1035 results about "Surface water" patented technology

The invention provides an underground water pollution source tracing and evaluation method for a riverside water source in a karst area, and the method comprises the following steps: collecting and preprocessing multi-source information, and obtaining a multi-source data set; a water quality sample is collected and analyzed, the surface water-underground water interaction process and pollution characteristics are comprehensively analyzed, and a pollution source type is obtained; performing space-time analysis on the multi-source data set to obtain a pollution activity time period and a potential pollution source area; constructing a karst area hydrological model, simulating the hydrological characteristics of the karst area, constructing a pollutant migration model, and simulating the migration process of pollutants; and constructing a traceability algorithm, tracking pollutants, confirming a pollution source, carrying out risk partitioning and risk assessment, and carrying out visual display of a result. According to the invention, interaction between surface water and underground water can be effectively assessed, accurate traceability of pollutants and multi-angle accurate identification of pollution sources can be realized, and management efficiency can be optimized through reliable risk assessment prediction.

The invention relates to the field of hydrology and water resource management and karst hydrodynamics, and discloses a karst basin coupling hydrology model prediction method, which comprises the following steps: S1, collecting and standardizing multi-source heterogeneous monitoring data of a karst basin; s2, constructing a hydrological model for dynamic coupling of surface runoff, fracture seepage and a pipeline network; s3, performing global optimization on the multi-dimensional hydrological parameters by adopting a hybrid intelligent optimization method; s4, performing iterative correction on the model based on a multi-level verification system; and S5, outputting a hydrological prediction result and generating disaster early warning information. By adopting a dynamic adjusting technology of karst area underground river and surface water flow network joint modeling, multi-karst water-containing medium characteristic analysis and integration of underground river and surface water system response characteristics, the problems that a traditional method cannot accurately predict underground water flow and flow velocity, and is difficult to deal with complexity of a karst water system, lack of data and the like are solved.

The invention provides an ocean near-surface sub-mesoscale process flow field inversion method and device. The method provided by the invention comprises the following steps: screening an ocean near-surface sub-mesoscale representative sea area; obtaining the structure image information of the frontal surface and the filament of the phytoplankton in the marine sub-mesoscale process; acquiring displacement velocity field information at the same position; the structure image information and the displacement velocity field information are matched, and a first training sample set is constructed; correcting the first training sample set based on the second data set and the third data set to obtain a second training sample set; training the initial model by using the second training sample set to obtain a flow field inversion model; obtaining a plurality of sub-mesoscale sea surface water color images of the sea area to be detected; and processing the sub-mesoscale sea surface water color image by using the flow field inversion model to obtain a displacement velocity field. The invention provides an ocean near-surface sub-mesoscale process flow field inversion method and device. The method and device are used for solving the problem that a current ocean flow field inversion algorithm is not high in sub-mesoscale process inversion precision.

The embodiment of the invention relates to the technical field of pollution traceability, and discloses a surface water multi-point source pollution traceability method, which comprises the following steps: preprocessing water quality time sequence data and environmental parameter information; performing feature extraction on the preprocessed water quality time sequence data to obtain water quality key features; the water quality key features are input into a pre-constructed deep learning model to be recognized so as to obtain a corresponding pollution recognition result, the deep learning model comprises a time sequence processing module, and the time sequence processing module is used for processing water quality time sequence features in the water quality key features; and outputting a corresponding pollution identification result, wherein the pollution identification result comprises pollution type information, pollution source position information and confidence degree information. According to the method, deep learning and classified calibration are performed on historical pollution source data through a deep learning algorithm, a pollutant label library and a knowledge library are formed, and support is provided for rapid identification of new pollution events.

The invention discloses an urban inland inundation simulation method based on an SWMM and SIMWE coupling model. The method comprises the steps that basic data and historical heavy rainfall data of a research area are collected and processed; rainstorm events in different recurrence periods are designed; an SWMM-SIMWE coupling model is constructed and verified; and simulating the urban inland inundation condition in a certain period of time in the future based on the designed rainstorm. According to the method, the SWMM model and the SIMWE model are combined and used for simulating an underground drainage system and surface runoff respectively, and water flow movement and accumulated water distribution under the complex urban terrain can be reflected more accurately and efficiently. According to the method, through a reasonable coupling mechanism, the problem that in the prior art, the urban drainage system and the surface runoff dynamic state are difficult to accurately and efficiently simulate is solved, and the water exchange efficiency and precision between the underground drainage system and the surface water flow are remarkably improved. The simulation result provides a scientific basis for urban inland inundation risk assessment and flood control and drainage system optimization, and is helpful for improving the disaster defense capability of cities.

The invention discloses a data-mechanism fused airport runway surface water and ice condition prediction method. The method comprises the following steps: establishing a theoretical model of a runway surface temperature field and a water and ice condition; thermal parameter inversion is carried out on the theoretical model based on actually measured data, and a dynamic theoretical model adapted to an actual application scene is obtained through multi-time iteration optimization of model parameters; and utilizing the fused time sequence data and the dynamic theoretical model to predict the water and ice condition on the surface of the airport runway, and providing dynamic evolution information of the icing process. According to the method, the problems of insufficient real-time performance and accuracy of runway icing prediction in the prior art are solved, the icing time, the ice layer thickness and the ice layer range of the runway surface can be accurately predicted, real-time deicing decision support is provided, and the runway operation safety and the airport operation efficiency are effectively improved.

The invention relates to the technical field of water quality monitoring, in particular to a surface water environment online monitoring method which comprises the following steps: acquiring water quality monitoring data of urban pipe network nodes, establishing a pipe network topological structure, adjusting the topological structure in combination with a water flow direction, determining the water flow direction, performing time segmentation on the topological structure, and calculating topological change frequency. And establishing a pipe network topology evolution structure. According to the method, the topological change frequency is calculated in combination with time segments, pipe segments with obvious changes are screened, and the continuous diffusion condition of pollutants is judged by removing trend influence, extracting stable water quality characteristic information, screening continuous abnormal points and analyzing the pollution diffusion trend in combination with the topological relation in the screening of abnormal fluctuation pipeline connection. The pollution influence range is combined with concentration changes, key diffusion channels are marked, pollution duration is combined, and pollution source candidate points are screened, so that water quality monitoring can adapt to pipe network changes, and the real-time performance and the intelligent level of an urban pipe network water quality monitoring system are enhanced.

The invention discloses a surface water prediction system and method based on a hydrological optimization Informer model. The method comprises the following steps: collecting multi-source data of an upstream monitoring point and a downstream monitoring point of surface water; preprocessing the multi-source data to obtain preprocessed data; performing feature extraction on the preprocessed data to obtain water quality features and hydrological spatial-temporal features of the upstream monitoring point and the downstream monitoring point, and constructing accumulated dissolved oxygen saturation features; inputting the upstream and downstream water quality characteristics, the hydrological spatial-temporal characteristics and the dissolved oxygen saturation characteristics into a pre-trained multi-modal prediction model of an improved Informer model to obtain a prediction result of the upstream surface water and a prediction result of the downstream surface water; the multi-modal prediction model of the improved Informer model outputs a prediction result of the surface water obtained through fusion; according to the method, the Informer model is optimized, the GRU model is combined, hydrological spatial-temporal characteristics and accumulated dissolved oxygen saturation are introduced by utilizing an attention mechanism, the prediction precision is improved, errors are reduced, and the early warning capability for sudden pollution events is enhanced.

The invention discloses an urban area runoff pollutant transportation process simulation forecasting method, which is characterized in that a building area runoff production calculation method under the influence of a wind field is provided, and the building area runoff production calculation method is coupled with an SWMM rainfall flood model; secondly, constructing a two-dimensional hydrodynamic model based on an FVCOM and a Lagrange particle model, coupling the two-dimensional hydrodynamic model with the SWMM rainfall flood model, and driving the two-dimensional hydrodynamic model by taking the overflow flow and the pollutant concentration simulated by the SWMM rainfall flood model as boundary conditions; simulating a transportation process of pollutants along with evolution of surface ponding by establishing a'concentration-quantity 'conversion relation between the pollutants and particles at grid units and nodes, and obtaining a time sequence pollutant concentration data set; and training and establishing a pollutant concentration prediction model based on the obtained data, and then predicting the pollutant concentration of each prediction point after specific time in an actual rainfall event. According to the method, the runoff pollutant concentration can be predicted, and the urban non-point source pollution risk under the rainstorm weather is reduced.

The invention discloses an underground water exploitable quantity evaluation method and system based on coupling of a physical mechanism and a neural network, and relates to the technical field of water resource management, meteorological data, surface water hydrological monitoring data, geological survey data, underground water resource development and utilization data and hydrogeological parameter data are integrated and preprocessed, and a basic data set is obtained; a three-dimensional geological model of a heterogeneous structure is constructed by utilizing a digital twin physical engine and combining drilling geological data. By introducing a digital twin technology and a numerical model, the underground water flowing process can be simulated more accurately, a digital twin physical engine is utilized to construct a heterogeneous aquifer digital model, a dynamic interaction process of surface water and underground water is embedded, and the model is enhanced through a graph neural network and a physical information neural network, so that the underground water flowing process is simulated more accurately. Errors caused by hypothesis of aquifer homogeneity, neglecting of surface water-underground water coupling process and the like of a traditional model are effectively reduced, and the accuracy of underground water exploitable quantity evaluation is improved.

The invention discloses a slope physical similarity model device and a slope internal crack evolution identification method, and relates to the technical field of open pit coal mine slope ecological protection, and the slope physical similarity model device comprises a similar material simulation system, a monitoring system and an artificial rainfall system. Through cooperation of the similar material simulation system, the monitoring system and the artificial rainfall system, surface water seepage field change and instability process simulation caused by slope rock-soil mass fracture evolution under different main control factors can be artificially controlled, and temperature, rainfall, stress, fracture development and other characteristic changes in the whole process can be monitored in real time; the method can deeply explore the internal relationship with slope instability, obtain the slope instability failure path, failure source and key block, determine the main control factor threshold of each stage, reveal the seepage and instability mechanism of the open pit coal mine slope under the freeze-thaw cycle, and improve the stability of the open pit coal mine slope. And a theoretical basis is provided for establishment of multi-source criteria of seasonal freeze-thaw landslide of the high and cold opencast coal mine and early-and-middle-stage early warning.

The invention provides an urban water network drainage joint scheduling method and system, and relates to the technical field of urban flood control and drainage, and the method comprises the steps: carrying out the fusion processing of multi-source monitoring data, and obtaining a feature vector; inputting the feature vector into a runoff prediction model for runoff prediction to obtain a comprehensive runoff prediction result; based on the comprehensive runoff prediction result, pipe network water flow and surface accumulated water simulation is conducted through a drainage hydraulic model, and a target simulation result is obtained; performing waterlogging risk assessment based on the target simulation result and the monitoring data to obtain a waterlogging risk level; selecting a corresponding scheduling generation mode based on the weather forecast data, the monitoring data and the waterlogging risk level; and determining a corresponding scheduling strategy based on the selected scheduling generation mode and the waterlogging risk level. According to the urban water network drainage joint scheduling method and system provided by the invention, accurate prediction simulation and scientific scheduling are realized, and the drainage efficiency is further improved.

The invention discloses an SAR satellite remote sensing surface water extraction method for an African climate complex region, and the method comprises the steps: carrying out the preprocessing of satellite image data, and making sample point label data; making a shadow mask file, and removing the mountain shadow on the satellite image data; calculating a gray level co-occurrence matrix to generate texture features; establishing a multi-dimensional feature space, and screening the feature space; building a semi-supervised cooperative training model by using two random forest classifiers, and introducing label-free data to assist in model training; and predicting the global surface water distribution of the research area. According to the method, the SAR remote sensing image is combined with the semi-supervised collaborative random forest model, the manpower and time cost of actual sample labeling is greatly reduced, the surface water monitoring efficiency is improved, the problem of visible light remote sensing data missing in regions with complex climates can be solved by using microwave remote sensing data, and the method is suitable for popularization and application. And timely and accurate information is provided for water resource management in the African region.

The invention relates to acid-resistant sulfate reducing bacteria and application thereof, and belongs to the technical field of microorganisms. The acid-resistant sulfate reducing bacterium disclosed by the invention is Desulfovibrio desulfuricans QY411, and is preserved in the Guangdong Microbial Culture Collection Center on March 14, 2024, and the preservation number of the acid-resistant sulfate reducing bacterium is GDMCC No: 64412. The acid-resistant sulfate reducing bacterium provided by the invention can survive in an environment with the pH value of 4, and can be applied to ecological reconstruction of acid tailings and waste dump soil, the pH values of mining wasteland soil and surface water after ecological reconstruction are remarkably increased, the concentration of SO4 < 2-> in the soil is remarkably reduced, the acidification process in the mining wasteland soil is effectively inhibited, and the acid-resistant sulfate reducing bacterium has the advantages of being safe and reliable. Therefore, the acidification process in the mining wasteland is effectively controlled. Meanwhile, soil heavy metal pollution is reduced, and vegetation growth is recovered.

The invention discloses a gleying rice field intelligent irrigation and drainage regulation and control method based on reinforcement learning. The method comprises the steps that meteorological data, soil data and field surface water level data are collected; calculating crop state information based on the meteorological data and the soil data by using a crop growth model; inputting the meteorological data, the soil data, the field surface water level data and the crop state information into an offline training strategy model, outputting action suggestions, and performing verification and decision making according to preset regulation and control logic in combination with the meteorological data, the soil data, the field surface water level data, an external data source and agronomic rule base data; a control strategy is generated, irrigation, drainage or oxygenation is executed, and irrigation and drainage regulation and control are completed. Compared with the prior art, the method has the advantages that priority regulation and control logic for ORP / pH value real-time feedback is established, a prospective pre-drainage mechanism for rainfall forecast is fused, water layer constraint in the growth period and conditional filtering rules in the fertilization safety period are fused, and a perception-decision-execution closed-loop control system is formed.

The invention relates to the technical field of tailing pond model construction, in particular to an earth surface groundwater combined tailing pond model construction method and system. According to the method, the SWAT-MODFLOW coupling model is established, the model combines the advantages of the SWAT model in surface hydrological process simulation and the accuracy of the MODFLOW model in underground water flowing process simulation, the characteristics of the hydrodynamic field and the seepage field of the tailings pond can be more comprehensively described, and the seepage flow of the dam body can be accurately predicted. And meanwhile, a dam body slope stability CPSO-BP prediction model is established by utilizing a coordinated particle swarm optimization algorithm and a BP network, and the model can describe a complex nonlinear relationship between the slope stability and influence factors thereof, so that the prediction precision is improved. The influence of the surface water and the underground water on the tailings pond is comprehensively considered, and compared with a traditional model only considering the surface water, the running state and the instability mechanism of the tailings pond can be simulated more truly.

The invention discloses an ecological flow guarantee method based on runoff prediction and supply. Meteorological, hydrological and other data of the Tongkeng river basin are collected, an SWAT model is constructed and verified to simulate runoff, and extended rainfall is analyzed based on an R / S method and a wavelet method. And constructing a surface water and underground water coupling model, and predicting underground water volume, water level and water quality. And ecological flow safeguard measures are formulated after water resource supply and demand balance analysis, wherein the ecological flow safeguard measures comprise optimal allocation of water resources, enhanced management, ecological water supplementation, water environment treatment, ecological restoration project development and the like. The method has the advantages that measure implementation subjects and progresses are defined, monitoring system evaluation effects are established, adjustment and optimization are performed according to results, ecological flow is guaranteed, sustainable utilization of drainage basin water resources and ecological environment protection are realized, remarkable social, economic and environmental benefits are achieved, and a scientific and effective method is provided for water resource management.

The invention provides a roof rainwater collection system and method capable of achieving source discarding, and belongs to the technical field of rainwater collection. The system comprises a rainwater collection module arranged on a roof main body, the module comprises a photovoltaic unit, a water collection unit and a protection unit, the water collection unit comprises a water collection tank, a tank cover, a flow guide eave and the like, synchronous control of overturning of the tank cover and sliding of the flow guide eave is achieved through a gear and rack linkage mechanism, and polluted rainwater is automatically discarded at the initial stage of rainfall; in the later period, the photovoltaic panel, the inner surface of the box cover and the three rainwater collecting faces of the protection plate cooperatively collect rainwater, and the rainwater collecting efficiency is effectively improved; the protection plate has functions of normal water collection and extreme weather protection, can resist hail impact, and realizes protection of the photovoltaic panel. According to the scheme, through the three-dimensional design of source discarding, multi-surface water collection and intelligent protection, deep integration of the photovoltaic function and the rainwater collection function is constructed, rainwater cleaning is achieved from the source, and the advantages of efficient water collection, source pollution control and equipment protection are achieved.

The invention discloses a surface water reserve monitoring method and system based on satellite gravity data, electronic equipment and a storage medium, and the monitoring method comprises the steps: S1, obtaining the satellite gravity data, and carrying out the omni-directional filtering and denoising of the satellite gravity data, and obtaining the preprocessed gravity data; s2, performing time domain and frequency domain decomposition on the preprocessed gravity data, and extracting surface water reserve change signals on different spatial and temporal scales based on time domain and frequency domain information; and S3, constructing a surface water level virtual change value based on the surface water reserve change signals on different spatial and temporal scales, and performing analog calculation based on the surface water level virtual change value to complete surface water reserve monitoring.

The invention discloses a surface water and underground water combined regulation and control method considering runoff and underground water level recovery, and belongs to the technical field of comprehensive regulation and control of water resources. According to drainage basin water resource supply and demand conditions and engineering characteristics, on the basis of fully considering multiple factors such as economy, society and ecology, organic combination of multiple regulation and control measures is implemented, and the method becomes an important way for achieving efficient combined utilization of water resources, restoring the underground water level, improving the regional ecological environment and guaranteeing food safety. Besides, in order to comprehensively evaluate the combined regulation and control effect of the surface water and the underground water, an evaluation index system of the system needs to be established and is used for evaluating the recovery conditions of the river runoff and the underground water level. By quantitatively evaluating actual effects of different regulation and control measures, a decision maker can be helped to judge whether water resource distribution and use are reasonable or not, the regulation and control measures are adjusted and optimized according to evaluation results, an appropriate surface water-underground water combined regulation and control scheme is selected, and reference can be provided for sustainable management of drainage basin water resources.

The multi-field coupling collaborative modeling and parameter autonomous intelligent decision-making method for the roller type quenching process comprises the steps that four key process parameters including the nozzle flow, the water ratio, the roller gap distance and the plate passing speed are collected and subjected to normalization preprocessing, and a training set and a test set are divided; the four key process parameters of the training set serve as input, the water-cooling convective heat transfer coefficient and the phase change plasticity coefficient serve as output, a BP neural network is trained, and the workpiece surface water-cooling convective heat transfer coefficient and the material internal phase change plasticity coefficient are predicted through the trained BP neural network; a multi-field coupling model composed of a temperature field, a structure phase change field and a stress-strain field is solved, and quantitative calculation of quenching core quality indexes is achieved; by taking water consumption minimization as a target, constructing a nonlinear optimization model under the condition that multiple core quality index constraints of the plate temperature, the outlet hardness and the plate shape are met; and performing global optimization on the optimization model by adopting a differential evolution algorithm, and autonomously deciding an optimal process parameter set value.

The invention discloses a surface water storage amount monitoring method and system based on space-air-ground water multi-source collaboration, and relates to the technical field of water resource investigation, and the method comprises the steps: obtaining multi-source collaboration collection data of a target water body, and generating a multi-source data set of a unified space-time reference; carrying out automatic extraction and change detection on a surface water area range by using a water body index method and deep learning to obtain a water area boundary; taking a water area boundary as a spatial constraint, extracting ashore terrain and underwater terrain data, and inputting the ashore terrain and underwater terrain data into a deep learning fusion model based on an encoder-decoder structure to generate a water-land integrated digital elevation model; and according to the water body types, based on the model, respectively adopting corresponding deep learning models to carry out storage volume monitoring, and calculating the water storage volumes and dynamic changes of different water body types. Efficient fusion and intelligent processing of multi-source data are achieved, the precision and efficiency of surface water storage capacity monitoring are remarkably improved, and the method is suitable for refined dynamic monitoring of various water bodies such as rivers, reservoirs and ponds.

The invention belongs to the related technical field of waterlogging simulation, and particularly relates to an urban waterlogging simulation device and method based on a digital twin system, and the device comprises the digital twin system, a physical sand table, a sensor, and a microcontroller. The twin system is connected with the physical sand table through a microcontroller and sensors arranged on the physical sand table, and is used for simulating the underground pipe network and surface ponding conditions of the urban target area under the rainfall condition, and regulating and controlling the physical sand table through the microcontroller to realize dynamic verification of the urban inland inundation process; the sensor is used for collecting underground pipe network and surface water accumulation condition data in the physical sand table in real time and transmitting the data back to the twin system, bidirectional interaction and synchronous display of the virtual environment and the physical sand table are achieved, and dynamic simulation and verification of the urban inland inundation process are achieved on the whole. Wherein the twinborn model is composed of a pipe network model, a road model and a building model. According to the invention, real-time mapping and interaction of the physical experiment and the virtual model of the urban drainage system can be realized.

The invention discloses an arid region groundwater reserve estimation method and system based on multi-source remote sensing data, and relates to the technical field of groundwater monitoring, and the method comprises the steps: collecting land water reserve data and remote sensing image data of a target arid region, obtaining a land water reserve change sequence according to the land water reserve data, carrying out the region weighting of the target arid region, and obtaining a target arid region groundwater reserve change sequence; obtaining a land water reserve change sequence of the target arid region; based on the remote sensing image data of the target arid region, using a digital elevation model to obtain a surface water reserve change sequence of the target arid region, using a land surface process model to obtain a soil water reserve change sequence of the target arid region, and establishing an underground water reserve model of the target arid region; and performing error analysis on an output result of the groundwater reserve model by using a Monte Carlo simulation method. According to the method, through collaborative inversion of multi-source remote sensing data and integration of the groundwater reserve models, accurate quantification of spatial-temporal dynamic of the groundwater reserves in the arid region is realized.

The invention relates to a coastal city flood multi-system coupling evaluation method and system, and the method comprises the steps: obtaining multi-source data, and carrying out the unified projection and time resolution normalization processing of the data; constructing an upstream river network one-dimensional hydrodynamic model, an urban drainage pipe network one-dimensional hydrodynamic model and an urban two-dimensional surface water dynamic model based on the multi-source data, and setting tide boundary conditions; coupling each model and the tide boundary; performing model calibration and error constraint on the coupled multi-dimensional hydrodynamic coupling model; constructing a composite scene, taking each group of scenes as an input boundary condition to drive the multi-dimensional hydrodynamic coupling model, and obtaining a flood evolution result; and performing risk assessment and sensitivity analysis based on a flood evolution result. According to the method, a unified river network-pipe network-earth surface-tide multi-scale coupling framework is constructed, so that the defect that a traditional single model or result superposition method is difficult to reflect multi-system interaction is effectively overcome.

The invention discloses an airport area underground water and surface water system coupling seepage regulation and control method and system, and the method comprises the steps: employing a multi-source data fusion investigation mode to find out regional stratum and structure characteristics, and determining an underground water occurrence migration rule and a surface water and underground water supplement and drainage relation; constructing a coupling seepage model of the underground water and the surface water system under the current condition by applying a numerical simulation method, and defining a dynamic association mechanism of the underground water and the surface water system in time and space; based on a simulation result, determining a transformation scheme that a main stream adopts a double-hole box culvert and a branch stream adopts a single-hole box culvert, and arranging an electric gate at the box culvert; arranging monitoring points of groundwater level, pore water pressure and surface water system flow in combination with field spring water and well distribution, and constructing a cooperative monitoring network; the coupling seepage law of underground water and surface water systems is analyzed based on monitoring data, and the opening degree of a box culvert electric gate is dynamically adjusted to control rising of the underground water level in the flood period. The stability of a water system in an airport area is ensured.

The invention relates to the field of remote sensing image processing and surface hydrology information acquisition, and provides a soil moisture downscaling method based on a self-attention mechanism, which is used for realizing high-precision space refinement prediction of a low-resolution soil moisture map. According to the method, multi-source high-resolution remote sensing factors are fully fused, and an end-to-end framework with a remote dependent modeling capability is constructed. According to the method, multi-level spatial features of auxiliary factors are extracted through multi-scale convolution, low-resolution soil moisture features serve as query vectors, high-resolution auxiliary factors serve as key / value vectors, and a cross attention fusion module is introduced to enhance the features. And then modeling a space context and remote dependence through a Transform encoder. And finally, generating a high-resolution soil moisture prediction map through a shallow convolutional decoder. Experiments prove that compared with an existing mainstream method, the method shows better precision and robustness in a soil moisture downscaling task, and has good application potential.

The invention provides an intelligent target supervision method and system based on data analysis. The method comprises the steps that visible light and thermal infrared image sequences are synchronously collected through a coastline monitoring camera, and plastic garbage contour features and temperature distribution differences are recognized; segmenting the contour, extracting displacement to generate an ocean current trajectory prediction path, arranging a buoy collection device, and driving surface water flow to converge by using a propeller to guide garbage to move along the path to form a dynamic accumulation area; plastic garbage difficult to decompose is recognized and marked based on visible light reflection difference, offset is calculated in combination with temperature difference to generate a path correction instruction, the track of a collecting device is adjusted to preferentially intercept a target, and real-time images are synchronized to update closed-loop supervision. According to the technical scheme, intelligent recognition, dynamic gathering and precise interception closed-loop supervision of marine plastic garbage difficult to decompose are achieved, the pollution treatment efficiency is improved, and secondary diffusion is restrained.

The invention provides a surface water depth ultrasonic measurement correction method, and belongs to the technical field of water depth measurement. According to the method, surface water depth ultrasonic measurement correction is divided into two processes of correction before measurement and correction after measurement; corresponding correction methods are set according to different correction processes; specifically, the method simulates the propagation path condition of ultrasonic waves in a surface water environment to be measured by establishing a three-dimensional propagation path compensation model, and is used for eliminating the influence of temperature gradient distribution, suspended matter concentration distribution and flow velocity distribution on ultrasonic propagation, namely correction before surface water depth ultrasonic measurement; when correction is carried out after measurement, correction parameters are calculated through information of an ultrasonic wave transmitting beam angle and a reflection angle; correcting the ideal depth information through the correction parameters to obtain real depth information of the surface water; according to the method, a complete process from correction before measurement to correction after measurement is given, so that the corrected surface water depth information is more accurate and reliable.

The invention relates to the technical field of ecological protection, in particular to an ecological protection red line basic survey method based on territorial space planning, which comprises the following steps of: acquiring data including satellite remote sensing, unmanned aerial vehicle aerial survey, ground sensors and the like; and high-precision spatial data of ecological elements such as vegetation coverage, surface water distribution and soil erosion intensity are obtained. And combining spatial-temporal feature matching and an improved spatial clustering algorithm to dynamically partition the ecological factors to generate a dynamic partition map of the ecological factors. Based on the graph, a three-dimensional ecological sensitivity evaluation model is constructed, and a dynamic threshold adjustment algorithm is adopted to carry out automatic optimization of the red line boundary. And finally, through multi-dimensional verification and evaluation of natural ecological stability, regional economic bearing degree, social acceptance and the like, generating a final ecological protection red line scheme. According to the method, the adaptability and flexibility of red line delimiting are improved, and the method can be widely applied to the fields of ecological protection, territorial space planning, environment management and the like.