Ecological risk prediction method for offshore floating structure

Abstract

The invention relates to the technical field of offshore floating structures, in particular to an offshore floating structure ecological risk prediction method which comprises the following steps: S1, data collection: collecting environmental data around an offshore floating structure; s2, data preprocessing: preprocessing the collected environment data; s3, sediment ecotoxicity analysis: evaluating the influence of pollutants in the sediment on marine organisms and the ecological environment; s4, establishing an ecological risk model: predicting the ecological risk of the offshore floating structure; s5, model training and verification: adjusting ecological risk model parameters; s6, risk assessment: predicting the risk of the marine floating structure to the surrounding ecological environment; and S7, report generation: generating an ecological risk assessment report based on a risk prediction result output by the ecological risk model. According to the method, the potential risk of the marine floating structure to the surrounding ecological environment can be comprehensively and accurately predicted.

Description

Technical Field

[0001] The invention relates to the technical field of offshore floating structures, and in particular to an ecological risk prediction method for offshore floating structures. Background Art

[0002] With the continuous deepening of ocean development and utilization, offshore floating structures (such as offshore wind power platforms, marine aquaculture facilities and marine observatories) are widely used around the world. However, while these structures bring economic and social benefits, they also pose potential risks and impacts on the marine ecological environment. For example, floating structures may cause changes in seawater flow and sediment distribution, causing accumulation of pollutants in local sea areas, and further affecting the survival and reproduction of surrounding marine organisms. Therefore, it is particularly important to evaluate and predict the risks of offshore floating structures to the ecological environment.

[0003] Existing ecological risk assessment methods usually focus on the analysis of a single factor and lack the comprehensive integration of multidimensional environmental data, and are unable to accurately predict the diffusion of pollutants and biological exposure processes in complex marine ecosystems. In addition, traditional models often ignore the transmission of pollutants in the food chain and the biomagnification effect, resulting in greater uncertainty in risk assessment results.

[0004] The present invention provides an ecological risk prediction method for offshore floating structures, which aims to comprehensively evaluate and predict the impact of offshore floating structures on the surrounding ecological environment by integrating multiple environmental data and advanced ecological risk models. Summary of the invention

[0005] Based on the above purpose, the present invention provides a method for predicting ecological risks of offshore floating structures.

[0006] The ecological risk prediction method of offshore floating structures includes the following steps: S1, Data Collection: Collect environmental data around offshore floating structures through a variety of sensors and remote sensing technologies. Environmental data include water quality parameters, biodiversity data, meteorological data, and ocean dynamics data; S2, data preprocessing: preprocessing the collected environmental data, including cleaning, noise reduction and completion; S3, Sediment Ecotoxicity Analysis: Collect seabed sediment samples around offshore floating structures for chemical and ecotoxicity analysis to assess the impact of pollutants in sediments on marine organisms and the ecological environment, and predict the diffusion path and ecological impact of sediment pollution by establishing a sediment-organism model; S4, Establishing an ecological risk model: Based on the results of sediment ecotoxicity analysis, an ecological risk model is constructed to predict the ecological risks of offshore floating structures; S5, model training and verification: use historical data and experimental data to train and verify the constructed ecological risk model, and adjust the parameters of the ecological risk model; S6, risk assessment: input the pre-processed environmental data into the trained ecological risk model to predict the risk of offshore floating structures to the surrounding ecological environment; S7, report generation: Generate an ecological risk assessment report based on the risk prediction results output by the ecological risk model, including risk level, impact scope and recommended measures.

[0007] Furthermore, the data collection in S1 includes: Water quality parameter monitoring: Use water quality sensors (such as multi-parameter water quality detectors) to monitor the temperature, salinity, pH value, dissolved oxygen concentration, ammonia nitrogen content, nitrate and phosphate concentration in seawater, and obtain real-time data on changes in water quality parameters; Biodiversity data survey: Record and analyze the species, quantity and distribution of organisms around floating structures at sea through underwater cameras, acoustic monitoring equipment and environmental DNA (eDNA) sampling technology; Meteorological data collection: using meteorological stations and satellite remote sensing technology to collect wind speed, wind direction, temperature, rainfall and solar radiation intensity in the area where the offshore floating structure is located; Ocean dynamics data acquisition: Using wave buoys, tide gauges, and current meters to measure the height, period, tidal changes, current speed, and direction of ocean waves.

[0008] Furthermore, the sediment ecotoxicity analysis in S3 includes: S31, Sediment Collection: Collect seafloor sediment samples in the area around the offshore floating structure using a sediment trap; S32, chemical analysis: chemical analysis of the collected sediment samples to detect the content of pollutants in the sediments, including heavy metals, organic pollutants, and microplastics, and quantitatively analyze the composition and concentration of pollutants; S33, Ecotoxicity Test: Conduct ecotoxicity tests on sediment samples to evaluate the toxic effects of pollutants in sediment samples on marine organisms. Use biological indicator species (such as marine copepods, benthic organisms, etc.) to conduct biological toxicity experiments and determine ecotoxicity indicators, including lethal concentration and growth inhibition rate; S34, Sediment-Organism Model Establishment: Based on the results of chemical analysis and ecotoxicity testing, a sediment-organism model is established to simulate the diffusion path and ecological impact of pollutants in sediments, consider sediment particle migration, pollutant release and biological exposure mechanisms, and predict the spread and impact of sediment pollutants in the ecological environment.

[0009] Furthermore, the sediment collection in S31 includes: S311, Locate sampling points: Determine sediment sampling points in the area around the floating structure at sea based on ocean dynamics data and environmental conditions; S312, sediment trap selection: select a sediment trap, including a box-type mud sampler, a grab bucket mud sampler or a columnar mud sampler, and select the corresponding sediment trap according to the sediment type and sampling depth; S313, sediment collection: placing sediment traps at the determined sediment sampling points, operating the sediment traps to sink to the seafloor, and closing the traps by mechanical or hydraulic equipment; S314, sample processing: lifting the captured sediment samples to the sea surface to avoid loss or contamination of the sediment samples, and then transferring the sediment samples to the preset sampling containers, and numbering and recording them; S315, Sample preservation and transportation: Preservation of collected sediment samples, including refrigeration and sealing.

[0010] Further, the chemical analysis in S32 includes: S321, Sample processing: homogenize, dry, grind and sieve the collected sediment samples in preparation for chemical analysis; S322, heavy metal detection: Use strong acid (such as a mixture of nitric acid, hydrochloric acid and hydrofluoric acid) to digest the sediment sample at high temperature and high pressure, and use inductively coupled plasma optical emission spectrometry (ICP-OES) to detect the digested solution and quantitatively analyze the content of heavy metals in the sample. The calculation formula is: ; in, is the heavy metal concentration, is the signal intensity of the sample, is the signal intensity of the blank sample, is the slope of the standard curve; S323, organic pollutant detection: Use a solvent (such as dichloromethane or n-hexane) to perform Soxhlet extraction on the organic pollutants in the sediment sample, dissolve the organic pollutants in the organic solvent, purify the extract by gel permeation chromatography, remove interfering substances, obtain the organic pollutant extract, and use gas chromatography-mass spectrometry (GC-MS) to detect the purified organic pollutant extract, quantitatively analyze the organic pollutants in the sample, and quantify the concentration of organic pollutants by the internal standard method. The calculation formula is: ; in, is the concentration of organic pollutants, is the peak area of ​​organic pollutants in the sample, is the peak area of ​​the internal standard, is the internal standard correction factor; S324, Microplastic Detection: Microplastic particles are separated from sediments by flotation, and microplastic particles are floated by high-density solution (such as zinc chloride solution) to separate them. The morphology of microplastic particles is observed by microscope, and chemical composition is identified by Fourier transform infrared spectrometer (FTIR). The number and mass of microplastic particles are counted, and the content of microplastic particles in sediments is calculated. The calculation formula is: ; in, is the concentration of microplastics, is the number of separated microplastic particles, is the mass of the sediment sample.

[0011] Furthermore, the ecotoxicity test in S33 includes: S331, Selection of biological indicator species: Select biological indicator species for ecotoxicity testing. Biological indicator species include marine copepods (e.g. marine copepods) and benthic organisms (e.g. Daphnia, worms, etc.); S332, sediment sample preparation: the collected sediment samples are mixed with seawater in a predetermined ratio to prepare sediment suspensions of different concentrations for ecotoxicity testing; S333, Experimental design: Design an experimental group and a control group. The experimental group is set with sediment suspensions of different concentration gradients, and the control group uses uncontaminated sediments; S334, toxicity test: placing biological indicator species in experimental and control groups, observing and recording biological responses within a predetermined time (e.g., 24 hours, 48 ​​hours, 96 hours), and determining ecotoxicity indicators, including lethal concentration LC50 test and growth inhibition rate test, among which; The lethal concentration LC50 test records the sediment concentration when 50% of the biological individuals in the experimental group die, and calculates the lethal concentration LC50. The calculation formula is: ; in, is the sediment concentration for each concentration group, is the number of dead organisms in this concentration group, and N is the total number of organisms in all experimental groups; The growth inhibition test measures the growth changes of biological indicator species in sediment suspensions of different concentrations and calculates the growth inhibition rate. The calculation formula is: ; in, is the growth of organisms in the experimental group, is the growth of organisms in the control group; S335, Data Analysis: Perform statistical analysis on experimental data, compare the survival and growth rates of bio-indicator species at different concentrations, draw dose-response curves, and evaluate the toxicity intensity of pollutants in sediments.

[0012] Furthermore, the establishment of the sediment-organism model in S34 includes: S341, Data Integration: Integrate the results of sediment chemical analysis and ecotoxicity testing, including the types, concentrations, and ecotoxicity indicators of pollutants in sediments, as basic data for the sediment-organism model; S342, Model Construction: Based on the mechanisms of sediment particle migration, pollutant release and biological exposure, a sediment-organism model is constructed to simulate the diffusion path and ecological impact of pollutants in sediments, including; The sediment particle migration uses the sediment dynamics equation to simulate the migration of sediment particles in the water body, taking into account the factors of water flow, waves and sedimentation. The calculation formula is: ; in, is the sediment particle concentration, is the water velocity vector, is the sediment diffusion coefficient, is the sediment settling rate; The pollutant release is calculated by simulating the release process of pollutants from sediment particles, taking into account the factors of desorption, diffusion and bioturbation. The release rate is calculated as follows: ; in, is the pollutant release rate, is the release rate constant, is the pollutant concentration in the sediment, is the sediment porosity; The biological exposure mechanism simulates the process of marine organisms being exposed to pollutants through ingestion, respiration and skin contact through a biological exposure model. The calculation formula is: ; in, is the biological exposure dose, , , are the pollutant concentrations in water, sediment, and organisms, respectively. , , They are the water ingestion rate, sediment ingestion rate, and skin absorption rate; S343, model calibration: using real-time sediment samples to calibrate the sediment-organism model and adjust the model parameters of the sediment-organism model; S344, simulation prediction: Use the calibrated sediment-organism model to simulate the diffusion path and impact range of pollutants in sediments in the ecological environment and predict the ecological impact of pollutants; S345, Result Analysis and Application: Evaluate the spread and impact of pollutants in the marine ecological environment based on the results of sediment-organism model simulation.

[0013] Furthermore, the ecological risk model in S4 adopts a food web model, and the food web model includes: S41, initial setting of pollutant concentration: Set the initial pollutant concentration in seawater and sediment for the initial conditions of the ecological risk model. The calculation formula is: ; ; in, and are the initial pollutant concentrations in seawater and sediment, respectively, and is the initial concentration actually monitored; S42, Dynamic changes of pollutants in seawater and sediments: Simulate the diffusion, adsorption and desorption of pollutants in seawater and sediments, taking into account the water flow and sediment dynamics. The calculation formula is: ; ; in, is the adsorption rate constant, is the desorption rate constant, is the diffusion coefficient in water, is the deposition rate; S43, Bioabsorption and Biomagnification: Simulate the accumulation and biomagnification effect of pollutants in organisms through ingestion and respiration. The calculation formula is: ; in, is the pollutant concentration in the i-th organism, is the absorption rate constant in water, is the absorption rate constant in the sediment, is the feeding rate of the ith organism, is the deposition rate constant, is the excretion rate constant; S44, Pollutant transfer in the food chain: simulate the transfer of pollutants in the food chain, taking into account the biomagnification effect between different trophic levels. The calculation formula is: ; in, is the pollutant concentration in the i-th organism, is the pollutant concentration in the jth organism, is the biomagnification factor from the jth organism to the ith organism; S45, Ecological Risk Assessment: Assess the impact of pollutant concentrations in organisms on the ecological environment and predict the ecological risk of offshore floating structures. The calculation formula is: ; in, is the ecological risk value of the i-th organism, is the pollutant concentration in the i-th organism, is the toxicity threshold of the i-th organism.

[0014] Furthermore, the model training and verification in S5 includes: S51, Data Preparation: Collect and organize historical data and experimental data, including historical monitoring of pollutant concentrations in sediments and water bodies, pollutant accumulation data in organisms, and ecotoxicity experimental results; S52, initial model parameter setting: according to the existing experimental and preliminary analysis results, the initial parameters of the ecological risk model are set, including pollutant diffusion coefficient, adsorption and desorption rate, biological absorption and excretion rate; S53, model training: historical data and experimental data are input into the ecological risk model to simulate the distribution and transfer process of pollutants in sediments, water bodies and organisms. The prediction results of the ecological risk model are compared with the actual data, and the prediction error is calculated by the root mean square error (RMSE) and the mean absolute percentage error (MAPE). The calculation formula is: ; ; in, is the value of the ith data point predicted by the ecological risk model, is the value of the ith data point actually monitored, and n is the total number of data points; S54, parameter adjustment: According to the error analysis results, adjust the ecological risk model parameters to reduce the prediction error. The calculation formula is: ; in, is the adjusted parameter value, is the parameter value before adjustment, For actual monitoring data, Predict results for ecological risk models; S55, Model Validation: Use independent data sets from different times or locations as validation data, input the validation data into the trained ecological risk model, run simulations and predict the diffusion path and biological exposure of pollutants, compare the actual test data of the validation data with the prediction results of the ecological risk model, evaluate the prediction performance and reliability of the ecological risk model, and calculate the validation error. The validation formula is: ; S56, Model optimization: Optimize ecological risk model parameters based on validation errors and performance evaluation results.

[0015] Furthermore, the risk assessment in S6 includes: S61, Data input: Input the preprocessed environmental data into the trained and validated ecological risk model; S62, model operation: Run the ecological risk model to simulate the diffusion path, transfer process and accumulation of pollutants in sediments, water bodies and organisms; S63, Pollutant diffusion and absorption simulation: Use ecological risk models to simulate the diffusion of pollutants in water and sediments, as well as the absorption and biomagnification effects in organisms, to generate pollutant concentration distribution data at different time points; S64, Food Chain Transfer Simulation: Simulate the transfer process of pollutants in the food chain, consider the biomagnification effect between different trophic levels, and calculate the concentration of pollutants in each organism; S65, Ecological Risk Assessment: Calculate the ecological risk value of each organism based on the pollutant concentration data output by the ecological risk model , assess the toxic effects of pollutants on organisms, based on the calculated ecological risk value , classify ecological risks into different levels, and identify risk areas and biological groups at different levels; S66, Impact Scope Analysis: Analyze the scope and intensity of the impact of pollutants on different ecological and environmental components (such as fish, benthic organisms, plankton, etc.).

[0016] Beneficial effects of the present invention: The present invention collects multi-dimensional environmental data including water quality parameters, biodiversity data, meteorological data and ocean dynamics data through a variety of sensors and remote sensing technologies to ensure the comprehensiveness and accuracy of the data. Through systematic pretreatment and sediment ecotoxicity analysis, the impact of pollutants in sediments on marine organisms and the ecological environment is evaluated. The diffusion path and ecological impact of pollutants are simulated through a sediment-organism model, which can comprehensively and accurately predict the potential risks of offshore floating structures to the surrounding ecological environment.

[0017] The present invention combines the results of sediment ecotoxicity analysis through a food web model, can more accurately simulate the dynamic changes of pollutants in water bodies, sediments and organisms, takes into account the adsorption, desorption, diffusion of pollutants and their accumulation and biomagnification effects in organisms, and through model training and verification, uses historical data and experimental data to calibrate and optimize model parameters to ensure the high accuracy and reliability of the model. The model can predict the transfer process of pollutants in the food chain, evaluate the toxic effects of pollutants on organisms at different trophic levels, and provide scientific ecological risk assessment.

[0018] The present invention generates a detailed ecological risk assessment report by inputting the pre-processed environmental data into the trained and verified ecological risk model, running the model to simulate the diffusion path and impact range of pollutants in the ecological environment. This method can identify high-risk areas and biological populations, provide the diffusion path and concentration distribution data of pollutants, analyze the impact of pollutants on different ecosystem components, provide an important scientific basis for environmental protection and management decisions, and improve the accuracy and reliability of predictions. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 A schematic diagram of a prediction method flow chart of an embodiment of the present invention; Figure 2 Schematic diagram of sediment ecotoxicity analysis according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0022] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0023] like Figure 1-Figure 2 As shown, the method for predicting ecological risks of offshore floating structures includes the following steps: S1, Data Collection: Collect environmental data around offshore floating structures through a variety of sensors and remote sensing technologies. Environmental data include water quality parameters, biodiversity data, meteorological data, and ocean dynamics data; S2, data preprocessing: preprocess the collected environmental data, including cleaning, noise reduction, and completion, to ensure the integrity and accuracy of the data; S3, Sediment Ecotoxicity Analysis: Collect seabed sediment samples around offshore floating structures for chemical and ecotoxicity analysis to assess the impact of pollutants in sediments on marine organisms and the ecological environment, and predict the diffusion path and ecological impact of sediment pollution by establishing a sediment-organism model; S4, Establishing an ecological risk model: Based on the results of sediment ecotoxicity analysis, an ecological risk model is constructed to predict the ecological risks of offshore floating structures; S5, model training and verification: Use historical data and experimental data to train and verify the constructed ecological risk model, adjust the parameters of the ecological risk model, and improve the prediction accuracy; S6, risk assessment: input the pre-processed environmental data into the trained ecological risk model to predict the risk of offshore floating structures to the surrounding ecological environment; S7, report generation: based on the risk prediction results output by the ecological risk model, generate an ecological risk assessment report, including risk level, impact scope and recommended measures; Through the above steps, a variety of environmental data and analysis techniques are integrated to provide a comprehensive and accurate ecological risk prediction of offshore floating structures, which will help improve the accuracy and reliability of the prediction and provide an important scientific basis for environmental protection and management decisions.

[0024] Data collection in S1 includes: Water quality parameter monitoring: Use water quality sensors (such as multi-parameter water quality detectors) to monitor the temperature, salinity, pH value, dissolved oxygen concentration, ammonia nitrogen content, nitrate and phosphate concentration in seawater, and obtain real-time data on changes in water quality parameters; Biodiversity data survey: Using underwater cameras, acoustic monitoring equipment and environmental DNA (eDNA) sampling technology, the species, quantity and distribution of organisms around floating structures at sea will be recorded and analyzed, with a particular focus on communities such as plankton, benthic organisms and fish; Meteorological data collection: using meteorological stations and satellite remote sensing technology to collect wind speed, wind direction, temperature, rainfall and solar radiation intensity in the area where the offshore floating structure is located, ensuring comprehensive coverage of changes in meteorological conditions; Ocean dynamics data acquisition: using wave buoys, tide gauges, and current meters to measure the height, period, tidal changes, current speed, and direction of ocean waves, providing detailed data support for the flow characteristics of the ocean environment; Through the comprehensive application of the above-mentioned multiple sensors and remote sensing technologies, it is possible to comprehensively and accurately collect environmental data around offshore floating structures, providing a reliable data basis for subsequent ecological risk prediction.

[0025] Sediment ecotoxicity analysis in S3 includes: S31, Sediment Collection: Collect seafloor sediment samples in the area around the offshore floating structure using sediment traps to ensure that the samples are representative and sufficient in number to reflect the characteristics of the regional sediments; S32, chemical analysis: chemical analysis of the collected sediment samples to detect the content of pollutants in the sediments, including heavy metals, organic pollutants, and microplastics, and quantitatively analyze the composition and concentration of pollutants; S33, Ecotoxicity Test: Conduct ecotoxicity tests on sediment samples to evaluate the toxic effects of pollutants in sediment samples on marine organisms. Use biological indicator species (such as marine copepods, benthic organisms, etc.) to conduct biological toxicity experiments and determine ecotoxicity indicators, including lethal concentration and growth inhibition rate; S34, Sediment-organism model establishment: Based on the results of chemical analysis and ecotoxicity testing, a sediment-organism model is established to simulate the diffusion path and ecological impact of pollutants in sediments, consider sediment particle migration, pollutant release and biological exposure mechanisms, and predict the spread and impact of sediment pollutants in the ecological environment; Through the above steps, the impact of pollutants in sediments on marine life and the ecological environment is comprehensively assessed, and their diffusion paths and long-term ecological impacts are predicted through models, providing a scientific basis for the prediction of ecological risks of offshore floating structures.

[0026] Sediment collection in S31 includes: S311, Locate sampling points: In the area around the offshore floating structure, determine the sediment sampling points based on ocean dynamics data and environmental conditions to ensure that the sediment samples reflect the characteristics of the regional sediments; The specific positioning sampling points include: Current and wave data analysis: using equipment such as current meters and wave buoys to collect ocean dynamics data such as current speed, direction and wave height, analyze water flow and energy distribution characteristics, and select areas where sediments are likely to accumulate and accumulate; Seabed topography survey: Use multi-beam sonar or side-scan sonar equipment to draw seabed topography maps, identify the ups and downs and changes in the seabed topography, and select areas with relatively flat terrain and thick sediments as sampling points; Water quality parameter monitoring: Combined with the data from water quality sensors, monitor the concentration of suspended matter and the characteristics of sediment particles in the water body, and select areas with high suspended matter concentrations and easy sedimentation; Environmental condition assessment: Considering environmental conditions such as seasonal changes, weather conditions and human activities, select areas with less external interference and long-term stability for sampling; Historical data reference: Utilize existing sediment sampling and analysis data, refer to the location and sediment characteristics of historical sampling points, and optimize the current sampling point layout; S312, sediment trap selection: select a sediment trap, including a box-type mud sampler, a grab bucket mud sampler or a columnar mud sampler, and select the corresponding sediment trap according to the sediment type and sampling depth; Sediment trap options include: Determine sediment type: Collect preliminary data on regional sediment types and determine the main sediment types (such as mud, sand, mixed sediment, etc.) through historical records or preliminary surveys; Determine sampling depth: Determine the depth of sediment to be collected (surface, shallow, deep) based on research objectives and analysis requirements; Choose the right trap: choose a box sampler for surface muddy sediments to preserve bedding, choose a grab sampler for surface mixed or coarse-grained sediments to obtain large area samples, and choose a column sampler for deep sediments to obtain a complete vertical profile; Consider equipment and operating conditions: Ensure that the selected equipment is suitable for the vessel and operating conditions to avoid equipment limitations that affect sampling effectiveness; S313, Sediment Collection: Deploy sediment traps at the determined sediment sampling points, operate the sediment traps to sink to the seafloor, ensure that the traps are fully in contact with and penetrate the sediment layer, and close the traps by mechanical or hydraulic equipment to ensure the integrity and representativeness of the sediment samples; S314, sample processing: lift the captured sediment samples to the sea surface to avoid loss or contamination of the sediment samples, then transfer the sediment samples to the preset sampling containers, number and record them to ensure that the source and characteristics of each sample are clear; S315, Sample preservation and transportation: The collected sediment samples should be preserved, including refrigeration and sealing, to ensure that the samples are not contaminated or degraded during transportation, and promptly sent to the laboratory for subsequent analysis; Through the above steps, sediment traps are used to collect seabed sediment samples in the areas surrounding offshore floating structures to ensure the representativeness and integrity of the samples, providing a reliable basis for subsequent chemical and ecotoxicity analyses.

[0027] Chemical analysis in S32 includes: S321, Sample processing: The collected sediment samples are homogenized to ensure the uniformity of the samples, and dried, ground and sieved in preparation for chemical analysis; S322, heavy metal detection: Use strong acid (such as a mixture of nitric acid, hydrochloric acid and hydrofluoric acid) to digest the sediment sample at high temperature and high pressure to ensure that the heavy metals are completely dissolved in the solution. Use inductively coupled plasma optical emission spectrometry (ICP-OES) to detect the digested solution and quantitatively analyze the content of heavy metals in the sample. The calculation formula is: ; in, is the heavy metal concentration, is the signal intensity of the sample, is the signal intensity of the blank sample, is the slope of the standard curve; The slope of the standard curve The way to obtain is as follows: (1) Prepare standard solutions of known concentrations: Prepare a series of standard solutions of known concentrations. The concentration of each solution should cover the expected range of sample concentrations. (2) Measure the signal intensity of each standard solution: Use appropriate instruments (such as spectrometer, colorimeter, conductivity meter, etc.) to measure the signal intensity of each standard solution. These signal intensities will correspond to the concentration of the solution. (3) Draw a concentration-signal intensity relationship graph: Plot the concentration of the standard solution (x-axis) and the corresponding signal intensity (y-axis) on a graph. In the graph, a trend close to a straight line will appear. (4) Calculate the slope by linear regression: Use the linear regression analysis method to fit these data points into a straight line. The equation of the line is expressed as: y=mx+b; Where y is the signal intensity, x is the concentration, and m is the slope, which represents the change in signal intensity per unit change in concentration; (5) Obtain the slope of the standard curve: The slope m calculated by regression analysis is the slope of the standard curve. ; S323, organic pollutant detection: Use a solvent (such as dichloromethane or n-hexane) to perform Soxhlet extraction on the organic pollutants in the sediment sample, dissolve the organic pollutants in the organic solvent, purify the extract by gel permeation chromatography, remove interfering substances, obtain the organic pollutant extract, and use gas chromatography-mass spectrometry (GC-MS) to detect the purified organic pollutant extract, quantitatively analyze the organic pollutants in the sample, and quantify the concentration of organic pollutants by the internal standard method. The calculation formula is: ; in, is the concentration of organic pollutants, is the peak area of ​​organic pollutants in the sample, is the peak area of ​​the internal standard, is the internal standard correction factor; S324, Microplastic Detection: Microplastic particles are separated from sediments by flotation, and microplastic particles are floated by high-density solution (such as zinc chloride solution) to separate them. The morphology of microplastic particles is observed by microscope, and chemical composition is identified by Fourier transform infrared spectrometer (FTIR). The number and mass of microplastic particles are counted, and the content of microplastic particles in sediments is calculated. The calculation formula is: ; in, is the concentration of microplastics, is the number of separated microplastic particles, is the mass of the sediment sample; Through the above steps, the collected sediment samples are chemically analyzed to detect the content of heavy metals, organic pollutants and microplastics in the sediments, and the composition and concentration of pollutants are quantitatively analyzed to provide reliable scientific data for the ecological risk prediction of offshore floating structures.

[0028] Ecotoxicity tests in S33 include: S331, Selection of biological indicator species: Select biological indicator species for ecotoxicity testing. Biological indicator species include marine copepods (e.g., marine copepods) and benthic organisms (e.g., water fleas, worms, etc.), which are sensitive to environmental pollutants and easy to culture; S332, sediment sample preparation: the collected sediment samples are mixed with seawater in a predetermined ratio to prepare sediment suspensions of different concentrations for ecotoxicity testing; S333, Experimental design: Design experimental and control groups. The experimental group is set with sediment suspensions of different concentration gradients, and the control group uses uncontaminated sediments to ensure the reliability and comparability of the experimental results; S334, toxicity test: placing biological indicator species in experimental and control groups, observing and recording biological responses within a predetermined time (e.g., 24 hours, 48 ​​hours, 96 hours), and determining ecotoxicity indicators, including lethal concentration LC50 test and growth inhibition rate test, among which; The lethal concentration LC50 test records the sediment concentration when 50% of the biological individuals in the experimental group die, and calculates the lethal concentration LC50. The calculation formula is: ; in, is the sediment concentration for each concentration group, is the number of dead organisms in this concentration group, and N is the total number of organisms in all experimental groups; The growth inhibition test measures the growth changes of biological indicator species in sediment suspensions of different concentrations and calculates the growth inhibition rate. The calculation formula is: ; in, is the growth of organisms in the experimental group, is the growth of organisms in the control group; S335, Data Analysis: Statistical analysis of experimental data, comparison of survival and growth rates of bioindicator species at different concentrations, plotting dose-response curves, and assessing the toxicity intensity of pollutants in sediments; Through the above steps, ecotoxicity tests are carried out on sediment samples using biological indicator species, and ecotoxicity indicators such as lethal concentration and growth inhibition rate are determined. The toxic effects of pollutants in sediments on marine organisms are evaluated, providing reliable biotoxicity data for ecological risk prediction of offshore floating structures.

[0029] The sediment-organism model in S34 includes: S341, Data Integration: Integrate the results of sediment chemical analysis and ecotoxicity testing, including the types, concentrations, and ecotoxicity indicators of pollutants in sediments, as basic data for the sediment-organism model; S342, Model Construction: Based on the mechanisms of sediment particle migration, pollutant release and biological exposure, a sediment-organism model is constructed to simulate the diffusion path and ecological impact of pollutants in sediments, including; Sediment particle migration uses the sediment dynamics equation to simulate the migration of sediment particles in the water body, taking into account the factors of water flow, waves and sedimentation. The calculation formula is: ; in, is the sediment particle concentration, is the water velocity vector, is the sediment diffusion coefficient, is the sediment settling rate; Pollutant release The release process of pollutants from sediment particles is simulated, taking into account the factors of desorption, diffusion and bioturbation. The release rate is calculated as follows: ; in, is the pollutant release rate, is the release rate constant, is the pollutant concentration in the sediment, is the sediment porosity; The biological exposure mechanism uses a biological exposure model to simulate the process of marine organisms being exposed to pollutants through ingestion, respiration and skin contact. The calculation formula is: ; in, is the biological exposure dose, , , are the pollutant concentrations in water, sediment, and organisms, respectively. , , They are the water ingestion rate, sediment ingestion rate, and skin absorption rate; S343, Model calibration: Use real-time sediment samples to calibrate the sediment-organism model, adjust the model parameters of the sediment-organism model, and ensure the accuracy and reliability of the model; Model calibration and validation specifically include: S3431, Real-time sediment sample collection and processing: Regularly collect sediment samples in the area around the offshore floating structure, process and analyze the samples to obtain pollutant concentration data and sediment characteristics data; S3432, Initial model parameter setting: Based on the results of chemical analysis and ecotoxicity testing, set the initial parameters of the sediment-organism model, including sediment diffusion coefficient, pollutant release rate, and biological exposure rate; S3433, model calibration: input the pollutant concentration and sediment characteristic data in the real-time sediment sample into the model, run the initial sediment-organism model, simulate the diffusion path of pollutants and biological exposure, compare the simulation results output by the model with the real-time sediment sample data, calculate the prediction error, and gradually adjust the model parameters such as sediment diffusion coefficient, pollutant release rate and biological exposure rate according to the error analysis results, so that the model prediction results are more consistent with the actual monitoring data. The adjustment formula is: ; in, is the adjusted parameter value, is the parameter value before adjustment, For real-time sediment samples, Predict results for the model; S344, simulation prediction: Use the calibrated sediment-organism model to simulate the diffusion path and impact range of pollutants in sediments in the ecological environment and predict the ecological impact of pollutants; S345, Result Analysis and Application: Based on the simulation results of the sediment-organism model, the spread and impact of pollutants in the marine ecological environment are evaluated to provide a scientific basis for ecological risk assessment and management; Through the above steps, the diffusion path and ecological impact of pollutants in sediments are simulated to ensure the accuracy and reliability of the model. This method can provide detailed predictions of pollutant diffusion and biological exposure, provide a scientific basis for ecological risk assessment and environmental management decisions, and improve the real-time and regional applicability of predictions.

[0030] The ecological risk model in S4 adopts the food web model, which includes: S41, initial setting of pollutant concentration: Set the initial pollutant concentration in seawater and sediment for the initial conditions of the ecological risk model. The calculation formula is: ; ; in, and are the initial pollutant concentrations in seawater and sediment, respectively, and is the initial concentration actually monitored; S42, Dynamic changes of pollutants in seawater and sediments: Simulate the diffusion, adsorption and desorption of pollutants in seawater and sediments, taking into account the water flow and sediment dynamics. The calculation formula is: ; ; in, is the adsorption rate constant, is the desorption rate constant, is the diffusion coefficient in water, is the deposition rate; S43, Bioabsorption and Biomagnification: Simulate the accumulation and biomagnification effect of pollutants in organisms through ingestion and respiration. The calculation formula is: ; in, is the pollutant concentration in the i-th organism, is the absorption rate constant in water, is the absorption rate constant in the sediment, is the feeding rate of the ith organism, is the deposition rate constant, is the excretion rate constant; S44, Pollutant transfer in the food chain: simulate the transfer of pollutants in the food chain, taking into account the biomagnification effect between different trophic levels. The calculation formula is: ; in, is the pollutant concentration in the i-th organism, is the pollutant concentration in the jth organism, is the biomagnification factor from the jth organism to the ith organism; S45, Ecological Risk Assessment: Assess the impact of pollutant concentrations in organisms on the ecological environment and predict the ecological risk of offshore floating structures. The calculation formula is: ; in, is the ecological risk value of the i-th organism, is the pollutant concentration in the i-th organism, is the toxicity threshold of the i-th organism; Through the above-mentioned food web model, combined with the results of sediment ecotoxicity analysis, the diffusion path of pollutants in the ecological environment around offshore floating structures and the accumulation process in organisms can be simulated more accurately. In particular, the dynamic changes of pollutants in water bodies and sediments, the absorption and amplification effects in organisms, and the transmission process in the food chain are taken into account, making the model more suitable for predicting the ecological risks of offshore floating structures. In this way, a more scientific ecological risk assessment can be provided, providing a reliable basis for environmental protection and management decisions.

[0031] Model training and validation in S5 include: S51, Data Preparation: Collect and organize historical data and experimental data, including historical monitoring of pollutant concentrations in sediments and water bodies, pollutant accumulation data in organisms, and ecotoxicity experimental results; S52, initial model parameter setting: according to the existing experimental and preliminary analysis results, the initial parameters of the ecological risk model are set, including pollutant diffusion coefficient, adsorption and desorption rate, biological absorption and excretion rate; S53, model training: historical data and experimental data are input into the ecological risk model to simulate the distribution and transfer process of pollutants in sediments, water bodies and organisms. The prediction results of the ecological risk model are compared with the actual data, and the prediction error is calculated by the root mean square error (RMSE) and the mean absolute percentage error (MAPE). The calculation formula is: ; ; in, is the value of the ith data point predicted by the ecological risk model, is the value of the ith data point actually monitored, and n is the total number of data points; S54, parameter adjustment: According to the error analysis results, adjust the ecological risk model parameters to reduce the prediction error. The calculation formula is: ; in, is the adjusted parameter value, is the parameter value before adjustment, For actual monitoring data, Predict results for ecological risk models; S55, Model Validation: Use independent data sets from different times or locations as validation data, input the validation data into the trained ecological risk model, run simulations and predict the diffusion path and biological exposure of pollutants, compare the actual test data of the validation data with the prediction results of the ecological risk model, evaluate the prediction performance and reliability of the ecological risk model, and calculate the validation error. The validation formula is: ; S56, Model optimization: Based on the verification error and performance evaluation results, optimize the ecological risk model parameters to ensure the applicability and stability of the model under different environmental conditions; Through the above steps, the constructed ecological risk model is trained and verified using historical data and experimental data, the model parameters are adjusted, the accuracy and reliability of the model are improved, and a scientific basis is provided for the ecological risk prediction of offshore floating structures.

[0032] The risk assessment in S6 includes: S61, Data input: Input the preprocessed environmental data into the trained and validated ecological risk model; S62, model operation: Run the ecological risk model to simulate the diffusion path, transfer process and accumulation of pollutants in sediments, water bodies and organisms; S63, Pollutant diffusion and absorption simulation: Use ecological risk models to simulate the diffusion of pollutants in water and sediments, as well as the absorption and biomagnification effects in organisms, to generate pollutant concentration distribution data at different time points; S64, Food Chain Transfer Simulation: Simulate the transfer process of pollutants in the food chain, consider the biomagnification effect between different trophic levels, and calculate the concentration of pollutants in each organism; S65, Ecological Risk Assessment: Calculate the ecological risk value of each organism based on the pollutant concentration data output by the ecological risk model , assess the toxic effects of pollutants on organisms, based on the calculated ecological risk value , classify ecological risks into different levels, and identify risk areas and biological groups at different levels; S66, Impact Scope Analysis: Analyze the scope and intensity of the impact of pollutants on different ecological and environmental components (such as fish, benthic organisms, plankton, etc.); Through the above steps, the ecological risk model is used to input the pre-processed environmental data into the model to simulate the diffusion path and impact range of pollutants in the ecological environment, predict the ecological impact of pollutants, and provide a scientific basis for environmental management and decision-making.

[0033] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present invention is limited to these examples. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the present invention as described above, which are not provided in detail for the sake of simplicity.

[0034] The present invention is intended to cover all such substitutions, modifications and variations that fall within the broad scope of the claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting ecological risks of offshore floating structures, characterized in that: The following steps are involved: S1, Data Collection: Collect environmental data around offshore floating structures through a variety of sensors and remote sensing technologies. Environmental data include water quality parameters, biodiversity data, meteorological data, and ocean dynamics data; S2, data preprocessing: preprocessing the collected environmental data, including cleaning, noise reduction and completion; S3, Sediment Ecotoxicity Analysis: Collect seabed sediment samples around offshore floating structures for chemical and ecotoxicity analysis to assess the impact of pollutants in sediments on marine organisms and the ecological environment, and predict the diffusion path and ecological impact of sediment pollution by establishing a sediment-organism model; S4, Establishing an ecological risk model: Based on the results of sediment ecotoxicity analysis, an ecological risk model is constructed to predict the ecological risks of offshore floating structures; S5, model training and verification: use historical data and experimental data to train and verify the constructed ecological risk model, and adjust the parameters of the ecological risk model; S6, risk assessment: input the pre-processed environmental data into the trained ecological risk model to predict the risk of offshore floating structures to the surrounding ecological environment; S7, report generation: Generate an ecological risk assessment report based on the risk prediction results output by the ecological risk model, including risk level, impact scope and recommended measures.

2. The method for predicting ecological risks of offshore floating structures according to claim 1, characterized in that: The data collection in S1 includes: Water quality parameter monitoring: Use water quality sensors to monitor the temperature, salinity, pH value, dissolved oxygen concentration, ammonia nitrogen content, nitrate and phosphate concentration in seawater, and obtain real-time data on water quality parameter changes; Biodiversity data survey: Record and analyze the species, quantity and distribution of organisms around floating structures at sea through underwater cameras, acoustic monitoring equipment and environmental DNA sampling technology; Meteorological data collection: using meteorological stations and satellite remote sensing technology to collect wind speed, wind direction, temperature, rainfall and solar radiation intensity in the area where the offshore floating structure is located; Ocean dynamics data acquisition: Using wave buoys, tide gauges, and current meters to measure the height, period, tidal changes, current speed, and direction of ocean waves.

3. The method for predicting ecological risks of offshore floating structures according to claim 1, characterized in that: The sediment ecotoxicity analysis in S3 includes: S31, Sediment Collection: Collect seafloor sediment samples in the area around the offshore floating structure using a sediment trap; S32, chemical analysis: chemical analysis of the collected sediment samples to detect the content of pollutants in the sediments, including heavy metals, organic pollutants, and microplastics, and quantitatively analyze the composition and concentration of pollutants; S33, Ecotoxicity Test: Conduct ecotoxicity tests on sediment samples to evaluate the toxic effects of pollutants in sediment samples on marine organisms, use biological indicator species to conduct biological toxicity experiments, and determine ecotoxicity indicators, including lethal concentration and growth inhibition rate; S34, Sediment-Organism Model Establishment: Based on the results of chemical analysis and ecotoxicity testing, a sediment-organism model is established to simulate the diffusion path and ecological impact of pollutants in sediments, consider sediment particle migration, pollutant release and biological exposure mechanisms, and predict the spread and impact of sediment pollutants in the ecological environment.

4. The method for predicting ecological risks of offshore floating structures according to claim 3, characterized in that: The sediment collection in S31 includes: S311, Locate sampling points: Determine sediment sampling points in the area around the floating structure at sea based on ocean dynamics data and environmental conditions; S312, sediment trap selection: select a sediment trap, including a box-type mud sampler, a grab bucket mud sampler or a columnar mud sampler, and select the corresponding sediment trap according to the sediment type and sampling depth; S313, sediment collection: placing sediment traps at the determined sediment sampling points, operating the sediment traps to sink to the seafloor, and closing the traps by mechanical or hydraulic equipment; S314, sample processing: lifting the captured sediment samples to the sea surface to avoid loss or contamination of the sediment samples, and then transferring the sediment samples to the preset sampling containers, and numbering and recording them; S315, Sample preservation and transportation: Preservation of collected sediment samples, including refrigeration and sealing.

5. The method for predicting ecological risks of offshore floating structures according to claim 4, characterized in that: The chemical analysis in S32 includes: S321, Sample processing: homogenize, dry, grind and sieve the collected sediment samples in preparation for chemical analysis; S322, heavy metal detection: Use strong acid to digest the sediment sample at high temperature and high pressure, use inductively coupled plasma emission spectrometer to detect the digested solution, and quantitatively analyze the content of heavy metals in the sample. The calculation formula is: ； in, is the heavy metal concentration, is the signal intensity of the sample, is the signal intensity of the blank sample, is the slope of the standard curve; S323, organic pollutant detection: Use solvent to perform Soxhlet extraction on organic pollutants in sediment samples, dissolve organic pollutants in organic solvents, purify the extract by gel permeation chromatography, remove interfering substances, obtain organic pollutant extracts, detect the purified organic pollutant extracts by gas chromatography-mass spectrometry, quantitatively analyze organic pollutants in samples, and quantify organic pollutant concentrations by internal standard method. The calculation formula is: ； in, is the concentration of organic pollutants, is the peak area of ​​organic pollutants in the sample, is the peak area of ​​the internal standard, is the internal standard correction factor; S324, Microplastic Detection: Microplastic particles are separated from sediments by flotation, and microplastic particles are floated by high-density solution to separate them. The morphology of microplastic particles is observed by microscope, and the chemical composition is identified by Fourier transform infrared spectrometer. The number and mass of microplastic particles are counted, and the content of microplastic particles in sediments is calculated. The calculation formula is: ； in, is the concentration of microplastics, is the number of separated microplastic particles, is the mass of the sediment sample.

6. The method for predicting ecological risks of offshore floating structures according to claim 5, characterized in that: The ecotoxicity tests in S33 include: S331, Selection of bio-indicator species: Select bio-indicator species for ecotoxicity testing. Bio-indicator species include marine copepods and benthic organisms; S332, sediment sample preparation: the collected sediment samples are mixed with seawater in a predetermined ratio to prepare sediment suspensions of different concentrations for ecotoxicity testing; S333, Experimental design: Design an experimental group and a control group. The experimental group is set with sediment suspensions of different concentration gradients, and the control group uses uncontaminated sediments; S334, toxicity test: placing biological indicator species in experimental and control groups, observing and recording biological responses within a predetermined period of time, and determining ecotoxicity indicators, including lethal concentration LC50 test and growth inhibition rate test, among which; The lethal concentration LC50 test records the sediment concentration when 50% of the biological individuals in the experimental group die, and calculates the lethal concentration LC50. The calculation formula is: ； in, is the sediment concentration for each concentration group, is the number of dead organisms in this concentration group, and N is the total number of organisms in all experimental groups; The growth inhibition test measures the growth changes of biological indicator species in sediment suspensions of different concentrations and calculates the growth inhibition rate. The calculation formula is: ； in, is the growth of organisms in the experimental group, is the growth of organisms in the control group; S335, Data Analysis: Perform statistical analysis on experimental data, compare the survival and growth rates of bio-indicator species at different concentrations, draw dose-response curves, and evaluate the toxicity intensity of pollutants in sediments.

7. The method for predicting ecological risks of offshore floating structures according to claim 6, characterized in that: The sediment-organism model establishment in S34 includes: S341, Data Integration: Integrate the results of sediment chemical analysis and ecotoxicity testing, including the types, concentrations, and ecotoxicity indicators of pollutants in sediments, as basic data for the sediment-organism model; S342, Model Construction: Based on the mechanisms of sediment particle migration, pollutant release and biological exposure, a sediment-organism model is constructed to simulate the diffusion path and ecological impact of pollutants in sediments, including; The sediment particle migration uses the sediment dynamics equation to simulate the migration of sediment particles in the water body, taking into account the factors of water flow, waves and sedimentation. The calculation formula is: ； in, is the sediment particle concentration, is the water velocity vector, is the sediment diffusion coefficient, is the sediment settling rate; The pollutant release is calculated by simulating the release process of pollutants from sediment particles, taking into account factors such as desorption, diffusion and bioturbation. The release rate is calculated as follows: ； in, is the pollutant release rate, is the release rate constant, is the pollutant concentration in the sediment, is the sediment porosity; The biological exposure mechanism simulates the process of marine organisms being exposed to pollutants through ingestion, respiration and skin contact through a biological exposure model. The calculation formula is: ； in, is the biological exposure dose, , , are the pollutant concentrations in water, sediment, and organisms, respectively. , , They are the water ingestion rate, sediment ingestion rate, and skin absorption rate; S343, model calibration: using real-time sediment samples to calibrate the sediment-organism model and adjust the model parameters of the sediment-organism model; S344, simulation prediction: Use the calibrated sediment-organism model to simulate the diffusion path and impact range of pollutants in sediments in the ecological environment and predict the ecological impact of pollutants; S345, Result Analysis and Application: Evaluate the spread and impact of pollutants in the marine ecological environment based on the results of sediment-organism model simulation.

8. The method for predicting ecological risks of offshore floating structures according to claim 7, characterized in that: The ecological risk model in S4 adopts a food web model, which includes: S41, initial setting of pollutant concentration: Set the initial pollutant concentration in seawater and sediment for the initial conditions of the ecological risk model. The calculation formula is: ； ； in, and are the initial pollutant concentrations in seawater and sediment, respectively, and is the initial concentration actually monitored; S42, Dynamic changes of pollutants in seawater and sediments: Simulate the diffusion, adsorption and desorption of pollutants in seawater and sediments, taking into account the water flow and sediment dynamics. The calculation formula is: ； ； in, is the adsorption rate constant, is the desorption rate constant, is the diffusion coefficient in water, is the deposition rate; S43, Bioabsorption and Biomagnification: Simulate the accumulation and biomagnification effect of pollutants in organisms through ingestion and respiration. The calculation formula is: ； in, is the pollutant concentration in the i-th organism, is the absorption rate constant in water, is the absorption rate constant in the sediment, is the feeding rate of the ith organism, is the deposition rate constant, is the excretion rate constant; S44, Pollutant transfer in the food chain: simulate the transfer of pollutants in the food chain, taking into account the biomagnification effect between different trophic levels. The calculation formula is: ； in, is the pollutant concentration in the i-th organism, is the pollutant concentration in the jth organism, is the biomagnification factor from the jth organism to the ith organism; S45, Ecological Risk Assessment: Assess the impact of pollutant concentrations in organisms on the ecological environment and predict the ecological risk of offshore floating structures. The calculation formula is: ； in, is the ecological risk value of the i-th organism, is the pollutant concentration in the i-th organism, is the toxicity threshold of the i-th organism.

9. The method for predicting ecological risks of offshore floating structures according to claim 8, characterized in that: The model training and verification in S5 includes: S51, Data Preparation: Collect and organize historical data and experimental data, including historical monitoring of pollutant concentrations in sediments and water bodies, pollutant accumulation data in organisms, and ecotoxicity experimental results; S52, initial model parameter setting: according to the existing experimental and preliminary analysis results, the initial parameters of the ecological risk model are set, including pollutant diffusion coefficient, adsorption and desorption rate, biological absorption and excretion rate; S53, model training: input historical data and experimental data into the ecological risk model, simulate the distribution and transfer process of pollutants in sediments, water bodies and organisms, compare the prediction results of the ecological risk model with the actual data, and calculate the prediction error through the root mean square error and mean absolute percentage error. The calculation formula is: ； ； in, is the value of the ith data point predicted by the ecological risk model, is the value of the ith data point actually monitored, and n is the total number of data points; S54, parameter adjustment: According to the error analysis results, adjust the ecological risk model parameters to reduce the prediction error. The calculation formula is: ； in, is the adjusted parameter value, is the parameter value before adjustment, For actual monitoring data, Predict results for ecological risk models; S55, Model Validation: Use independent data sets from different times or locations as validation data, input the validation data into the trained ecological risk model, run simulations and predict the diffusion path and biological exposure of pollutants, compare the actual test data of the validation data with the prediction results of the ecological risk model, evaluate the prediction performance and reliability of the ecological risk model, and calculate the validation error. The validation formula is: ； S56, Model optimization: Optimize ecological risk model parameters based on validation errors and performance evaluation results.

10. The method for predicting ecological risks of offshore floating structures according to claim 9, characterized in that: The risk assessment in S6 includes: S61, Data input: Input the preprocessed environmental data into the trained and validated ecological risk model; S62, model operation: Run the ecological risk model to simulate the diffusion path, transfer process and accumulation of pollutants in sediments, water bodies and organisms; S63, Pollutant diffusion and absorption simulation: Use ecological risk models to simulate the diffusion of pollutants in water and sediments, as well as the absorption and biomagnification effects in organisms, to generate pollutant concentration distribution data at different time points; S64, Food Chain Transfer Simulation: Simulate the transfer process of pollutants in the food chain, consider the biomagnification effect between different trophic levels, and calculate the concentration of pollutants in each organism; S65, Ecological Risk Assessment: Calculate the ecological risk value of each organism based on the pollutant concentration data output by the ecological risk model , assess the toxic effects of pollutants on organisms, based on the calculated ecological risk value , classify ecological risks into different levels, and identify risk areas and biological groups at different levels; S66, Impact Scope Analysis: Analyze the scope and intensity of the impact of pollutants on different ecological and environmental components.

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