A method and system for monitoring the flow of an under-ice river at a constant depth

Abstract

The application provides a kind of under-ice river flow monitoring method and system of depth cruise, and the application relates to the technical field of hydrological monitoring and hydraulic engineering, steps include starting unmanned aerial vehicle equipped with laser radar and oblique photography camera to fly to the preset height of aerial survey, air scanning is carried out on the river section containing the preset monitoring section, high-precision ice surface three-dimensional model is generated and weak risk area of ice surface is identified, and data is sent to control center;The control center plans the location of the acoustic base station and the ice surface water inlet point according to the scanning data;The navigation coordinate system is established according to the latitude and longitude coordinates of the base station, and the underwater robot is laid to the predetermined depth, and the relative / absolute flow velocity profile is measured by reciprocating depth cruise and using ADCP;The method is a combination of long baseline underwater acoustic positioning network and reciprocating cruise speed measurement method, which provides double, complementary carrier absolute speed acquisition and correction means, and the absolute speed of the robot to the ground is directly solved by using high-precision underwater acoustic positioning data.

Description

Technical Field

[0001] This invention relates to the field of hydrological monitoring and water conservancy engineering technology, specifically a method and system for monitoring subglacial river flow using constant-depth cruise. Background Technology

[0002] Subglacial rivers are channels formed by meltwater from glaciers flowing under the ice through crevasses, melting and eroding the surface. These channels drain the glacial meltwater and emerge at the glacier terminus as proglacial rivers. Subglacial river systems can be dendritic, forming systems hundreds of kilometers long. A dendritic subglacial river system stretching 460 kilometers has been discovered beneath the Antarctic ice sheet. Some valleys on Mars are also thought to have been formed by the erosion of meltwater channels beneath ancient ice sheets. These subglacial channels can transport large amounts of high-pressure freshwater, potentially influencing the flow of the overlying ice.

[0003] Patent publication number CN116754030A discloses a method and device for automatic online monitoring of H-ADCP flow under ice at a hydrological station measuring section. It includes the following steps: a) Drilling holes in the ice surface of the river channel, the hole diameter being adapted to the outer diameter of the underwater antifreeze and insulation sleeve; b) Fixing the cylindrical insulation wall of the ice-covered antifreeze and insulation cavity to the ice surface, and also fixing the antifreeze and insulation sleeve to the ice surface; c) Placing the guide rail frame into the antifreeze and insulation sleeve, fixing the fixing plate according to a set position, and using a power source to generate heat through the heating element to prevent the water inside the antifreeze and insulation sleeve from freezing; d) Lowering the fixing frame using a crank handle, carrying the Doppler monitor to the measurement position, with the fixing frame and fixing plate interlocking to maintain measurement stability, and the water flow velocity and water level signals monitored by the Doppler monitor transmitted to the control center. This invention can operate in frozen environments and is suitable for automatic monitoring of water levels and flows in reservoirs and rivers during the freezing period. Patent publication number CN117723119B discloses a method for real-time monitoring of ecological flow in natural rivers based on tower-based video, including: tower-based video sensor equipment installation; intelligent imaging and data transmission sensor system detection and related parameter acquisition; UAV river cross-section measurement; underwater topographic measurement of the river cross-section; construction of a three-dimensional digital river model and generation of an ecological flow calculation method; extraction of water surface width based on tower-based video; and ecological flow calculation and visualization. This invention constructs a method suitable for real-time monitoring of ecological flow in natural rivers based on tower-based video; significantly improves the time frequency of existing remote sensing ecological flow monitoring, achieving rapid data acquisition, data transmission, and data visualization based on ecological flow targets; reduces the cost of acquiring river flow data in areas without data, and increases its applicability from the method's structure.

[0004] While the aforementioned patents can improve the effectiveness of water monitoring, they still have the following shortcomings: Traditional monitoring methods mainly rely on manual drilling on ice, requiring workers to drill multiple measuring holes on the ice surface and use a current meter to measure each point. This method poses extremely high safety hazards and risks. In the early stages of river freezing and thawing, or in river sections with fast flow and warm drainage, the ice layer's load-bearing capacity is extremely unevenly distributed, posing a life-threatening risk of workers falling into the water due to ice collapse. Furthermore, this method is inefficient, often taking several hours to complete the measurement of a single cross-section, and the acquired data is discrete point velocity, making it difficult to capture the details of the velocity field under complex riverbed morphology and accurately reflect the velocity field distribution under complex riverbeds, resulting in large errors in flow calculation. Although there are currently automated monitoring methods, there are still obvious shortcomings. Fixed acoustic Doppler current meter bottom mounting method: avoids manual ice loading, but bottom mounting equipment can only measure the velocity profile of a single vertical line and cannot move laterally to scan the entire river width; non-contact radar / visual method: these technologies rely on observing the movement of water surface ripples or floating objects. During the freezing period, the thick ice cover completely obscures the water body, causing radar current meters and flow measurement technologies based on UAV images to become completely ineffective. Therefore, existing technologies urgently need an automated monitoring method that can achieve high-precision positioning and flow calculation in complex ice-covered environments without GPS signals and with moving bed interference. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for monitoring subglacial river flow using constant-depth cruise, aiming to solve the problems of high risk factor in manual monitoring and low data acquisition and accuracy of automated monitoring in the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method and system for monitoring subglacial river flow using constant-depth cruise, comprising the following steps: S1, Network Construction: Launch a drone equipped with a lidar and oblique photography camera to fly to the preset aerial survey altitude, perform an aerial scan of the river section containing the preset monitoring section, generate a high-precision 3D model of the ice surface and identify weak and risky areas of the ice surface, and send the data to the control center. Based on the 3D model of the ice surface and the risk area data, the control center plans the deployment locations of the underwater acoustic positioning base stations and the ice surface entry points of the underwater robots. The deployment locations and entry points should avoid the identified weak and risky areas of the ice surface. Subsequently, underwater acoustic positioning base stations are deployed on both banks of the river section to be measured at the planned locations to build an underwater long-baseline acoustic positioning network covering the monitoring section. S2, Equipment Deployment: Drill ice holes at the planned water entry point and deploy an underwater robot equipped with ADCP and underwater acoustic positioning beacon under the ice to perform depth-keeping cruise and flow monitoring tasks. The underwater robot is also equipped with auxiliary sensors that can explore the way in advance and scan the riverbed topography, or follow the ADCP and underwater acoustic positioning beacon to perform encrypted measurements at specific locations. S3, Global Coordinate System Establishment: Through acoustic communication and ranging between the underwater acoustic positioning base station and the underwater acoustic positioning beacon on the underwater robot, the relative position of the underwater robot in the long baseline acoustic positioning network is determined. Combined with the known geographic coordinates of the underwater acoustic positioning base station, a global geodetic coordinate system is established for navigation and data fusion. S4, Guided Depth-Controlled Cruise: This function controls the underwater robot to descend and stabilize at a preset cruise depth. Based on real-time position information provided by a long-baseline acoustic positioning network, it guides the underwater robot to cruise across the river in a vertical plane perpendicular to the main current direction, where the monitoring section is located. During the cruise, the average moving bed velocity is calculated based on the trajectory recorded by bottom tracking. ; S5, Synchronous Data Acquisition: During the cruise motion, the following data are collected: a) Real-time acquisition of the relative flow velocity data of the river water at different depths relative to the underwater robot at the location of the underwater robot via ADCP; b) Synchronous recording of the underwater robot's real-time three-dimensional coordinates and three-dimensional motion velocity vector in the global geodetic coordinate system via the underwater long-baseline acoustic positioning network; c) Synchronous acquisition of water depth data at the monitoring section via ADCP. S6, Data Fusion Processing: The relative velocity data and the three-dimensional motion velocity vector are fused in a spatiotemporal synchronous manner. Based on the principle of motion synthesis, the absolute velocity profile of each sampling point in the global geodetic coordinate system is calculated. The fusion processing includes coordinate transformation and vector superposition. S7, Cross-sectional flow calculation: Based on absolute velocity profile and water depth data, integral calculation is performed within the spatial range of the monitoring cross-section to calculate the total flow of the subglacial river passing through the monitoring cross-section.

[0007] Preferably, in step S1, the underwater acoustic positioning base station includes a main base station and a slave base station, which are respectively deployed on the banks of the river. The underwater long-baseline acoustic positioning network adopts a positioning mode that combines long baselines or ultra-short baselines with long baselines; the underwater robot enters the water at an opening in the ice surface upstream or downstream, or in an unfrozen area.

[0008] Preferably, in step S4, the vertical plane perpendicular to the mainstream direction is determined in the following way: In the global geodetic coordinate system established in S3, the control center defines the main channel direction vector based on historical hydrological data, the direction of the main channel of the river identified by the three-dimensional model of the ice surface, or the direction of water flow obtained by the underwater robot in the vicinity of the cross section. Then, it calculates and generates a plane equation perpendicular to the main channel direction vector, which serves as the path reference plane for the underwater robot's depth-fixed cruise.

[0009] Preferably, in step S4, the trajectory calculation average moving bed speed is... Specifically, it includes: S401, the underwater robot departs from the deployment point at the ice hole on the shore, denoted as position S401. ; S402: The underwater robot maintains its cruising depth, crosses a cross-section perpendicular to the main current to the opposite bank, then turns around and returns to the starting point along the original path. ; S403, during navigation, the underwater robot propels at a constant speed and collects flow velocity information by emitting sound wave pulses at a fixed frequency through ADCP; S404, the acoustic bottom tracking position of the underwater robot should return to normal upon reentry. The underwater robot's trajectory, as recorded by bottom tracking, will show the distance it has moved upstream. ; S405, Calculate the average dynamic bottom velocity ,in This represents the total round-trip time.

[0010] Preferably, in step S6, the three-dimensional motion velocity vector is fused with the relative flow velocity data measured by ADCP. Specifically, the operation is as follows: S601, Obtain the water flow velocity vector relative to the robot measured by ADCP. ; S602, Obtain the robot's absolute velocity vector relative to the ground. ; S603, Calculate the absolute velocity vector of water flow. .

[0011] Preferably, in step 602, the robot's absolute velocity vector relative to the ground... Specifically, it includes: S6021, If ​​the ADCP beam acquires the riverbed echo, then extract the bottom tracking velocity. Calculate the absolute velocity vector of the underwater robot relative to the ground: ; S6022, if the bottom tracking signal-to-noise ratio falls below a threshold due to signal attenuation, then underwater acoustic positioning data is used to determine the coordinate difference between two adjacent positioning pulses. , For the sampling period, calculate the absolute velocity vector of the underwater robot relative to the ground: .

[0012] Preferably, in step S7, the total flow is calculated using the virtual partial flow accumulation method, specifically including: S701 divides the river cross-section into several virtual vertical survey lines based on the underwater robot's cruise trajectory; S702, for each virtual survey line, extract the corresponding absolute velocity profile data; S703, using the beam geometry of ADCP to calculate the vertical average velocity of each water depth unit; S704, Calculate the partial flow between adjacent virtual survey lines. ,in This represents the average flow velocity of this section. This refers to the water flow area of ​​this section; S705, summing all partial traffic to obtain the total traffic. .

[0013] A subglacial river flow monitoring system for a method of monitoring subglacial river flow by enabling underwater robot to cruise at a constant depth includes an underwater robot, a flow velocity measurement unit, an underwater acoustic positioning subsystem, and a shore-based control terminal. The underwater robot is equipped with a propulsion system, depth sensors, a main control unit, and an energy module, and is configured to perform a fixed-depth cruise mission underwater. The velocity measurement unit is an ADCP mounted on an underwater robot, used to measure the velocity profile of the water body. The underwater acoustic positioning subsystem includes several acoustic positioning base stations deployed on both banks of the river and an acoustic transponder installed on the underwater robot for real-time determination of the underwater robot's coordinates. The shore-based control terminal is wirelessly connected to the acoustic positioning base station to send cruise commands, receive positioning data and flow rate data, and perform flow calculations. Under the command of the shore-based control terminal, the underwater robot, guided by the underwater acoustic positioning subsystem, carries the current velocity measurement unit and traverses the river monitoring sections. Preferably, the underwater robot is also equipped with obstacle avoidance sonar, which is configured to detect obstacles such as ice floes or riverbed obstacles ahead and feed back the obstacle information to the main control unit to perform emergency obstacle avoidance maneuvers.

[0014] Preferably, the underwater acoustic positioning subsystem operates in the mid-frequency range of 10kHz to 50kHz to adapt to the acoustic environment of rivers with high sediment content and high background noise. The positioning base station has a multipath effect suppression function, which distinguishes between direct waves and riverbank reflected waves through spread spectrum signal modulation.

[0015] The beneficial effects are: 1. Under conditions where the riverbed can move, the bottom tracking velocity relied upon by traditional ADCP will produce significant errors, leading to distorted flow calculation results. However, this method provides a dual and complementary means of acquiring and correcting the absolute velocity of the carrier by combining a long-baseline underwater acoustic positioning network with a round-trip cruise velocity measurement method. It directly calculates the robot's absolute velocity relative to the ground using high-precision underwater acoustic positioning data, without relying on riverbed echoes, thus completely eliminating the fundamental error caused by the moving bed. Moreover, the round-trip cruise path can directly measure the average moving bed velocity. This data can be used to verify the positioning data and can also be used to accurately correct it when bottom tracking is effective. This double-insurance, mutually calibrated velocity calculation method ensures that a high-precision absolute velocity profile of the water flow can be obtained under any riverbed conditions, greatly improving the accuracy and reliability of flow monitoring.

[0016] 2. Compared with the traditional method of setting up multiple fixed points on the ice surface for measurement, this method uses a single underwater robot carrying an ADCP to automatically scan the entire cross section. This method has high measurement efficiency and requires less manpower. By using the virtual partial flow accumulation method, virtual vertical lines of arbitrary density can be flexibly divided according to the continuous cruise trajectory of the robot to perform high-resolution flow integration, which can more realistically reflect the continuous distribution of flow velocity on the cross section. It is especially suitable for river sections with complex flow patterns, and the calculated total flow is more accurate.

[0017] 3. Utilizing an underwater robot equipped with an upward-looking sonar or upward-looking ADCP, this system can simultaneously measure flow velocity and scan the bottom morphology of the ice sheet above in real time, obtaining continuous ice thickness data. Compared to the traditional method of estimating area solely based on water level, this further reduces the uncertainty in flow rate calculation. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram of the overall system scenario of the present invention; Figure 3 This is a schematic diagram of the absolute velocity vector calculation process of the present invention; Figure 4 This is a schematic diagram of the method for calculating total flow rate according to the present invention. Detailed Implementation

[0019] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0020] Example 1 A method for monitoring subglacial river flow using constant-depth cruise is described below: S1, Network Construction and Equipment Deployment: Three underwater acoustic positioning base stations are deployed on both banks of the river to be measured. Each base station includes a master base station and slave base stations, which are anchored to the banks of the river (as known coordinate points). In this embodiment, the underwater acoustic positioning base stations refer to the deployment of base stations in a long baseline system. Typically, to calculate the two-dimensional coordinates (X,Y) on the horizontal plane, at least three non-collinear base stations are needed, three on each bank for a total of six. This is to increase redundancy, improve positioning accuracy, and expand coverage. Long baseline acoustic positioning beacons (as...) are also deployed. (Reference points), construct an underwater long-baseline acoustic positioning network covering the monitoring section. The underwater long-baseline acoustic positioning network adopts a positioning mode that combines long baselines or ultra-short baselines with long baselines. After the underwater long-baseline acoustic positioning network is constructed, network accuracy verification is required. The specific operation is as follows: Hover the underwater robot at the known coordinate points of the section, compare the network positioning results with the known coordinates, and confirm that the horizontal positioning error is less than 0.5 meters before starting the formal flow monitoring task. The network uses a time division multiple access (TDMA) mechanism to allocate communication time slots for each transponder and tag to avoid signal collisions. The underwater robot establishes a command and data link with the ice surface main base station through the underwater acoustic communication device, and executes a "surfacing-hovering" failure protection strategy when the task is out of control. S101, Drill four 30cm diameter positioning holes on the ice surface to suspend the coded acoustic transponder at a depth of approximately 1.5 meters below the ice. In this embodiment, the water flow near the surface (especially at the ice-water interface) is unstable and may be turbulent. At a depth of 1.5 meters, the water flow is usually more stable, providing a more stable acoustic signal. This prevents the equipment from being struck by ice when it moves or melts, ensuring it is in a region of stable water flow. In this embodiment, the positioning holes are for suspending the transponders. These transponders form a known coordinate reference network underwater. The four points can better cover the entire measurement section and are used to calibrate the sound velocity profile. Sound velocity profile calibration: Temperature stratification may occur in the water under the ice (e.g., The 0-1 meter depth is a mixture of ice and water, while the depth below 1 meter is warmer river water. The temperature sensor built into the ADCP is insufficient. It is usually necessary to measure a sound velocity profile using a CTD (Celestial Temperature-Depth) or SVP (Sound Velocity Profiler) before measurement and input it into the ADCP processing software. Otherwise, the vertical velocity profile will be inaccurate. The coded acoustic transponder, when it receives an acoustic interrogation signal from the base station, will reply with a specific coded signal after a fixed delay. By measuring the round-trip time of the "interrogation-response" sound wave, multiplying it by the sound velocity, and then dividing by 2, the distance between the base station and the transponder can be obtained. By measuring the distance from multiple base stations, the precise three-dimensional coordinates of the transponder underwater can be calculated. S102, an underwater robot equipped with a 300kHz ADCP and an underwater acoustic positioning tag is placed into the ice hole. In this embodiment, the higher the frequency of the ADCP, the higher the accuracy, but the shallower the effective flow measurement depth (easily absorbed and attenuated by the water). 300kHz is a mid-to-low frequency, and in a river environment, the effective flow measurement depth can reach tens of meters, suitable for most river cross-section measurements. Under ice, the ADCP cannot use GPS to locate its own position. The 300kHz beam can penetrate the water well. Using bottom tracking mode or combined with long baseline positioning, the water flow velocity can be inferred. The underwater robot hovers at a depth of 1 meter under the ice for 8 minutes to allow the ceramic transducer and internal oscillator of the ADCP to reach thermal equilibrium with the water temperature, thereby eliminating frequency drift and sound velocity calculation errors caused by thermal expansion and contraction. In this embodiment, the core component of the ADCP is the ceramic piezoelectric transducer, which generates sound waves through vibration. Temperature changes cause slight thermal expansion and contraction of the ceramic plate and internal oscillator, which changes the resonant frequency of the oscillator, resulting in the emission... When the sound wave frequency drifts, ADCP velocimetry is based on the Doppler effect (frequency change). If the frequency reference is inaccurate, the velocity calculation will be completely wrong. ADCP velocity calculation requires knowing the current sound speed in the water. The sound speed formula is C≈1449.2+4.6T-0.055T² (T is the water temperature). 1449.2 is the reference sound speed, which is the typical propagation speed of sound waves in fresh water at 0℃. 4.6 is the first-order temperature coefficient, which increases the sound speed by 4.6 m / s for every 1℃ increase in temperature (physical property of water). -0.055 is the second-order temperature coefficient, used to correct the nonlinear effect of slower sound speed growth at high temperatures (higher-order compensation). It is very sensitive to temperature. If the internal temperature of the transducer is not stable, the reading of its built-in temperature sensor will be inaccurate, resulting in incorrect sound speed calculation. This is an engineering experience time. When the transducer is placed from cold air (or ice storage) into ice water close to 0°C, the electronic equipment and ceramic components need sufficient time (usually 5-10 minutes) to make their internal temperature completely consistent with the external water temperature and eliminate the internal temperature gradient.

[0021] S2, Global Coordinate System Establishment: Through acoustic communication and ranging between the underwater acoustic positioning base station and the underwater acoustic positioning beacon on the underwater robot, the relative position of the underwater robot in the long-baseline acoustic positioning network is determined. Combined with the known geographic coordinates of the underwater acoustic positioning base station, a global geodetic coordinate system is established for navigation and data fusion. The real-time acoustic positioning results of the underwater robot are transformed from the temporary network coordinate system to the WGS-84 or CGCS2000 global geodetic coordinate system. The specific process includes: S201 uses high-precision GNSS to accurately determine the geodetic coordinates of the antenna centers of all underwater acoustic positioning base stations (master / slave base stations) on both banks, with a planar accuracy of 2cm. These base stations are the sources of acoustic signal transmission / reception, and their coordinates are the only absolute reference for calculating the position of the underwater robot. S202, Install a pressure sensor at the ice block, reset the depth sensor reading to zero, and establish... The pressure reference surface is established, and its elevation is determined. The water depth measured by the pressure sensor is converted into elevation to achieve vertical coordinate unification. S203 utilizes the known coordinates of the shore base station to perform acoustic ranging with the underwater transponder, calculates the precise coordinates of the underwater transponder in the global coordinate system through the adjustment algorithm, generates a beacon ephemeris, and transmits the shore coordinate reference to the underwater via sound waves to construct an underwater known point network. S204 uses high-precision real-time dynamic differential GPS to accurately record the precise latitude and longitude coordinates of each ice hole. It is used for equipment deployment, retrieval path navigation, and data management.

[0022] S3, Guided Depth-Fixing Cruise: This method controls the underwater robot to descend and stabilize at a preset cruise depth. Based on real-time position information provided by a long-baseline acoustic positioning network, it guides the underwater robot to cruise back and forth along a cross-section perpendicular to the main river channel, located at the monitored cross-section. (Here, "deep-fixing" means the underwater robot maintains a fixed depth throughout the cruise (e.g., 2 meters below the ice). The cross-section is a two-dimensional vertical plane; therefore, the underwater robot's actual trajectory is a horizontal straight line with a constant depth within this vertical plane. It doesn't wander aimlessly in three-dimensional space, but rather...) Like a ruler, the underwater robot is swept back and forth from the left bank to the right bank at a fixed depth on the riverbed. This ensures that all velocity data comes from the same horizontal layer on the same vertical profile, greatly simplifying subsequent flow integral calculations. High-density velocity data is collected simultaneously, and the underwater robot's absolute trajectory relative to the riverbed is recorded using acoustic bottom tracking. In this embodiment, the bottom-tracking ADCP emits sound waves towards the riverbed, and the Doppler frequency shift is used to measure the underwater robot's absolute velocity relative to the riverbed surface (ground reference). This is the standard method for obtaining the underwater robot's speed relative to the ground, combined with its theoretical value in the global coordinate system. The trajectory is calculated and the measurement deviation caused by the movement of sediment in the riverbed is separated. Finally, the accurate vertical average flow velocity is obtained by correcting the dynamic bottom velocity. In this embodiment, when the riverbed is composed of movable sand and gravel, the bed surface itself will move along the direction of water flow (such as bedload transport), causing the "riverbed" to not be a static reference frame. At this time, the velocity measured by bottom tracking is the "velocity of the underwater robot relative to the moving riverbed", not the absolute velocity of the underwater robot relative to the stationary ground. Since the positioning in the global coordinate system provides the absolute trajectory of the underwater robot in the stationary ground coordinate system, while bottom tracking provides the relative trajectory... Regarding the trajectory of the (potentially moving) riverbed, the two should be consistent under the assumption of a static riverbed. If a systematic deviation exists, this deviation can be attributed to the "moving bottom" effect. The vertical plane perpendicular to the mainstream direction is determined as follows: In the global geodetic coordinate system established by S3, the control center defines the mainstream direction vector based on historical hydrological data, the river's main channel orientation identified by the three-dimensional ice surface model, or the water flow direction obtained from the underwater robot's preliminary detection near the cross-section. Then, a plane equation perpendicular to this mainstream direction vector is calculated and generated, serving as the path reference plane for the underwater robot's depth-fixed cruise. The specific operation is as follows: S301, the underwater robot departs from the deployment point (point A) at the ice hole on the shore and resets the relative displacement measured by the bottom tracking system to zero, that is, sets the starting coordinates of bottom tracking as the position. ; S302, the underwater robot maintains a cruising depth of 2 meters below the ice, crosses a cross section perpendicular to the main current to the opposite bank, then turns around and returns to the starting point along the original path. S303, during navigation, the underwater robot propels at a constant speed and collects flow velocity information by emitting sound wave pulses at a fixed frequency through ADCP; S304, the acoustic bottom tracking position of the underwater robot should return to normal upon reentry. The underwater robot's trajectory, as recorded by bottom tracking, will show the distance it has moved upstream. ; S305, Calculate the average dynamic bottom velocity ,in Total round-trip time; S306. If the difference in average flow velocity between two measurements exceeds a threshold (e.g., 10%), the flow is determined to be unsteady, and linear interpolation or time-weighted methods are used to further analyze the flow. Make corrections or trigger a remeasurement.

[0023] S4, Synchronous Data Acquisition: During the cruise motion, the following data are collected: a) Three-dimensional relative velocity profiles of river water at each water layer relative to the underwater robot platform coordinate system are acquired via ADCP, and quality control parameters such as echo intensity and correlation are recorded simultaneously; b) The underwater long-baseline acoustic positioning network fuses inertial navigation data to output the robot's absolute three-dimensional position, velocity vector, and attitude angle in the Earth coordinate system in real time; c) The bottom tracking function of ADCP continuously measures the distance from the robot to the riverbed, and combines it with the robot's real-time depth data to jointly construct the underwater topographic profile of the monitoring section. All data streams are strictly aligned through a unified time label to form a spatiotemporally synchronized observation dataset, providing a complete and accurate data foundation for subsequent conversion of relative velocity to absolute ground velocity, correction of dynamic bottom error, and calculation of cross-sectional flow.

[0024] S5, Data Fusion Processing: The relative flow velocity data and the three-dimensional motion velocity vector are spatiotemporally fused. Based on the principle of motion synthesis, the absolute flow velocity profile of each sampling point in the global geodetic coordinate system is calculated. The fusion processing includes coordinate transformation and vector superposition. In this embodiment, the coordinate transformation specifically includes: using the inertial measurement unit (IMU) or magnetometer data carried by the underwater robot to obtain the robot's heading angle, roll angle, and pitch angle, and establishing a three-dimensional rotation matrix from the ADCP beam coordinate system (radial velocity) to the robot carrier coordinate system, and then to the global geodetic coordinate system. The three-dimensional motion velocity vector is used to fuse the relative flow velocity data measured by ADCP. The specific operation is as follows: S501 extracts the water flow velocity vector relative to the robot platform coordinate system, measured at timestamp t, from the raw ADCP data. ; S502, Obtain the robot's absolute velocity vector relative to the ground. The specific process is as follows: S5021, If ​​the ADCP beam acquires the riverbed echo, then extract the bottom tracking velocity. Calculate the absolute velocity vector of the underwater robot relative to the ground: S5022, if bottom tracking fails due to deep water or high sediment content, then underwater acoustic positioning data is used to determine the location based on two adjacent positioning pulses (sampling period). Coordinate difference Calculate the absolute velocity vector of the underwater robot relative to the ground: In S6022, when the bottom tracking signal-to-noise ratio (SNR) is lower than the threshold, the update frequency (≥1Hz) and horizontal accuracy (better than 0.5m) of the underwater acoustic positioning data are prioritized. If the positioning data does not meet the requirements, the system switches to IMU-based dead reckoning (DR) mode and uses the underwater acoustic positioning data for periodic calibration.

[0025] S503, Calculate the absolute velocity vector of the water flow. .

[0026] S504, if the ADCP has bottom tracking capability and the riverbed sediment echo is good, bottom tracking velocity should be used as the preferred method. The correction reference; if bottom tracking fails, then the velocity vector provided by the underwater acoustic positioning system is relied upon entirely.

[0027] S6, Cross-sectional Discharge Calculation: Based on absolute velocity profile and water depth data, integral calculations are performed within the spatial range of the monitored cross-section to calculate the total discharge of the subglacial river through the monitored cross-section. The specific operation is as follows: S601. Based on the underwater robot's cruise trajectory, the river cross-section is divided into 50 virtual vertical survey lines; S602. For each virtual survey line, extract the corresponding absolute velocity profile data; S603. Calculate the vertical average velocity of each depth element using the beam geometry of ADCP. ; S604. Calculate the partial flow between adjacent virtual survey lines. ,in This refers to the water flow area of ​​this section; S605, sum up all partial flows to get the total flow. .

[0028] Example 2 Based on the above embodiments, the similarities between this embodiment and Embodiment 1 will not be repeated. The difference is that, in order to further accurately determine the location of the ice hole, this embodiment uses a drone for monitoring first.

[0029] In this embodiment, in step S1, network construction is performed as follows: A drone equipped with a lidar and an oblique photography camera is launched and flies to a preset aerial survey altitude to perform an aerial scan of the river section containing the preset monitoring section, generating a high-precision three-dimensional model of the ice surface and identifying weak risk areas on the ice surface. The data is then sent to the control center. Based on the three-dimensional model of the ice surface and the risk area data, the control center plans the deployment locations of the underwater acoustic positioning base stations and the ice entry points of the underwater robots. The deployment locations and entry points should avoid the identified weak risk areas on the ice surface. Subsequently, underwater acoustic positioning base stations are deployed on both banks of the river section to be measured at the planned locations to construct an underwater long-baseline acoustic positioning network covering the monitoring section. In step S1, equipment deployment involves drilling ice holes at the planned water entry point and deploying an underwater robot equipped with an ADCP and a hydroacoustic beacon under the ice to perform depth-keeping cruises and flow monitoring tasks. The underwater robot is also equipped with auxiliary sensors that can explore the riverbed and scan the terrain in advance, or follow the ADCP and hydroacoustic beacon to perform intensive measurements at specific locations.

[0030] Compared to Example 1, in this example, the position of the ice hole can be determined, avoiding deviations in the position of the ice hole.

[0031] Example 3 Based on Embodiments 1 and 2, this embodiment provides a subglacial river flow monitoring system for a constant-depth cruise method. Specifically, it includes an underwater robot, a flow velocity measurement unit, an underwater acoustic positioning subsystem, and a shore-based control terminal. The underwater robot is equipped with a propulsion system, a depth sensor, a main control unit, and an energy module, and is configured to perform a constant-depth cruise mission underwater. The flow velocity measurement unit is an ADCP mounted on the underwater robot, used to measure the water flow velocity profile. The underwater acoustic positioning subsystem includes several acoustic positioning base stations deployed on both banks of the river and an acoustic transponder installed on the underwater robot, used to determine the underwater robot's coordinates in real time. The shore-based control terminal is wirelessly connected to the acoustic positioning base stations, used to send cruise commands, receive positioning data and flow velocity data, and perform flow calculations. Under the command of the shore-based control terminal and guided by the underwater acoustic positioning subsystem, the underwater robot carries the flow velocity measurement unit and traverses the river monitoring section.

[0032] Specifically, the underwater robot is also equipped with obstacle avoidance sonar, which is configured to detect obstacles such as ice floes or riverbed obstacles ahead and feed the obstacle information back to the main control unit to execute emergency obstacle avoidance maneuvers.

[0033] The underwater acoustic positioning subsystem operates in the mid-frequency range of 10kHz to 50kHz to adapt to the acoustic environment of rivers with high sediment content and high background noise. The positioning base station has a multipath effect suppression function and distinguishes between direct waves and riverbank reflected waves through spread spectrum signal modulation.

[0034] The embodiments of the present invention described above do not constitute a limitation on the scope of protection of the present invention. The basic concept of the present invention is to provide underwater robots with sub-meter-level absolute geographic coordinate references through a shore-based long-baseline underwater acoustic positioning network, ensuring that the robot can accurately cruise along a predetermined cross-section in narrow river channels. Simultaneously, it provides an accurate "geographic reference system" for ADCP flow velocity measurement, realizing fully automated unmanned measurement. Operators only need to deploy acoustic beacons in a safe area on the shore or on structurally stable ice to remotely control the underwater robot to complete flow monitoring across the entire cross-section. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method for monitoring subglacial river flow using constant-depth cruise, characterized in that, Includes the following steps: S1, Network Construction: Launch a drone equipped with a lidar and oblique photography camera to fly to the preset aerial survey altitude, perform an aerial scan of the river section containing the preset monitoring section, generate a high-precision 3D model of the ice surface and identify weak and risky areas of the ice surface, and send the data to the control center. Based on the 3D model of the ice surface and the risk area data, the control center plans the deployment locations of the underwater acoustic positioning base stations and the ice surface entry points of the underwater robots. The deployment locations and entry points should avoid the identified weak and risky areas of the ice surface. Subsequently, underwater acoustic positioning base stations are deployed on both banks of the river section to be measured at the planned locations to build an underwater long-baseline acoustic positioning network covering the monitoring section. S2, Equipment Deployment: Drill ice holes at the planned water entry point and deploy an underwater robot equipped with ADCP and underwater acoustic positioning beacon under the ice to perform depth-keeping cruise and flow monitoring tasks. The underwater robot is also equipped with auxiliary sensors that can explore the way in advance and scan the riverbed topography, or follow the ADCP and underwater acoustic positioning beacon to perform encrypted measurements at specific locations. S3, Global Coordinate System Establishment: Through acoustic communication and ranging between the underwater acoustic positioning base station and the underwater acoustic positioning beacon on the underwater robot, the relative position of the underwater robot in the long baseline acoustic positioning network is determined. Combined with the known geographic coordinates of the underwater acoustic positioning base station, a global geodetic coordinate system is established for navigation and data fusion. S4, Guided Depth-Controlled Cruise: This function controls the underwater robot to descend and stabilize at a preset cruise depth. Based on real-time position information provided by a long-baseline acoustic positioning network, it guides the underwater robot to cruise across the river in a vertical plane perpendicular to the main current direction, where the monitoring section is located. During the cruise, the average moving bed velocity is calculated based on the trajectory recorded by bottom tracking. ; S5, Synchronous Data Acquisition: During the cruise motion, the following data are collected: a) Real-time acquisition of the relative flow velocity data of the river water at different depths relative to the underwater robot at the location of the underwater robot via ADCP; b) Synchronous recording of the underwater robot's real-time three-dimensional coordinates and three-dimensional motion velocity vector in the global geodetic coordinate system via the underwater long-baseline acoustic positioning network; c) Synchronous acquisition of water depth data at the monitoring section via ADCP. S6, Data Fusion Processing: The relative velocity data and the three-dimensional motion velocity vector are fused in a spatiotemporal synchronous manner. Based on the principle of motion synthesis, the absolute velocity profile of each sampling point in the global geodetic coordinate system is calculated. The fusion processing includes coordinate transformation and vector superposition. S7, Cross-sectional flow calculation: Based on absolute velocity profile and water depth data, integral calculation is performed within the spatial range of the monitoring cross-section to calculate the total flow of the subglacial river passing through the monitoring cross-section.

2. The method for monitoring subglacial river flow using constant-depth cruise as described in claim 1, characterized in that, In step S1, the underwater acoustic positioning base station includes a main base station and a slave base station, which are respectively deployed on the banks of the river. The underwater long-baseline acoustic positioning network adopts a positioning mode that combines long baselines or ultra-short baselines with long baselines; the underwater robot enters the water at an opening in the ice surface upstream or downstream, or in an unfrozen area.

3. The method for monitoring subglacial river flow using constant-depth cruise as described in claim 1, characterized in that, In step S4, the vertical plane perpendicular to the mainstream direction is determined in the following way: In the global geodetic coordinate system established in S3, the control center defines the main channel direction vector based on historical hydrological data, the direction of the main channel of the river identified by the three-dimensional model of the ice surface, or the direction of water flow obtained by the underwater robot in the vicinity of the cross section. Then, it calculates and generates a plane equation perpendicular to the main channel direction vector, which serves as the path reference plane for the underwater robot's depth-fixed cruise.

4. The method for monitoring subglacial river flow using constant-depth cruise as described in claim 1, characterized in that, In step S4, the trajectory is calculated to determine the average moving bed speed. Specifically, it includes: S401, the underwater robot departs from the deployment point at the ice hole on the shore, denoted as position S401. ; S402: The underwater robot maintains its cruising depth, crosses a cross-section perpendicular to the main current to the opposite bank, then turns around and returns to the starting point along the original path. ; S403, during navigation, the underwater robot propels at a constant speed and collects flow velocity information by emitting sound wave pulses at a fixed frequency through ADCP; S404, the acoustic bottom tracking position of the underwater robot should return to normal upon reentry. The underwater robot's trajectory, as recorded by bottom tracking, will show the distance it has moved upstream. ; S405, Calculate the average dynamic bottom velocity ,in This represents the total round-trip time.

5. The method for monitoring subglacial river flow using constant-depth cruise as described in claim 1, characterized in that, S6 In this step, the three-dimensional motion velocity vector is used to fuse the relative flow velocity data measured by ADCP. The specific operation is as follows: S601, Obtain the water flow velocity vector relative to the robot measured by ADCP. ; S602, Obtain the robot's absolute velocity vector relative to the ground. ; S603, Calculate the absolute velocity vector of the water flow. .

6. The method for monitoring subglacial river flow using constant-depth cruise as described in claim 5, characterized in that, In step 602, the robot's absolute velocity vector relative to the ground... Specifically, it includes: S6021, If ​​the ADCP beam acquires the riverbed echo, then extract the bottom tracking velocity. Calculate the absolute velocity vector of the underwater robot relative to the ground: ； S6022, if the bottom tracking signal-to-noise ratio falls below a threshold due to signal attenuation, then underwater acoustic positioning data is used to determine the coordinate difference between two adjacent positioning pulses. , For the sampling period, calculate the absolute velocity vector of the underwater robot relative to the ground: 。 7. The method for monitoring subglacial river flow using constant-depth cruise as described in claim 1, characterized in that, In step S7, the total flow is calculated using the virtual partial flow accumulation method, specifically including: S701 divides the river cross-section into several virtual vertical survey lines based on the underwater robot's cruise trajectory; S702, for each virtual survey line, extract the corresponding absolute velocity profile data; S703, using the beam geometry of ADCP to calculate the vertical average velocity of each water depth unit; S704, Calculate the partial flow between adjacent virtual survey lines. ,in This represents the average flow velocity of this section. For this section, the water area is calculated as follows: In S701, the first and last virtual survey lines are located at the waterline on both banks. For the bank area, the water area is... The calculation uses a trapezoidal or triangular approximation method, and the flow velocity is extrapolated from the outermost effective ADCP beam data; S705, summing all partial traffic to obtain the total traffic. .

8. A subglacial river flow monitoring system for implementing the constant-depth cruise method for subglacial river flow monitoring as described in any one of 1-7, characterized in that, Includes underwater robots, current velocity measurement units, underwater acoustic positioning subsystems, and shore-based control terminals; The underwater robot is equipped with a propulsion system, depth sensors, a main control unit, and an energy module, and is configured to perform a fixed-depth cruise mission underwater. The velocity measurement unit is an ADCP mounted on an underwater robot, used to measure the velocity profile of water flow. The underwater acoustic positioning subsystem includes several acoustic positioning base stations deployed on both banks of the river and an acoustic transponder installed on the underwater robot for real-time determination of the underwater robot's coordinates. The shore-based control terminal is wirelessly connected to the acoustic positioning base station to send cruise commands, receive positioning data and flow rate data, and perform flow calculations. Under the command of the shore-based control terminal, the underwater robot, guided by the underwater acoustic positioning subsystem, carries the flow velocity measurement unit to traverse the river monitoring sections.

9. A constant-depth cruise subglacial river flow monitoring system according to claim 8, characterized in that, The underwater robot is also equipped with obstacle avoidance sonar, which is configured to detect obstacles such as ice floes or riverbed obstacles ahead and feed back the obstacle information to the main control unit to execute emergency obstacle avoidance maneuvers.

10. A constant-depth cruise subglacial river flow monitoring system according to claim 9, characterized in that, The underwater acoustic positioning subsystem operates in the mid-frequency range of 10kHz to 50kHz to adapt to the acoustic environment of rivers with high sediment content and high background noise. The positioning base station has a multipath effect suppression function, which distinguishes between direct waves and riverbank reflected waves through spread spectrum signal modulation.

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