A Trend Prediction and Early Warning Method Applied to the Health Assessment of Gulf Ecosystems

Abstract

The present invention discloses a trend prediction and early warning method for evaluating the health of a bay ecosystem, relating to the field of bay ecological early warning technology. The method comprises the following steps: collecting bay ecological monitoring data and dividing the monitoring data into historical data and real-time data, wherein the monitoring data includes water quality data, geological data, and hydrometeorological data; preprocessing the collected monitoring data; screening for factors influencing the bay ecosystem, wherein the factors influencing the bay ecosystem include physical factors and chemical factors; and utilizing the preprocessed historical data and the factors influencing the bay ecosystem. By constructing a bay ecological prediction model, the present invention predicts the trend of the ecosystem health status over a period of time in the future based on historical data and real-time monitoring information, enabling relevant departments and the public to take action before problems occur and effectively prevent potential ecological risks.

Description

Technical Field

[0001] The present invention relates to the technical field of bay ecological early warning technology, and in particular to a trend prediction and early warning method applied to bay ecosystem health assessment. Background Art

[0002] With the rapid development of the economy and society, ecological and environmental problems are becoming increasingly prominent around the world, especially in coastal areas with prominent locational characteristics such as bays and islands. Marine environmental pollution is becoming increasingly serious, resulting in a high degree of "pathology" in the bay ecosystem, with a significant decline in production functions, service functions, and natural purification functions. Bay ecosystem health assessment is the basis for evaluating the overall status of the bay ecosystem, identifying potential problems, and formulating protection strategies. Therefore, conducting health assessments of bay ecosystems and conducting trend forecasts and early warnings based on the assessment results have become important means to protect the marine ecological environment and achieve sustainable development.

[0003] Since there are multiple ecological factors in the health assessment of the bay ecosystem, it is difficult to analyze the carrying capacity of pollutants for different bay conditions and then conduct targeted health assessment, which affects the matching degree of response measures. Therefore, how to ensure the matching degree between ecological factors and the bay ecological health assessment to improve the matching degree of response measures is the problem we need to solve. To this end, a trend prediction and early warning method applied to the health assessment of the bay ecosystem is proposed. Summary of the Invention

[0004] The present invention aims to provide a trend prediction and early warning method for bay ecosystem health assessment to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A trend prediction and early warning method for evaluating the health of a bay ecosystem comprises the following steps:

[0007] Step 1: Collect monitoring data on the bay's ecology and divide the monitoring data into historical data and real-time data. The monitoring data includes water quality data, bottom sediment data, and hydrometeorological data. Water quality data includes dissolved oxygen, pH value, temperature, salinity, nutrients, heavy metal content, etc.; bottom sediment data includes sediment composition, organic matter content, heavy metal deposition, etc.; hydrometeorological data includes tides, water flow velocity, wind direction, wind speed, precipitation, etc.

[0008] Step 2: Preprocess the collected monitoring data to screen for factors affecting the bay ecosystem. These factors include physical factors and chemical factors. Physical factors include water temperature, salinity, tides, and water velocity, while chemical factors include dissolved oxygen, pH, nutrient concentration, and heavy metal content.

[0009] Step 3: Using preprocessed historical data and bay ecosystem impact factors, a bay ecological prediction model is constructed to obtain the physical impact index and chemical impact index to analyze the overall health of the bay ecosystem. For example, when both the physical impact index and the chemical impact index are at low levels, it indicates that the overall health of the bay ecosystem is good; conversely, if the index is high, it means that the ecosystem may be facing greater pressure;

[0010] Step 4: Based on the physical impact index and chemical impact index, obtain the bay ecological health assessment coefficient and predict the development trend of the bay ecosystem health, including the changing trend of health status and the time when potential problems will appear. Combined with historical data, determine the early warning level of the bay ecosystem health and set the corresponding early warning assessment threshold;

[0011] Step 5: Determine the corresponding warning level for the health of the bay ecosystem based on the bay ecological prediction model and generate corresponding warning information. The warning information should include the warning level, the potentially affected areas, changes in major ecological factors, and recommended response measures, so that relevant departments and the public can take timely action and be reminded to take corresponding targeted response measures, such as strengthening pollution control, carrying out ecological restoration, and strengthening monitoring and evaluation.

[0012] A further improvement of the technical solution of the present invention is that in step 1, the process of acquiring the bay ecological monitoring data is as follows:

[0013] Step 101: Establish multiple monitoring stations based on the geographical characteristics of the bay, the direction of water flow, and the distribution of surrounding pollution sources. Install sensors and monitoring equipment at the monitoring stations to collect real-time water quality data, bottom sediment data, and hydrological and meteorological data. The data is then wirelessly transmitted to a data center for real-time processing and storage. The sensors include temperature sensors, salinity sensors, dissolved oxygen sensors, etc., and the monitoring equipment includes water quality analyzers, bottom sediment samplers, and hydrological and meteorological monitors.

[0014] Step 102: Collect historical data from previous research reports, monitoring records, and public official databases, and organize, verify, and archive the historical data to ensure data integrity and reliability;

[0015] Step 103 , the acquired historical data and real-time data are classified and stored according to time series and data type, and a data recovery mechanism is established to regularly back up the database to ensure timely recovery in case of data loss or damage.

[0016] A further improvement of the technical solution of the present invention is that in step 2, the process of obtaining the influencing factors of the bay ecosystem is:

[0017] Step 201: Clean, standardize, integrate and pre-process the collected historical data and real-time data.

[0018] Step 202 , screening and extracting the water temperature, salinity, tide, water velocity, wind direction, and wind speed of the bay ecosystem to obtain physical influencing factors;

[0019] Step 203 , performing feature screening and extraction based on the dissolved oxygen, pH value, and nutrient concentrations such as nitrogen, phosphorus, and heavy metal content of the bay ecosystem to obtain chemical influencing factors;

[0020] Step 204 : Analyze the correlation between the influencing factors based on the acquired physical influencing factors and chemical influencing factors.

[0021] A further improvement of the technical solution of the present invention is that in step 3, the process of obtaining the physical impact index and the chemical impact index is as follows:

[0022] Step 301: Integrate the correlation data of physical influencing factors and chemical influencing factors in the pre-processed historical data to form a unified data set;

[0023] Step 302 , performing a time series analysis on the physical and chemical influencing factors, analyzing the temporal trends of the physical and chemical influencing factors, and constructing a bay ecological prediction model;

[0024] Step 303: Divide the preprocessed data into a training set and a test set, use the training set data to train the bay ecological prediction model, adjust model parameters, and optimize model performance, and use the test set data to verify the bay ecological prediction model and evaluate the accuracy and reliability of the bay ecological prediction model.

[0025] Step 304 : Utilize the trained bay ecological prediction model and combine the acquired physical impact factors and chemical impact factors to calculate the physical impact index and the chemical impact index, and analyze the overall health status of the bay ecosystem.

[0026] A further improvement of the technical solution of the present invention is that the calculation formula of the physical impact index is:

[0027] ;

[0028] Among them, PII is the physical impact index, is the real-time measurement value of the i-th physical influencing factor, such as water temperature, salinity, tide, and water flow velocity, is the standard value of the i-th physical influencing factor, which is used to evaluate the deviation degree of the factor, is the standard deviation of the ith physical influencing factor, which is used to standardize the measured value of the factor so that it is comparable in different dimensions. is the weight of the i-th physical impact factor, which is used to adjust the contribution of different factors to the total impact index, and n is the total number of physical impact factors;

[0029] The calculation formula of the chemical impact index is:

[0030] ;

[0031] Among them, CII is the chemical impact index, which is the real-time measurement value of the jth chemical impact factor such as dissolved oxygen, pH value, nutrient concentration, heavy metal content, etc. is the standard value of the jth chemical influencing factor, is the maximum allowable deviation of the jth chemical influencing factor, which is used to evaluate whether the deviation of the factor is acceptable. is the weight of the jth chemical impact factor, which is used to adjust the contribution of different factors to the total impact index, and m is the total number of chemical impact factors.

[0032] A further improvement of the technical solution of the present invention is that in step 4, the process of obtaining the bay ecological health assessment coefficient is:

[0033] Step 401 , combining the physical impact index and the chemical impact index based on the pre-processed historical data to analyze the correlation between the bay ecosystem health and the physical impact index and the chemical impact index;

[0034] Step 402: Calculate the standardized value of each factor based on the screened physical impact index and chemical impact index, assign different weights to the physical impact index and chemical impact index, and perform a weighted summation of the two indices to obtain the bay ecological health assessment coefficient and predict the development trend of the bay ecosystem health;

[0035] Step 403: Based on the bay ecological health assessment coefficient and combined with historical data, the warning level of the bay ecosystem health is divided into blue warning level, yellow warning level, orange warning level and red warning level, wherein the warning level increases from blue warning level to red warning level;

[0036] In step 404, it is determined whether the current bay ecosystem health warning level matches the bay ecosystem health assessment coefficient, and a corresponding warning assessment threshold is set.

[0037] A further improvement of the technical solution of the present invention is that the calculation formula of the bay ecological health assessment coefficient is:

[0038] ;

[0039] Among them, EHAC is the Bay Ecological Health Assessment Coefficient, PII is the Physical Impact Index, and CII is the Chemical Impact Index. It is the benchmark value of the physical impact index, which means a reference value or average value of the physical impact index under ideal conditions or in historical data. It is the baseline value of the chemical impact index, which means a reference value or average value of the chemical impact index under ideal conditions or historical data. is a function of the physical impact index, used to adjust or standardize the value of the physical impact index to make it more consistent with the evaluation requirements. A function related to the chemical impact index that is used to adjust or normalize the value of the chemical impact index.

[0040] A further improvement of the technical solution of the present invention is that: the multiple warning levels correspond to multiple warning assessment thresholds, wherein the warning assessment thresholds include an upper threshold and a lower threshold;

[0041] The multiple warning levels and the multiple warning assessment thresholds satisfy the following relationship:

[0042] Blue alert level ;

[0043] Yellow warning level ;

[0044] Orange alert level ;

[0045] Red alert level ;

[0046] Among them, EHAC is the bay ecological health assessment coefficient, A is the upper threshold corresponding to the blue warning level and the lower threshold corresponding to the yellow warning level, B is the upper threshold corresponding to the yellow warning level and the lower threshold corresponding to the orange warning level, and C is the upper threshold corresponding to the orange warning level and the lower threshold corresponding to the red warning level.

[0047] A further improvement of the technical solution of the present invention is that in step 5, the process of obtaining the warning information is as follows:

[0048] Step 501: input the pre-processed real-time data into the bay ecological prediction model, calculate the physical impact index and chemical impact index respectively, and obtain the bay ecological health assessment coefficient;

[0049] Step 502: determining a corresponding warning level of the bay ecosystem health based on matching the obtained bay ecological health assessment coefficient with a preset warning assessment threshold;

[0050] Step 503: Generate corresponding warning information based on the predicted warning level, formulate specific response measures, and transmit the warning information to the corresponding departments and the public. For example, the warning information will be promptly conveyed to the environmental protection department, marine management department, fishery department and other relevant functional departments through the internal office system of each department, SMS platform, telephone conference, etc.

[0051] Due to the adoption of the above technical solution, the present invention has the following technical advancements compared to the prior art:

[0052] The present invention provides a trend prediction and early warning method for bay ecosystem health assessment. By constructing a bay ecological prediction model, based on historical data and real-time monitoring information, a trend prediction of the ecosystem health status in the future period is made, enabling relevant departments and the public to take action before problems occur and effectively prevent potential ecological risks.

[0053] The present invention provides a trend prediction and early warning method applied to the health assessment of bay ecosystems. By constructing a comprehensive bay ecosystem health assessment indicator system and combining the physical impact index and the chemical impact index, the health status of the bay ecosystem is more comprehensively assessed. Not only the impact of a single indicator is considered, but multiple indicators are integrated together through a comprehensive index method, which helps management departments to more accurately understand the health status of the bay ecosystem and thus formulate more effective protection and management measures.

[0054] The present invention provides a trend prediction and early warning method for evaluating the health of the bay ecosystem. Through long-term monitoring and trend analysis of both physical and chemical impacts, it can identify changing trends in the health of the bay ecosystem in advance and issue early warning signals in a timely manner. By setting different early warning levels, preventive measures can be taken in advance to avoid further deterioration of the health of the ecosystem, which helps to promptly discover potential problems, take targeted response measures, and reduce damage to the ecosystem. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0056] Figure 1 is a flow chart of the method of the present invention;

[0057] Figure 2 The flowchart of obtaining the physical influencing factors and chemical influencing factors of the present invention is as follows;

[0058] Figure 3 This is a flow chart for obtaining the bay ecological health assessment coefficient of the present invention. DETAILED DESCRIPTION

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0060] Example 1, as Figures 1 to 3 As shown, the present invention provides a trend prediction and early warning method for bay ecosystem health assessment, comprising the following steps:

[0061] Step 1: Collect monitoring data of the bay ecology and divide the monitoring data into historical data and real-time data. The monitoring data includes water quality data, bottom sediment data and hydrometeorological data. Water quality data includes dissolved oxygen, pH value, temperature, salinity, nutrients, heavy metal content, etc. Bottom sediment data includes the composition of bottom mud, organic matter content, heavy metal deposition, etc. Hydrometeorological data includes tides, water flow velocity, wind direction, wind speed, precipitation, etc. The acquisition process of the bay ecological monitoring data is as follows: according to the geographical characteristics of the bay, the direction of water flow and the distribution of surrounding pollution sources, multiple monitoring stations are set up, and sensors and monitoring equipment are installed at the monitoring stations to collect water quality data in real time. , bottom sediment data and hydrological and meteorological data, and transmit them wirelessly to the data center for real-time processing and storage. Sensors include temperature sensors, salinity sensors, dissolved oxygen sensors, etc. Monitoring equipment includes water quality analyzers, bottom sediment samplers, hydrological and meteorological monitors, etc. Historical data are collected from previous research reports, monitoring records and public official databases, and the historical data are sorted, verified and archived to ensure the integrity and reliability of the data. The acquired historical data and real-time data are classified and stored according to time series and data type. At the same time, a data recovery mechanism is established and the database is backed up regularly to ensure timely recovery in case of data loss or damage;

[0062] Step 2: Preprocess the collected monitoring data and screen the influencing factors of the bay ecosystem. The influencing factors of the bay ecosystem include physical influencing factors and chemical influencing factors. Physical influencing factors include water temperature, salinity, tide, water flow velocity, etc., and chemical influencing factors include dissolved oxygen, pH value, nutrient concentration, heavy metal content, etc. The process of obtaining the influencing factors of the bay ecosystem is as follows: data cleaning, data standardization, data integration and preprocessing of the collected historical data and real-time data, screening and extracting the physical influencing factors based on the water temperature, salinity, tide, water flow velocity, wind direction and wind speed of the bay ecosystem, and performing feature screening and extraction based on the dissolved oxygen, pH value, nutrient concentration such as nitrogen, phosphorus and heavy metal content of the bay ecosystem to obtain chemical influencing factors. Based on the obtained physical and chemical influencing factors, the correlation between the influencing factors is analyzed.

[0063] Step 3: Use the pre-processed historical data and the bay ecosystem influencing factors to build a bay ecological prediction model, obtain the physical impact index and the chemical impact index, and analyze the overall health status of the bay ecosystem. For example, when the physical impact index and the chemical impact index are both at a low level, it indicates that the overall health status of the bay ecosystem is good; conversely, if the index is high, it means that the ecosystem may be facing greater pressure. The process of obtaining the physical impact index and the chemical impact index is as follows: integrate the associated data of the physical impact factors and the chemical impact factors in the pre-processed historical data to form a unified data set, perform time series analysis on the physical impact factors and the chemical impact factors, analyze the changing trends of the physical impact factors and the chemical impact factors over time, and build a bay ecological prediction model at the same time. Divide the pre-processed data into a training set and a test set, use the training set data to train the bay ecological prediction model, adjust the model parameters, optimize the model performance, use the test set data to verify the bay ecological prediction model, evaluate the accuracy and reliability of the bay ecological prediction model, use the trained bay ecological prediction model and combine it with the obtained physical impact factors and chemical impact factors to calculate the physical impact index and the chemical impact index, and analyze the overall health status of the bay ecosystem.

[0064] Step 4: Based on the physical impact index and chemical impact index, obtain the bay ecological health assessment coefficient, predict the development trend of the bay ecosystem health, including the trend of changes in health status, the time of emergence of potential problems, etc., and determine the early warning level of the bay ecosystem health in combination with historical data, such as blue warning, the ecosystem health is good, but attention should be paid to potential risks, yellow warning, the ecosystem health has declined to a certain extent, and preventive measures should be taken, orange warning, the ecosystem health is poor, and immediate repair measures should be taken, and red warning, the ecosystem health has seriously deteriorated, and the emergency response mechanism needs to be urgently activated, and the corresponding early warning assessment threshold is set at the same time; the process of obtaining the bay ecological health assessment coefficient is as follows: according to the pre-processed historical data, the physical impact index and chemical impact index are combined to obtain the bay ecological health assessment coefficient. Combined, the correlation between the health of the bay ecosystem and the physical impact index and the chemical impact index was analyzed. Based on the screened physical impact index and chemical impact index, the standardized value of each factor was calculated, different weights were assigned to the physical impact index and the chemical impact index, and the two indices were weighted and summed to obtain the bay ecological health assessment coefficient. The development trend of the health of the bay ecosystem was predicted. Based on the bay ecological health assessment coefficient and combined with historical data, the early warning level of the bay ecosystem health was divided into blue warning level, yellow warning level, orange warning level and red warning level. Among them, the warning level increases step by step from blue warning level to red warning level. The current bay ecosystem health warning level will be determined to match the bay ecological health assessment coefficient, and the corresponding early warning assessment threshold will be set;

[0065] Step 5: Determine the corresponding warning level for the health of the bay ecosystem based on the bay ecological prediction model and generate corresponding warning information. The warning information should include the warning level, the potentially affected areas, changes in major ecological factors, and recommended response measures, so that relevant departments and the public can take timely action and be reminded to take corresponding targeted response measures, such as strengthening pollution control, carrying out ecological restoration, and strengthening monitoring and assessment. The process of obtaining warning information is as follows: input the preprocessed real-time data into the bay ecological prediction model, calculate the physical impact index and chemical impact index respectively, and obtain the bay ecological health assessment coefficient. Based on the obtained bay ecological health assessment coefficient and the preset warning assessment threshold, the corresponding warning level for the health of the bay ecosystem is determined. Based on the predicted warning level, corresponding warning information is generated and specific response measures are formulated. At the same time, the warning information is transmitted to the relevant departments and the public, such as the environmental protection department, marine management department, fishery department, etc. through internal office systems of each department, text message platforms, telephone conferences, etc.

[0066] Example 2, as Figures 1 to 3As shown, based on Example 1, the present invention provides a technical solution: Preferably, the calculation formula of the physical impact index is:

[0067] ;

[0068] Among them, PII is the physical impact index, is the real-time measurement value of the i-th physical influencing factor, such as water temperature, salinity, tide, and water flow velocity, is the standard value of the i-th physical influencing factor, which is used to evaluate the deviation degree of the factor, is the standard deviation of the ith physical influencing factor, which is used to standardize the measured value of the factor so that it is comparable in different dimensions. is the weight of the i-th physical impact factor, which is used to adjust the contribution of different factors to the total impact index, and n is the total number of physical impact factors;

[0069] The calculation formula of chemical impact index is:

[0070] ;

[0071] Among them, CII is the chemical impact index, which is the real-time measurement value of the jth chemical impact factor such as dissolved oxygen, pH value, nutrient concentration, heavy metal content, etc. is the standard value of the jth chemical influencing factor, is the maximum allowable deviation of the jth chemical influencing factor, which is used to evaluate whether the deviation of the factor is acceptable. is the weight of the jth chemical impact factor, which is used to adjust the contribution of different factors to the total impact index, and m is the total number of chemical impact factors;

[0072] The calculation formula for the bay ecological health assessment coefficient is:

[0073] ;

[0074] Among them, EHAC is the Bay Ecological Health Assessment Coefficient, PII is the Physical Impact Index, and CII is the Chemical Impact Index. It is the benchmark value of the physical impact index, which means a reference value or average value of the physical impact index under ideal conditions or in historical data. It is the baseline value of the chemical impact index, which means a reference value or average value of the chemical impact index under ideal conditions or historical data. is a function of the physical impact index, used to adjust or standardize the value of the physical impact index to make it more consistent with the evaluation requirements. is a function related to the chemical impact index, used to adjust or standardize the value of the chemical impact index;

[0075] Multiple warning levels correspond to multiple warning assessment thresholds, where the warning assessment thresholds include an upper threshold and a lower threshold;

[0076] Multiple warning levels and multiple warning assessment thresholds satisfy the following relationship:

[0077] Blue alert level ;

[0078] Yellow warning level ;

[0079] Orange alert level ;

[0080] Red alert level ;

[0081] Among them, EHAC is the bay ecological health assessment coefficient, A is the upper threshold corresponding to the blue warning level and the lower threshold corresponding to the yellow warning level, B is the upper threshold corresponding to the yellow warning level and the lower threshold corresponding to the orange warning level, and C is the upper threshold corresponding to the orange warning level and the lower threshold corresponding to the red warning level.

[0082] The above are only specific embodiments of the present application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A trend prediction and early warning method for bay ecosystem health assessment, characterized by: The following steps are involved: Step 1: Collect monitoring data of the bay ecology and divide the monitoring data into historical data and real-time data, where the monitoring data includes water quality data, bottom sediment data, and hydrological and meteorological data; Step 2: pre-process the collected monitoring data to screen the factors affecting the bay ecosystem, where the factors affecting the bay ecosystem include physical factors and chemical factors; Step 3: Using the pre-processed historical data and the factors affecting the bay ecosystem, a bay ecological prediction model is constructed to obtain the physical impact index and chemical impact index to analyze the overall health status of the bay ecosystem; Step 4: Based on the physical impact index and chemical impact index, obtain the bay ecological health assessment coefficient, predict the development trend of the bay ecosystem health, and determine the early warning level of the bay ecosystem health in combination with historical data, and set the corresponding early warning assessment threshold; Step 5: Determine the corresponding warning level of the bay ecosystem health based on the bay ecological prediction model, generate corresponding warning information, and remind relevant departments and the public to take corresponding targeted response measures.

2. The trend prediction and early warning method for bay ecosystem health assessment according to claim 1, characterized in that: In step 1, the process of acquiring the bay ecological monitoring data is as follows: Step 101: Based on the geographical characteristics of the bay, the direction of water flow, and the distribution of surrounding pollution sources, multiple monitoring stations are established. Sensors and monitoring equipment are installed at the monitoring stations to collect real-time water quality data, bottom sediment data, and hydrological and meteorological data. The data is then wirelessly transmitted to a data center for real-time processing and storage. Step 102: Collect historical data from previous research reports, monitoring records, and public official databases, and organize, verify, and archive the historical data; Step 103: The acquired historical data and real-time data are classified and stored according to time series and data type, and a data recovery mechanism is established to regularly back up the database.

3. The trend prediction and early warning method for bay ecosystem health assessment according to claim 1 is characterized by: In step 2, the process of obtaining the impact factors of the bay ecosystem is as follows: Step 201: performing data cleaning, data standardization, data integration and preprocessing on the collected historical data and real-time data; Step 202 , screening and extracting the water temperature, salinity, tide, water velocity, wind direction, and wind speed of the bay ecosystem to obtain physical influencing factors; Step 203 , performing feature screening and extraction based on the dissolved oxygen, pH value, nutrient concentration, and heavy metal content of the bay ecosystem to obtain chemical influencing factors; Step 204 : Analyze the correlation between the influencing factors based on the acquired physical influencing factors and chemical influencing factors.

4. The trend prediction and early warning method for bay ecosystem health assessment according to claim 1 is characterized by: In step 3, the process of obtaining the physical impact index and the chemical impact index is as follows: Step 301: Integrate the correlation data of physical influencing factors and chemical influencing factors in the pre-processed historical data to form a unified data set; Step 302 , performing a time series analysis on the physical and chemical influencing factors, analyzing the temporal trends of the physical and chemical influencing factors, and constructing a bay ecological prediction model; Step 303: Divide the preprocessed data into a training set and a test set, use the training set data to train the bay ecological prediction model, adjust the model parameters, and optimize the model performance, and use the test set data to verify the bay ecological prediction model and evaluate the accuracy and reliability of the bay ecological prediction model. Step 304 : Utilize the trained bay ecological prediction model and combine the acquired physical impact factors and chemical impact factors to calculate the physical impact index and the chemical impact index, and analyze the overall health status of the bay ecosystem.

5. The trend prediction and early warning method for bay ecosystem health assessment according to claim 4 is characterized by: The calculation formula of the physical impact index is: ； Among them, PII is the physical impact index, is the ith physical impact factor, is the standard value of the ith physical impact factor, is the standard deviation of the ith physical influencing factor, is the weight of the ith physical impact factor, and n is the total number of physical impact factors; The calculation formula of the chemical impact index is: ； Among them, CII is the chemical impact index, which is the real-time measurement value of the j-th chemical impact factor. is the standard value of the jth chemical influencing factor, is the maximum allowable deviation of the jth chemical influencing factor, is the weight of the jth chemical influencing factor, and m is the total number of chemical influencing factors.

6. The trend prediction and early warning method for bay ecosystem health assessment according to claim 5 is characterized by: In step 4, the process of obtaining the bay ecological health assessment coefficient is as follows: Step 401 , combining the physical impact index and the chemical impact index based on the pre-processed historical data to analyze the correlation between the bay ecosystem health and the physical impact index and the chemical impact index; Step 402: Calculate the standardized value of each factor based on the screened physical impact index and chemical impact index, assign different weights to the physical impact index and chemical impact index, and perform a weighted summation of the two indices to obtain the bay ecological health assessment coefficient and predict the development trend of the bay ecosystem health; Step 403: Based on the bay ecological health assessment coefficient and combined with historical data, the warning level of the bay ecosystem health is divided into blue warning level, yellow warning level, orange warning level and red warning level, wherein the warning level increases from blue warning level to red warning level; In step 404, it is determined whether the current bay ecosystem health warning level matches the bay ecosystem health assessment coefficient, and a corresponding warning assessment threshold is set.

7. The trend prediction and early warning method for bay ecosystem health assessment according to claim 6, characterized in that: The calculation formula of the bay ecological health assessment coefficient is: ； Among them, EHAC is the Bay Ecological Health Assessment Coefficient, PII is the Physical Impact Index, and CII is the Chemical Impact Index. is the base value of the physical impact index, is the baseline value of the chemical impact index, is a function of the physical impact index, is a function of the chemical impact index.

8. The trend prediction and early warning method for bay ecosystem health assessment according to claim 7 is characterized by: The plurality of warning levels correspond to a plurality of warning assessment thresholds, wherein the warning assessment thresholds include an upper threshold and a lower threshold; The multiple warning levels and the multiple warning assessment thresholds satisfy the following relationship: Blue alert level ; Yellow warning level ; Orange alert level ; Red alert level ; Among them, EHAC is the bay ecological health assessment coefficient, A is the upper threshold corresponding to the blue warning level and the lower threshold corresponding to the yellow warning level, B is the upper threshold corresponding to the yellow warning level and the lower threshold corresponding to the orange warning level, and C is the upper threshold corresponding to the orange warning level and the lower threshold corresponding to the red warning level.

9. The trend prediction and early warning method for bay ecosystem health assessment according to claim 8, characterized in that: In step 5, the process of obtaining the warning information is as follows: Step 501: input the pre-processed real-time data into the bay ecological prediction model, calculate the physical impact index and chemical impact index respectively, and obtain the bay ecological health assessment coefficient; Step 502: determining a corresponding warning level of the bay ecosystem health based on matching the obtained bay ecological health assessment coefficient with a preset warning assessment threshold; Step 503: Generate corresponding warning information based on the predicted warning level, formulate specific response measures, and transmit the warning information to corresponding departments and the public.

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