample by combining the biomass and the collection area information.

[0083] In this embodiment, the sample evaluation result is a comprehensive evaluation of the first collection sample by combining the first evaluation result and the second evaluation result. This evaluation result includes both information on the types and quantities of organisms and information on the biomass.

[0084] In this embodiment, the collection area information and the area information of the target pond are such that the collection area information refers to the specific collection location information of the first collection sample, while the area information of the target pond refers to the geographical, ecological and other characteristic information of the entire pond. Combining these two types of information helps to more accurately understand the distribution and characteristics of the biological community in the entire pond.

[0085] In this embodiment, the comprehensive prediction of the biological community is an overall prediction of the biological community of the target pond based on the sample evaluation result and the area information, including predictions in aspects such as the types, quantities, distributions, and ecological relationships of organisms.

[0086] In this embodiment, the evaluation result of the biological community of the target pond is a comprehensive evaluation of the status of the biological community of the target pond, including information on the composition, structure, function, etc. of the biological community, providing an important basis for subsequent pond management and ecological protection.

[0087] The beneficial effects of the above technical solution are: By analyzing and evaluating the first collection sample and combining the area information of the target pond to comprehensively predict the evaluation result of the biological community of the target pond, the evaluation of the biological community of the target pond can be made more accurate.

[0088] Example 7: Based on Example 6, the evaluation result of the biological community of the target pond is obtained, including: Step 031: Obtain the collection area information corresponding to the first collection sample and the area information of the target pond, and extract the first area volume of the collection area information and the second area volume in the area information of the target pond; Step 032: Based on the ratio of the first area volume to the second area volume, combine with the sample evaluation result of the first collection sample for prediction, so as to obtain the initial evaluation result of the biological community of the target pond; Step 033: Optimize the initial evaluation result of the biological community based on the seasonal cycle community change trend of the target pond combined with the real-time season of the target pond to obtain the first evaluation result of the biological community; Step 034: Compare the first biological community assessment result with the historical biological community assessment result of the target pond to obtain the community change trend of the biological community in the target pond. Step 035: Predict the biological community of the target pond based on the community change trend combined with the community prediction model, and optimize the first biological community assessment result based on the prediction result to obtain the biological community assessment result of the target pond.

[0089] In this embodiment, the collection area information corresponding to the first collection sample refers to the specific location information recorded when collecting the first collection sample, which may include water depth, longitude and latitude, bottom substrate type, etc. These information help to understand the distribution and characteristics of the biological community.

[0090] In this embodiment, the area information of the target pond is the geographical, ecological and other characteristic information about the entire target pond, such as the total area of the pond, water depth distribution, ecological environment, etc.

[0091] In this embodiment, the first regional volume is the volume of the area where the first collection sample is located calculated according to the collection area information, which may be calculated based on parameters such as water depth and area.

[0092] In this embodiment, the second regional volume is the volume of the entire pond calculated according to the area information of the target pond.

[0093] In this embodiment, the ratio is the proportional relationship between the first regional volume and the second regional volume, which is used to evaluate the representativeness of the collection sample in the target pond.

[0094] In this embodiment, the sample assessment result is a comprehensive assessment of the first collection sample, including information such as biological species, quantity, biomass, etc.

[0095] In this embodiment, the initial biological community assessment result is a preliminary assessment of the biological community of the target pond based on the ratio and the sample assessment result.

[0096] In this embodiment, the seasonal cycle community change trend is the regular change trend of the biological community in the target pond with the change of seasons.

[0097] In this embodiment, the optimization is to adjust and improve the initial biological community assessment result based on the seasonal cycle community change trend and the real-time season to improve the accuracy of the assessment.

[0098] In this embodiment, the historical biological community assessment result is the assessment result of the biological community of the target pond in the past, which may include data at multiple time points.

[0099] In this embodiment, the community change trend is the trend of the biological community changing over time obtained by comparing the current (the first biological community assessment result) with the historical biological community assessment results.

[0100] In this embodiment, the community prediction model is a mathematical model or algorithm used to predict the future change trend of the biological community, which may be constructed based on historical data, environmental factors, etc.

[0101] In this embodiment, the prediction result is the prediction result of the future change trend of the biological community of the target pond using the community prediction model.

[0102] In this embodiment, optimization is to further adjust and improve the first biological community assessment result based on the community change trend and the prediction result, and finally obtain the biological community assessment result of the target pond. This result combines the current situation, historical trend and future prediction, providing an important basis for pond management and ecological protection.

[0103] The beneficial effects of the above technical solution are: By analyzing and evaluating the first collected sample, and comprehensively predicting the biological community assessment result of the target pond in combination with the regional information of the target pond and the seasonal cycle community change trend, the biological community assessment of the target pond can be made more accurate.

[0104] Example 8: Based on Example 6, comprehensively judge the monitoring optimization measures of the target pond based on the real-time water quality trend and the biological community assessment result, and perform dynamic optimization, including: Step 41: Comprehensively judge the ecological environment status of the target pond by combining the real-time water quality trend and the biological community assessment result; Step 42: Screen the monitoring optimization measures matching the current ecological environment status from the preset pond monitoring optimization database based on the ecological environment status of the target pond to obtain the first optimization measure; Step 43: Integrate the first optimization measure with the first water quality parameter and the sample assessment result of the target pond to determine the monitoring optimization measure for the target pond; Step 44: Dynamically optimize the corresponding area of the target pond based on the monitoring optimization measure, and monitor the real-time water quality and biological community situation of the target pond in real time, so as to adjust the optimization measure in time and achieve the dynamic optimization and continuous improvement of the target pond.

[0105] In this embodiment, the real-time water quality trend refers to the change trend of the water quality parameters of the target pond over time obtained by continuous monitoring and analysis, which reflects the real-time status of the pond water quality.

[0106] In this embodiment, the biological community assessment result is a comprehensive assessment of the biological community in the target pond, including information such as biological species, quantity, distribution, biomass, etc., as well as the overall health status and stability of the biological community.

[0107] In this embodiment, the ecological environment condition is a comprehensive evaluation of the overall ecological environment of the target pond by integrating the real-time water quality trend and the biological community assessment result, reflecting the overall quality and potential problems of the pond ecological environment.

[0108] In this embodiment, the preset pond monitoring optimization database is a database storing various pond monitoring optimization measures, which may be designed for different types of ponds, different ecological environment conditions, different management objectives, etc.

[0109] In this embodiment, the monitoring optimization measure is a specific measure aimed at improving the pond monitoring efficiency and improving the pond ecological environment, which may include adjusting the monitoring frequency, increasing the monitoring indicators, optimizing the sampling location, etc.

[0110] In this embodiment, the first optimization measure is the monitoring optimization measure selected from the preset pond monitoring optimization database that best matches the current ecological environment condition of the target pond.

[0111] In this embodiment, the first water quality parameter is the key water quality parameter value after data cleaning and standardization processing, used to reflect the real-time condition of the pond water quality.

[0112] In this embodiment, the sample assessment result is a comprehensive assessment of the first collected sample, including information such as biological species, quantity, biomass, etc.

[0113] In this embodiment, the determination of the monitoring optimization measure is to combine the first optimization measure with the first water quality parameter and the sample assessment result, comprehensively consider the ecological environment, water quality condition and biological community characteristics of the pond, and finally determine the monitoring optimization measure to be implemented for the target pond.

[0114] In this embodiment, dynamic optimization is a process of flexibly adjusting and improving the pond monitoring optimization measure according to the real-time monitoring data and the change of the ecological environment condition.

[0115] In this embodiment, the corresponding area refers to the specific area in the target pond where the monitoring optimization measure needs to be implemented, which may be determined based on factors such as water quality condition and biological community distribution.

[0116] In this embodiment, real-time monitoring is to continuously monitor the water quality and biological community of the target pond to obtain the latest ecological environment data.

[0117] In this embodiment, the timely adjustment and optimization measures are to timely adjust and improve the monitoring and optimization measures according to the real-time monitoring data and the changes in the ecological environment conditions, so as to ensure their pertinence and effectiveness.

[0118] In this embodiment, the dynamic optimization and continuous improvement are to continuously improve the ecological environment of the target pond through real-time monitoring, dynamic adjustment and optimization measures, so as to achieve continuous improvement of environmental quality and ecological protection.

[0119] The beneficial effects of the above technical solution are as follows: By carrying out real-time monitoring on the target pond and dynamically optimizing the monitoring and optimization measures based on the monitoring results, the management and protection of the target pond can be made more timely and accurate.

[0120] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring pond water environment and biological community, characterized in that: include: Step 1: Determine the corresponding key water quality monitoring parameter type based on the real-time monitoring requirements of the target pond, thereby collecting the key water quality monitoring parameters of the target pond in real time, and perform parameter processing to obtain the first water quality parameter; Step 2: Determine a corresponding biological community sampling scheme based on the real-time monitoring requirements of the target pond, and collect samples based on the biological community sampling scheme to obtain a first collected sample; Step 3: Perform parameter analysis on the first water quality parameter, perform parameter visualization based on the parameter analysis result, obtain the real-time water quality trend of the target pond, and at the same time, perform sample analysis on the first collected sample, thereby evaluating the analysis result, obtaining the sample evaluation result of the target pond, and predicting the biological community evaluation result of the target pond; Step 4: Comprehensively judge the monitoring optimization measures of the target pond based on the real-time water quality trend and biological community assessment results, and perform dynamic optimization.

2. A 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, the corresponding key water quality monitoring parameter type is determined, so as to collect the key water quality monitoring parameters of the target pond in real time, and perform parameter processing to obtain the first water quality parameter, including: Step 11: Determine the real-time monitoring requirements of the target pond based on the historical water quality data of the target pond 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 data standardization on key water quality monitoring parameters to obtain the first water quality parameter of the target pond.

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

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

5. A method for monitoring pond water environment and biological community according to claim 3, characterized in that: Perform parameter analysis on the first water quality parameter, and perform parameter visualization based on the parameter analysis result 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 a preset statistical tool to obtain a distribution of water quality parameters of the target pond; Step 32: Obtain the first water quality parameter of the target pond at each moment in the current cycle, and obtain a water quality change curve of the target pond in the current cycle based on the time series; Step 33: Obtain the average water quality parameters of the target pond in the previous cycle, and input the average water quality parameters into the water quality change curve of the current cycle, thereby obtaining a first water quality change curve of the target pond; Step 34: Analyze the parameter correlations between different water quality parameters in the first water quality parameter based on a preset correlation technology, and obtain a comprehensive parameter correlation matrix of the first water quality parameter based on the parameter correlations of the different water quality parameters; Step 35: Obtain the monitoring and analysis purpose of the target pond, and determine the corresponding visualization scheme based on the monitoring and analysis purpose; Step 36: adjusting the initial visualization tool based on the visualization scheme, and inputting the first water quality change curve and the comprehensive parameter correlation matrix into the adjusted initial visualization tool to obtain parameter visualization results of the target pond; Step 37: Comprehensively determine the real-time water quality trends corresponding to different water quality parameters of the target pond based on the parameter visualization results.

6. A method for monitoring pond water environment and biological community according to claim 5, characterized in that: Performing sample analysis on the first collected sample, thereby evaluating the analysis result, obtaining a sample evaluation result of the target pond, and predicting a biological community evaluation result of the target pond, including: Step 01: Perform a first analysis on the species and quantity of organisms in a first collected sample based on a preset technology to obtain a first evaluation result of the first collected sample; Step 02: Determine the biomass of the organisms contained in the first collected sample based on a preset measurement technology, and obtain a second evaluation result of the first collected sample in combination with the collection area information of the first collected sample; Step 03: Integrate the first evaluation result and the second evaluation result to determine the sample evaluation result of the first collected sample, and make a comprehensive prediction of the biological community of the target pond based on the collection area information corresponding to the first collected sample and the area information of the target pond combined with the sample evaluation result to obtain the biological community evaluation result of the target pond.

7. A method for monitoring pond water environment and biological community according to claim 6, characterized in that: Based on the collection area information corresponding to the first collected sample and the area information of the target pond combined with the sample evaluation result, a comprehensive prediction of the biological community of the target pond is performed to obtain the biological community evaluation result of the target pond, including: Step 031: obtaining the collection area information corresponding to the first collection sample and the area information of the target pond, and extracting the first area volume of the collection area information and the second area volume in the area information of the target pond; Step 032: Based on the ratio of the volume of the first area to the volume of the second area, combined with the sample evaluation result of the first collected sample, a prediction is made to obtain an initial biological community evaluation result of the target pond; Step 033: Optimizing the initial biological community assessment result based on the seasonal cycle community change trend of the target pond and the real-time season of the target pond to obtain a first biological community assessment result; Step 034: Compare the first biological community assessment result with the historical biological community assessment result of the target pond, so as to obtain the community change trend of the biological community in the target pond; Step 035: Predict the biological community of the target pond based on the community change trend and the community prediction model, and optimize the first biological community assessment result based on the prediction result to obtain the biological community assessment result of the target pond.

8. A method for monitoring pond water environment and biological community according to claim 6, characterized in that: Based on the real-time water quality trend and biological community assessment results, the monitoring optimization measures of the target pond are comprehensively judged and dynamically optimized, including: Step 41: Comprehensively judge the ecological environment status of the target pond by combining the real-time water quality trend and the biological community assessment results; Step 42: Based on the ecological environment status of the target pond, a monitoring optimization measure matching the current ecological environment status is selected from a preset pond monitoring optimization database to obtain a first optimization measure; Step 43: integrating the first optimization measure with the first water quality parameter and sample evaluation result of the target pond, thereby determining the monitoring optimization measure for the target pond; Step 44: Dynamically optimize the corresponding area of ​​the target pond based on the monitoring optimization measures, 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 time to achieve dynamic optimization and continuous improvement of the target pond.

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