408results 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 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 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 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 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.

The invention provides a water depth pressure dynamic data characteristic value real-time calculation method and system, electronic equipment and a storage medium, and relates to the technical field of water pressure monitoring. The method comprises the steps that voltage signals reflecting water depth changes of multiple channels are collected, the relevance of the voltage signals is analyzed, and the main fluctuation frequency of water flow is determined; setting a merging proportion, and fusing the multi-channel signals into a target signal; separating the target signal into a smooth trend part and an abrupt change part, and setting an abrupt change judgment threshold based on the energy change; detecting and marking a mutation time interval in the mutation part by using the threshold, and extracting the maximum fluctuation amplitude and duration in the interval as a first feature value; meanwhile, the smooth trend part is used for predicting and correcting the long-term reference offset of the voltage collecting device, the maximum value, the minimum value and the fluctuation range are output on the basis of the corrected signal to serve as second feature values, real-time feature extraction of the dynamic water depth pressure can be achieved, meanwhile, a sudden change event is accurately captured, and a stable extreme value range is output after drift is corrected.

The invention provides a laying tool, a laying method and a recovery method for a sailing type temperature-salinity-depth detector, and the tool comprises a tow fish which is provided with an attitude sensor on the surface of a housing and is used for detecting the pitch angle of the tow fish; the throwing frame is installed on the ship body and used for guiding the laying path of the tow fish; the winch is installed on a ship afterdeck or in a cabin, and the tow fish is hung through a mooring rope. Wherein an executing mechanism of the winch is in communication connection with the attitude sensor and is configured to respond to an attitude signal generated when the tow fish enters water and drive the tow fish to be adjusted to be in a vertical state; and driving the tow fish to be adjusted to be in a horizontal state in response to a posture signal when the tow fish is out of water. The laying tool provided by the invention is suitable for various laying scenes, realizes automatic posture adjustment of the tow fish when the tow fish enters and exits water, improves the automation degree and safety of operation, avoids human interference, and is beneficial to improving the measurement precision of the temperature-salinity-depth sensor.

The invention belongs to the technical field of underwater measurement, and discloses a test probe underwater depth automatic positioning method and system, and the method comprises the steps: collecting an absolute water pressure value of a current underwater environment, and carrying out the calculation of a hydrostatic pressure value through combining with water surface reference air pressure data; meanwhile, acoustic signals from the water surface base station are received, response is returned, and the round-trip propagation time of sound waves in the water body is measured and obtained; collecting water body temperature data and salinity change data, estimating density information of the current water body, and converting a hydrostatic pressure value into a pressure depth value; calculating an average sound wave propagation speed by adopting an empirical sound velocity model, and calculating an acoustic depth value of the probe in combination with back-and-forth propagation time of sound waves in the water body; the depth positioning precision and stability of the underwater probe in a complex environment are effectively improved, and high-reliability and high-precision underwater depth automatic positioning is realized.

The invention provides a shallow sea water depth inversion method and system based on a multi-angle optical radiation transmission model, and relates to the technical field of remote sensing space information. The method comprises the following steps: on the basis of a water body biological optical model, constructing a shallow sea water depth inversion model in combination with a water body and water bottom optical radiation transmission process; and according to the obtained multi-angle satellite remote sensing observation data, calculating and obtaining shallow sea water depth information by using the shallow sea water depth inversion model. According to the invention, by fusing multi-angle satellite remote sensing observation data and a physical model and comprehensively considering water body absorption, scattering and bottom reflection characteristics, a high-robustness and high-precision shallow sea water depth inversion method and system are constructed. The method has adaptive capacity to a complex optical environment in a shallow water area, can realize large-range and high-precision water depth inversion, provides a new technical means for shallow water depth measurement, and has wide application prospects.

The invention provides a river flow online measurement and calculation method based on multi-source data fusion, and belongs to the technical field of river flow measurement. A Bayesian neural network and active learning collaborative hydrological memory reconstruction model is adopted to carry out high-confidence data interpolation on a sensor failure period and quantify uncertainty, fractional calculus is introduced to model a river memory effect, and flow evolution is analyzed through a fractional order water balance equation. And selecting a steady-state or non-constant flow calculation mode according to the flow change rate, inverting an optimal flow field for the non-constant flow by adopting a four-dimensional variational data assimilation method in combination with regularization constraint and time smoothing constraint, and outputting a flow measurement result and an uncertainty quantitative index. The technical problems that flow measurement and calculation data are missing and accurate interpolation is difficult due to sensor failure under the extreme hydrological condition are solved.

The invention discloses a hydrological flow and speed measurement method, which relates to the technical field of hydrological measurement and comprises the following steps: selecting a dynamic anchor point in a target speed measurement area, and carrying out anchor point hovering on an unmanned aerial vehicle according to the dynamic anchor point; the unmanned aerial vehicle collects surrounding images of the unmanned aerial vehicle to obtain obstacle data, and a motion route is generated in real time; the unmanned aerial vehicle performs video acquisition on the target velocity measurement area to generate a three-waveband water surface video, and analyzes the three-waveband water surface video to generate an initial velocity distribution diagram; the unmanned aerial vehicle collects riverbed data and water surface fluctuation data of the target flow measurement area, and according to the riverbed data, a riverbed terrain is obtained, and water depth data and a section average flow velocity are obtained; and constructing a three-dimensional water flow model, collecting a movement track of the buoy group and gyroscope data, correcting the three-dimensional water flow model, and outputting a hydrological flow and velocity measurement result. The method has the effects of improving the measurement precision of flow measurement and speed measurement and improving the flexibility and universality when facing a complex water area.

The invention discloses a topographic change uncertainty analysis method based on time sequence sounding data, and relates to the technical field of marine surveying and mapping. According to the method, high-precision seabed deformation sequence data is acquired through time-space reference unification and data fusion correction processing based on multi-beam sounding data acquired by multiple periods and multiple platforms, and the influence of terrain gradient, seawater depth and the coupling effect of the terrain gradient and the seawater depth on the sounding uncertainty is systematically and quantitatively analyzed; comprehensively considering a coupling effect relationship between water depth and terrain gradient, combining horizontal uncertainty information obtained by the gradient-uncertainty statistical model with vertical uncertainty information obtained by the water depth-uncertainty statistical model based on an error propagation theory, and establishing a gradient-water depth joint probability statistical model under multi-period data constraint; the statistical separation capability of terrain deformation signals and measurement noise is remarkably improved, real and accurate seabed deformation information can be obtained, and precise detection and dynamic monitoring of seabed micro-landform changes in a complex deep sea environment are achieved.