56 results about "Estuary" patented technology

The invention relates to a coastal wetland ecological restoration effect evaluation method and system, and belongs to the technical field of ecological monitoring and restoration. Aiming at the problems of static evaluation index lag, insufficient data fragmentation integration and lack of causal diagnosis mechanism in the prior art, multi-source time sequence ecological data are acquired by constructing a three-dimensional monitoring network consisting of satellite remote sensing, an unmanned aerial vehicle, an Internet of Things sensor and an underwater robot; a fusion data set is generated based on space-time alignment and tidal phase marking, dynamic evolution characteristics are extracted by using an LSTM network, and a spatial distribution difference chart of ecological parameters before and after restoration is generated in combination with a GAN; and furthermore, through hot area clustering and historical data association mining, a degradation driving factor is positioned, and an optimization suggestion is generated. The method breaks through the space-time limitation of a traditional evaluation method, remarkably improves the degradation diagnosis precision and the regulation and control efficiency of restoration engineering, and is suitable for various ecological restoration scenes such as estuary delta and coral reefs.

The invention discloses a microplastic transport simulation and risk identification method based on multi-factor coupling, which comprises the following steps: by coupling a hydrodynamic model and a microplastic transport model, comprehensively considering multiple environmental factors such as tide, water level, runoff, wind speed, wind direction and the like, constructing a wave flow coupling microplastic migration and diffusion model suitable for complex hydrodynamic conditions of a Pearl River estuary; the model is calibrated and verified through measured data, and the precision of the model is evaluated by using indexes such as a Nash efficiency coefficient and a root-mean-square error; in combination with the simulation result and the spatial distribution characteristics of the typical sensitive area, representative sections and stations are selected, and annual-scale micro-plastic concentration change analysis is carried out; and further introducing an ecological risk index to carry out regional ecological risk grade identification, and determining a micro-plastic high-risk area and influence main control factors. The method has high regional adaptability and expansibility, and scientific support and technical reference can be provided for prevention and control of microplastic pollution of estuary and coastal water.

The invention provides a Yangtze river export deep and far sea environment data association analysis method based on multi-modal fusion, belongs to the technical field of far sea environment analysis, and achieves accurate data registration by establishing a multi-source data space-time standardization model and adopting an adaptive space-time Kriging interpolation algorithm. A sparse coding ocean signal separation algorithm is utilized to construct an over-complete dictionary separation mixed signal to extract pure features, a feature extraction network is constructed based on an attention mechanism to automatically learn deep feature representation of physicochemical biological parameters, and a matrix rank loss detection algorithm is adopted to automatically supplement feature compensation vectors to ensure feature integrity. A cross-scale attention mechanism is constructed based on wavelet transform to fuse multi-scale features, a Shapley value interpretability evaluation system is established to quantify correlation feature importance, and the technical problem that correlation feature extraction is inaccurate in the multi-source heterogeneous marine environment data fusion process is solved.

The invention relates to the technical field of water quality early warning, in particular to a sea-entering estuary water quality monitoring automatic early warning network construction method, which comprises the following steps of data acquisition, data preprocessing, model construction, model training and verification and model application. According to the method for constructing the automatic early warning network for monitoring the water quality of the estuary, the real-time monitoring of the water quality of the estuary is realized through an automatic monitoring sensor network, the time delay of a traditional method is overcome, and early warning can be quickly given out at the initial stage of a water quality problem by adopting an advanced data processing and early warning algorithm; compared with traditional manual sampling and laboratory analysis, the technical scheme has the advantages that the monitoring cost is remarkably reduced, the working efficiency is improved, interference to river ecology is reduced, friendly monitoring on the natural environment is realized, and the water quality monitoring system can be widely applied to the field of water quality monitoring and early warning by providing detailed water quality data and analysis reports. And a scientific basis is provided for water resource management and environmental protection decision making.

The invention discloses an estuary sediment transport simulation method considering environmental factor coupling, and belongs to the technical field of offshore marine deposition dynamics, and the method comprises the steps: processing the geographic data of a target sea area, constructing a non-structural computational grid region of the target sea area, and generating an initial terrain field; for a target sea area, setting boundary conditions and an initial field, and constructing a three-dimensional hydrodynamic numerical model; performing systematic verification and parameter calibration on the three-dimensional hydrodynamic numerical model in S2 by adopting multi-source observation data; based on the three-dimensional hydrodynamic force numerical model verified in S3, constructing a three-dimensional hydrodynamic force-sediment coupling numerical model considering environmental factor driving; and performing systematic verification and parameter calibration on the three-dimensional hydrodynamic force-sediment coupling numerical model in the step S4 by adopting multi-source observation data. According to the method, the real-time dynamic coupling relation between the environmental factors and the sediment settling velocity is established by modifying the sediment settling velocity equation, the flocculation effect of the estuary high-concentration fine-particle sediment is represented, and the accuracy of suspended sediment concentration simulation is improved.

The present invention relates to the field of hydrological and water resource application technology, and more specifically, to a method for predicting upstream saltwater tides in estuaries using a machine learning algorithm. Partial correlation coefficients and Pearson correlation coefficients are used to optimize forecasting factors with appropriate lead times. These optimized forecasting factors are then input into a GRU (Gated Recurrent Unit) model to perform salinity forecasts for different forecast periods. This method can effectively predict the salinity of upstream saltwater tides in estuaries during the dry season, providing a scientific basis for early warning of salinity exceeding standards in estuaries and enabling timely intervention and prevention.

The invention relates to the technical field of water quality parameter remote sensing inversion, and discloses a simple method suitable for high-turbidity estuary particulate organic carbon concentration remote sensing inversion, which comprises the following steps: collecting and preprocessing suspended particulate matter (SPM) concentration, particulate organic carbon (POC) concentration data and corresponding remote sensing reflectivity data of a water body; according to a wave spectrum response function of each wave band of a common optical satellite sensor, the equivalent remote sensing reflectivity Rrs (lambda i) of each wave band is obtained through simulation, and by comparing the correlation between the remote sensing reflectivity Rrs (lambda i) of the visible light-near infrared wave band and the actually measured suspended particulate matter (SPM) concentration, the POC inversion model constructed by the method adopts a subsection modeling strategy, so that the concentration of the SPM can be calculated. The concentration of the suspended particulate matters with strong correlation is preferably selected as a correlation parameter, so that a relatively large error generated by an existing multi-parameter model is effectively avoided, and the precision of the inversion of the concentration of the particulate organic carbon in the high-turbidity estuary region is remarkably improved.

Methods, systems and apparatuses including systems and methods that can be used for operating a water turbine in combination with a system including a plurality of tidal estuaries and flow channels created by human activity for power generation and further including plurality of man-made dams communicating with at least some of the tidal estuaries and the flow channels.

The present invention discloses a method for synergistically solidifying heavy metal contaminated soil at the estuary of the sea using urease and its modifiers in combination with microwave technology, including: 1. Mix soy flour and deionized water, stir and centrifuge to remove soybean dregs, and take the supernatant as the urease solution; 2. Mix the urea solution and the calcium salt solution to obtain the cementitious liquid; 3. Crush waste concrete waste to obtain fine building aggregates, and add milky quartz powder to make a urease-induced carbonate modifier; 4. Dig the surface heavy metal contaminated soil and mix it with the modifier in step 3, and air-dry it; 5. Add water to the air-dried contaminated soil to the optimal moisture content and backfill it; 6. Lay a white cleaning cloth on the surface of the backfilled contaminated soil, pour the urease solution and the cementitious liquid in sequence, and use the self-weight seepage to make the urease solution and the cementitious liquid penetrate into the interior of the contaminated soil; 7. Turn on the microwave generator to irradiate the soil. The present invention can solidify heavy metal contaminated soil in a high salinity environment, reduce the leaching concentration of heavy metals in the contaminated soil, and improve the strength of the contaminated soil.

This invention provides a multimodal fusion-based method for correlation analysis of deep-sea environmental data outside the Yangtze River Estuary, belonging to the field of deep-sea environmental analysis technology. This invention achieves accurate data registration by establishing a spatiotemporal standardization model for multi-source data and employing an adaptive spatiotemporal kriging interpolation algorithm. It utilizes a sparse coding marine signal separation algorithm to construct an overcomplete dictionary to separate mixed signals and extract pure features. Based on an attention mechanism, a feature extraction network is constructed to automatically learn deep feature representations of physical, chemical, and biological parameters. A matrix rank deficiency detection algorithm is used to automatically supplement feature compensation vectors to ensure feature integrity. A cross-scale attention mechanism based on wavelet transform is constructed to fuse multi-scale features. A Shapley value interpretability evaluation system is established to quantify the importance of correlated features. This invention solves the technical problem of inaccurate correlated feature extraction during the fusion of multi-source heterogeneous marine environmental data.

The application discloses an underwater acoustic tomography flow measurement method based on phase difference. The method comprises the following steps: collecting bidirectional propagation acoustic signals of a water area to be measured, and extracting the propagation time and phase change of the bidirectional propagation acoustic signals; establishing the relationship among the phase change of the bidirectional propagation acoustic signals, the propagation time of the bidirectional propagation acoustic signals, the average flow velocity of the water area to be measured and the average sound velocity of the water area to be measured through wave acoustic, and inversely deriving the average flow velocity of the water area to be measured and the average sound velocity of the water area to be measured through the relationship. The purpose of the application is to provide an underwater acoustic tomography flow measurement method based on phase difference, which is more suitable for use in acoustic tomography technology with lower frequency. The uncertainty in flow velocity measurement can be reduced by simultaneously considering the time difference and the phase difference, and the automatic and high-precision flow measurement technology is promoted. The application is suitable for flow velocity measurement of water areas such as river channels, estuaries and bay areas.

The invention discloses a microplastic distribution prediction and tracing method, and relates to the field of model detection. Collecting multi-source monitoring data of a target water area, and performing space-time alignment processing on the multi-source monitoring data to generate a structured space-time data set; constructing a three-dimensional ocean current dynamic model of the target water area, simulating ocean current field distribution under different time-space conditions by using ocean environment auxiliary data, and extracting ocean current dynamic characteristic data; processing the spatio-temporal data set and the ocean current dynamic characteristic data through a micro-plastic prediction sub-model, and predicting and outputting a micro-plastic diffusion path and a micro-plastic concentration prediction value of each monitoring station; and processing the current micro-plastic distribution data and the ocean current dynamic characteristic data through the micro-plastic tracing sub-model, and predicting and outputting the current micro-plastic distribution backtracked estuary pollution source. According to the scheme, prediction of the micro-plastic diffusion path and tracing of the pollution source are achieved, the micro-plastic diffusion path can be accurately predicted, the pollution source can be accurately traced, and the efficiency and accuracy of marine micro-plastic pollution treatment are improved.

The present invention discloses a method for repairing and predicting dissolved oxygen concentration data, comprising collecting water quality data and establishing an original data set; identifying missing values ​​and performing outlier analysis on the water quality data using a box plot to remove outliers; calculating and repairing the identified missing values ​​and removed outliers using a Lagrange interpolation method; analyzing the correlation between dissolved oxygen and other water quality parameters using an improved grey correlation analysis method; optimizing the parameters of an LSTM neural network using a sparrow search algorithm to establish an improved LSTM model; and predicting dissolved oxygen data using the improved LSTM model. The present invention utilizes the sparrow search algorithm to establish an improved LSTM model. By optimizing missing values ​​and outliers in the original data set, the improved LSTM model accurately predicts changes in dissolved oxygen concentration, providing a high-precision water quality prediction technology for estuaries with complex hydrodynamics.

The invention provides an estuary multi-source pollution monitoring method and system based on dynamic traceability. The method comprises the following steps: acquiring pollution information of an estuary of a target water area; acquiring pollution information of a pollution point of the target water area; constructing a multi-source pollution convection diffusion model; the pollution information of the estuary of the target water area and the pollution information of the pollution points of the target water area are input into the multi-source pollution convection diffusion model, and the pollution concentration value of each pollution point diffused to the estuary is obtained; according to the pollution concentration value corresponding to each pollution point, obtaining the pollution contribution degree of each pollution point to the estuary; and according to the pollution contribution degree corresponding to each pollution point, in combination with a preset water area monitoring criterion, carrying out pollution point monitoring on the target water area. Therefore, by applying the method provided by the invention, the traceability, monitoring and treatment efficiency of the estuary pollution can be improved.

The present invention relates to a method for inverting chlorophyll a concentration in an estuary based on multi-model fusion, and relates to the technical field of water quality monitoring. ESTARFM is used to fuse MODIS remote sensing images and Landsat 8 remote sensing images to obtain high-temporal and spatial resolution remote sensing images, thereby solving the problem that existing remote sensing images cannot simultaneously achieve high-temporal and spatial resolution, resulting in poor accuracy in inverting chlorophyll a concentration in the estuary. The reflectivity of the band combination screened out from the high-temporal and spatial resolution remote sensing images is used as input, and the corresponding monitored chlorophyll a concentration is used as output to construct a random forest model and a GBR model, respectively. A TPE search weight method is used to establish a fusion model of the random forest model and the GBR model, thereby solving the problem that a single machine learning model in the existing technology cannot adapt to the complex environmental conditions of the estuary, resulting in low accuracy in inverting chlorophyll a concentration in the estuary.

The present invention discloses a method for determining the outflow threshold value of a river channel in a river-controlled estuary based on an improved entropy weight method, comprising the following steps: S1: collecting historical topographic data of a fixed section of a main stream channel at the tail end of a river-controlled estuary, and historical daily average hydrological data of hydrological stations along the channel; S2: applying the improved entropy weight method to the main stream channel at the tail end of the estuary based on the hydrological and topographic data, calculating the contribution weights of different indicators in water-sediment conditions and riverbed boundary conditions to the outflow of the channel, and identifying the main controlling factors of the outflow of the channel according to the calculation results; S3: establishing a prediction model for the outflow threshold value of an estuary channel under the joint control of riverbed boundary conditions and water-sediment conditions based on the main controlling factors of the outflow; the present invention simplifies the calculation method of the outflow threshold value and greatly improves the applicability of the method; the present invention proposes a method for determining the outflow threshold value of an estuary channel by considering water-sediment and boundary conditions at the same time, which can be applied to river-controlled estuaries with different outflow periods, and provides guidance for estuary flood control and river channel management.

The application discloses a nitrogen and phosphorus synergic management method of river-estuary continuum, and belongs to the technical field of ecological management, and the method comprises the following steps: S1, using the coastal eutrophication potential index to diagnose the key nutrient elements affecting the stoichiometry of nutrient salts and flux; S2, determining the ecological threshold values of total nitrogen, total phosphorus, dissolved inorganic nitrogen and dissolved inorganic phosphorus in different zones of the estuary according to the relationship between the nutrient concentration and the ecological response index; S3, comprehensively diagnosing the eutrophication risk based on the coastal eutrophication potential index and the ecological threshold value, and judging whether to select the basin management or the estuary management; S4, identifying the key source area of nitrogen and phosphorus pollution which substantially limits the water quality target of the downstream under the water function zoning and the environmental capacity limitation; and S5, putting forward the nitrogen and phosphorus synergic management strategy based on the cost-benefit analysis; the application realizes the whole-chain nitrogen and phosphorus synergic management and control of land-sea overall planning, zoning refinement, accurate tracing, and economic efficiency, and is popularized and applied to the comprehensive treatment of eutrophication of river-estuary continuum.

The application discloses a kind of water diversion project water storage reservoir pollutant reduction amount prediction method and system, comprising the following steps: (1) collecting water source area of water diversion project, water storage reservoir and its main tributary water quality routine monitoring data and different river reach pollutant inflow, water storage reservoir shoreline data, reservoir inflow and outflow;(2) predict water quality condition of water storage reservoir, calculate water storage reservoir pollutant reduction amount;(3) calculate pollutant allowable concentration of main tributary estuary of water storage reservoir and inverse calculate pollutant allowable concentration of different river reaches, calculate the pollutant concentration of different river reaches, determine the land pollutant reduction amount of water storage reservoir and the land pollutant reduction amount of different river reaches of main tributary;(4) calculate water area pollutant reduction amount of water storage reservoir.The present application proposes water-land integrated pollutant reduction method, establishes water quality safety guarantee prediction system of water diversion project water storage reservoir, and provides systematic methodology for regional (basin) pollutant inflow reduction amount calculation.

The application discloses a method for predicting eel fry resource quantity, comprising the following steps: obtaining initial factors, screening the initial factors to obtain influence factors, obtaining historical data according to the influence factors, and constructing a generalized linear model and a nonlinear model; optimizing and verifying the generalized linear model and the nonlinear model through the historical data, obtaining current data according to the influence factors, predicting the current data through the verified generalized linear model and the nonlinear model, and combining the prediction results by weighting to generate an eel fry resource quantity prediction result. Through the technical scheme, the eel fry resource quantity in an estuary can be effectively and universally predicted.

This invention belongs to the field of environmental monitoring technology and discloses a remote sensing inversion method for dissolved inorganic nitrogen and silicate in estuaries based on salinity synergy. The method includes the following steps: S1. During a field survey in the land-sea interaction zone of the estuary, remote sensing reflectance, salinity, and nutrient data are collected simultaneously. The measured hyperspectral reflectance is simulated as the equivalent reflectance of the satellite band using the spectral response function of the target satellite, which is used to construct the training and validation datasets for the model. S2. A nonlinear inversion model of remote sensing reflectance and salinity is established, and a nutrient mixture model of salinity and nutrients is constructed. The training dataset is used for model training. S3. The satellite remote sensing reflectance data of the estuarine area to be predicted is input into the trained nonlinear inversion model and combined with the nutrient mixture model to generate the spatial distribution of DIN concentration and DSi concentration in the estuarine area. This method achieves high-precision remote sensing inversion prediction of DIN concentration and dissolved silicate DSi concentration in the estuarine area.

According to the method for efficiently monitoring the motion behaviors of the fishes near the estuary shore based on the unmanned aerial vehicle, by combining the unmanned aerial vehicle high-resolution image technology, the video monitoring technology and the fish motion behavior analysis data processing algorithm, efficient and accurate monitoring of the motion behaviors and distribution of the fishes in the estuary area is achieved. Through data acquisition and accurate motion trail analysis, the method not only improves the monitoring efficiency, but also provides accurate data support for researching fish behaviors, is helpful to better understand the motion migration mode of fish in the estuary area, assesses the habitat quality, and improves the fish habitat quality. And an activity mode of influence of environment change on fish behaviors is monitored, so that a scientific basis is provided for ecological environment protection and fishery sustainable management measures in the near-shore of the estuary.

This invention relates to the field of marine acoustic detection technology and discloses a dynamic suppression algorithm for real-time elimination of the influence of tidal motion on sonar signals. The method collects sonar signal sequences and tidal motion parameter sequences for the current sea area and divides the sonar signal into multiple time windows. Within each window, the phase offset is calculated based on the tidal parameters and converted into time-domain compensation coefficients through an established dynamic coupling model, performing preliminary phase correction on the sonar signal. Spectral analysis is performed on the initially suppressed signal to extract residual interference features, and the parameter weights of the dynamic coupling model are adjusted accordingly to generate an optimized model. This optimized model is applied to the processing of the next time window, forming an iterative suppression closed-loop process. This method can adaptively track the dynamic changes of tidal motion, effectively weakening its periodic modulation interference on sonar signals and improving the accuracy of sonar detection data in strong tidal areas such as nearshore and estuaries.

The utility model discloses an ultra-large span tide gate with a self-stabilizing structure, which comprises gate foundations arranged on two sides of a riverway estuary, and the gate foundations are provided with arc-shaped guide grooves and spherical trunnions; the spherical trunnions are connected with one ends of the water retaining gates, the other ends of the water retaining gates make contact with each other to be in a closed state when storm surge comes, and the closing point of the water retaining gates is located on the open sea side of the connecting line of the two spherical trunnions. An arc-shaped stability maintaining piece matched with the arc-shaped guide groove is arranged in the arc-shaped guide groove, one end of the arc-shaped stability maintaining piece is fixedly connected with the water retaining gate, and the other end of the arc-shaped stability maintaining piece is connected with the hoist. The device has the advantages of being stable in structure, flexible to open and close, safe in operation, convenient and fast to overhaul and the like, navigation and the hydrological river regime of an original river channel are not affected in the processes of structural design, manufacturing, transportation, installation, overhaul and maintenance and the like, and the influence on the original river channel can be reduced to the maximum extent.

The present application relates to the technical field of sediment cross-section erosion, and particularly relates to a method for predicting sediment cross-section erosion variation under the influence of a water gate. A current erosion and deposition topography sequence corresponding to a current time of a target gate is obtained, and future precipitation-runoff data, future water level difference between upstream and downstream, and future tide change data within a future preset time length corresponding to the target gate are obtained; based on the future precipitation-runoff data, the future water level difference between upstream and downstream, and the future tide change data, future gate scheduling data corresponding to the target gate is determined; the current erosion and deposition topography sequence, the future precipitation-runoff data, the future water level difference between upstream and downstream, the future tide change data, and the future gate scheduling data are input into a preset erosion and deposition variation prediction model, and output of sediment cross-section erosion variation within the future preset time length corresponding to the target gate is output. Timely and reliable technical support is provided for hydraulic scheduling and risk management, and safe and efficient operation of a tidal gate in an estuary is realized.

The application belongs to the technical field of total nitrogen surface pollution into the sea in agricultural planting, and particularly relates to a calculation method and system for quantifying the space of total nitrogen surface pollution into the sea in agricultural planting, which comprises the following steps: obtaining the total nitrogen pollution output coefficient of each agricultural planting unit; calculating the total nitrogen surface pollution transport capacity index of agricultural planting based on the minimum cumulative resistance model of surface pollution migration; calculating the actual total nitrogen surface pollution into the sea value of agricultural planting, the correction coefficient of the total nitrogen surface pollution into the sea value of agricultural planting and the total nitrogen surface pollution transport coefficient of agricultural planting according to the monitoring data of the estuary; and calculating the total nitrogen surface pollution into the sea value of the agricultural planting unit in the space scale according to the total nitrogen surface pollution transport coefficient of agricultural planting and the total nitrogen pollution output coefficient of each agricultural planting unit, so as to complete the space quantification calculation of the total nitrogen surface pollution into the sea in agricultural planting.

The present invention relates to the field of marine environmental protection technology, and specifically discloses a method for water quality evaluation and pollutant reduction in high-latitude estuaries and bays, including: obtaining measured data of a study area; constructing a three-dimensional ecological hydrodynamic numerical model covering the study area, and calibrating and verifying the model; obtaining the spatiotemporal distribution characteristics of hydrodynamics and pollutants in the study area under current conditions in the past year; evaluating the water quality status of the study area after emission reduction using the WQI method, and analyzing the impact of pollutant reduction under different reduction schemes on changes in ecological parameters in the study area; and evaluating the ecological status in the study area after the implementation of different reduction schemes with reference to the actual situation in the study area; and selecting the most suitable pollutant reduction scheme based on the simulation results under different reduction schemes. The present invention overcomes the deficiency of traditional methods that ignore the impact of the freezing period, and can more accurately reflect the impact of the freezing period on water quality, ecological conditions, and pollutant diffusion.

The invention provides a tropical estuary water quality dynamic evaluation method based on a multi-dimensional index, and the method comprises the steps: S11, selecting sampling points in a sea-entering tropical estuary water area, collecting sampling indexes which comprise a biological index, a physicochemical index and a hydrological index, and setting a dynamic threshold value according to the characteristics of the sampling indexes and the environmental characteristics of the tropical estuary; s12, dividing the biological indexes, the physicochemical indexes and the hydrological indexes into positive indexes, negative indexes and neutral indexes, and respectively calculating risk quotients of the positive indexes, the negative indexes and the neutral indexes; s13, respectively standardizing the positive index, the negative index and the neutral index, and sequentially calculating the proportion of each index, the entropy value of each index and the weight of each index; and S14, comprehensively evaluating the water quality of the tropical estuary by combining the calculation results of the step S12 and the step S13. According to the method, the multi-dimensional indexes are introduced, and a dynamic weight adjustment mechanism is adopted, so that the method is more comprehensively and accurately adapted to complex and changeable environment characteristics of the tropical estuary region.

The invention relates to the technical field of hydrology and water resources, in particular to a salt tide upstream salinity forecasting model construction method and system. The method comprises the following steps: determining a salt tide monitoring section of a target estuary, and obtaining the real-time salinity of the salt tide monitoring section; when the real-time salinity exceeds a preset salinity threshold value and the continuous rising trend reaches a preset duration, judging the current time period as a high-salinity event; extracting daily average salinity, fresh water flow and tide level data of the associated hydrological monitoring station based on the high-salinity event to form high-salinity event data; and calculating the ratio of the salinity peak time difference and the salinity change amplitude of the salt tide monitoring section and the downstream tide level monitoring station. The method can accurately capture the typical propagation time-lag characteristic and the amplitude response characteristic of the salt tide upstream, overcomes the limitation based on an empirical threshold in the prior art, and remarkably improves the scientificity and the accuracy of salt tide upstream judgment.

The invention discloses an estuary-based ecological sensitivity analysis method and system, and relates to the technical field of ecological sensitivity analysis. The method comprises the following steps: collecting species data of an estuary region, and analyzing to obtain a basic adaptive value of an estuary ecological environment; historical ecological data of the estuary area are collected, and the ecological fitness value of the estuary ecological environment is obtained through analysis; combining the basic fitness value and the ecological fitness value to obtain an ecological environment fitness value of the estuary region; acquiring climate data of the estuary area, and estimating the human activity amount of the estuary area according to the climate data; obtaining human activity data, and evaluating according to the human activity data to obtain the environmental awareness degree of human in the estuary area; the ecological damage degree of human beings in the estuary area is obtained through analysis according to the human activity amount and the environmental awareness degree, and the ecological sensitive value of the estuary is obtained through evaluation according to the ecological environment fitness value. According to the method, the accuracy of estuary-based ecological sensitivity analysis is improved.

An intelligent fusion and processing method for remote sensing products for water quality monitoring of estuaries and bays includes: S1. setting criteria for image retrieval, performing iterative image retrieval and downloading, and achieving batch downloading of remote sensing images automatically; S2. performing recursive call of an Acolite settings file in Python to directly perform batch atmospheric correction of multi-source remote sensing satellite data; S3. fusing multi-source remote sensing data products based on machine learning to generate a layer of high-frequency water quality parameter remote sensing products; S4. superimposing a layer of tidal boundary vectors for different water levels onto the layer of water quality parameter remote sensing products, and adding map elements to generate a thematic map of different water quality parameters; S5. performing intelligent statistical analysis of water quality parameters; and S6. outputting a report sheet based on the thematic map of water quality parameters and the statistical chart.