634results about "Measuring open water depth" patented technology

The invention provides a water level distributed monitoring method and system based on a visual sensing network, and relates to the technical field of water level monitoring, and the method comprises the steps: constructing a water level propagation prediction model through multi-modal comparative learning and a graph neural network, processing a real-time water level image through the combination of adaptive wavelet transform, decoupling representation and a dense connection network, and obtaining a real-time water level prediction model; the water level measurement value and the reliability score are obtained, anomaly analysis and emergency monitoring are carried out based on state estimation, causal discovery and hierarchical reinforcement learning, high-precision and high-reliability distributed water level monitoring can be achieved, abnormal water level changes can be effectively recognized, and timely emergency monitoring parameters are provided.

The invention relates to a real-time river water level monitoring and early warning method and system based on deep learning. The method comprises the following steps: acquiring a target watershed remote sensing image and real-time hydrological data of multiple monitoring points; performing water flow direction topology analysis on the remote sensing image of the target watershed, and constructing a water flow topology network; performing basin structure dynamic change feature analysis on the target basin remote sensing image to generate basin structure dynamic change data; carrying out topology situation evolution fitting on the water flow topology network based on the basin structure dynamic change data to obtain a dynamic topology evolution network; performing multi-scale time sequence trend evolution analysis on the multi-monitoring-point real-time hydrological data to generate water flow time sequence evolution characteristics; and evolution characteristic space position mapping is performed on the dynamic topology evolution network based on water flow time sequence evolution characteristics, and a three-dimensional hydrological evolution model is constructed. According to the invention, timely and accurate river water level monitoring and early warning are realized.

The invention discloses an integrated measurement method and system for hydrological elements in a high-salinity and high-sand environment, and relates to the technical field of hydrological monitoring, and the method comprises the steps: correcting the theoretical signal receiving strength of each sonar through an established sound attenuation model, and then calculating an effective signal-to-noise ratio, thereby achieving the measurement of the underwater topography in the high-salinity and high-sand environment. According to the method, a dynamic weight fusion algorithm is adopted to perform data fusion on the water depth data of each sonar to obtain fused water depth data, and an inversion method based on residual error minimization is adopted to perform iterative optimization on model parameters, so that the accuracy is relatively high. When the water velocity and the flow rate are measured in the high-salt and high-sand environment, iterative decoupling is carried out based on the sediment particle motion comprehensive model to obtain the sediment particle velocity, then the water velocity is updated based on the measured apparent velocity and the difference value, and after the updated water velocity is converged, the flow rate is calculated. And the accurate water flow rate can be calculated by combining the flow cross section area. The measurement precision of the unmanned ship on the hydrological elements in the saline-alkali area can be improved.

The invention discloses a deep and far sea unmanned aerial vehicle monitoring and management platform based on multi-sensor fusion, and relates to the technical field of unmanned aerial vehicle marine monitoring. The intelligent analysis module is used for receiving the fusion data after time-space alignment and the real-time ocean current data, optimizing the moving path of the unmanned aerial vehicle according to the received data, evaluating the resource development possibility, obtaining an analysis result and transmitting the analysis result; an anti-interference communication module; an energy management module; and dynamically adjusting an energy distribution strategy. The module combines the task priority weight and the environment energy consumption weight, optimizes the energy use efficiency, prolongs the endurance time of the unmanned aerial vehicle, and ensures the smooth completion of the task. Particularly in a complex marine environment, navigation errors are corrected in real time through a quantum navigation error compensation model, the positioning precision is improved, and the moving path of the unmanned aerial vehicle is optimized in combination with real-time ocean current data and an ocean flow field cost function.

The present disclosure provides a method for remote sensing blue-green wave band ratio logarithmic water depth retrieval of wavelet spline instantaneous tidal height correction, and belongs to the field of remote sensing water depth retrieval. Aiming at water depth retrieval precision reduced by blue-green light and a tidal height in a remote sensing water depth retrieval process, the model fully considers a linear correlation between an attenuation ratio of the blue-green light in water and a depth, the smoothness of the tidal height, and the characteristics of consistent convergence, first-order continuous derivation and second-order continuous derivation of the tidal height with time change, and constructs the method for remote sensing blue-green wave band ratio logarithmic water depth retrieval of wavelet spline instantaneous tidal height correction, and according to Molokai experiment verification, compared with an early model, the invention improves the remote sensing water depth retrieval precision.

The invention discloses a multi-source data-combined pit-pond water depth calculation and storage capacity calculation method, which comprises the following steps of: acquiring actually measured water depth data, performing data preprocessing, and dividing the data into a training sample point set and a test sample point set; acquiring a multispectral remote sensing image of the reckoning area, and executing image preprocessing; unifying to the same coordinate system; fractal dimensions of each wave band and the combined wave band are calculated, and a water body region is segmented; establishing a mapping relation between the water depth values of the training sample points and the standardized multispectral apparent reflectance; establishing a water depth inversion model, and verifying the water depth inversion model by using the test sample point set; calculating discrete water depth points of the pit pond by using the optimal water depth inversion model; and establishing a minimum energy curved surface to obtain the water storage amount of a single pit pond, and accumulating to generate the total water storage amount. According to the method, actual measurement and remote sensing data are fused, the energy minimization water depth inversion model is constructed, accurate calculation of the water storage capacity of the pit pond is achieved, and the method has the advantages of being high in precision and high in applicability.

The invention relates to the technical field of channel monitoring, and discloses an unmanned aerial vehicle water depth monitoring method for channel inspection. The method comprises the following steps: deploying an unmanned aerial vehicle to a target channel area, initializing a carried sonar sensor, a camera and a positioning module, and planning a flight path to cover a to-be-detected point according to a preset algorithm; water depth and image data are collected in real time during flight, position information is obtained, multi-modal monitoring data are formed through space-time alignment, a water depth fusion model is input to generate a channel water depth distribution diagram, an abnormal area is recognized through an abnormal detection model, and finally the position and water depth data of the abnormal area are encrypted and transmitted to a ground control terminal. The method improves the efficiency and accuracy of channel water depth monitoring, can timely discover the abnormality, guarantees the safety and smoothness of the channel, and provides an effective technical means for channel management.

The invention discloses a multi-field sensing fusion deep sea geological environment dynamic monitoring system and an application method. The system comprises a buoy measuring platform, a multi-beam sounding system, a high-precision marine gravimeter, an external camera, a GPS, a data acquisition and transmission control unit and a power supply system. By designing a modularized and integrated multi-sensor buoy platform, various sensors are fused and integrated. A plurality of sensors are connected to the data acquisition control terminal, the steps of sensor calibration, data synchronization and clock calibration, correction and compensation, data acquisition, real-time processing, fine post-processing, data transmission and the like are completed, and multi-sensor collaborative operation is realized, so that submarine topography and ocean gravity data of a deep sea ditch area are synchronously acquired in real time; and thus, diving erosion information experienced by the area can be accurately monitored. The method can provide important support for submarine topography and landform detection and application and marine geographic information system construction, and has application value in the aspects of geological disaster early warning, resource development and the like.

The invention relates to a sea area island remote sensing information change monitoring method and system, and relates to the technical field of remote sensing monitoring, and the method comprises the steps: obtaining a remote sensing image time sequence of a target sea area island, the remote sensing image time sequence comprises a plurality of remote sensing images, and each remote sensing image has an acquisition timestamp; collecting tide height information corresponding to the target sea area island at each collection timestamp, and water depth distribution information of the monitored sea area where the target sea area island is located; and performing correction processing on each remote sensing image according to the tidal height information and the water depth distribution information corresponding to each acquisition timestamp, and generating an island boundary contour change time sequence. The invention solves the problems that the traditional sea area island remote sensing monitoring adopts a single-moment image for analysis, the real coastline change and temporary boundary offset caused by tide cannot be distinguished, the boundary extraction precision is reduced due to shallow water area seabed reflection interference, the monitoring error is large, and the monitoring precision is low. The application precision requirements of sea area management, coastal zone protection and the like cannot be met.

The invention belongs to the technical field of marine surveying and mapping, and discloses an equivalent sound velocity automatic inversion method and system based on multi-beam overlap region constraint. The method comprises the following steps of: performing beam point location tracking on multi-beam original data by using surface sound velocity of multi-beam data to obtain an overlapping region of a multi-beam strip; gridding overlapped areas of the multi-beam strips, minimizing water depth deviation between overlapped grids by using a genetic algorithm, and performing inversion to obtain the optimal equivalent sound velocity of each measuring line; and performing beam point location tracking again on each measuring line by using the corresponding equivalent sound velocity obtained by inversion, weakening sound velocity deviation existing in beam point location tracking by using the surface sound velocity, weakening a curved terrain between the strips in the overlapping region, and obtaining a submarine topography with continuous splicing of the overlapping regions of the adjacent strips. According to the invention, the precision and reliability of submarine topography measurement can be ensured, and the speed of submarine topography measurement field operation is improved.

The invention belongs to the technical field of hydraulic engineering measurement, and discloses a seawall measurement method and system based on multi-source data fusion, and the method comprises the steps: collecting geological data and hydrological data through a data collection module; the route planning module formulates a route; the overwater data acquisition equipment and the underwater data acquisition equipment are used for monitoring; the auxiliary equipment provides a high-precision positioning reference; the meteorological data module obtains meteorological data; the data processing module processes the data; the three-dimensional modeling module carries out point cloud registration and DEM model construction; the comprehensive analysis module performs comprehensive evaluation and predicts potential problems and risks; when an abnormal condition or a potential risk is monitored, the early warning module gives an alarm. Multi-source data acquisition equipment such as unmanned aerial vehicle aerial survey, a laser radar, a multi-beam depth finder, a side-scan sonar, a shallow profiler and a micro-motion exploration instrument are integrated, seawall overwater and underwater full-dimensional data acquisition, processing, modeling and volume calculation are realized, and high precision and reliability of measurement results are ensured.

The invention provides a floating type marine hydrology real-time monitoring device, and belongs to the technical field of marine hydrology monitoring. The floating type marine hydrology real-time monitoring device comprises a buoy, a bracket, a monitoring mechanism, a cleaning mechanism and an equipment box, wherein the bracket is fixedly mounted on the surface of the buoy; a sampling mechanism is mounted in an inner cavity of the equipment box and is used for replacing a water sample in the equipment box. The monitoring mechanism is arranged, the sea surface condition and the sea surface wind speed can be monitored through a camera and a wind speed sensor, the seawater salinity and the seawater solubility are monitored in real time through a conductivity sensor and an optical dissolved oxygen sensor, and the conductivity sensor and the optical dissolved oxygen sensor are arranged in the inner cavity of the equipment box, so that the sea surface condition and the sea surface wind speed can be monitored in real time. A filter plate is arranged at the bottom of the equipment box, so that impurities and marine organisms in seawater are prevented from being attached to the surfaces of the conductivity sensor and the optical dissolved oxygen sensor, and the measurement precision is ensured.

The invention provides an artificial intelligence submarine topography inversion system and method using gravitational field spatial spectrum data, and the system comprises a gravitational field spatial spectrum calculation module which uses a plurality of band-pass filters to intercept gravity data under different wavelengths; and the gravity-water depth mapping relation establishing module is used for processing gravity and water depth data and establishing a correlation between the gravity and water depth data. A gravitational field spatial spectrum of a sparse ship water depth measuring position is obtained and is paired with water depth data. Dividing the data set into a training set and a test set in proportion; and designing an artificial intelligence model suitable for a regression task for training and predicting the water depth. And the artificial intelligence submarine topography inversion module is used for predicting a water depth value by using the gravitational field spatial spectrum of the trained model input test set, and evaluating a prediction effect through a precision index. The method has the advantages that the characteristics of the gravity data are enriched through the calculation of the gravity field spatial spectrum, and different degrees of influences of gravity on terrain inversion are considered.

The invention provides a hyperspectral water depth inversion method based on spectrum enhancement and a radiation transmission model. The method comprises the following steps: acquiring original hyperspectral data of a target area water body through a detector; performing noise reduction processing on the original hyperspectral data to obtain first hyperspectral data; performing spectral feature enhancement on the first hyperspectral data by adopting a spectral response function to obtain second hyperspectral data; carrying out radiation transfer calculation on the water body in the target area by adopting the water body radiation transfer model subjected to imaging observation geometric correction to obtain simulated hyperspectral data; and according to the second hyperspectral data and the simulated hyperspectral data, performing water depth inversion on the target area water body to obtain the water depth of the target area water body. According to the invention, the spectrum enhancement technology and the improved water body radiation transmission model are introduced, so that the precision and stability of hyperspectral water depth inversion are remarkably improved.

The invention relates to the technical field of water conservancy surveying and mapping, in particular to a detection method and device for rapidly constructing an underwater terrain of a dike breach based on unmanned aerial vehicle carrying. Aiming at the defects of underwater terrain detection at the current dike breach, the method comprises the following steps of: acquiring water flow speeds, water flow depths, infrared spectrum images and visible light images of a plurality of point clouds by unmanned aerial vehicle carried equipment; processing the water flow depth according to a related algorithm, and processing the infrared spectrum image by using an image processing algorithm to obtain a breach obstacle map; and processing the visible light image by adopting an image processing algorithm to obtain the edge information of the breach, and finally generating a three-dimensional terrain model of the breach in the same coordinate system according to the edge information of the breach, the corrected water flow depth and the breach obstacle map. According to the method, the underwater terrain at the dike breach can be rapidly, accurately and safely detected, and the method is of great significance in improving the plugging engineering efficiency, optimizing the plugging scheme and ensuring the safety and effectiveness of plugging work.

The invention discloses a method and system for monitoring the lake water level based on remote sensing images, and particularly relates to the technical field of remote sensing monitoring, and the method comprises the steps: constructing a complete three-dimensional terrain model of a lake through historical remote sensing images and data of underwater detection equipment, including water surface and underwater shapes; a quantitative relation model of the terrain and the water level is established by utilizing a digital twinborn technology and actually measured water level data, the model is repeatedly tested and optimized, the precision is ensured, and the model is finally applied to real-time water level monitoring, so that the water level information of a target lake is automatically acquired and updated; the problem that a terrain-water level relation model is difficult to accurately monitor lake water level changes in the prior art is solved. The system further comprises a water body boundary correction module and a boundary contour processing module, the boundary of the lake is recognized and extracted more accurately through a remote sensing image and a machine learning model, the boundary is optimized, and accuracy and completeness of water body information are guaranteed.

The invention relates to the technical field of sand excavation metering, in particular to an intelligent metering method of a sand excavation amount monitoring system, which comprises the following steps of: S1, scanning and recording an operation area of a sand dredger by adopting a depth finder in cooperation with RTK GPS, and establishing a three-dimensional map before operation; s2, after sand excavation operation is finished, the operation area of the sand dredger is scanned again, the three-dimensional map after operation is obtained and compared with the three-dimensional map before operation, and topographic changes before and after sand excavation are calculated. When the method is used, high-precision gravel data can be stably obtained under different water flow conditions, sand excavation dispatching optimization and overload avoiding are facilitated through high-precision volume calculation, and the working efficiency of the sand dredger is improved. The method is beneficial to reducing sensor noise, improving measurement precision, realizing real-time monitoring of the volume of the sandstone in the cabin, accurately calculating the volume of the sandstone, improving the precision of supervision data, avoiding oversampling, improving the quality calculation precision, avoiding errors caused by fixed density calculation, automatically calculating in the whole process, avoiding manual intervention, and improving the measurement efficiency and stability.

The invention provides an ICESat-2 turbid water area sounding correction and water depth inversion method based on optical characteristics of a water body. The method comprises the following steps: S1, obtaining photon data and an optical remote sensing image of a near-shore turbid water research area, and carrying out preprocessing operation on the data; s2, performing spectral sensitivity analysis by acquiring an ICESat-2 photon error value and combining optical characteristics of a water body; s3, constructing an ICESat-2 turbid water area sounding compensation model based on water optical characteristics, and selecting the model preferentially according to evaluation indexes; s4, synthesizing a multi-temporal image, and realizing model adaptive adjustment of different space weight distribution based on the spectral sensitivity difference of the turbid water area; s5, constructing an ICESat-2 and remote sensing image joint inversion water depth model based on turbidity partitioning; s6, spatial interpolation is carried out on a water depth inversion result, residual noise and adjacent pixel differences possibly occurring in the image are suppressed, and continuous water depth is obtained; according to the invention, large-range water depth inversion without field actual measurement work can be realized.

The invention discloses a water environment monitoring method based on image vision, and relates to the technical field of water environments, and the method comprises the steps: continuously shooting water body images of different depths at preset intervals in the vertical direction through an underwater camera; calculating the color difference of two adjacent pictures, and determining a water quality mutation layer; when it is detected that the turbidity in the water quality abrupt change layer interval exceeds a preset threshold value, infrared spectral imaging and ultrasonic ranging cooperative work is switched, the penetrability characteristic of an infrared image and ultrasonic depth calibration data are combined, the layering positioning error is corrected, and the water quality abrupt change layer interval is obtained. Through vertical interval shooting, color difference analysis, infrared and ultrasonic collaborative correction and a dynamic sampling strategy, the precision and efficiency of water quality layered monitoring are improved.

The invention relates to the technical field of water temperature monitoring, in particular to a sea cucumber spawning environment data monitoring method and system and a medium. Collecting sea cucumber oviposition historical water temperature time sequence data in the target water area, water area depth and area, and historical temperature time sequence data in a preset historical time period; analyzing the historical water temperature time sequence data, determining a water temperature abnormal data segment, analyzing the temperature difference in the historical temperature time sequence data, and quantifying the influence of the external temperature on the water temperature to obtain a temperature abnormal value; considering different depths and areas of water areas, and determining an influence lag degree value; the length of the water temperature data is calculated based on the indexes so as to collect real-time water temperature time sequence data, so that the hysteresis influence is reduced to the maximum extent, and the water temperature change is reflected in time; calculating an abnormal characteristic value by combining the temperature abnormal value, the fluctuation characteristic of the real-time water temperature time sequence data and the similarity between the fluctuation characteristic and the water temperature abnormal data segment; finally, water temperature anomaly monitoring is performed based on the anomaly characteristic value, and the accuracy of water temperature anomaly monitoring is improved.

The invention discloses an intelligent water depth measurement method for waterway maintenance of a water transportation project, and particularly relates to the technical field of water conservancy projects. Historical sounding data, meteorological and hydrological parameters, real-time sonar echo data and unmanned surveying ship path information of the target channel area are acquired; a multi-source sounding data fusion model is constructed, and heterogeneous data fusion is realized by adopting wavelet domain feature extraction, remote sensing delay compensation and a graph attention mechanism; constructing a water depth evolution characteristic spectrum based on multi-scale spatial domain characteristic extraction; modeling a water depth propagation relationship between the sounding units by using a graph neural network; projecting the evolution graph to a section grid, and outputting a continuous water depth prediction value in combination with residual error correction and a rolling prediction strategy; identifying a water depth deviation by comparing with a designed navigation depth, and constructing a risk map layer; the method has the advantages of high prediction precision, strong adaptability, good response real-time performance and the like, and can be widely applied to scenes of channel siltation monitoring, scouring early warning, shipping maintenance management and the like.

The invention discloses a water area and resource quantity monitoring and predicting method and system based on a remote sensing technology, and belongs to the technical field of water resource monitoring. The method comprises the following steps: determining a water area range according to historical data of a research area and an on-site survey condition, and determining a research area range; the method comprises the following steps: respectively acquiring ground data and water depth and water surface elevation data by using an unmanned aerial vehicle and an unmanned ship, respectively processing to obtain a land DEM and a water area DEM, and fusing to form an all-terrain DEM; downloading satellite image data of the research area, and performing geographical registration on the satellite image data; in the geographically registered satellite image data, describing the boundary of the water area through visual interpretation; superposing the water area boundary to an all-terrain DEM, obtaining the elevation of each point on the water area boundary line, calculating the average elevation of the water area boundary, and calculating the water area and the water resource amount to obtain the historical water area and the water resource amount; and on the basis of the obtained historical water area and water resource quantity, utilizing an ARIMA model to predict future water resource quantity and water area.

The invention provides an airborne sounding laser radar system structure error calibration method and device based on similar cone scanning. The method comprises the following steps: establishing a structure error calibration field; establishing a global control coordinate system, and acquiring coordinates of a global control point, a measurement station point, a local control point and the center of a reflector of the airborne sounding laser radar by using a total station; acquiring a slope distance from the center of a reflector to a laser foot point on a laser reflection sticker and a rotation angle of a driving motor based on a laser radar, and acquiring coordinates of the laser foot point by utilizing a total station; based on the displacement and rotation geometrical relationship between the laser scanning reference coordinate system and the global control coordinate system, an error equation is constructed according to the slope distance, the rotation angle of the driving motor and the laser foot point coordinates; and iteratively solving the error equation based on a least square indirect adjustment principle to obtain a structure error value of the airborne depth sounding laser radar system. According to the invention, the measurement quality and reliability of the whole depth sounding system can be significantly improved by accurately obtaining the structure error value of the cone-like scanning type airborne depth sounding laser radar.

The present invention provides a system for measuring real-time meteorological and oceanographic data using a buoyage network for smart ports and harbours. It consists of a moored floating station or moored buoy, or network of buoy-based measurement stations (A) moored at the port or harbour waters with the marine navigation and land-based measuring station (B) mounted at jetty or wharf or quay wall of port and harbours. The buoy-based system (A) is equipped with a cylindrical steel buoy structure featuring a mast (7) and is secured using a two-point mooring system. The present system comprises of an integrated monitoring and data transmission system that collects the real-time meteorological and oceanographic data from the sensors and processes the acquired data based on calibration, enabling accurate and reliable measurements. The processed data is then stored in the system's internal memory for analysis and transmitted to a remote-control station.

The invention provides an ocean internal wave data acquisition method, medium and system, and belongs to the technical field of ocean hydrological observation.The ocean internal wave data acquisition method comprises the steps that an acoustic Doppler flow velocity profiler is used for acquiring water body movement data, a temperature-salinity-depth profiler is used for acquiring seawater parameters, and meanwhile a satellite altimeter and drifting buoy data are combined. Performing time-frequency analysis on the water body motion data, and obtaining internal wave candidate data by using band-pass filtering; and constructing an internal wave mathematical equation set comprising a hydromechanics basic equation, buoyancy frequency, a frequency dispersion relation and the like, and verifying and screening out effective data. And inputting the effective data into a pre-trained classification model to determine an internal wave type, finally extracting a key waveform segment through a preset extraction equation set, and generating and outputting internal wave characteristic waveform data. According to the method, multi-source observation data and a mathematical physical model are combined, identification, classification and feature extraction of the ocean internal waves are realized, and the problem that a data acquisition method capable of effectively extracting effective signals of the ocean internal waves and accurately identifying the features of the internal waves is lacked at present is solved.

The invention relates to the field of laser water depth detection, in particular to a water surface fluctuation compensation method for laser sounding, and solves the problems of insufficient precision and water surface fluctuation interference in a traditional sounding technology in an extremely shallow water area. The measured water depth is corrected through the turbidity sensor, the IMU zero offset compensation sensor and the laser displacement sensor, and the purpose of improving the measurement accuracy is achieved. According to the scheme, the stability and precision of depth sounding of the extremely shallow water area are remarkably improved, and the method has high environmental adaptability and wide application prospects.

The invention discloses an airborne disposable temperature probe AXBT system for ocean temperature-depth profile measurement, and the system comprises a display control device which is used for transmitting a control instruction, and receiving and displaying temperature-depth profile data in real time; the putting and transporting equipment is provided with signal receiving and transmitting equipment and an airborne disposable seawater temperature and depth measuring device, and is used for flying to a specified sea area to put the device to a target coordinate point; the signal transceiving equipment is in communication connection with the shore-based display control equipment and the airborne disposable seawater temperature and depth measuring device, and is used for receiving wireless data of the airborne disposable seawater temperature and depth measuring device and forwarding the wireless data to the display control equipment; the airborne disposable seawater temperature and depth measuring device comprises a floating body part, an instrument cabin, a measuring part and a self-destruction mechanism which are sequentially arranged from top to bottom, and is used for acquiring temperature data and depth data, and carrying out data processing and data transmission, high-speed disposable temperature and depth profile measurement and temperature and depth measurement. The method has obvious advantages in the aspects of improving the efficiency, precision and safety of ocean temperature-depth profile measurement, and also shows good adaptability, intellectualization and anti-interference capability.

The invention discloses an automatic channel flow monitoring device, and belongs to the technical field of water flow measurement. An automatic channel flow monitoring device comprises a mounting frame mounted above a to-be-measured channel, the mounting frame spans the two banks of the to-be-measured channel, a detection beam for measuring the flow velocity and the water depth of a water body is arranged in the middle of the mounting frame, and the detection beam is mounted on the mounting frame in a lifting mode in the vertical direction. The mounting frame comprises two vertical beams and a cross beam connected with the two vertical beams, the lower parts of the vertical beams are provided with ground pile parts, the upper parts of the vertical beams are provided with lifting grooves for mounting the lifting mechanisms, and the detection beam is connected with the mounting frame through the lifting mechanisms; the flow monitoring device has the advantages that the flow monitoring device is suitable for flow monitoring in a channel with a wide water surface, and the flow velocity and water depth at different positions below the water surface can be conveniently detected.

The invention relates to an underwater three-dimensional topographic surveying and mapping method and device in a reservoir high sand concentration density current period, and the method comprises the steps: carrying out the shallow stratum profile measurement of a planning reservoir region surveying and mapping region of a reservoir in a density current generation period through a hydrological survey ship carrying a shipborne shallow stratum profiler, and obtaining a plurality of ASC format profile data; interpreting the plurality of ASC format profile data to obtain all observation data of a shallow stratum profile in the surveying and mapping area of the planning reservoir area, and extracting water depth data of the surveying and mapping area of the planning reservoir area according to all the observation data; and determining a thalweg line, a left bank line and a right bank line of the underwater topography of the surveying and mapping area of the planned reservoir area, and generating a three-dimensional topographic surveying and mapping result of the target reservoir during density current occurrence in combination with the water depth data and a preset linear interpolation strategy. Therefore, the problems of low terrain observation efficiency, low result confidence, even incapability of obtaining effective data, high detection cost, poor practicability and the like of the existing underwater terrain observation method during the high sand concentration density flow period of the reservoir are solved.

The invention provides a river sediment physical habitat evolution identification method, device and system and a medium. The method comprises the following steps: acquiring a multi-temporal remote sensing image and hydrological data (flow Q, water level Zw and slope S), screening and other hydrological condition image pairs; extracting a water surface range, and calculating the average width B of the main groove; deducing the average water depth h by using a Manning formula, and calculating the riverbed elevation zbed by combining the Zw; the difference value delta zbed of zbed in different periods is calculated, and the substrate state is judged according to the difference value delta zbed and a threshold value epsilon; and performing segment processing along the center line to output a spatial distribution result. On-site measurement is not needed by relying on conventional data, and consumption is reduced; water level interference is eliminated through equal hydrological condition matching, and comparability is ensured; water depth inversion and differential analysis directly reflect scour deposition and quantitatively reveal rules; long-distance automatic processing improves space-time coverage capability and precision, and provides a basis for river regulation, ecological restoration and drainage basin management.