Multidimensional Hydrological Real-time Mapping and Disaster Early Warning System and Method for Smart Ocean

Abstract

This invention belongs to the field of smart ocean monitoring technology and discloses a multi-dimensional hydrological real-time mapping and disaster early warning system and method for smart oceans. It includes: collecting multi-dimensional hydrological mapping datasets of the target sea area within a continuous monitoring period, and extracting seabed sedimentation, seabed erosion, slope change, and channel migration to form a seabed topographic change feature set; analyzing the coupled and enhanced effects of seabed topographic changes on local velocity amplification, flow direction reversal, and wave aggregation based on the seabed topographic change feature set and the multi-dimensional hydrological mapping dataset, forming a coupled risk result set; dynamically identifying scour instability precursor zones, nearshore erosion precursor zones, and channel siltation precursor zones based on the coupled risk result set, forming a disaster precursor feature set, and outputting multi-dimensional hydrological disaster early warning results. This invention provides systematic real-time mapping and disaster early warning technology support for channel navigation safety management, nearshore shoreline protection, and marine engineering safety operation and maintenance in smart ocean scenarios.

Description

Technical Field

[0001] This invention relates to the field of smart ocean monitoring technology, and more specifically, to a multi-dimensional real-time hydrological mapping and disaster early warning system and method for smart oceans. Background Technology

[0002] With the continuous advancement of smart ocean construction, marine environmental monitoring is gradually developing from traditional discrete, single-point observation to continuous, networked, and intelligent methods. Especially in ports, waterways, nearshore waters, island areas, and areas with frequent marine engineering activities, various hydrological processes such as seabed topography evolution, tidal fluctuations, current field changes, and wave aggregation are coupled, directly affecting navigation safety, nearshore shoreline stability, and the operational safety of marine facilities. Among existing marine monitoring technologies, one type of approach mainly focuses on using bathymetry equipment to obtain seabed topographic information and generate nautical charts or water depth data. Another type of approach mainly focuses on independent monitoring and threshold alarms for single hydrological parameters such as tide level, current velocity, or waves. Although these technologies can reflect local seabed topographic conditions or single hydrological change characteristics, they usually lack the ability to comprehensively analyze the relationship between multi-temporal seabed topographic evolution processes and multi-dimensional hydrodynamic changes, making it difficult to meet the needs of real-time mapping and disaster precursor identification in smart ocean scenarios.

[0003] Furthermore, marine disasters are often not directly triggered by a single anomalous parameter, but rather formed by the long-term coupling effect of seabed topographic changes and hydrodynamic field redistribution. For example, local seabed scouring and siltation may alter the nearshore flow field structure, thereby inducing risks such as nearshore erosion, scour instability, or channel blockage. However, existing technologies can only passively identify local velocity or depth anomalies after they have already occurred, lacking the ability to identify disaster precursor areas in advance based on the correlation mechanism between topographic changes and multi-dimensional hydrological information such as tide level, current velocity, and waves. Therefore, there is an urgent need for a multi-dimensional hydrological real-time mapping and disaster early warning method that can be used for smart ocean scenarios to integrate and analyze multi-temporal seabed mapping data and multi-dimensional hydrodynamic observation data, and thereby achieve disaster precursor identification and early warning output.

[0004] In view of this, the present invention proposes a multi-dimensional real-time hydrological mapping and disaster early warning system and method for smart oceans to solve the above problems. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the existing technology and achieve the above objectives, the present invention provides the following technical solution: a multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans, comprising: Multi-temporal acoustic bathymetry data of the target sea area are collected during the continuous monitoring period. Based on the multi-temporal acoustic bathymetry data, the seabed topography grid corresponding to each monitoring time is generated. At the same time, tide level sequence, current velocity profile sequence and wave sequence are collected to form a multi-dimensional hydrological mapping dataset. Based on the seabed topographic grid at adjacent monitoring times in the multidimensional hydrological mapping dataset, seabed sedimentation, seabed erosion, slope change and channel migration are extracted to form a seabed topographic change feature set. Based on the seabed topographic change feature set, combined with the tide level sequence, current velocity profile sequence and wave sequence in the multidimensional hydrological mapping dataset, the coupling enhancement effect of seabed topographic change on local current velocity amplification, current direction reversal and wave aggregation is analyzed, and a coupling risk result set is formed. Based on the coupled risk result set, the precursor areas of scour instability, nearshore erosion, and channel siltation are dynamically identified to form a disaster precursor feature set. Based on the disaster precursor feature set, spatial distribution maps, evolution trend prediction curves and risk levels of each precursor area are generated, and multi-dimensional hydrological disaster early warning results are output.

[0006] Furthermore, methods for forming multidimensional hydrological mapping datasets include: The seabed topographic grid, tide level records in the tide level sequence, single-phase current velocity profile data in the current velocity profile sequence, and wave records in the wave sequence are correlated and matched at the same monitoring time to form multidimensional hydrological mapping data for each monitoring time; the multidimensional hydrological mapping data for all monitoring times are summarized to form a multidimensional hydrological mapping dataset. The seabed topography grid includes multiple grid nodes, each with grid node coordinates and grid depth values. The grid node coordinates include the east and north coordinates of the grid node in a preset plane coordinate system. The tide level record includes a monitoring time and a tide level value. The single-phase current velocity profile data includes a monitoring time and multiple layered current velocity records. Each layered current velocity record includes a depth layer identifier, current velocity magnitude, and current velocity direction. The wave record includes a monitoring time and a set of wave characteristic parameters, including significant wave height, mean wave period, and main wave direction.

[0007] Furthermore, methods for forming a set of seafloor topographic variation features include: Based on the grid water depth value of each grid node, the corresponding water depth change is calculated, and based on the water depth change, sedimentation and scour classification and connected component aggregation operations are performed to obtain multiple sedimentation or scour regions. For each sedimentation region, the corresponding seabed sedimentation volume is calculated; for each scour region, the corresponding seabed scour volume is calculated; the slope change value of each grid node is calculated, and based on the slope change value, slope anomaly node labeling and connected component aggregation operations are performed to obtain multiple slope change regions; for each slope change region, the corresponding slope change volume is calculated. Identify trench structures in each seabed topographic grid and determine whether a matching relationship has been established; mark each pair of trench structures with an established matching relationship as a trench pair, which includes early trenches and late trenches; calculate the corresponding trench migration amount for each trench pair. The seabed sedimentation volume of all sedimentation areas, the seabed scour volume of all scour areas, the slope change volume of all slope change areas, and the gully migration volume of all gully pairs corresponding to two adjacent monitoring times are summarized and integrated to form a record of topographic change characteristics between corresponding adjacent monitoring times; the topographic change characteristic records between all adjacent monitoring times are summarized to form a set of seabed topographic change characteristics.

[0008] Furthermore, methods for forming a set of coupled risk outcomes include: For each scour area, the local velocity amplification effect caused by scour is evaluated, and the velocity amplification evaluation record for the corresponding scour area is obtained; for each sedimentation area, the local velocity amplification effect caused by sedimentation is evaluated, and the velocity amplification evaluation record for the corresponding sedimentation area is obtained; the velocity amplification evaluation records corresponding to all scour areas and sedimentation areas are summarized to form the velocity amplification coupling analysis results. For each slope change area, the flow direction reversal effect caused by the slope change is evaluated, and the flow direction reversal evaluation record for each slope change area is obtained; the flow direction reversal evaluation records corresponding to all slope change areas are summarized to form the flow direction reversal coupling analysis results. For each siltation area, the wave aggregation effect caused by siltation is evaluated, and the corresponding wave aggregation evaluation record is obtained; for each later trench in a trench pair, the trench morphology is evaluated on the wave refraction aggregation effect, and the corresponding wave refraction aggregation evaluation record is obtained; all wave aggregation evaluation records and all wave refraction aggregation evaluation records are summarized to form the wave aggregation coupling analysis results. The results of velocity amplification coupling analysis, flow direction reversal coupling analysis, and wave aggregation coupling analysis are integrated to form a set of coupling risk results.

[0009] Furthermore, the method for obtaining the velocity amplification assessment records of the scour zone is as follows: Of the two monitoring times corresponding to the seabed scour volume in the scour area, the later monitoring time is marked as the analysis time. From the single-phase velocity profile data corresponding to the analysis time, the velocity magnitude of the bottom layer velocity record is obtained and marked as the bottom velocity. Based on the vertical contraction effect of the upstream to the pit section caused by scour, the velocity amplification factor of the scour area is calculated. Based on the bottom velocity and the velocity amplification factor, the velocity amplification estimate of the scour area is calculated. The center coordinates of the scour area, the average scour thickness of the area, the velocity amplification factor, the bottom velocity, and the velocity amplification estimate are integrated to form the velocity amplification assessment record of the scour area. The method for obtaining the flow direction reversal assessment record is as follows: From the slope change, obtain the main slope direction, the center coordinates of the slope change area, and the average slope change range of the area; From the single-phase velocity profile data corresponding to the analysis time, obtain the velocity direction of the bottom layer velocity record and mark it as the bottom layer flow direction; Calculate the angle between the main slope direction and the bottom layer flow direction to obtain the direction angle; Based on the direction angle and the average slope change range of the area, assess the flow direction reversal intensity index; Integrate the center coordinates of the slope change area, the main slope direction, the direction angle, the average slope change range of the area, the flow direction reversal intensity index, and the bottom layer flow direction to form the flow direction reversal assessment record.

[0010] Furthermore, the method for obtaining the wave aggregation assessment record is as follows: from the seabed sedimentation volume, obtain the center coordinates of the sedimentation area and the average sedimentation thickness of the area; according to the wave shallow water deformation theory, assess the aggregation effect of the water depth reduction caused by sedimentation on wave propagation, and obtain the wave aggregation enhancement coefficient; calculate the wave height aggregation estimate based on the wave aggregation enhancement coefficient, and integrate it with the center coordinates of the sedimentation area, the average sedimentation thickness of the area, and the wave aggregation enhancement coefficient to form the wave aggregation assessment record; The method for obtaining wave refraction and concentration assessment records is as follows: obtain the center coordinates of the later-stage trench from the trench migration amount corresponding to the trench pair; obtain the main wave direction from the wave records at the corresponding monitoring time of the later-stage trench; evaluate the refraction and concentration effect of the trench on the waves by analyzing the relationship between the trench structure and the main wave direction, and determine whether the later-stage trench should be marked as a wave concentration trench; calculate the corresponding wave refraction and concentration coefficient for each wave concentration trench, and integrate it with the trench center coordinates to form a wave refraction and concentration assessment record.

[0011] Furthermore, methods for dynamically identifying precursory zones of scour instability include: For each scour region, the corresponding cumulative scour trend is evaluated sequentially: a time series sequence of scour thickness is constructed for the scour region, and the effective time series length is obtained statistically; if the effective time series length is less than the preset number of trend analysis backtracking periods, the cumulative scour trend is marked as insufficient data; if the effective time series length is greater than or equal to the number of trend analysis backtracking periods, the monotonicity of the scour thickness time series is determined, and the cumulative scour trend is marked as either continuously aggravated or fluctuating based on the determination result. For each scour area, the corresponding slope instability state is evaluated sequentially: from all slope change areas, the corresponding slope area is identified; if no slope area exists, the slope instability state is marked as unrelated; if a slope area exists, the average slope change of the slope area is obtained and compared with the preset slope instability slope threshold. Based on the comparison result, the slope instability state is marked as high risk or low risk. Based on the cumulative scour trend and the coordinated instability of the slope, a comprehensive judgment of the precursors of scour instability is performed, and the scour areas that meet the preset scour path one or scour path two are marked as the precursor areas of scour instability.

[0012] Furthermore, methods for dynamically identifying nearshore erosion precursor zones include: For each slope change area, determine whether it is located in the nearshore area, and mark the slope change area in the nearshore area as the nearshore slope change area; for each nearshore slope change area, determine whether the corresponding main slope direction points to the shoreline direction, and evaluate the corresponding wave coordination state in turn; for each nearshore slope change area, determine whether there is a scour area around it, and evaluate the corresponding nearshore scour coordination state based on the judgment result; based on the judgment result of the main slope direction, the wave coordination state and the nearshore scour coordination state, perform a comprehensive judgment of nearshore erosion precursors, and mark the nearshore slope change areas that meet the preset nearshore path one or nearshore path two as nearshore erosion precursor areas; The method for assessing wave coordination status is as follows: calculate the nearshore plane distance between the center coordinates of the slope change area corresponding to the nearshore slope change area and the center coordinates of the siltation area in all wave aggregation assessment records; compare each nearshore plane distance with the preset wave coordination search radius, and determine whether to mark the wave coordination status as unrelated based on the comparison results; if not, obtain the wave aggregation enhancement coefficient from the corresponding wave aggregation assessment record and compare it with the preset wave aggregation danger threshold, and mark the wave coordination status as high risk or low risk based on the comparison results.

[0013] Furthermore, methods for dynamically identifying precursory areas of waterway siltation include: For each siltation area, determine whether it is located in a waterway area, and mark the siltation area located in the waterway area as a waterway siltation area; for each waterway siltation area, calculate the corresponding water depth margin ratio and evaluate the corresponding cumulative siltation trend; sequentially determine whether there is a trend of ditch migration towards the waterway direction around each waterway siltation area to obtain the corresponding ditch-waterway coordination state; based on the water depth margin ratio, cumulative siltation trend and ditch-waterway coordination state, perform a comprehensive judgment of waterway siltation precursors, and mark the waterway siltation areas that meet the preset waterway path one or waterway path two as waterway siltation precursor areas; The method for obtaining the channel-ditch cooperative status is as follows: from the channel migration amount of all channel pairs, obtain the channel center coordinates and migration direction of the later channel; based on the channel center coordinates, migration direction and preset channel centerline coordinate sequence, calculate the channel deviation distance and channel migration deviation angle, and compare them with the preset channel approach threshold and channel influence distance, respectively. According to the comparison results, the channel-ditch cooperative status is marked as approaching or not approaching.

[0014] A multi-dimensional real-time hydrological mapping and disaster early warning system for smart oceans, implementing the aforementioned multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans, including: The multi-dimensional hydrological mapping module is used to collect multi-temporal acoustic bathymetry data of the target sea area within a continuous monitoring period. Based on the multi-temporal acoustic bathymetry data, it generates the seabed topography grid corresponding to each monitoring time and simultaneously collects tide level sequence, current velocity profile sequence and wave sequence to form a multi-dimensional hydrological mapping dataset. The topographic change extraction module is used to extract seabed sedimentation, seabed erosion, slope change and channel migration from the seabed topographic grid of adjacent monitoring times in the multidimensional hydrological mapping dataset, forming a seabed topographic change feature set; The dynamic coupling analysis module is used to analyze the coupling enhancement effect of seabed topographic changes on local velocity amplification, flow direction reversal and wave aggregation based on the seabed topographic change feature set and the tide level sequence, current velocity profile sequence and wave sequence in the multidimensional hydrological mapping dataset, and to form a coupling risk result set. The precursor dynamic identification module is used to dynamically identify the precursor areas of scour instability, nearshore erosion, and channel siltation based on the coupled risk result set, forming a disaster precursor feature set; The disaster early warning output module is used to generate spatial distribution maps, evolution trend prediction curves and risk levels of each precursor area based on the disaster precursor feature set, and output multi-dimensional hydrological disaster early warning results.

[0015] The technical effects and advantages of this invention, a multi-dimensional real-time hydrological mapping and disaster early warning system and method for smart oceans, are as follows: By simultaneously collecting multi-temporal acoustic bathymetry data, tidal level sequences, current velocity profile sequences, and wave sequences of the target sea area within a continuous monitoring period, a unified spatiotemporal representation framework for multi-source hydrological observation data was established, effectively overcoming the shortcomings of the separation between seabed topographic measurement and hydrodynamic observation. Through node-by-node differential analysis, connected component aggregation, and channel matching tracing of seabed topographic grids at adjacent monitoring times, seabed sedimentation, seabed erosion, slope change, and channel migration were extracted sequentially, achieving multi-scale seabed topographic change information extraction from grid-level micro-changes to regional-level macro-features. By coupling seabed topographic change features with multi-dimensional hydrodynamic information such as tidal level, current velocity profiles, and waves, the effects of erosion and sedimentation were quantitatively assessed. The study revealed the collaborative response mechanism between topographic change and hydrodynamic field by investigating the contribution of topographic features to the velocity amplification effect, the driving effect of slope changes on the flow direction reversal effect, and the enhancement of wave aggregation effect by siltation topography and gully structure. By comprehensively coupling risk analysis results with cumulative trend judgment and multi-factor collaborative risk assessment, the study dynamically identified scour instability precursor zones, nearshore erosion precursor zones, and channel siltation precursor zones, achieving a technological upgrade from passive anomaly detection to active precursor identification. Finally, the study generated multi-dimensional hydrological disaster early warning results including spatial distribution maps, evolution trend prediction curves, and risk levels, providing systematic real-time mapping and disaster early warning technology support for channel navigation safety management, nearshore shoreline protection, and marine engineering safety operation and maintenance in the context of smart ocean scenarios. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the multi-dimensional real-time hydrological mapping and disaster early warning system for smart oceans according to Embodiment 1 of the present invention; Figure 2 This is a flowchart of the multi-dimensional hydrological real-time mapping and disaster early warning method for smart oceans according to Embodiment 2 of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example 1:

[0018] Please see Figure 1 As shown in this embodiment, the multi-dimensional hydrological real-time mapping and disaster early warning system for smart oceans includes a multi-dimensional hydrological mapping module, a terrain change extraction module, a dynamic coupling analysis module, a precursor dynamic identification module, and a disaster early warning output module. The modules are connected by wired and / or wireless means to realize data transmission between the modules.

[0019] The multi-dimensional hydrographic mapping module is used to collect multi-temporal acoustic bathymetry data of the target sea area within a continuous monitoring period. Based on the multi-temporal acoustic bathymetry data, it generates the seabed topographic grid corresponding to each monitoring time and simultaneously collects tide level sequences, current velocity profile sequences and wave sequences to form a multi-dimensional hydrographic mapping dataset.

[0020] Methods for collecting multi-temporal acoustic bathymetry data of the target sea area include: Multi-temporal acoustic bathymetry data of the target sea area are acquired from an acoustic bathymetry system (i.e., an underwater acoustic detection platform used to transmit acoustic pulses to the seabed and receive reflected echoes to measure water depth). The target sea area refers to a pre-defined marine monitoring area with clear geographical boundaries, as required by the monitoring mission. The continuous monitoring period refers to the complete observation time interval from the start of the monitoring mission to the current moment, containing multiple monitoring moments arranged sequentially according to preset sampling intervals. The sampling intervals are pre-set by those skilled in the art based on the activity level of topographic changes in the target sea area and the required monitoring accuracy. Multi-temporal acoustic bathymetry data is used to record seabed depth measurement information of the target sea area at various monitoring times, specifically including multiple sets of single-temporal bathymetry data; each set of single-temporal bathymetry data includes a monitoring time and multiple bathymetry records, and each bathymetry record includes the plane coordinates of the bathymetry point and the water depth value of the bathymetry point; the plane coordinates of the bathymetry point include the east and north coordinates of the bathymetry point under a preset plane coordinate system; the plane coordinate system is preset by a person skilled in the art based on the projection coordinate system selected by the geographical region where the target sea area is located; the water depth value of the bathymetry point is the vertical distance from the local mean sea level datum to the seabed obtained by the acoustic bathymetry system.

[0021] Methods for generating seabed topographic grids corresponding to each monitoring time include: The grid resolution and coverage area are preset. The grid resolution is the planar spacing between adjacent grid nodes in the seabed topography grid, and the grid coverage area is the rectangular area covered by the seabed topography grid in the planar direction. Both the grid resolution and the grid coverage area are preset by those skilled in the art according to the spatial scale and monitoring accuracy requirements of the target sea area. Based on the grid resolution and grid coverage area, a regular rectangular grid is established in the preset planar coordinate system, resulting in multiple grid nodes. Each grid node has unique grid node coordinates, which include the east and north coordinates of the grid node in the preset planar coordinate system. For each set of single-time-phase bathymetry data, the water depth values ​​of the bathymetry points in the corresponding multiple bathymetry records are interpolated to each grid node to obtain the grid water depth value of each grid node at the corresponding monitoring time. The interpolation method used is Kriging interpolation, which is a well-known spatial interpolation technique in the field. The specific implementation process will not be elaborated here. The grid node coordinates of each grid node are associated with the corresponding grid water depth value to form the seabed topography grid at the corresponding monitoring time. The seabed topography grid is used to describe the spatial distribution of the seabed topography of the target sea area at the corresponding monitoring time in the form of a regular grid.

[0022] Methods for simultaneously acquiring tidal level sequences, current velocity profile sequences, and wave sequences include: The tide level sequence of the target sea area within a continuous monitoring period is obtained from the tide level observation system (i.e., a water level monitoring platform used to observe and record changes in sea surface tide level in real time). The tide level sequence is used to record the sea surface tide level information of the target sea area at each monitoring time, specifically including multiple tide level records. Each tide level record includes a monitoring time and a tide level value, where the tide level value is the instantaneous height of the sea surface relative to the local mean sea level reference level. The current profile sequence of the target sea area is obtained from the acoustic Doppler current profiler system (i.e., a current observation platform used to measure current velocity information at different depths of water using the Doppler effect) over a continuous monitoring period. The current profile sequence records the vertical current velocity distribution information of the target sea area at each monitoring time, specifically including multiple sets of single-temporal current profile data. Each set of single-temporal current profile data includes one monitoring time and multiple stratified current velocity records. Each stratified current velocity record includes a depth layer identifier, current velocity magnitude, and current velocity direction. The depth layer identifier identifies the water depth at which the corresponding stratified current velocity record is located; the current velocity magnitude is the flow rate of the water at the corresponding depth layer; and the current velocity direction is the azimuth angle of the water flow at the corresponding depth layer. Wave sequences of the target sea area are obtained from the wave observation system (i.e., the wave monitoring platform used for real-time observation and recording of sea surface wave elements) within a continuous monitoring period. The wave sequence records the wave state information of the target sea area at each monitoring time, specifically including multiple wave records. Each wave record includes a monitoring time and a set of wave characteristic parameters, specifically including significant wave height, mean wave period, and dominant wave direction. The significant wave height is the average of the highest third of the wave heights in the statistical distribution of wave heights within the observation period. The mean wave period is the average of all wave periods within the observation period. The dominant wave direction is the direction of propagation where wave energy is most concentrated within the observation period.

[0023] Methods for generating multidimensional hydrological mapping datasets include: The seabed topographic grid, tide records, single-phase current velocity profile data and wave records corresponding to the same monitoring time are correlated and matched to form multidimensional hydrological mapping data for each monitoring time. The multidimensional hydrological mapping data of all monitoring times are summarized to form a multidimensional hydrological mapping dataset. The multidimensional hydrological mapping dataset is used to uniformly store the seabed topographic spatial information and multidimensional hydrodynamic observation information of the target sea area in a time series form during a continuous monitoring period.

[0024] The topographic change extraction module is used to extract seabed sedimentation, seabed erosion, slope change and channel migration from the seabed topographic grid of adjacent monitoring times in the multidimensional hydrological mapping dataset, forming a seabed topographic change feature set.

[0025] Methods for extracting seabed sedimentation and seabed erosion include: From the multidimensional hydrological mapping dataset, seafloor topographic grids corresponding to two adjacent monitoring times are obtained and labeled as the earlier topographic grid and the later topographic grid, respectively. The earlier topographic grid corresponds to the seafloor topographic grid at an earlier monitoring time, and the later topographic grid corresponds to the seafloor topographic grid at a later monitoring time. For each grid node, the difference between the corresponding grid depth value in the later topographic grid and the corresponding grid depth value in the earlier topographic grid is calculated to obtain the water depth change of each grid node. A positive water depth change indicates that the water depth of the corresponding grid node has increased (i.e., the seafloor has dropped, and erosion has occurred), a negative water depth change indicates that the water depth of the corresponding grid node has decreased (i.e., the seafloor has risen, and siltation has occurred), and a water depth change of zero indicates that there has been no vertical change in the seafloor of the corresponding grid node. For each grid node, a sedimentation and scour classification labeling process is performed, sequentially labeling each grid node as a stable node, a sedimentation node, or a scour node. Specifically, a sedimentation and scour identification threshold is preset, which is pre-set by those skilled in the art based on the measurement accuracy of the sounding system and the minimum meaningful topographic change in the target sea area. If the absolute value of the water depth change is less than the sedimentation and scour identification threshold, the corresponding grid node is labeled as a stable node, indicating that no significant vertical topographic change has occurred at the corresponding location between adjacent monitoring times. If the water depth change is less than zero and the absolute value of the water depth change is greater than or equal to the sedimentation and scour identification threshold, the corresponding grid node is labeled as a sedimentation node, and the absolute value of the water depth change is used as the node sedimentation amount of the corresponding sedimentation node. If the water depth change is greater than zero and the water depth change is greater than or equal to the sedimentation and scour identification threshold, the corresponding grid node is labeled as a scour node, and the water depth change is used as the node scour amount of the corresponding scour node. Based on the spatial distribution of all sedimentation and scour nodes, a connected component aggregation operation is performed to aggregate spatially adjacent nodes of the same type into independent sedimentation or scour regions. Specifically, a spatial adjacency determination rule is preset, which states that any two grid nodes in the seabed topography grid are considered spatially adjacent if they are within a preset adjacency search radius in the east or north direction. The adjacency search radius is preset by those skilled in the art based on the grid resolution and the typical spatial scale of topographic changes in the target sea area. All spatially adjacent sedimentation nodes are aggregated into one sedimentation region, resulting in multiple sedimentation regions. All spatially adjacent scour nodes are aggregated into one scour region, resulting in multiple scour regions. The connected component aggregation operation uses a connected component extraction algorithm based on breadth-first search, which is a well-known technology in the field, and the specific implementation process will not be elaborated here. For each siltation area, the corresponding seabed siltation volume is calculated. Specifically, the average siltation volume of all siltation nodes within the siltation area is calculated to obtain the average siltation thickness of the area. The number of siltation nodes within the siltation area is counted and marked as the number of siltation nodes. The area of ​​the siltation area is obtained by multiplying the number of siltation nodes by the square of the grid resolution. The average east and north coordinates of the grid node coordinates corresponding to all siltation nodes within the siltation area are calculated to obtain the center coordinates of the siltation area. The average siltation thickness, the area of ​​the siltation area, and the center coordinates of the siltation area are integrated to form the seabed siltation volume of the corresponding siltation area. The seabed siltation volume is used to describe the degree and spatial extent of sediment deposition in the corresponding siltation area between adjacent monitoring times and to identify the spatial location of the siltation area. For each scour area, the corresponding seabed scour volume is calculated. The calculation method for seabed scour volume is the same as that for seabed sedimentation volume, except that sedimentation nodes are replaced with scour nodes and node sedimentation volume is replaced with node scour volume. Seabed scour volume includes the average scour thickness of the area, the area of ​​the scour area, and the center coordinates of the scour area. It is used to describe the degree and spatial range of seabed scour in the corresponding scour area between adjacent monitoring times, and to identify the spatial location of the scour area.

[0026] Methods for extracting slope variation include: For both the early and later topographic grids, the local slope corresponding to each grid node is calculated. Specifically, for each grid node, the grid water depth values ​​of two adjacent grid nodes in the eastward direction and two adjacent grid nodes in the northward direction are obtained. The difference between the grid water depth values ​​of two adjacent grid nodes in the eastward direction is calculated and then divided by twice the grid resolution to obtain the eastward water depth gradient. The difference between the grid water depth values ​​of two adjacent grid nodes in the northward direction is calculated and then divided by twice the grid resolution to obtain the northward water depth gradient. The sum of the squares of the eastward water depth gradient and the squares of the northward water depth gradient is calculated and then the square root is taken to obtain the local slope of the corresponding grid node. The local slope is used to reflect the inclination of the seabed at the corresponding grid node. For grid nodes located at the grid boundary that lack adjacent grid nodes, the gradient is calculated using the one-sided difference method, which is a conventional technique in this field and will not be elaborated on here. The local slope corresponding to each grid node in the early topographic grid is marked as the early slope, and the local slope corresponding to each grid node in the later topographic grid is marked as the later slope. For each grid node, the difference between the later slope and the early slope is calculated to obtain the slope change value. A positive slope change value indicates that the inclination of the sea surface at the corresponding grid node has increased, and a negative slope change value indicates that the inclination of the sea surface at the corresponding grid node has decreased. A slope change significance threshold is preset, which is pre-set by those skilled in the art based on the seabed slope stability requirements of the target sea area and the slope resolution capability of the bathymetry system. The absolute value of the slope change value of each grid node is compared with the slope change significance threshold. If the absolute value of the slope change value is greater than or equal to the slope change significance threshold, the corresponding grid node is marked as a slope change node; if the absolute value of the slope change value is less than the slope change significance threshold, the corresponding grid node is not marked. Perform connected component aggregation on all slope variation nodes to aggregate spatially adjacent slope variation nodes into multiple slope variation regions. For each slope variation region, calculate the average of the absolute values ​​of the slope variation values ​​of all slope variation nodes within it to obtain the average slope variation range of the region. Count the number of slope variation nodes in the region and multiply it by the square of the grid resolution to obtain the area of ​​the slope variation region. Calculate the average eastward and northward coordinates of the grid node coordinates corresponding to all slope variation nodes within the slope variation region to obtain the center coordinates of the slope variation region. For each slope change region, the directional characteristics of the slope change are further calculated to obtain the corresponding principal slope aspect. Specifically, the eastward and northward water depth gradients of all slope change nodes in the later topographic grid are obtained; the mean eastward water depth gradient of all slope change nodes is calculated to obtain the mean eastward gradient of the region; the mean northward water depth gradient of all slope change nodes is calculated to obtain the mean northward gradient of the region; based on the mean eastward and northward gradients of the region, the principal slope aspect of the slope change region is calculated using the arctangent function; the principal slope aspect is used to reflect the main direction of seabed tilt in the slope change region; it should be noted that the calculation method of the arctangent function is a well-known mathematical operation in this field and will not be elaborated further here. The average slope change, area of ​​the slope change region, center coordinates of the slope change region and main slope direction of the same slope change region are integrated to form the slope change amount of the corresponding slope change region. The slope change amount is used to describe the degree, spatial range and direction of change of the seabed slope morphology of the corresponding slope change region between adjacent monitoring times.

[0027] Methods for extracting trench migration include: For both early and late-stage topographic grids, trench structures are identified. Specifically, for each grid node in each seabed topographic grid, the water depth values ​​of all grid nodes within a radius of a preset trench search window are obtained, with the corresponding grid node as the center node. The trench search window is preset by those skilled in the art based on the typical width of trenches in the target sea area. The water depth value of the center grid node is compared one by one with the water depth values ​​of all grid nodes within the corresponding search window. The number of grid nodes within the search window whose water depth values ​​are less than the corresponding water depth value of the center grid node is counted and marked as shallower than the center node. The ratio of the number of shallower than the center node to the total number of grid nodes within the search window is calculated to obtain the local concavity degree. The local concavity degree reflects the degree of concavity of the center grid node relative to its local neighborhood. A higher local concavity degree indicates that the center grid node is more likely to be located at the bottom of the trench. A preset trench indentation threshold is established, which is pre-set by those skilled in the art based on the typical depth characteristics of trenches in the target sea area. The local indentation of each grid node is compared with the trench indentation threshold. If the local indentation is greater than or equal to the trench indentation threshold, the corresponding grid node is marked as a trench candidate node. If the local indentation is less than the trench indentation threshold, the corresponding grid node is not marked. A connected component aggregation operation is performed on all trench candidate nodes to aggregate spatially adjacent trench candidate nodes into multiple trench structures. For each trench structure, the mean eastward and mean northward coordinates of the grid node coordinates corresponding to all trench candidate nodes are calculated to obtain the trench center coordinates. The grid water depth value corresponding to the trench candidate node with the largest grid water depth value in the trench structure is obtained and used as the water depth of the deepest point of the trench. The number of trench candidate nodes in the trench structure is counted to obtain the number of candidates. The product of the number of candidates and the square of the grid resolution is calculated to obtain the trench area.

[0028] The trench structures identified in the early-stage topographic grid are marked as early-stage trenches, and the trench structures identified in the later-stage topographic grid are marked as later-stage trenches. A matching and association operation is performed between the early-stage and later-stage trenches to determine whether a matching association relationship has been established. Specifically, for each early-stage trench, the Euclidean distance between the corresponding trench center coordinates and the trench center coordinates of each later-stage trench is calculated and marked as the trench planar distance. Each trench planar distance is compared with a preset trench matching distance threshold, which is preset by those skilled in the art based on the maximum possible migration distance of trenches in the target sea area between adjacent monitoring times. If the trench planar distance... If the trench distance is less than or equal to the trench matching distance threshold, the corresponding early trench and later trench are determined to be the same trench at different times, and a matching relationship is established between the corresponding early trench and later trench. If the trench plane distance is greater than the trench matching distance threshold, no matching relationship is established between the corresponding early trench and later trench. If no matching relationship is established between the early trench and all later trenches, the corresponding early trench is determined to have disappeared at the later monitoring time, and the corresponding early trench is marked as a disappeared trench. If no matching relationship is established between the later trench and all early trenches, the corresponding later trench is determined to be a newly generated trench, and the corresponding later trench is marked as a newly generated trench. Each pair of pre- and post-trench trenches with established matching relationships is marked as a trench pair, and the corresponding trench migration amount is calculated for each trench pair. Specifically, the eastward migration component is obtained by calculating the difference between the center coordinates of the post-trench trench and the center coordinates of the pre-trench trench in the eastward direction; the northward migration component is obtained by calculating the difference between the center coordinates of the post-trench trench and the center coordinates of the pre-trench trench in the northward direction; the migration distance is obtained by summing the squares of the eastward and northward migration components and then taking the square root; the migration direction is calculated using the arctangent function based on the eastward and northward migration components; and the maximum trench depth of the post-trench trench is calculated. The difference between the water depth at the initial point and the deepest point of the previous trench is used to obtain the trench depth change; a positive change in trench depth indicates that the trench has deepened, while a negative change in trench depth indicates that the trench has become shallower. The difference between the trench area of ​​the later trench and the trench area of ​​the earlier trench is used to obtain the trench area change. The migration distance, migration direction, trench depth change, trench area change, and the center coordinates of the earlier and later trenches for the same trench pair are integrated to form the trench migration amount for the corresponding trench pair. The trench migration amount is used to describe the spatial displacement, depth evolution, and scale change characteristics of the same trench between adjacent monitoring times.

[0029] Methods for forming a set of features of seafloor topographic changes include: The seabed sedimentation volume of all sedimentation areas, the seabed erosion volume of all erosion areas, the slope change volume of all slope change areas, and the channel migration volume of all channel pairs corresponding to two adjacent monitoring times are summarized and integrated to form a record of topographic change characteristics between corresponding adjacent monitoring times. The records of topographic change characteristics between all adjacent monitoring times within a continuous monitoring period are summarized to form a set of seabed topographic change characteristics. The set of seabed topographic change characteristics is used to record the entire process of seabed topography sedimentation, erosion, slope evolution, and channel migration in the target sea area in a time series form within a continuous monitoring period.

[0030] It should be understood that by calculating the water depth difference node by node and classifying sedimentation and scour at adjacent monitoring times, a refined identification of vertical changes in seabed topography was achieved. Through a breadth-first search-based connected component aggregation operation, scattered sedimentation and scour nodes were automatically aggregated into spatially continuous sedimentation and scour regions. This enabled the automatic extraction of micro-level changes at the discrete grid node level and macro-level topographic evolution features at the regional level, overcoming the limitation of relying solely on single-point water depth thresholds to identify areas of spatially continuous topographic change. Furthermore, by performing local slope calculations and slope change significance screening on grid nodes, combined with the extraction of directional features of the main slope direction, a comprehensive understanding of seabed slope morphology was achieved. Quantitative characterization of the transformation process can reveal the spatial distribution patterns and directional characteristics of the steepening or gentlening of seafloor slopes, providing a directional information basis for subsequent slope instability risk analysis and nearshore erosion direction determination. Through the identification of candidate trench nodes based on local depression degree, the extraction of trench structure by connected domain aggregation, and the cross-temporal trench matching and association mechanism based on the Euclidean distance of trench center coordinates, a complete analysis chain for seafloor trenches from identification, tracking to migration quantification has been realized. It can automatically distinguish between persistent trenches, disappearing trenches, and newly formed trenches, and quantitatively describe the spatial displacement, depth evolution, and scale change characteristics of the same trench between adjacent monitoring times, thereby overcoming the lack of ability to dynamically track trench topography across time phases.

[0031] The dynamic coupling analysis module is used to analyze the coupling enhancement effect of seafloor topography changes on local velocity amplification, flow direction reversal and wave aggregation based on the seafloor topography change feature set and the tide level sequence, current velocity profile sequence and wave sequence in the multidimensional hydrological mapping dataset, and to form a coupling risk result set.

[0032] Methods for analyzing the coupled and enhanced effects of seafloor topographic changes on local velocity amplification include: For each scour zone, the local velocity amplification effect caused by scour is evaluated, resulting in a velocity amplification evaluation record for that zone. Similarly, for each sedimentation zone, the local velocity amplification effect caused by sedimentation is evaluated, resulting in a velocity amplification evaluation record for that zone. The reasons for this local velocity amplification effect are as follows: when seabed scour occurs, the local water depth increases, but the boundary of the scour zone forms a steep slope structure, causing the water velocity to increase at the upstream cross-section before entering the scour pit due to the narrowing topography; conversely, when seabed sedimentation causes a decrease in local water depth, the water velocity increases as the cross-section narrows when passing through the sedimentation zone. The velocity amplification evaluation records for all scour zones and all sedimentation zones are then combined to form the velocity amplification coupling analysis results. Specifically, the later of the two monitoring times corresponding to the seabed scour volume in the scour area is marked as the analysis time. From the single-phase velocity profile data corresponding to the analysis time, the velocity magnitude of the bottom stratified velocity record is obtained and marked as the bottom velocity. The bottom stratified velocity record is the velocity record of the stratum closest to the seabed corresponding to the depth layer identifier. Based on the vertical contraction effect of the upstream to the pit section caused by scour, the velocity amplification factor of the scour area is calculated. The product of the bottom velocity and the velocity amplification factor is calculated to obtain the velocity amplification estimate of the scour area. The center coordinates of the scour area, the average scour thickness, the velocity amplification factor, the bottom velocity, the velocity amplification estimate, and the corresponding monitoring time are integrated to form the velocity amplification assessment record of the scour area. It should be noted that the method for obtaining the velocity amplification assessment record for the sedimentation area is the same as that for the scour area.

[0033] The methods for calculating the velocity amplification factor in the scouring zone include: From the seabed erosion volume corresponding to the erosion area, obtain the corresponding average erosion thickness and the center coordinates of the erosion area; from the tide level record corresponding to the analysis time, obtain the tide level value; from the seabed topography grid corresponding to the analysis time, obtain the grid water depth value corresponding to the center coordinates of the erosion area, and mark it as the local water depth; calculate the sum of the local water depth and the tide level value to obtain the local actual water depth; whereby the local actual water depth is used to reflect the actual water thickness of the erosion area at the analysis time; From the previous topographic grid, obtain the grid water depth value corresponding to the center coordinates of the scour area and mark it as the previous local water depth; calculate the sum of the previous local water depth and the tide level value to obtain the previous actual water depth; calculate the ratio of the local actual water depth to the previous actual water depth to obtain the water depth contraction ratio; the water depth contraction ratio is used to reflect the multiple by which the local water depth increases due to scour. The larger the water depth contraction ratio, the deeper the scour and the stronger the velocity amplification effect when the surrounding water flows into the scour pit. The grid water depth values ​​of all grid nodes within a circular area centered on the center coordinates of the scour region and with a preset velocity influence radius are obtained from the later-stage topographic grid. The velocity influence radius is preset by those skilled in the art based on the typical spatial scale of the scour region and the propagation range of water flow disturbance. The average grid water depth values ​​of all grid nodes within the circular area are calculated to obtain the surrounding average water depth. The sum of the surrounding average water depth and the tidal level is calculated to obtain the surrounding actual water depth. The ratio of the local actual water depth to the surrounding actual water depth is calculated to obtain the cross-sectional contraction ratio. The cross-sectional contraction ratio reflects the degree of increase in water depth in the scour region relative to the surrounding normal water depth; a larger cross-sectional contraction ratio indicates a more significant local topographic depression formed in the scour region. Amplification weights are set for the water depth contraction ratio and the cross-sectional contraction ratio respectively. Each amplification weight is pre-set by a person skilled in the art based on the hydrodynamic characteristics of the target sea area and the response law of the scour topography to the flow velocity. Based on the amplification weights, the water depth contraction ratio and the cross-sectional contraction ratio are weighted and summed to obtain the flow velocity amplification coefficient. The flow velocity amplification coefficient is used to quantitatively describe the degree of local flow velocity increase caused by topographic changes in the scour area. The larger the flow velocity amplification coefficient, the stronger the local flow velocity amplification effect.

[0034] Methods for analyzing the coupled and enhanced effects of seafloor topography changes on current direction reversal include: For each slope change area, the flow direction reversal effect caused by the slope change is evaluated, and the flow direction reversal evaluation record of each slope change area is obtained; the flow direction reversal evaluation records of all slope change areas are summarized to form the flow direction reversal coupling analysis results. Specifically, from the slope change data, the coordinates of the main slope direction and the center of the slope change area are obtained; from the single-phase velocity profile data corresponding to the analysis time, the velocity direction of the bottom layer velocity record is obtained and marked as the bottom flow direction; the angle between the main slope direction and the bottom flow direction is calculated to obtain the direction angle; specifically, the absolute value of the difference between the main slope direction and the bottom flow direction is calculated to obtain the original angle; if the original angle is greater than 180 degrees, the result of subtracting the original angle from 360 degrees is taken as the direction angle; if the original angle is less than or equal to 180 degrees, the original angle is taken as the direction angle; the direction angle is used to reflect the degree of deviation between the tilt direction of the seabed slope and the direction of the bottom water flow. The intensity index of flow direction reversal is assessed based on the regional average slope change magnitude in the directional angle and slope variation. Specifically, a normalized reference value for the directional angle is preset, which is pre-set by those skilled in the art based on the minimum topographic deflection angle required for a significant flow direction reversal. The ratio of the directional angle to the normalized reference value is calculated to obtain the directional deflection degree. If the directional deflection degree is greater than one, it is set to one. The directional deflection degree reflects the relative intensity of the slope direction's deflection of the bottom water flow. A normalized reference value for slope variation is preset, which is pre-set by those skilled in the art based on the minimum slope change magnitude required to induce a significant flow direction reversal. The regional average slope is calculated. The slope driving degree is obtained by dividing the slope change amplitude by the normalized baseline value of the slope change. If the slope driving degree is greater than one, it is set to one. The slope driving degree reflects the driving intensity of slope change on water flow deflection. Corresponding turning weights are set for the directional deflection degree and the slope driving degree. Each turning weight is pre-set by those skilled in the art based on the topography and water flow deflection response characteristics of the target sea area. The directional deflection degree and the slope driving degree are weighted and summed based on the turning weights to obtain the flow direction turning intensity index. The flow direction turning intensity index is used to quantitatively describe the degree of risk of local flow direction deflection caused by changes in seabed slope morphology in the slope change area. The larger the flow direction turning intensity index, the more significant the flow direction turning effect. The center coordinates of the slope change area, main slope aspect, directional angle, average slope change range, flow direction inflection intensity index, bottom flow direction, and corresponding monitoring time are integrated to form a flow direction inflection assessment record for the slope change area.

[0035] Methods for analyzing the coupled and enhanced effects of seafloor topography changes on wave convergence include: For each siltation area, the wave aggregation effect caused by siltation is assessed, and corresponding wave aggregation assessment records are obtained. Specifically, the center coordinates and average siltation thickness of the siltation area are obtained from the seabed siltation volume corresponding to the siltation area; the significant wave height, average wave period, and dominant wave direction are obtained from the wave records corresponding to the analysis time; the tide level value is obtained from the tide level records corresponding to the analysis time; the grid water depth value corresponding to the center coordinates of the siltation area is obtained from the seabed topography grid corresponding to the analysis time and marked as the siltation water depth; the sum of the siltation water depth and the tide level value is calculated to obtain the actual siltation water depth. Based on the theory of shallow water wave deformation, the impact of reduced water depth due to siltation on wave propagation and the wave concentration enhancement coefficient of the siltation area are evaluated. Specifically, based on the mean wave period, the corresponding deep-water wavelength is calculated using the dispersion relation in linear wave theory. The calculation method for the dispersion relation is a well-known basic calculation in marine physics, and the specific process will not be elaborated here. The ratio of the actual siltation depth to the deep-water wavelength is calculated to obtain the water depth-wavelength ratio. A preset wave concentration water depth ratio threshold is set, and the water depth-wavelength ratio is compared with the wave concentration water depth ratio threshold. The wave concentration water depth ratio threshold is preset by those skilled in the art based on the theoretical criteria of the shallow water wave effect. If the water depth-wavelength ratio is less than the wave concentration water depth ratio threshold, the siltation area is determined to be in the shallow water wave deformation zone, and the waves will increase in wave height and energy concentration when propagating in this area due to the reduced water depth. From the preliminary topographic grid, the grid water depth value corresponding to the center coordinates of the siltation area is obtained and marked as the preliminary siltation water depth. The sum of the preliminary siltation water depth and the tidal level value is calculated, and the ratio of the calculated sum to the actual siltation water depth is calculated to obtain the water depth reduction ratio. A wave aggregation sensitivity coefficient is preset, which is pre-set by those skilled in the art based on the wave response characteristics of the target sea area to water depth changes. If the siltation area is located in a shallow water wave deformation zone, the product of the water depth reduction ratio and the wave aggregation sensitivity coefficient is calculated to obtain the wave aggregation enhancement coefficient. If the siltation area is not located in a shallow water wave deformation zone, it is determined that there is no significant wave aggregation effect in the corresponding siltation area, and no corresponding wave aggregation assessment record is generated. Among them, the wave aggregation enhancement coefficient is used to quantitatively describe the degree of wave energy aggregation caused by the reduction of water depth in the siltation area. The larger the wave aggregation enhancement coefficient, the higher the wave aggregation risk. The product of the significant wave height and the wave concentration enhancement coefficient is calculated to obtain the estimated wave height concentration value of the siltation area. The center coordinates of the siltation area, the average siltation thickness of the area, the wave concentration enhancement coefficient, the significant wave height, the estimated wave height concentration value, the water depth-wavelength ratio, and the corresponding monitoring time are integrated to form a wave concentration assessment record of the siltation area.

[0036] For the later-stage trench in each trench pair, the refraction and aggregation effect of the trench morphology on waves is evaluated, and the corresponding wave refraction and aggregation evaluation records are obtained. Specifically, the trench center coordinates and the water depth of the deepest point of the later-stage trench are obtained from the trench migration amount corresponding to the trench pair; the main wave direction is obtained from the wave records at the corresponding monitoring time of the later-stage trench; by analyzing the relationship between the orientation of the trench structure and the main wave direction, the refraction and aggregation effect of the trench on waves is evaluated; specifically, the grid node coordinates of all candidate nodes in the later-stage trench are obtained, and the least squares method is used to perform linear fitting on the grid node coordinates of all candidate nodes to obtain the direction of the trench axis. The least squares method is a well-known technique in this field, and its specific implementation process will not be elaborated here. The same angle calculation method as in the flow direction reversal analysis is used to calculate the angle between the trench axis direction and the main wave direction to obtain the trench wave direction angle. The trench refraction critical angle is preset, and the trench wave direction angle is compared with the trench refraction critical angle. The trench refraction critical angle is preset by those skilled in the art based on the wave refraction theory's criterion for the deflection effect of trench topography on waves. If the trench wave direction angle is greater than or equal to the trench refraction critical angle, the trench is determined to have a significant refraction and aggregation effect on waves, and the corresponding trench is marked as a wave aggregation trench. For each wave accumulation channel, the corresponding wave refraction accumulation coefficient is calculated. Specifically, the difference between the deepest point of the channel and the surrounding water depth is calculated to obtain the channel depth difference. The ratio of the channel depth difference to the surrounding water depth is calculated to obtain the relative channel depth. The calculation method for the surrounding water depth is the same as that for the average surrounding water depth in the velocity amplification analysis. A preset refraction accumulation reference coefficient is established, which is pre-set by those skilled in the art based on the channel refraction accumulation theory. The product of the relative channel depth and the refraction accumulation reference coefficient is calculated and then one is added to obtain the wave refraction accumulation coefficient. The center coordinates of the channel, the wave direction angle, the wave refraction accumulation coefficient, and the corresponding monitoring time are integrated to form a corresponding wave refraction accumulation assessment record. The wave accumulation assessment records of all siltation areas and the wave refraction accumulation assessment records of all wave accumulation channels are summarized to form the wave accumulation coupling analysis results.

[0037] Methods for forming a set of coupling risk results include: The results of velocity amplification coupling analysis, flow direction reversal coupling analysis, and wave aggregation coupling analysis are integrated to form a coupling risk result set. The coupling risk result set is used to fully record the coupling enhancement relationship between seabed topography changes and hydrodynamic field in the target sea area during continuous monitoring periods.

[0038] It should be understood that by conducting spatiotemporal correlation analysis between the seabed topographic change feature set and the velocity profile, tidal level, and wave sequences in the multidimensional hydrological mapping dataset, a quantitative coupling assessment framework for the relationship between seabed topographic change and hydrodynamic field response was established. This overcomes the shortcomings of the disconnect between seabed topographic monitoring and hydrodynamic monitoring, which fails to reveal the enhanced mechanism of topographic-hydrodynamic coupling. In the velocity amplification coupling analysis, a two-factor weighted velocity amplification coefficient calculation method based on the water depth contraction ratio and cross-sectional contraction ratio was constructed. This method simultaneously considers the synergistic amplification effect of vertical cross-sectional changes caused by scouring or siltation and the surrounding horizontal water depth differences on velocity, thus achieving a quantitative assessment of the degree of local velocity amplification. In the flow direction turning coupling... In the analysis, a two-factor normalized assessment method combining directional deflection and slope driving force was constructed to integrate the directional characteristics of slope changes with the amplitude characteristics of slope changes. This quantitatively assessed the driving effect of seafloor slope morphology changes on near-bottom water flow directional deflection, thus overcoming the shortcomings of focusing only on changes in flow velocity while ignoring the risk of flow direction deflection. In the wave aggregation coupling analysis, the shallow water deformation zone was determined by combining the dispersion relation in linear wave theory, the wave aggregation enhancement effect caused by siltation was assessed by calculating the water depth to shallowing ratio, and the channel refraction aggregation effect was assessed by the angle relationship between the channel axis direction and the main wave direction. This achieved a comprehensive assessment of wave aggregation risk from two mechanisms: shallow water deformation of silted topography and channel refraction aggregation.

[0039] The precursor dynamic identification module is used to dynamically identify precursor zones of scour instability, nearshore erosion, and channel siltation based on the coupled risk result set, forming a disaster precursor feature set.

[0040] Methods for dynamically identifying precursory zones of scour instability include: For each scour area, a comprehensive assessment of the precursors to scour instability is performed, and the scour area is marked as a precursor zone for scour instability based on the assessment results. For each scour area marked as a precursor zone for scour instability, the corresponding precursor record for scour instability is calculated sequentially. The precursor record for scour instability includes the center coordinates of the scour area, the average scour thickness of the area, the area of ​​the scour area, the velocity amplification factor, the estimated velocity amplification value, the cumulative scour trend, the slope co-instability state, and the corresponding monitoring time. Specifically, the cumulative scour trend of the scour area is assessed as follows: the scour area where a comprehensive judgment of the precursors of scour instability is performed is marked as the current scour area, and the center coordinates of the scour area corresponding to the current scour area are marked as the current scour coordinates; from the set of seafloor topographic change features, all topographic change feature records containing the current scour coordinates are obtained and marked as historical change feature records; the number of trend analysis backtracking periods is preset, which is the number of adjacent monitoring time pairs backtracked, and is preset by those skilled in the art based on the minimum time series sample size required for scour trend judgment; from the most recent From the historical change characteristic records, the corresponding regional average scour thickness is obtained to form a time series sequence of scour thickness; among which, The trend analysis backtracking period is used to determine the number of regional average scour thicknesses in the scour thickness time series and mark them as the effective time series length. If the effective time series length is less than the trend analysis backtracking period, it indicates insufficient historical scour records, and the cumulative scour trend is marked as having insufficient data. If the effective time series length is greater than or equal to the trend analysis backtracking period, a monotonicity check is performed on the scour thickness time series. Specifically, all regional average scour thicknesses in the scour thickness time series are arranged in chronological order, and the relationship between adjacent regional average scour thicknesses is compared sequentially. The next scour thickness is then statistically analyzed. The number of times the brush thickness value is greater than or equal to the previous brush thickness value is marked as the increasing number; the ratio between the increasing number and the effective time sequence length minus one is calculated to obtain the increasing percentage; a preset increasing percentage judgment threshold is set, and the increasing percentage is compared with the increasing percentage judgment threshold; wherein, the increasing percentage judgment threshold is preset by those skilled in the art according to the degree of conservatism in judging the brushing trend; if the increasing percentage is greater than or equal to the increasing percentage judgment threshold, the cumulative brushing trend is marked as a continuously aggravated state; if the increasing percentage is less than the increasing percentage judgment threshold, the cumulative brushing trend is marked as a fluctuating state; Assessing the coordinated instability of slopes in the scour zone: Obtain the center coordinates of the corresponding slope change areas from the slope change amounts of all slope change areas; calculate the Euclidean distance between the current scour coordinates and the center coordinates of each slope change area, and mark it as the slope plane distance; preset the slope coordination search radius, and compare the slope plane distance with the slope coordination search radius; wherein, the slope coordination search radius is preset by those skilled in the art based on engineering experience of the scour instability influence range; if there are slope change areas with slope plane distances less than or equal to the slope coordination search radius, then the slope change area with the smallest slope plane distance is marked as the coordinated slope area; from the slope of the coordinated slope area... In the area change data, the average slope change range of the region is obtained; a slope instability slope threshold is preset, and the average slope change range of the region is compared with the slope instability slope threshold; wherein, the slope instability slope threshold is preset by those skilled in the art based on the critical slope criterion for seabed soil stability analysis; if the average slope change range of the region is greater than or equal to the slope instability slope threshold, the slope collaborative instability state is marked as high risk; if the average slope change range of the region is less than the slope instability slope threshold, the slope collaborative instability state is marked as low risk; if there is no slope change area with a slope plane distance less than or equal to the slope collaborative search radius, the slope collaborative instability state is marked as unrelated. A pre-defined set of criteria for identifying precursors to scour instability is established. This set of criteria is pre-set by those skilled in the art based on engineering criteria for scour instability disasters. Specifically, it includes a velocity amplification factor threshold, a velocity amplification threshold, a regional average scour thickness threshold, and a scour area threshold. If the velocity amplification factor is greater than or equal to the velocity amplification factor threshold, and the estimated velocity amplification value is greater than or equal to the velocity amplification threshold, and the regional average scour thickness is greater than or equal to the regional average scour thickness threshold, and the scour area is greater than or equal to the scour area... If the threshold is met and the cumulative scouring trend is continuously intensifying, then scouring path one is deemed to be met, and the corresponding scouring area is marked as a precursor zone of scouring instability. If all conditions of scouring path one are not met, but the slope collaborative instability state is of high risk, and the velocity amplification factor is greater than or equal to the velocity amplification factor threshold, and the cumulative scouring trend is continuously intensifying, then scouring path two is deemed to be met, and the corresponding scouring area is also marked as a precursor zone of scouring instability. If neither scouring path one nor scouring path two is met, then the corresponding scouring area is not marked.

[0041] Methods for dynamically identifying nearshore erosion precursor zones include: The nearshore area is defined by pre-set standards, including the upper limit of nearshore water depth and the upper limit of nearshore shoreline distance. The upper limit of nearshore water depth is the maximum water depth threshold for determining whether a grid node is located in the nearshore area. The upper limit of nearshore shoreline distance is the maximum offshore distance threshold for determining whether a grid node is located in the nearshore area. Both the upper limit of nearshore water depth and the upper limit of nearshore shoreline distance are pre-set by those skilled in the art based on the nearshore topographic features of the target sea area and the typical occurrence areas of erosion disasters. The coastline coordinate sequence is obtained from the pre-set coastline data (i.e., the geographic reference data used to describe the spatial location of the coastline of the target sea area, which is pre-acquired and stored by those skilled in the art based on the basic surveying and mapping data). For each slope change area, it is determined whether it is located in the nearshore area, and slope change areas located in the nearshore area are marked as nearshore slope change areas. Specifically, the center coordinates of the slope change area are obtained from the slope change amount; the grid water depth value corresponding to the center coordinates of the slope change area is obtained from the seabed topography grid corresponding to the analysis time, and marked as the slope water depth; if the slope water depth is greater than the upper limit of the nearshore water depth, the corresponding slope change area is determined not to be in the nearshore area and is not included in the nearshore erosion precursor analysis; if the slope water depth is less than or equal to the upper limit of the nearshore water depth, the Euclidean distance between the center coordinates of the slope change area and each coastline coordinate in the coastline coordinate sequence is calculated and marked as the coastal plane distance, and the minimum value among all coastal plane distances is taken as the offshore distance; if the offshore distance is greater than the upper limit of the nearshore coastline distance, the corresponding slope change area is determined not to be in the nearshore area; if the offshore distance is less than or equal to the upper limit of the nearshore coastline distance, the corresponding slope change area is determined to be in the nearshore area. For each nearshore slope change area, it is sequentially determined whether the corresponding main slope direction points towards the shoreline. Specifically, from the flow direction reversal assessment record corresponding to the nearshore slope change area, the corresponding flow direction reversal intensity index and main slope direction are obtained, and it is determined whether the main slope direction points towards the shoreline. Specifically, the azimuth angle of the line connecting the center coordinates of the slope change area to the coordinates of the corresponding coastal point at the offshore distance is calculated and marked as the shoreline direction angle. Using the same angle calculation method as in the flow direction reversal analysis, the angle between the main slope direction and the shoreline direction angle is calculated to obtain the slope-shore angle. A slope-shore same direction determination threshold is preset, which is preset by those skilled in the art according to the directional requirements of the erosion effect. If the slope-shore angle is less than or equal to the slope-shore same direction determination threshold, it is determined that the main slope direction points towards the shoreline, indicating that the seabed slope is inclined towards the shoreline, and there is a risk of erosion of the shoreline by guiding water flow. If the slope-shore angle is greater than the slope-shore same direction determination threshold, it is determined that the main slope direction does not point towards the shoreline. For each nearshore slope change area, the corresponding wave coordination state is evaluated sequentially. Specifically, the Euclidean distance between the center coordinates of the slope change area and the center coordinates of the sedimentation areas in all wave aggregation assessment records is calculated and marked as the nearshore horizontal distance. A wave coordination search radius is preset and compared with each nearshore horizontal distance. The wave coordination search radius is preset by those skilled in the art based on the spatial influence range of the wave aggregation effect. If there is a sedimentation area with a nearshore horizontal distance less than or equal to the wave coordination search radius, the corresponding wave aggregation enhancement coefficient is obtained from the corresponding wave aggregation assessment record and compared with a preset wave aggregation hazard threshold. The wave aggregation hazard threshold is preset by those skilled in the art based on the safety criteria for wave impact on the nearshore foundation. If the wave aggregation enhancement coefficient is greater than the wave aggregation hazard threshold, the wave coordination state is marked as high risk. If the wave aggregation enhancement coefficient is less than or equal to the wave aggregation hazard threshold, the wave coordination state is marked as low risk. If there is no sedimentation area with a nearshore horizontal distance less than or equal to the wave coordination search radius, the wave coordination state is marked as unrelated. For each nearshore slope change area, it is determined whether there are surrounding scour areas, and the corresponding nearshore scour coordination state is evaluated based on the determination results. Specifically, the Euclidean distance between the center coordinates of the nearshore slope change area and the center coordinates of all scour areas is calculated and marked as the regional planar distance. A pre-set scour coordination search radius is used, and the planar distance of each region is compared with the scour coordination search radius. The scour coordination search radius is pre-set by those skilled in the art based on the spatial correlation range between nearshore scour and scour. If there are scour areas whose regional planar distance is less than or equal to the scour coordination search radius, the nearshore scour coordination state is marked as present; if there are no scour areas whose regional planar distance is less than or equal to the scour coordination search radius, the nearshore scour coordination state is marked as absent. For each nearshore slope change area, a comprehensive assessment of nearshore erosion precursors is performed, and based on the assessment results, it is determined whether the nearshore slope change area should be marked as a nearshore erosion precursor area. Specifically, a pre-set set of nearshore erosion precursor assessment criteria is established. This set of criteria is pre-set by those skilled in the art based on engineering criteria for nearshore erosion disasters, specifically including a flow direction reversal intensity index threshold and a slope change amplitude threshold. If the flow direction reversal intensity index is greater than or equal to the flow direction reversal intensity index threshold, and the main slope direction points towards the shoreline, and... If the average slope change in the area is greater than or equal to the slope change threshold, then it is determined that nearshore path one is met, and the corresponding nearshore slope change area is marked as a nearshore erosion precursor area. If the flow direction turning intensity index is greater than or equal to the flow direction turning intensity index threshold, and the wave coordination state is high risk, and the nearshore scour coordination state exists, then it is determined that nearshore path two is met, and the corresponding nearshore slope change area is also marked as a nearshore erosion precursor area. If neither nearshore path one nor nearshore path two is met, then the corresponding nearshore slope change area is not marked.

[0042] For each nearshore slope change area marked as a precursor zone of nearshore erosion, the corresponding center coordinates of the slope change area, distance from the shore, main slope direction, flow direction inflection intensity index, wave coordination status, nearshore scour coordination status, regional average slope change amplitude, and corresponding monitoring time are integrated to form a nearshore erosion precursor record for the corresponding nearshore erosion precursor zone.

[0043] Methods for dynamically identifying precursory areas of waterway siltation include: The pre-set channel area data includes the channel centerline coordinate sequence, the channel design depth, and the channel width. The channel centerline coordinate sequence consists of the planar coordinates of each point on the channel centerline arranged sequentially according to the channel's direction. The channel design depth is the minimum depth required to maintain safe navigation. The channel width is the effective width allowed for navigation in the cross-sectional direction of the channel. The channel area data is pre-set by those skilled in the art based on channel design data and navigation management requirements. For each siltation area, it is determined whether it is located within a waterway area, and siltation areas located within a waterway area are marked as waterway siltation areas. Specifically, the center coordinates of the siltation area are obtained from the seabed siltation volume; the Euclidean distance between the center coordinates of the siltation area and each plane coordinate in the waterway centerline coordinate sequence is calculated and marked as the waterway plane distance, and the minimum value among all waterway plane distances is taken as the waterway deviation distance; half of the waterway width is calculated to obtain the waterway half-width; if the waterway deviation distance is less than or equal to the waterway half-width, the corresponding siltation area is determined to be within a waterway area and is marked as a waterway siltation area; if the waterway deviation distance is greater than the waterway half-width, the corresponding siltation area is determined not to be within a waterway area and is not included in the waterway siltation precursor analysis. For each channel siltation area, the corresponding depth margin ratio is calculated. Specifically, the average siltation thickness and area of ​​the siltation area are obtained from the seabed siltation volume; the grid depth value corresponding to the center coordinates of the siltation area is obtained from the seabed topography grid at the analysis time and marked as the channel depth; the tide level value is obtained from the tide level record at the analysis time; the sum of the channel depth and the tide level value is calculated to obtain the actual siltation depth of the channel; the difference between the channel design depth and the actual siltation depth is calculated to obtain the margin depth; a positive margin depth indicates that the actual depth of the siltation area no longer meets the design depth requirements, and navigation safety is directly threatened; a negative margin depth indicates that the actual depth of the siltation area is still greater than the design depth; the ratio of the margin depth to the channel design depth is calculated to obtain the depth margin ratio, which reflects the degree of margin between the actual siltation depth and the design depth. For each channel siltation area, the corresponding cumulative siltation trend is assessed. Specifically, the same method used to assess the cumulative scour trend in the analysis of precursors to scour instability is adopted to form a time series of siltation thickness in the channel siltation area, and the monotonicity of the siltation thickness time series is determined to obtain the cumulative siltation trend. The cumulative siltation trend includes a continuously aggravating state, a fluctuating state, and a data insufficiency state. The process involves sequentially determining whether there is a trend of ditch migration towards the waterway direction around each waterway siltation area, thus obtaining the ditch-waterway coordination state corresponding to each siltation area. Specifically, from the ditch migration amounts of all ditch pairs, the coordinates of the ditch center and the migration direction of the later ditch are obtained. The azimuth angle of the plane coordinates corresponding to the deviation distance of the ditch center coordinates from the waterway is calculated and marked as the ditch pointing towards the waterway direction. The angle between the migration direction and the ditch pointing towards the waterway direction is calculated to obtain the ditch migration deviation angle. A preset threshold for determining ditch approaching the waterway and the ditch-waterway influence distance are established. The threshold for determining channel approach is preset by those skilled in the art based on engineering experience regarding the impact of channel migration on the waterway. The channel-waterway influence distance is preset by those skilled in the art based on the channel size and the safe distance of the waterway. If the waterway deviation distance is less than or equal to the channel-waterway influence distance, and the channel migration deviation angle is less than or equal to the threshold for determining channel approach, then the channel-waterway cooperative state is marked as approaching. If the waterway deviation distance is greater than the channel-waterway influence distance, or the channel migration deviation angle is greater than the threshold for determining channel approach, then the channel-waterway cooperative state is marked as no approach. For each channel siltation area, a comprehensive assessment of precursor signs of siltation is performed, and the assessment results determine whether the channel siltation area should be marked as a precursor area of ​​siltation. Specifically, a set of criteria for judging precursor signs of siltation is preset. This set of criteria is pre-set by those skilled in the art based on engineering criteria for siltation disasters, and includes a threshold for the average siltation thickness, a threshold for the water depth margin ratio, and a threshold for the silted area. If the average siltation thickness is greater than or equal to the threshold for the average siltation thickness, and the water depth margin ratio is less than or equal to the water depth margin... If the siltation area is greater than or equal to the threshold value and the cumulative siltation trend is continuously aggravating, then the channel path one is satisfied, and the corresponding siltation area is marked as a precursor area for channel siltation. If the water depth margin ratio is less than or equal to the water depth margin ratio threshold value, the channel-channel coordination is approaching, and the cumulative siltation trend is continuously aggravating, then the channel path two is satisfied, and the corresponding siltation area is also marked as a precursor area for channel siltation. If neither channel path one nor channel path two is satisfied, then the corresponding siltation area is not marked.

[0044] For each channel siltation area marked as a precursor to channel siltation, the corresponding center coordinates of the siltation area, the average siltation thickness of the area, the area of ​​the siltation area, the actual water depth of the siltation, the excess water depth, the water depth margin ratio, the cumulative siltation trend, the channel-channel coordination status, and the corresponding monitoring time are integrated to form a channel siltation precursor record.

[0045] Methods for forming a disaster precursor feature set include: All records of precursors to scour instability, nearshore erosion, and channel siltation are compiled and integrated to form a disaster precursor feature set. This disaster precursor feature set is used to fully record all disaster precursor areas and their multidimensional feature information identified in the target sea area during a continuous monitoring period.

[0046] It should be understood that by constructing a multi-condition combination judgment logic for three types of disasters—scour instability, nearshore erosion, and channel siltation—a technological improvement has been achieved, moving from single-indicator threshold judgment to multi-factor synergistic comprehensive judgment. This overcomes the high false alarm and high false negative rates caused by relying solely on single-parameter threshold alarms. In the identification of precursors to scour instability, by combining instantaneous features such as flow velocity amplification coefficient, scour thickness, and scour area with cumulative scour trends based on temporal monotonicity judgment, and integrating spatial correlation analysis of slope synergistic instability states, a comprehensive judgment mechanism that considers instantaneous risk levels, historical evolution trends, and spatial synergistic effects has been constructed. This mechanism can effectively distinguish between sporadic scour and continuously escalating precursors to scour instability. In the identification of precursors to nearshore erosion, by considering the directional characteristics of slope changes (main slope direction is...)... The method combines multiple paths (whether pointing towards the shoreline) with the intensity of flow direction change, wave aggregation synergy, and nearshore scouring synergy to determine the risk of nearshore erosion. This enables directionally sensitive identification of nearshore erosion risk and accurately determines whether slope changes have a directional risk of guiding water flow to scour the shoreline. This overcomes the shortcomings of focusing only on the magnitude of changes while ignoring the impact of the direction of change on disaster patterns. In the identification of precursors to channel siltation, the method introduces the water depth margin ratio as a core judgment indicator and incorporates the angular relationship between the gully migration direction and the channel direction into the synergistic analysis. This enables a comprehensive assessment of channel siltation risk from two dimensions: water depth safety margin and the trend of external sediment input. It can identify precursor areas of channel siltation with the dual risks of continuous siltation aggravation and gully approaching the channel before the channel water depth exceeds the safety threshold.

[0047] The disaster early warning output module is used to generate spatial distribution maps, evolution trend prediction curves and risk levels of each precursor area based on the disaster precursor feature set, and output multi-dimensional hydrological disaster early warning results.

[0048] Methods for generating spatial distribution maps of each precursor region include: All records of precursors to scour instability, nearshore erosion, and channel siltation were obtained from the disaster precursor feature set. The center coordinates (i.e., the center coordinates of the scour area, the center coordinates of the slope change area, or the center coordinates of the siltation area) and the corresponding precursor type identifiers (i.e., scour instability, nearshore erosion, or channel siltation) of each precursor record were extracted. According to the preset plane coordinate system, the center coordinates and precursor type identifiers of all precursor areas were spatially labeled and visualized on the geographic base map of the target sea area to obtain the spatial distribution map of each precursor area. The spatial distribution map is used to intuitively display the spatial location, distribution density, and coverage of various disaster precursor areas in the target sea area in map form.

[0049] Methods for generating evolution trend prediction curves for each precursor region include: For each precursor zone, all corresponding precursor records are obtained from the disaster precursor feature set and marked as precursor evolution records. According to the type of precursor zone, corresponding key evolution indicators are selected. Specifically, if the precursor zone is a scour instability precursor zone, the regional average scour thickness is selected as the key evolution indicator; if the precursor zone is a nearshore erosion precursor zone, the regional average slope change range is selected as the key evolution indicator; if the precursor zone is a channel siltation precursor zone, the water depth margin ratio is selected as the key evolution indicator. From the precursor evolution records corresponding to the precursor areas, the values ​​of the corresponding key evolution indicators at each monitoring time are extracted to form the time series data of the key evolution indicators for the corresponding precursor areas. Using the monitoring time as the independent variable and the key evolution indicators as the dependent variable, the linear regression method is used to fit the trend of the time series data of each key evolution indicator to obtain the evolution trend fitting function of the corresponding precursor area. The linear regression method is a well-known technique in this field, and the specific implementation process will not be elaborated here. Based on the evolution trend fitting function, extrapolation is performed into a future preset prediction time window to obtain the predicted value sequence of the corresponding precursor area. The prediction time window is preset by those skilled in the art according to the time lead requirements of disaster warning. The time series data of the key evolution indicators corresponding to the same precursor area are concatenated with the predicted value sequence, and plotted with time as the horizontal axis and key evolution indicators as the vertical axis to obtain the evolution trend prediction curve of the corresponding precursor area. The evolution trend prediction curve is used to show the historical change trajectory and future expected development trend of the key evolution indicators in the precursor area.

[0050] The methods for generating the risk level of each precursor zone include: For each precursor zone, select the corresponding set of risk level assessment indicators and risk level classification standards according to the corresponding type; If the precursor zone is a precursor zone of scour instability, the corresponding risk level assessment index set includes the velocity amplification factor, the average regional scour thickness, the cumulative scour trend, and the slope's coordinated instability state. A pre-set scour instability risk level classification standard is provided, which includes the judgment conditions corresponding to three levels: high risk, medium risk, and low risk. This standard is pre-set by those skilled in the art based on the engineering safety level requirements of scour instability disasters. The values ​​of the corresponding risk level assessment indicators in the scour instability precursor records are compared and matched with the scour instability risk level classification standard item by item to determine the risk level of the corresponding precursor zone. If the precursor area is a nearshore erosion precursor area, the risk level assessment index set includes the flow direction turning intensity index, offshore distance, wave coordination state and nearshore scour coordination state; a nearshore erosion risk level classification standard is preset, which is pre-set by those skilled in the art based on the degree of threat of nearshore erosion disaster to shoreline safety; the corresponding risk level assessment index in the nearshore erosion precursor record is compared and matched with the nearshore erosion risk level classification standard one by one to determine the risk level of the corresponding precursor area; If the precursor area is a precursor area for channel siltation, the risk level assessment index set includes the water depth margin ratio, the regional average siltation thickness, the cumulative siltation trend, and the coordination status of the channel and ditch. A preset channel siltation risk level classification standard is set in advance by those skilled in the art based on the channel navigation safety level and dredging and maintenance standards. The corresponding risk level assessment index in the channel siltation precursor record is compared and matched with the channel siltation risk level classification standard item by item to determine the risk level of the corresponding precursor area.

[0051] Methods for outputting multidimensional hydrological disaster early warning results include: The spatial distribution map, evolution trend prediction curve, risk level, precursor type identifier, and corresponding precursor evolution record of each precursor area are integrated to form disaster early warning information for each precursor area. The disaster early warning information of all precursor areas is summarized to form multidimensional hydrological disaster early warning results. Among them, the multidimensional hydrological disaster early warning results are used to provide marine monitoring and management personnel with spatial location, evolution trend, risk level, and detailed characteristic information of various disaster precursor areas in the target sea area, providing a basis for decision-making for channel dredging and maintenance, nearshore protection engineering deployment, and marine engineering safety management.

[0052] This embodiment establishes a unified spatiotemporal representation framework for multi-source hydrological observation data by simultaneously acquiring multi-temporal acoustic bathymetry data, tidal level sequences, current velocity profile sequences, and wave sequences of the target sea area within a continuous monitoring period. This effectively overcomes the shortcomings of the separation between seabed topographic measurement and hydrodynamic observation. By performing node-by-node differential analysis, connected component aggregation, and channel matching tracing on seabed topographic grids at adjacent monitoring times, seabed sedimentation, seabed erosion, slope change, and channel migration are extracted sequentially, realizing the extraction of multi-scale seabed topographic change information from grid-level micro-changes to regional-level macro-features. By coupling seabed topographic change features with multi-dimensional hydrodynamic information such as tidal level, current velocity profiles, and waves, erosion and sedimentation are quantitatively assessed. The study revealed the collaborative response mechanism between topographic change and hydrodynamic field by investigating the contribution of siltation topography to the velocity amplification effect, the driving effect of slope changes on the flow direction reversal effect, and the enhancement of wave aggregation effect by siltation topography and gully structure. By comprehensively coupling risk analysis results with cumulative trend judgment and multi-factor collaborative risk assessment, the study dynamically identified scour instability precursor zones, nearshore erosion precursor zones, and channel siltation precursor zones, achieving a technological upgrade from passive anomaly detection to active precursor identification. Finally, the study generated multi-dimensional hydrological disaster early warning results including spatial distribution maps, evolution trend prediction curves, and risk levels, providing systematic real-time mapping and disaster early warning technology support for channel navigation safety management, nearshore shoreline protection, and marine engineering safety operation and maintenance in the context of smart ocean scenarios.

[0053] Example 2

[0054] Please see Figure 2 As shown, for parts not described in detail in this embodiment, please refer to the description in Embodiment 1. A multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans is provided, the method including: Multi-temporal acoustic bathymetry data of the target sea area are collected during the continuous monitoring period. Based on the multi-temporal acoustic bathymetry data, the seabed topography grid corresponding to each monitoring time is generated. At the same time, tide level sequence, current velocity profile sequence and wave sequence are collected to form a multi-dimensional hydrological mapping dataset. Multidimensional hydrological mapping datasets are used to collect seabed topographic grids at adjacent monitoring times, and seabed sedimentation, seabed erosion, slope change and channel migration are extracted to form a seabed topographic change feature set; Based on the seabed topographic change feature set, combined with the tide level sequence, current velocity profile sequence and wave sequence in the multidimensional hydrological mapping dataset, the coupling enhancement effect of seabed topographic change on local current velocity amplification, current direction reversal and wave aggregation is analyzed, and a coupling risk result set is formed. Based on the coupled risk result set, the precursor areas of scour instability, nearshore erosion, and channel siltation are dynamically identified to form a disaster precursor feature set. Based on the disaster precursor feature set, spatial distribution maps, evolution trend prediction curves and risk levels of each precursor area are generated, and multi-dimensional hydrological disaster early warning results are output.

[0055] Example 3

[0056] This application also provides an electronic device. The electronic device may include one or more processors and one or more memories. The memories store computer-readable code, which, when executed by the one or more processors, can perform the multi-dimensional hydrological real-time mapping and disaster early warning method for smart oceans as described above.

[0057] The methods or systems according to the embodiments of this application can also be implemented using the architecture of the electronic device shown in this application. The electronic device may include a bus, one or more CPUs, ROM, RAM, a communication port connected to a network, input / output, a hard disk, etc. The storage device in the electronic device, such as a ROM or hard disk, may store the multi-dimensional hydrological real-time mapping and disaster early warning method for smart oceans provided in this application. Furthermore, the electronic device may also include a user interface. Of course, the architecture shown in this application is merely exemplary; when implementing different devices, one or more components of the electronic device shown in this application may be omitted according to actual needs.

[0058] Example 4

[0059] One embodiment of this application discloses a computer-readable storage medium. The computer-readable storage medium stores computer-readable instructions. When the computer-readable instructions are executed by a processor, the multi-dimensional hydrological real-time mapping and disaster early warning method for smart oceans, as described in the above-described embodiments of this application, can be performed. The storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0060] Furthermore, according to embodiments of this application, the processes described in the above-referenced flowcharts can be implemented as computer software programs. For example, this application provides a non-transitory machine-readable storage medium storing machine-readable instructions that can be executed by a processor to perform instructions corresponding to the method steps provided in this application, such as a multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans. When this computer program is executed by a central processing unit (CPU), it performs the functions defined in the method of this application.

[0061] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0062] All formulas in this manual are dimensionless and calculated numerically. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0063] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans, characterized in that, include: Multi-temporal acoustic bathymetry data of the target sea area are collected during the continuous monitoring period. Based on the multi-temporal acoustic bathymetry data, the seabed topography grid corresponding to each monitoring time is generated. At the same time, tide level sequence, current velocity profile sequence and wave sequence are collected to form a multi-dimensional hydrological mapping dataset. Based on the seabed topographic grid at adjacent monitoring times in the multidimensional hydrological mapping dataset, seabed sedimentation, seabed erosion, slope change and channel migration are extracted to form a seabed topographic change feature set. Based on the seabed topographic change feature set, combined with the tide level sequence, current velocity profile sequence and wave sequence in the multidimensional hydrological mapping dataset, the coupling enhancement effect of seabed topographic change on local current velocity amplification, current direction reversal and wave aggregation is analyzed, and a coupling risk result set is formed. Based on the coupled risk result set, the precursor areas of scour instability, nearshore erosion, and channel siltation are dynamically identified to form a disaster precursor feature set. Based on the disaster precursor feature set, spatial distribution maps, evolution trend prediction curves and risk levels of each precursor area are generated, and multi-dimensional hydrological disaster early warning results are output.

2. The multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans according to claim 1, characterized in that, Methods for generating multidimensional hydrological mapping datasets include: The seabed topographic grid, tide level records in the tide level sequence, single-phase current velocity profile data in the current velocity profile sequence, and wave records in the wave sequence are correlated and matched at the same monitoring time to form multidimensional hydrological mapping data for each monitoring time; the multidimensional hydrological mapping data for all monitoring times are summarized to form a multidimensional hydrological mapping dataset. The seabed topography grid includes multiple grid nodes, each with grid node coordinates and grid depth values. The grid node coordinates include the east and north coordinates of the grid node in a preset plane coordinate system. The tide level record includes a monitoring time and a tide level value. The single-phase current velocity profile data includes a monitoring time and multiple layered current velocity records. Each layered current velocity record includes a depth layer identifier, current velocity magnitude, and current velocity direction. The wave record includes a monitoring time and a set of wave characteristic parameters, including significant wave height, mean wave period, and main wave direction.

3. The multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans according to claim 2, characterized in that, Methods for forming a set of features of seafloor topographic changes include: Based on the grid water depth value of each grid node, the corresponding water depth change is calculated, and based on the water depth change, sedimentation and scour classification and connected component aggregation operations are performed to obtain multiple sedimentation or scour regions. For each sedimentation region, the corresponding seabed sedimentation volume is calculated; for each scour region, the corresponding seabed scour volume is calculated; the slope change value of each grid node is calculated, and based on the slope change value, slope anomaly node labeling and connected component aggregation operations are performed to obtain multiple slope change regions; for each slope change region, the corresponding slope change volume is calculated. Identify trench structures in each seabed topographic grid and determine whether a matching relationship has been established; mark each pair of trench structures with an established matching relationship as a trench pair, which includes early trenches and late trenches; calculate the corresponding trench migration amount for each trench pair. The seabed sedimentation volume of all sedimentation areas, the seabed scour volume of all scour areas, the slope change volume of all slope change areas, and the gully migration volume of all gully pairs corresponding to two adjacent monitoring times are summarized and integrated to form a record of topographic change characteristics between corresponding adjacent monitoring times; the topographic change characteristic records between all adjacent monitoring times are summarized to form a set of seabed topographic change characteristics.

4. The multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans according to claim 3, characterized in that, Methods for forming a set of coupling risk results include: For each scour area, the local velocity amplification effect caused by scour is evaluated, and the velocity amplification evaluation record for the corresponding scour area is obtained; for each sedimentation area, the local velocity amplification effect caused by sedimentation is evaluated, and the velocity amplification evaluation record for the corresponding sedimentation area is obtained; the velocity amplification evaluation records corresponding to all scour areas and sedimentation areas are summarized to form the velocity amplification coupling analysis results. For each slope change area, the flow direction reversal effect caused by the slope change is evaluated, and the flow direction reversal evaluation record for each slope change area is obtained; the flow direction reversal evaluation records corresponding to all slope change areas are summarized to form the flow direction reversal coupling analysis results. For each siltation area, the wave aggregation effect caused by siltation is evaluated, and the corresponding wave aggregation evaluation record is obtained; for each later trench in a trench pair, the trench morphology is evaluated on the wave refraction aggregation effect, and the corresponding wave refraction aggregation evaluation record is obtained; all wave aggregation evaluation records and all wave refraction aggregation evaluation records are summarized to form the wave aggregation coupling analysis results. The results of velocity amplification coupling analysis, flow direction reversal coupling analysis, and wave aggregation coupling analysis are integrated to form a set of coupling risk results.

5. The multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans according to claim 4, characterized in that, The method for obtaining the velocity amplification assessment records of the scour zone is as follows: Of the two monitoring times corresponding to the seabed scour volume in the scour area, the later monitoring time is marked as the analysis time. From the single-phase velocity profile data corresponding to the analysis time, the velocity magnitude of the bottom layer velocity record is obtained and marked as the bottom velocity. Based on the vertical contraction effect of the upstream to the pit section caused by scour, the velocity amplification factor of the scour area is calculated. Based on the bottom velocity and the velocity amplification factor, the velocity amplification estimate of the scour area is calculated. The center coordinates of the scour area, the average scour thickness of the area, the velocity amplification factor, the bottom velocity, and the velocity amplification estimate are integrated to form the velocity amplification assessment record of the scour area. The method for obtaining the flow direction reversal assessment record is as follows: From the slope change, obtain the main slope direction, the center coordinates of the slope change area, and the average slope change range of the area; From the single-phase velocity profile data corresponding to the analysis time, obtain the velocity direction of the bottom layer velocity record and mark it as the bottom layer flow direction; Calculate the angle between the main slope direction and the bottom layer flow direction to obtain the direction angle; Based on the direction angle and the average slope change range of the area, assess the flow direction reversal intensity index; Integrate the center coordinates of the slope change area, the main slope direction, the direction angle, the average slope change range of the area, the flow direction reversal intensity index, and the bottom layer flow direction to form the flow direction reversal assessment record.

6. The multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans according to claim 5, characterized in that, The method for obtaining wave aggregation assessment records is as follows: from the seabed sedimentation volume, obtain the center coordinates of the sedimentation area and the average sedimentation thickness of the area; based on the wave shallow water deformation theory, assess the impact of the reduced water depth caused by sedimentation on wave propagation aggregation, and obtain the wave aggregation enhancement coefficient; The wave height concentration estimate is calculated based on the wave concentration enhancement coefficient, and then integrated with the center coordinates of the sedimentation area, the average sedimentation thickness of the area, and the wave concentration enhancement coefficient to form a wave concentration assessment record. The method for obtaining wave refraction and aggregation assessment records is as follows: obtain the center coordinates of the later trench from the trench migration amount corresponding to the trench pair; obtain the main wave direction from the wave record at the corresponding monitoring time of the later trench; evaluate the refraction and aggregation effect of the trench on the waves by analyzing the relationship between the trench structure and the main wave direction, and determine whether the later trench should be marked as a wave aggregation trench. For each wave accumulation trench, the corresponding wave refraction accumulation coefficient is calculated and integrated with the trench center coordinates to form a wave refraction accumulation assessment record.

7. The multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans according to claim 6, characterized in that, Methods for dynamically identifying precursory zones of scour instability include: For each scour region, the corresponding cumulative scour trend is evaluated sequentially: a time series sequence of scour thickness is constructed for the scour region, and the effective time series length is obtained statistically; if the effective time series length is less than the preset number of trend analysis backtracking periods, the cumulative scour trend is marked as insufficient data; if the effective time series length is greater than or equal to the number of trend analysis backtracking periods, the monotonicity of the scour thickness time series is determined, and the cumulative scour trend is marked as either continuously aggravated or fluctuating based on the determination result. For each scour area, the corresponding slope instability state is evaluated sequentially: from all slope change areas, the corresponding slope area is identified; if no slope area exists, the slope instability state is marked as unrelated; if a slope area exists, the average slope change of the slope area is obtained and compared with the preset slope instability slope threshold. Based on the comparison result, the slope instability state is marked as high risk or low risk. Based on the cumulative scour trend and the coordinated instability of the slope, a comprehensive judgment of the precursors of scour instability is performed, and the scour areas that meet the preset scour path one or scour path two are marked as the precursor areas of scour instability.

8. The multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans according to claim 7, characterized in that, Methods for dynamically identifying nearshore erosion precursor zones include: For each slope change area, determine whether it is located in the nearshore area, and mark the slope change area in the nearshore area as the nearshore slope change area; for each nearshore slope change area, determine whether the corresponding main slope direction points to the shoreline direction, and evaluate the corresponding wave coordination state in turn; for each nearshore slope change area, determine whether there is a scour area around it, and evaluate the corresponding nearshore scour coordination state based on the judgment result; based on the judgment result of the main slope direction, the wave coordination state and the nearshore scour coordination state, perform a comprehensive judgment of nearshore erosion precursors, and mark the nearshore slope change areas that meet the preset nearshore path one or nearshore path two as nearshore erosion precursor areas; The method for assessing wave coordination status is as follows: calculate the nearshore plane distance between the center coordinates of the slope change area corresponding to the nearshore slope change area and the center coordinates of the siltation area in all wave aggregation assessment records; compare each nearshore plane distance with the preset wave coordination search radius, and determine whether to mark the wave coordination status as unrelated based on the comparison results; if not, obtain the wave aggregation enhancement coefficient from the corresponding wave aggregation assessment record and compare it with the preset wave aggregation danger threshold, and mark the wave coordination status as high risk or low risk based on the comparison results.

9. The multi-dimensional real-time hydrological mapping and disaster early warning method for smart oceans according to claim 8, characterized in that, Methods for dynamically identifying precursory areas of waterway siltation include: For each siltation area, determine whether it is located in a waterway area, and mark the siltation area located in the waterway area as a waterway siltation area; for each waterway siltation area, calculate the corresponding water depth margin ratio and evaluate the corresponding cumulative siltation trend; sequentially determine whether there is a trend of ditch migration towards the waterway direction around each waterway siltation area to obtain the corresponding ditch-waterway coordination state; based on the water depth margin ratio, cumulative siltation trend and ditch-waterway coordination state, perform a comprehensive judgment of waterway siltation precursors, and mark the waterway siltation areas that meet the preset waterway path one or waterway path two as waterway siltation precursor areas; The method for obtaining the channel-ditch cooperative status is as follows: from the channel migration amount of all channel pairs, obtain the channel center coordinates and migration direction of the later channel; based on the channel center coordinates, migration direction and preset channel centerline coordinate sequence, calculate the channel deviation distance and channel migration deviation angle, and compare them with the preset channel approach threshold and channel influence distance, respectively. According to the comparison results, the channel-ditch cooperative status is marked as approaching or not approaching.

10. A multi-dimensional hydrological real-time mapping and disaster early warning system for smart oceans, implementing the multi-dimensional hydrological real-time mapping and disaster early warning method for smart oceans as described in any one of claims 1-9, characterized in that, include: The multi-dimensional hydrological mapping module is used to collect multi-temporal acoustic bathymetry data of the target sea area within a continuous monitoring period. Based on the multi-temporal acoustic bathymetry data, it generates the seabed topography grid corresponding to each monitoring time and simultaneously collects tide level sequence, current velocity profile sequence and wave sequence to form a multi-dimensional hydrological mapping dataset. The topographic change extraction module is used to extract seabed sedimentation, seabed erosion, slope change and channel migration from the seabed topographic grid of adjacent monitoring times in the multidimensional hydrological mapping dataset, forming a seabed topographic change feature set; The dynamic coupling analysis module is used to analyze the coupling enhancement effect of seabed topographic changes on local velocity amplification, flow direction reversal and wave aggregation based on the seabed topographic change feature set and the tide level sequence, current velocity profile sequence and wave sequence in the multidimensional hydrological mapping dataset, and to form a coupling risk result set. The precursor dynamic identification module is used to dynamically identify the precursor areas of scour instability, nearshore erosion, and channel siltation based on the coupled risk result set, forming a disaster precursor feature set; The disaster early warning output module is used to generate spatial distribution maps, evolution trend prediction curves and risk levels of each precursor area based on the disaster precursor feature set, and output multi-dimensional hydrological disaster early warning results.

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