Method for judging influence boundary of typhoon spatio-temporal variation in near-shore sea area

Abstract

The present application relates to the technical field of marine disaster assessment, and discloses a method for judging the influence boundary of typhoon spatiotemporal change in nearshore sea area, comprising the following steps: obtaining historical meteorological data to construct a representative tropical cyclone sample set; establishing a structureless grid water dynamic sediment coupling numerical model to calculate the spatial distribution of net sediment transport and demarcate the sediment transport boundary range; adjusting the meteorological parameters and translating the path of the cyclone sample set, obtaining the scouring and silting change distribution data based on the translated path by using the model, and extracting the future scenario scouring and silting warning boundary; analyzing the nearshore core storm deposit record data and regional wind field data, calculating the sediment record preservation potential percentage to define the high potential area; and finally, layering the sediment transport boundary range, the future scenario scouring and silting warning boundary and the high potential area to construct the influence boundary of typhoon spatiotemporal change in nearshore sea area. The present application introduces geological record verification of simulation results, and improves the reliability of boundary judgment.

Description

Technical Field

[0001] This invention relates to the field of marine disaster assessment technology, specifically a method for determining the impact boundary of typhoon spatiotemporal changes on nearshore waters. Background Technology

[0002] Typhoons can affect the topography and sedimentary environment of nearshore waters. Accurately determining the impact boundaries of typhoon spatiotemporal changes in nearshore waters is crucial for marine disaster assessment.

[0003] However, existing methods for determining impact boundaries have certain limitations. When assessing current hydrodynamic impacts, current technologies typically fail to effectively quantify the differences in sediment initiation and net sediment transport under typhoon wind conditions and windless environments, making it difficult to accurately delineate the boundary range of sediment transport. This results in low accuracy in determining the current hydrodynamic impact boundary in nearshore waters. In forecasting and extrapolation, conventional assessment methods often rely solely on historical static meteorological data, failing to incorporate changes in cyclone center parameters caused by ambient temperature variations and the long-term evolution of the spatial centroid path. This makes it impossible to dynamically calculate the scouring and sedimentation warning boundary under future climate change scenarios.

[0004] Furthermore, current judgment methods are mostly limited to short-term numerical simulation data and lack a mechanism to introduce long-term core geological sedimentary records to physically cross-verify the simulation results. Due to the lack of auxiliary definition of the geological record preservation potential, the reliability of the final generated typhoon comprehensive impact boundary is insufficient. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for determining the impact boundary of typhoon spatiotemporal variations in nearshore waters. This method solves the problem that existing technologies, when assessing the impact boundary of typhoons on nearshore waters, typically rely solely on historical meteorological data or conventional hydrodynamic models, failing to dynamically predict the spatiotemporal evolution characteristics of typhoon intensity and path under the background of climate change, and lack long-term geological sedimentary records as a means of verifying physical mechanisms. Consequently, the delineated impact boundary cannot objectively reflect the scope of extreme weather impacts and long-term erosion and sedimentation trends.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution: a method for determining the influence boundary of typhoon spatiotemporal variations in nearshore waters, including acquiring historical meteorological data of the target area and analyzing tropical cyclone center parameters to construct a representative tropical cyclone sample set; A coupled hydrodynamic and sediment numerical model was constructed. This model was used to simulate the water movement and sediment initiation process caused by representative tropical cyclone samples, and to calculate the spatial differences in net sediment transport to delineate the sediment transport boundary. By setting the cyclone parameter adjustment amount and path migration step size, the evolved cyclone samples are imported into the above model to predict the distribution changes of seabed erosion and sedimentation, and to extract the erosion and sedimentation early warning boundary for future scenarios. Collect and analyze the grain size and elemental characteristics of nearshore geological sedimentary cores, invert the sediment retention probability of historical typhoon events, and identify high-potential areas; By overlaying the sediment transport boundary, the future scenario erosion and deposition warning boundary, and the high-potential area in a unified coordinate system, a typhoon impact boundary is generated.

[0007] This invention calculates the spatiotemporal projection parameters of typhoon samples by setting empirical correlation rules between wind speed and air pressure and extracting translation step size from spatial centroid latitude and longitude variation data; at the same time, it extracts the grain size and elemental characteristics of core sedimentary records to calculate the percentage of sedimentary record preservation potential, and uses the percentage of preservation potential to perform coordinate registration and layer overlay on the sediment transport boundary range output by the hydrodynamic model and the future scenario erosion and deposition warning boundary, directly outputting quantified multi-boundary spatial distribution data.

[0008] Preferably, when constructing a representative tropical cyclone sample set, the latitude and longitude, central pressure, maximum wind speed, and maximum wind speed radius in historical tropical cyclone path data are analyzed. Based on the above parameters, a theoretical wind field is constructed within the spatial grid. By comparing with the obtained disaster-causing wind speed threshold, historical typhoon events that can generate wind speeds reaching or exceeding the threshold within the spatial grid are selected, and the extracted historical typhoon events are summarized and combined.

[0009] Preferably, the construction process of the coupled hydrodynamic and sediment numerical model is as follows: An unstructured triangular mesh system with gradually increasing dimensions from nearshore to offshore is established. A hydrostatic approximation mechanism is configured in the core computing engine to solve the three-dimensional fluid dynamics equations, and a vertical topographic coordinate transformation and turbulence closure model are configured. Transport and diffusion equations are configured to calculate the suspension and sedimentation processes of sediment in the water body, and a wave energy spectrum evolution model is configured to calculate the dissipation processes of waves and wind waves. Finally, measured hydrological and sediment data are used to verify and calibrate the model's boundary conditions and environmental forcing fields.

[0010] Preferably, the specific operations for calculating the spatial distribution of net sediment transport include: using a low-pass filter to separate the periodic flow field changes caused by tides in the simulated output velocity data, extracting the residual flow vector and decomposing it into mutually perpendicular horizontal orthogonal components. Aligning the timestamps of the velocity data and sediment concentration data, multiplying the horizontal orthogonal components of the residual flow with the corresponding sediment concentration data at each time point. Accumulating the multiplication results within a set typhoon impact period, calculating the sediment transport for each corresponding component, and performing vector synthesis processing.

[0011] Preferably, the sediment transport boundary is defined by comparing the sediment transport size of grid nodes under conditions without tropical cyclone wind field and conditions with tropical cyclone wind field, and extracting the outermost envelope of grid nodes where the sediment transport size under the tropical cyclone wind field condition is greater than that under the condition without tropical cyclone wind field, as the sediment transport boundary.

[0012] Preferably, parameter adjustment and path translation are performed on a representative tropical cyclone sample set to obtain the translation path. Specifically, this includes: setting a wind speed increase ratio based on the increase in ambient temperature to correct the cyclone's maximum wind speed, and calculating the central pressure based on the exponential correspondence between the maximum wind speed and the difference in ambient background pressure, thus completing the parameter adjustment. The spatial centroid is calculated using the mass moment method, and the translation step size is obtained based on the average value of long-term latitude and longitude variation data over many years. Multiple different translation tier scenarios, including the original path, are configured along the longitude or latitude direction, with the multiple translation tier scenarios increasing progressively according to multiples of the translation step size. Spatial coordinate translation operations are performed on the original path according to the configured multiple translation tier scenarios to obtain the translation path corresponding to each translation scenario.

[0013] Preferably, the future scenario scour and sedimentation early warning boundary is extracted by: using the adjusted parameters and the translation path-driven hydrodynamic sediment coupling numerical model to obtain scour and sedimentation change distribution data; and extracting the outer contour of the area where the scour and sedimentation change distribution data is greater than 0 or the preset effective scour and sedimentation tolerance value as the future scenario scour and sedimentation early warning boundary.

[0014] Preferably, the steps for defining high-potential areas include: aligning the formation year of the core stratigraphic profile with the recording time of regional wind fields measured by instruments; identifying tropical cyclone sedimentary layers based on the coarsening of sediment grains and abrupt changes in elemental properties within the core stratigraphic unit; calculating the ratio of the number of sedimentary identifications to the number of times disaster-causing wind speeds were recorded by instruments to generate a percentage of sedimentary record preservation potential; and extracting areas with values ​​higher than a set benchmark through standardization as high-potential areas.

[0015] Preferably, the impact boundary of typhoon spatiotemporal changes in nearshore waters is constructed, specifically including: uniformly converting the sediment transport boundary, the future scenario erosion and deposition warning boundary, and the high-potential area to the same standard geographic coordinate projection system to perform spatial coordinate registration and layer overlay; respectively using the sediment transport boundary as the current baseline boundary, the future scenario erosion and deposition warning boundary as the future planning warning boundary, and the outer edge of the high-potential area as the key protection boundary, to construct the impact boundary.

[0016] This invention provides a method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters. It has the following beneficial effects: 1. This invention constructs a hydrodynamic-sediment coupling numerical model and inputs a set of representative tropical cyclone samples into the model to calculate the spatial distribution of net sediment transport. It can quantify the differences in sediment initiation and transport under typhoon wind field conditions and without wind field conditions, thereby delineating the boundary range of sediment transport and improving the accuracy of determining the boundary of the current hydrodynamic influence in nearshore waters.

[0017] 2. This invention corrects the cyclone center parameters based on the increase in ambient temperature and generates an increasing translation path by combining the long-term evolution law of the historical spatial centroid. The adjusted cyclone parameters and translation path are then imported into a hydrodynamic sediment coupling numerical model to obtain data on scour and deposition changes. This overcomes the limitations of relying solely on historical static meteorological data and enables dynamic calculation of scour and deposition warning boundaries under future climate change scenarios.

[0018] 3. This invention generates a sediment record preservation potential percentage by comparing the number of tropical cyclone sediment identifications in core stratigraphic units with the number of disaster-causing wind speed records measured by instruments to define high-potential areas. This area is then overlaid with sediment transport boundaries and future scenario scour and deposition warning boundaries. Long-term geological records are introduced to physically cross-validate short-term numerical simulation results, thereby improving the reliability of the final generated typhoon comprehensive impact boundary. Attached Figure Description

[0019] Figure 1 This is a flowchart of the method for determining the boundary of the impact of typhoon spatiotemporal changes on nearshore waters according to the present invention; Figure 2 Figures (a), (b), and (c) show the net sediment transport impact range under a representative typhoon process according to the present invention. Figures (a), (b), and (c) are simulated sediment transport process diagrams for a northwest-trending tropical cyclone case according to the present invention. Figure 3 The diagrams show the scour changes under the typhoon latitude and intensity changes according to the process of Typhoon No. 9711, wherein Figures (a), (b), (c), (d), and (e) are the scour change diagrams corresponding to different latitudinal translation and intensity change scenarios of the present invention. Figure 4 The diagrams show the scour changes under the typhoon longitude and intensity changes according to the process of Typhoon No. 1509, wherein Figures (a), (b), (c), (d), and (e) are the scour change diagrams corresponding to different longitude translation and intensity change scenarios of the present invention. Figure 5 Spatial distribution map of the percentage of storm deposition records preserved in this invention. Detailed Implementation

[0020] The technical solutions in 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.

[0021] See attached document Figure 1 This invention provides a method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters, comprising the following steps: S10. Screening a representative tropical cyclone sample set. Historical tropical cyclone path data and regional wind field data for the study area are obtained. Tropical cyclone center data is extracted from the historical tropical cyclone path data, including longitude, latitude, central pressure, maximum near-center wind speed, and maximum wind speed radius. Using wind field formulas, wind speeds at various grid points over the sea area are calculated based on the obtained tropical cyclone center data. Tropical cyclones that cause wind speeds at grid points in the sea area to exceed or equal to a pre-set disaster-causing wind speed threshold are extracted and combined to generate a representative tropical cyclone sample set. S20. Construct a coupled hydrodynamic and sediment numerical model. Establish an unstructured grid finite volume marine model covering the target sea area (e.g., encompassing the southern Yellow Sea, East China Sea, and nearshore waters of the South China Sea); configure the operation mechanism of the unstructured grid finite volume marine model to perform calculations by solving the three-dimensional Navier-Stokes equations and coupling a wave model; configure open boundary conditions, tides, hydrological runoff, wind field, temperature and salinity field, seabed characteristics, and seafloor topography data into the unstructured grid finite volume marine model; verify the parameters by combining measured hydrological and sediment data, generate a coupled hydrodynamic and sediment numerical model suitable for the target sea area, and complete the steps of establishing and verifying the hydrodynamic and sediment model. S30. Extract the net transport boundary of sediments. Without adding a tropical cyclone wind field, perform basic simulation processing using the hydrodynamic-sediment coupling numerical model suitable for the target sea area generated in step S20. With the tropical cyclone wind field added, perform simulation processing on the representative tropical cyclone sample set generated in step S10 using the hydrodynamic-sediment coupling numerical model to obtain the corresponding flow velocity, sediment concentration, bed shear stress and scour-deposition variation distribution. For the acquired velocity data, a low-pass filter is used to eliminate the periodic tidal effects in the velocity data to extract the residual flow vector; combined with the acquired sediment concentration, the residual flow vector at each time moment is multiplied with the sediment concentration at the corresponding time moment, and the values ​​for a specific time period are calculated to obtain the sediment transport of the corresponding horizontal component, thus obtaining the spatial distribution of net sediment transport. By comparing the sediment transport direction and magnitude of each grid point under simulated conditions without and with tropical cyclone wind fields, the outermost envelope of the grid points with sediment transport magnitude under the tropical cyclone wind field condition being greater than that under the condition without tropical cyclone wind field condition is extracted and delineated as the sediment transport boundary range under the influence of historical typhoons. S40. Calculate the boundary of future siltation warning under future scenarios. Adjust the intensity parameters of tropical cyclones in the representative tropical cyclone sample set in step S10 according to the preset correspondence between the central pressure and maximum wind speed of tropical cyclones, and calculate the centroid of the tropical cyclone samples using the mass moment method. Combine the polar and shore migration characteristics of tropical cyclones, set the latitude and longitude translation rules for the spatial path, and translate the spatial path of the tropical cyclones according to the latitude and longitude translation rules to obtain the translation path. Based on the adjusted intensity parameters and translation path, a hydrodynamic-sediment coupling numerical model is driven to simulate the scour and sedimentation depth of the sea area under multiple path migration and intensity change scenarios. The simulation results of scour and sedimentation depth after changing the location and intensity parameters are subtracted from the original scour and sedimentation depth simulation results of the same tropical cyclone before changing the location and intensity parameters to obtain the scour and sedimentation change distribution data. The outer contour of the area with scour and sedimentation change greater than 0 or the preset effective scour and sedimentation tolerance value is extracted as the scour and sedimentation early warning boundary of the future scenario, and the scour and sedimentation pattern of different tropical cyclone trajectories in the future is output. S50. Quantifying the constraints on the preservation potential of sedimentary records. A sedimentary data processing workflow parallel to the numerical model data processing workflow in steps S20 to S40 is established. The storm sedimentary record screening step is executed, and storm sedimentary record data from nearshore cores is collected. The core stratigraphic position is determined by geological dating, and the number of tropical cyclone depositions within the stratigraphic year is identified by combining the grain size and elemental properties of the cores. The time span corresponding to the core records is aligned with the time span of instrument-measured records in the regional wind field data obtained in step S10. Based on time span alignment and core coordinate location, the number of instrument measurements at which the wind speed at a given location reaches the disaster-causing wind speed threshold is extracted from regional wind field data. The ratio of the number of tropical cyclone depositions to the number of instrument measurements at that location that reach the disaster-causing wind speed threshold is calculated to construct a representative tropical cyclone frequency-intensity relationship to generate the percentage of sedimentary record preservation potential. The percentage of preservation potential is standardized, and areas with standardized values ​​greater than a set benchmark value are defined as high-potential areas, thereby outputting spatial distribution data of nearshore sedimentary record preservation potential. S60. Output multi-dimensional sea-direction impact boundaries. This involves combining the sediment transport boundary range extracted in step S30, the future scenario scour and sedimentation warning boundary extracted in step S40, and the spatial distribution data of high-potential areas output in step S50. Spatial coordinate registration and layer overlay are performed to form a converged processing result. This integrates the sediment transport boundary range extracted from multi-event simulations, the scour and sedimentation warning boundary from future scenario projections, and the standardized high-potential areas. The sediment transport boundary range is used as the current baseline boundary, the scour and sedimentation warning boundary as the future planning warning boundary, and the outer edge of the high-potential area as the key protection boundary, thus constructing the impact boundary of typhoon spatiotemporal changes on nearshore waters.

[0022] When determining the impact boundary of typhoon spatiotemporal variations on nearshore waters, after obtaining historical meteorological database data for the study area, in order to construct a targeted tropical cyclone research sample library and solve the numerical calculation redundancy problem caused by distant, unaffected cyclones, the following sub-processing workflow is specifically executed for the step of selecting a representative tropical cyclone sample set for S10: S11. As a preferred method, historical meteorological database data for the study area is retrieved to extract historical tropical cyclone track data and regional wind field data. Based on the extracted historical tropical cyclone track data and regional wind field data, tropical cyclone center data is extracted for each historical tropical cyclone event. Specifically, the tropical cyclone center data includes the longitude and latitude coordinates of the tropical cyclone center, the central pressure value, the maximum wind speed near the center, and the maximum wind speed radius. The tropical cyclone center data serves as a core dynamic variable determining the energy level and impact range of tropical cyclones, supporting subsequent calculations of the spatial wind speed field.

[0023] S12. Establish a spatial grid matrix for the sea area. Before performing specific calculations, based on the general technical principle of pressure fields driving wind fields in meteorological dynamics, a wind field formula is introduced to calculate the theoretical wind speed at each target grid point in the spatial grid matrix. In this embodiment, the extracted tropical cyclone center data is input into the Holland wind field formula to construct a theoretical storm model for the study area. At the underlying calculation logic level, the gradient wind balance relationship is used to convert the input central pressure and maximum wind speed radius into spatial wind speed values ​​exhibiting radial attenuation characteristics.

[0024] For the specific empirical constant configurations involved in the Holland wind field formula, those skilled in the art can perform configuration calculations based on conventional meteorological dynamics principles. The derivation and calculation process are well-known techniques in this field and will not be elaborated upon here. By calculating each grid point individually, the spatial wind speed distribution field of a single historical tropical cyclone on the marine spatial grid matrix is ​​obtained.

[0025] S13. Set a disaster-causing wind speed threshold. Based on the abrupt changes in nearshore marine dynamics under the influence of tropical cyclones, when the wind speed reaches level 10 or above, the resulting strong winds and giant waves can enhance nearshore current velocity and seabed shear stress, effectively triggering the resuspension of sediments and changes in seabed sedimentary structure. Therefore, a preset critical wind speed value is obtained as the disaster-causing wind speed threshold. For example, the disaster-causing wind speed threshold is set to 24.5 m / s, corresponding to level 10 wind force, as the critical kinetic energy marker boundary for triggering the initiation of bottom sediment.

[0026] The process iterates through all target grid points in the spatial wind speed distribution field, determining whether the theoretical wind speed at each grid point is greater than or equal to a preset wind speed threshold (e.g., 24.5 m / s). If a historical tropical cyclone has a target grid point in the marine spatial grid matrix with a theoretical wind speed greater than or equal to the disaster-causing wind speed threshold, the corresponding historical tropical cyclone is extracted. All extracted historical tropical cyclones are then combined to generate a representative tropical cyclone sample set.

[0027] By using a disaster-causing wind speed threshold for preliminary screening, distant cyclones that cannot have a real hydrodynamic impact on the target sea area are eliminated, thereby accurately focusing the subsequent simulation on representative samples with actual impact capabilities and reducing the load of ineffective numerical calculations.

[0028] Based on the representative tropical cyclone sample set output in step S10, in order to construct a three-dimensional numerical computing environment capable of accurately simulating the extreme effects of tropical cyclones and to address the difficulty in quantitatively characterizing the evolution of hydrodynamics and sediment transport under complex nearshore topography, the following sub-processing steps are specifically executed for the construction of the coupled hydrodynamic and sediment numerical model: S21. Define the spatial boundary of the model computational domain. Establish a model computational domain covering the target nearshore sea area, ensuring the model range covers the coastal boundary of the area under study (e.g., covering the entire coastal boundary of China from the South Yellow Sea and East China Sea to the South China Sea). Divide the model computational domain into unstructured triangular meshes. When dividing the unstructured triangular meshes, set the mesh size distribution rule to gradually increase from the nearshore area to the offshore area. The mesh size configured in the nearshore area is approximately 500m, and the maximum mesh size at the open boundary of the model computational domain is approximately 10km. By adopting a transition rule where the mesh size gradually increases from the nearshore area to the offshore area, the propagation physical characteristics of long waves at different water depths are adapted, compressing the number of computational nodes in the offshore area while ensuring resolution of complex underwater topography in the nearshore region.

[0029] S22. Configure the operational control mechanism for the publicly available FVCOM unstructured mesh finite volume ocean model. Configure the core computational engine of the model system to solve the three-dimensional Navier-Stokes equations to simulate the momentum exchange physical processes of water flow. Employ a hydrostatic pressure approximation mechanism and utilize σ-coordinate system transformation to handle vertical topography, thereby eliminating the vertical stratification distortion caused by nearshore water depth variations. Configure the governing equations of the three-dimensional hydrodynamic model, including the fluid continuity equation to maintain fluid mass conservation, momentum equations corresponding to the x, y, and z spatial dimensions, heat conservation equations, salinity equations, and seawater density equations. Couple a turbulence closure model in the vertical dimension to calculate vertical mixing process parameters.

[0030] At the sediment dynamics level, suspended sediment transport and diffusion equations are configured to deduce the dynamic processes of sediment suspension and settling in water bodies. At the wave dynamics level, the SWAN wave model is coupled. For the calculation and derivation of wave energy spectrum evolution and wind wave generation and dissipation processes in the SWAN wave model, those skilled in the art can directly call mature wave modules based on the principle of wave action conservation; the mechanism and execution logic are well-known technologies in this field and will not be elaborated further here.

[0031] S23. Input Boundary Conditions and Background Parameters. Write open boundary conditions to the nodes of the established model computational domain, and input environmental forcing field data. This data includes marine tidal harmonic constant data, estuarine hydrological runoff data, sea surface wind field data, three-dimensional temperature and salinity field data, seabed sediment characteristic distribution data, and seabed topographic bathymetry data. When inputting boundary conditions and background parameters, confirm the alignment of the meteorological driving field and hydrological bathymetry data in terms of time nodes and spatial projection systems to ensure the synchronization of multi-source operating conditions.

[0032] Input measured hydrological and sediment data for model validation and verification, comparing the model's output of tidal levels, current velocities, and sediment concentrations with the measured data. Adjust the model's bed roughness and sediment settling parameters until the calculation error is reduced to within a preset tolerance range. The preset tolerance range uses the root mean square error (RMSE) range of water level and current velocity from measured hydrological stations in the target sea area as a reference benchmark to ensure the accuracy of hydrodynamic energy transfer and bed shear stress calculations. Generate a hydrodynamic-sediment coupling numerical model suitable for the target sea area for subsequent calculations of net sediment transport and extrapolation of sediment deposition patterns.

[0033] After obtaining the selected representative tropical cyclone sample set and constructing the hydrodynamic-sediment coupled numerical model, the following sub-processing flow is executed for the step of extracting the net transport boundary of sediments in S30: S31. Obtain basic hydrodynamic and sediment operation data. As a preferred approach, under baseline environmental conditions without adding tropical cyclone wind fields, initiate basic simulation calculations using a hydrodynamic-sediment coupling numerical model applicable to the target sea area. Subsequently, maintaining consistent background input conditions such as topography, open boundaries, and astronomical tides, wind field data corresponding to each tropical cyclone within a representative tropical cyclone sample set are used as meteorological driving conditions and added to the hydrodynamic-sediment coupling numerical model to perform typhoon condition simulation calculations.

[0034] By solving the spatiotemporal integral of the governing equations within the numerical model, data on flow velocity, sediment concentration, subsurface shear stress, and foundation scouring and deposition distribution over time were obtained for each grid node under both baseline and typhoon conditions. The numerical algorithm for solving the spatiotemporal integral of the governing equations can be configured and calculated using conventional computational fluid dynamics principles; its discretization and solution processes are well-known techniques in the field and will not be elaborated upon here. The basic operational data obtained from the multi-event simulation are summarized as the data basis for subsequently extracting the influence range of tropical cyclones.

[0035] S32. Calculate the spatial distribution of net sediment transport. Since regional hydrodynamics and sediment budget are mainly controlled by the residual current vector and sediment load scalar, and are influenced by tidal forces and local topography, after acquiring the velocity data of the grid nodes, a low-pass filter is used to filter the time-series velocity data to extract the residual current vector in order to remove the interference from the reciprocating flow caused by periodic tides. For the mathematical processing mechanism of setting the cutoff frequency parameter and separating the high-frequency periodic signal in the low-pass filter, those skilled in the art can perform the configuration calculation based on conventional oceanographic signal processing principles. The derivation and calculation process are well-known techniques in this field and will not be elaborated here.

[0036] Since the extracted residual flow vector has direction and magnitude attributes, the residual flow vector at each time point is decomposed into mutually perpendicular horizontal orthogonal components. In this embodiment, time node alignment logic for multi-source data is executed to extract sediment concentration data that has a synchronous timestamp with the residual flow vector. The extracted horizontal orthogonal components of the residual flow at each time point are multiplied with their corresponding sediment concentration data. The physical meaning of the product result is the instantaneous sediment transport flux.

[0037] The product results obtained from the multiplication calculations are accumulated and synthesized according to a set typhoon impact time period. The specific setting of the typhoon impact time period is based on the complete meteorological record span covering a single tropical cyclone from its entry into the model's computational domain to its departure or dissipation. Through accumulated synthesis calculations, the sediment transport volume of the corresponding horizontal component of the residual flow within a specific time period is obtained. Finally, the sediment transport volumes of each horizontal component are subjected to vector synthesis processing to calculate the spatial distribution data of net sediment transport volume, representing the degree of hydrodynamic influence of the tropical cyclone.

[0038] S33. Delineate the boundary of sediment transport under historical typhoon conditions. After obtaining spatial distribution data of net sediment transport, execute automated delineation rules based on grid node data comparison. Extract sediment transport direction and magnitude distribution data calculated at each grid point under baseline environmental conditions, and use them as a reference. Extract sediment transport direction and magnitude distribution data calculated at each grid point under typhoon conditions, and use them as the analysis object.

[0039] The analysis is performed on a grid-by-grid basis, comparing and judging each grid point. The judgment rule is as follows: compare the sediment transport direction and magnitude of the analysis object with the reference standard. When the sediment transport magnitude of a grid point under the condition of adding a tropical cyclone wind field is greater than the sediment transport magnitude of the same grid point under the condition of not adding a tropical cyclone wind field, it is determined that the grid point area is affected by tropical cyclone dynamics, and the grid point is marked as an affected grid point.

[0040] After obtaining all affected grid points, they are plotted on a planar coordinate map for spatial distribution. The outermost edge on the seaward side of the planar map containing all affected grid points is extracted. This outermost edge on the seaward side is directly defined as the sediment transport boundary under historical typhoon influence, thus obtaining the seaward influence boundary under the influence of typhoons in historical stages.

[0041] In conjunction with step S30, after obtaining the historical scouring and deposition depth simulation results under the influence of representative tropical cyclones, in order to characterize the potential impact of storm evolution on the nearshore seabed under the background of climate warming and to solve the problem that traditional static boundaries cannot cope with extreme ocean dynamic changes, the following sub-processing flow is specifically executed to extrapolate the future scenario scouring and deposition early warning boundary (step S40): S41. Adjust tropical cyclone intensity parameters. Based on the meteorological trend of frequent extreme disasters under global warming, obtain the preset wind speed increase ratio corresponding to the preset temperature increase value, and use this as the scenario parameter. In this embodiment, based on long-term marine meteorological statistical analysis literature as the parameter setting basis, the preset wind speed increase ratio (e.g., 5%) corresponding to the wind speed increase driven by the preset temperature increase value (e.g., 2°C) is configured. Extract the maximum wind speed near the center of the tropical cyclone from the representative tropical cyclone sample set in step S10, and adjust it in conjunction with the preset wind speed increase ratio. Specifically, multiply the original maximum wind speed near the center of the tropical cyclone by a coefficient consisting of 1 and the sum of the preset wind speed increase ratio (e.g., when the preset wind speed increase ratio is 5%, multiply the original maximum wind speed by 105%) to obtain the adjusted maximum wind speed of the tropical cyclone. To maintain the physical and dynamic coordination between the pressure field and the wind field, calculate the corresponding adjusted tropical cyclone center pressure based on the empirical correspondence between the tropical cyclone center pressure and the maximum wind speed. For the corresponding parameter conversion, the following formula is used for calculation: ; in, This indicates the maximum wind speed near the center of a tropical cyclone. This represents the central pressure of a tropical cyclone; the constant 10¹⁵ represents the preset background atmospheric pressure. This represents the pressure difference between the center of a tropical cyclone and the reference background atmospheric pressure. , These represent the first and second fitting coefficients, respectively. In actual calculations, the fitting coefficients are determined using the least squares method based on long-term historical meteorological observation data of the target sea area. The specific mathematical calculation mechanism for obtaining the coefficients using the least squares method can be configured and calculated by those skilled in the art based on conventional statistical and data analysis principles; its derivation and calculation process are well-known techniques in the field and will not be elaborated upon here. By applying this formula, the maximum wind speed near the known adjusted center is... Under the given conditions, the central pressure of the tropical cyclone under the corresponding environment is calculated in reverse. Through the above reverse calculation, a quantitative dynamic driving source applicable to future climate evolution trends is established, which is then used as the forced boundary of the hydrodynamic-sediment coupled numerical model.

[0042] S42. Set spatial path translation rules and obtain the translation path. Based on the adjusted environmental forcing parameters, the mass moment method is introduced to calculate the spatial distribution centroid of each tropical cyclone sample within the tropical cyclone sample set. The centroid calculation is achieved by weighted averaging of latitude and longitude coordinates at each time point based on the tropical cyclone intensity. The calculation mechanism for the spatial coordinate integral and mass distribution weighting in the mass moment method can be configured and calculated by those skilled in the art based on conventional spatial geometry and physics principles; its derivation and calculation process are well-known techniques in the field and will not be elaborated here.

[0043] After obtaining the representative centroids of each tropical cyclone sample, based on the polar and shoreline migration characteristics of the tropical cyclones, the average value of long-term latitude and longitude variation data was calculated as the translation step size, thereby setting the latitude and longitude translation rules for the spatial path. To cover the migration evolution of different dominant wind directions, two scenarios were set: latitude-dominated migration and longitude-dominated migration. Specifically, since the tropical cyclones affected by the target sea area mainly have northwest and northwest-northeast trajectories, a typical northwest-trajectory tropical cyclone was used as the object of latitudinal migration research. Based on the calculated latitudinal translation step size, multiple different latitudinal translation tiers were configured, including the original path. The latitudinal translation tiers were configured in ascending order according to multiples of the latitudinal translation step size. At the same time, a typical northwest-northeast trajectories tropical cyclone was used as the object of longitude migration research. Based on the calculated longitude translation step size, multiple different longitude translation tiers were configured, including the original path. The longitude translation tiers were configured in ascending order according to multiples of the longitude translation step size.

[0044] Therefore, by setting a preset number of offset gradients, the system describes the impact of tropical cyclone trajectory shifts on the dynamic field, avoiding limiting the simulation process to a single specific number or fixed angle translation. Based on the clearly defined latitude and longitude translation rules, multi-scenario spatial coordinate translation operations are performed on the original spatial path of the tropical cyclone to obtain the corresponding translation path sequence under each translation scenario.

[0045] S43. Develop future scenarios for scour and sedimentation warning boundaries. Based on the alignment logic between meteorological data and spatial grids, the adjusted maximum wind speed of tropical cyclones, the adjusted central pressure of tropical cyclones, and the acquired translational paths are sequentially imported into the hydrodynamic-sediment coupling numerical model. The model is then driven to perform spatiotemporal integration of its internal governing equations to simulate the dynamic scour and sedimentation depths of the sea area under multiple scenarios of combined path migration and intensity changes.

[0046] The simulated scour and sedimentation depths obtained after changing the location and intensity parameters are subtracted from the original scour and sedimentation depths of the same tropical cyclone before the change in location and intensity parameters. To avoid the superposition error of multi-source heterogeneous results, the spatial registration of grid nodes is pre-verified before performing the difference calculation. For the mathematical mapping and verification mechanism of multi-source data grid node spatial registration, those skilled in the art can configure and process it according to the principles of conventional geographic information spatial analysis. The coordinate alignment and topology matching process is a well-known technique in this field and will not be elaborated here.

[0047] Subsequently, the differential scour and deposition change distribution data was acquired and each grid node was traversed to identify regions with values ​​greater than 0 in the scour and deposition change distribution data. Here, a value of 0 is used as the physical critical threshold for determining whether deposition has occurred. This threshold benchmark is directly derived from the physical definition of the zero point of sediment balance, and is used to characterize the response of newly added sediment deposition at the seabed bottom under extreme climate conditions.

[0048] To avoid truncation errors and computational noise interference that has no practical engineering significance during numerical simulation, in specific applications, the physical critical threshold for determining whether siltation has occurred can be adjusted from an absolute value of 0 to a preset effective scouring and silting tolerance value slightly greater than 0 (e.g., 0.01m or 0.05m). This preset effective scouring and silting tolerance value is obtained by calibration based on the detection error limit of conventional seabed topographic surveying instruments in the target sea area and the grid calculation accuracy of the model itself.

[0049] Areas with scour and sedimentation changes greater than 0 or greater than a preset effective scour and sedimentation tolerance value are identified as affected areas, and the outermost contour of these affected areas is directly extracted. The outermost boundary results generated under different migration scenarios are integrated to avoid relying solely on local biases arising from a single scenario, ultimately defining the future scour and sedimentation warning boundary. By integrating and extrapolating the results, boundary data of scour and sedimentation patterns for different future tropical cyclone trajectories are output, providing a spatially predictive early warning benchmark for disaster prevention and mitigation.

[0050] After obtaining the scouring and deposition data based on the above steps, geological sedimentary records are introduced for comprehensive evaluation to assess the actual effects of marine dynamics and provide verification and constraints. The following sub-processing workflow is specifically executed for the step of quantifying the preservation potential constraints of the S50 sedimentary record: S51. Extract core sedimentary records and determine the number of tropical cyclone depositions. Sampling points are established within the target nearshore waters to collect nearshore core storm sedimentary record data. Geological dating is performed on the acquired nearshore core storm sedimentary record data to determine the depositional year corresponding to the core strata, establishing a time-correlation sequence between core depth and geological age. For the radioactive isotope testing and half-life calculation used in geological dating, those skilled in the art can perform the tests and calculations based on conventional marine geology principles; the derivation and analysis process are well-known techniques in the field and will not be elaborated upon here.

[0051] After determining the geological age of the core, the core is analyzed layer by layer based on stratigraphic stratification standards. As a preferred method, considering the conventional sedimentation rate of the target sea area and the requirements for high-resolution sampling accuracy, the core stratigraphic units are divided according to a preset thickness standard, for example, dividing the core stratigraphic units according to a thickness standard of 1 cm per layer.

[0052] For each core unit, grain size and elemental composition data were extracted. Specific grain size coarsening intervals and intervals exhibiting abrupt changes in elemental composition were identified and classified as tropical cyclone deposits. This method was used to determine the number of tropical cyclone deposits per year and to statistically analyze the number of tropical cyclone deposits identified within a stratigraphic year, supporting subsequent quantitative calculations of preservation potential.

[0053] S52. Align the spatiotemporal references of geological sedimentary records and meteorological instrument records. Extract the time span corresponding to the core strata obtained from geological dating. Since geological data and meteorological data come from different sources, to ensure the relevance of the analyzed objects in terms of time windows and geographical locations, execute spatiotemporal reference consistency alignment logic.

[0054] The time span corresponding to the core strata is matched with the time span of the instrument recordings in the regional wind field data obtained in step S10. The time span corresponding to the core strata is set to only analyze the time period that is consistent with the time span of the instrument recordings in the regional wind field data.

[0055] The specific latitude and longitude coordinates of the collected rock core samples are extracted. Based on the time span alignment results and the specific latitude and longitude coordinates of the collected rock core samples, location retrieval is performed in the regional wind field data. According to the critical kinetic energy boundary of tropical cyclones triggering the initiation of bottom sediments, the disaster-causing wind speed threshold set in step S13 is uniformly used as the screening standard for wind speeds that can cause the transport of bottom sediments.

[0056] This allows us to filter and statistically analyze the latitude and longitude coordinates of the collected core samples from regional wind field data, identifying the number of times tropical cyclones with wind speeds reaching the disaster-causing wind speed threshold have passed through the area. This leads to the number of times tropical cyclones that may have an impact have passed through the area at the specific latitude and longitude coordinates of the collected core samples.

[0057] S53. Quantify the preservation potential percentage and extract high-potential areas. Based on the aligned core sedimentation counts and meteorological instrument recording counts, construct a representative tropical cyclone frequency-intensity relationship. Calculate the ratio of tropical cyclone sedimentation counts to the number of instrument recording counts at the specific latitude and longitude coordinates of the collected core samples corresponding to wind speeds of level 10 or higher (i.e., the disaster-causing wind speed threshold), and generate the tropical cyclone sedimentation record preservation potential percentage. The physical purpose of calculating the tropical cyclone sedimentation record preservation potential percentage is to quantify the probability that sediments disturbed under extreme dynamic environments will ultimately be effectively preserved and recorded in the strata. The calculation process uses the following formula for conversion: ; in, This indicates the percentage of potential for preservation of tropical cyclone sedimentary records; This indicates the number of tropical cyclone deposits identified in the core sedimentary record; This indicates the number of times the wind speed at the specific latitude and longitude coordinates of the collected core sample corresponds to a tropical cyclone with a wind speed of 10 or higher. The ratio of the number of tropical cyclone deposits identified in the core sedimentary record to the number of tropical cyclone instrument records at the specific latitude and longitude coordinates corresponding to wind speeds of level 10 or above represents the basic retention ratio. This represents the conversion factor for converting the base retention rate to a percentage scale.

[0058] To ensure the integrity of the algorithm logic, the system performs a pre-check before performing the numerical division operation. The numerical state of the variable. If If the value approaches 0, it is determined that the specific latitude and longitude coordinates of the collected rock core sample lack an effective extreme weather driving force source in the corresponding time period. The specific latitude and longitude coordinates of the collected rock core sample are directly marked as having no effective storm driving point, and the calculation of the potential percentage of the specific latitude and longitude coordinates of the collected rock core sample is terminated, thereby avoiding system calculation anomalies and result divergence caused by dividing by zero.

[0059] After calculating the percentage of sediment record preservation potential at each sampling location within the sea area, the percentage of sediment record preservation potential is standardized. To eliminate the absolute magnitude differences caused by the sedimentary background environment of different sea areas, the percentage values ​​obtained at each location are divided by the maximum percentage value obtained across the entire region, i.e., the maximum percentage is taken as 1, so that the processed values ​​are mapped to a standard data range of 0 to 1. The specific mathematical mapping mechanism for the standardization process can be configured and calculated by those skilled in the art based on conventional data analysis principles; its derivation and calculation process are well-known techniques in the field and will not be elaborated here.

[0060] Through the above standardization process, spatial distribution data of nearshore sedimentary record preservation potential, containing standardized values ​​for each location, is output. This spatial distribution data provides a data foundation for subsequently extracting key protection boundaries that meet the constraints based on a set benchmark value of 0.5 (representing a threshold level of more than half of the region's highest preservation potential). This data is then combined with numerical simulations of scour and sedimentation impact distribution to comprehensively constrain and correct the influence boundaries of tropical cyclones in the sea direction.

[0061] Combining the sediment transport boundary range extracted in step S30, the future scenario erosion and deposition warning boundary projected in step S40, and the spatial distribution data of nearshore sedimentary record preservation potential quantified in step S50, based on the technical objective of constructing a multi-dimensional boundary system with spatial prediction characteristics and geological record verification, the following sub-processing flow is specifically executed in this embodiment for the step of outputting multi-dimensional sea-direction influence boundaries in step S60: S61. Perform multi-source geospatial data registration and layer fusion. Extract the sediment transport boundary data set under historical typhoon influence obtained in step S30, extract the future scenario erosion and deposition warning boundary data set output in step S40, and extract the nearshore sedimentary record preservation potential spatial distribution data generated in step S50. Since the data sets generated by different processing steps are attached to different computational grid nodes or core station coordinates, there are multi-source heterogeneous spatial distribution characteristics. In order to unify the spatial reference benchmark of multi-source data, the sediment transport boundary data set, the future scenario erosion and deposition warning boundary data set, and the nearshore sedimentary record preservation potential spatial distribution data are uniformly converted to the same standard geographic coordinate projection system for spatial coordinate registration.

[0062] During spatial coordinate registration, for data sources with spatial resolution differences, spatial interpolation algorithms are used to perform grid unification processing to avoid spatial overlay deviations and geometric distortions caused by resolution mismatch. For the spatial interpolation and grid unification processing mechanisms in multi-source heterogeneous spatial data registration, those skilled in the art can perform configuration calculations based on conventional geographic information spatial analysis principles. The interpolation fitting and topology correction processes are well-known techniques in the field and will not be elaborated upon here. For the coordinate projection transformation and layer overlay processing mechanisms of geospatial data, those skilled in the art can introduce conventional geographic information system spatial analysis tools for configuration processing. The spatial topology calculations and projection transformation processes are well-known techniques in the field and will not be elaborated upon here.

[0063] After completing the unified geographic coordinate projection transformation, a multi-dimensional boundary data layer overlay operation is performed in a planar geospatial coordinate system. Taking the land coastline as the inner reference, the outer contour lines of each data set are mapped towards the sea, forming a spatial distribution layer of multi-dimensional sea-direction-affected boundaries, thus completing the convergence processing of multi-dimensional geospatial boundary data.

[0064] S62. Construct a multi-dimensional influence boundary determination system and output comprehensive results of sea-direction influence boundaries. Based on the multi-level business needs of nearshore marine spatial planning and disaster prevention and mitigation, and in order to match the scale of natural change prediction research with the multi-stage planning period, assign specific physical meanings and application attribute definitions to each group of boundary data after layer overlay and fusion.

[0065] The sediment transport boundary extracted and mapped in step S30 is defined as the current baseline boundary. The current baseline boundary characterizes the outward-directed effect of net transport of bottom sedimentary material driven by tropical cyclones under historical ocean dynamic conditions. The current baseline boundary serves as the baseline for assessing the fortification status of existing nearshore engineering projects and the impact range of current routine development activities.

[0066] The scouring and sedimentation early warning boundary extracted and mapped in step S40 is defined as the future planning early warning boundary. The future planning early warning boundary represents the extended outer limit of new scouring or sedimentation evolution on the seabed under the environmental background of climate warming and the polar and shoreline shifts in the spatial trajectories of tropical cyclones. The future planning early warning boundary serves as a macro-spatial early warning reference line that conforms to the near-term, medium-term, and long-term reservations, port-adjacent industrial layout, and setbacks for major infrastructure construction in future national spatial planning.

[0067] Based on the standardized nearshore sedimentary record preservation potential spatial distribution data output in step S50, the areas with standardized values ​​greater than 0.5 in the spatial distribution data are directly defined as key protection boundaries.

[0068] By using the outer edge of high-potential areas with standardized values ​​greater than 0.5 as the core reference range for disaster prevention and mitigation, the key protection boundary clarifies that tropical cyclone disasters not only generate instantaneous hydrodynamic impacts, but also produce subsurface shear stresses sufficient to reshape the subsurface strata structure and achieve geological-scale preservation of high-risk activity areas. This key protection boundary is then designated as the primary defense and control area for reinforcing marine engineering disaster prevention structures and constructing ecological protection forests.

[0069] After defining the boundaries of each dimension, the system directly integrates and generates a comprehensive sea-direction impact boundary result that includes the current baseline boundary, the future planning early warning boundary, and the key protection boundary. Through nested boundary combination patterns, it provides quantitative assessment results that combine dynamic extrapolation and geological verification for the comprehensive impact of typhoon spatiotemporal variations on nearshore waters.

[0070] See attached document Figure 2 To be continued Figure 5 This paper presents an application example of a method for determining the impact boundary of typhoon spatiotemporal variations on nearshore waters. This application example uses the target coastal boundary as the study area, and the specific application process is as follows: First, historical meteorological database data for the study area was retrieved, and tropical cyclone center data were extracted. The Holland wind field formula was used to calculate the gridded wind speeds in the sea area to establish a spatial grid matrix, and a disaster-causing wind speed threshold (24.5 m / s) was set. A representative tropical cyclone sample set was then selected. A model computational domain covering all coastal boundaries of China was established. This model uses the FVCOM model to divide unstructured triangular meshes for calculation, with the mesh size gradually increasing from nearshore to offshore, approximately 500 m in the nearshore area and a maximum mesh size of approximately 10 km at the open boundary. Further configuration was used to solve the three-dimensional Navier-Stokes equations and couple them with the SWAN wave model. Parameter validation was performed using measured hydrological and sediment data, thereby generating a hydrodynamic and sediment coupled numerical model suitable for the target sea area.

[0071] Then, the net sediment transport boundary was extracted. Simulations were performed in the model with and without tropical cyclone wind fields. A low-pass filter was used to eliminate the periodic tidal effects in the velocity data to extract the residual flow vector. This vector was then multiplied by the corresponding sediment concentration and summed to calculate the spatial distribution of net sediment transport.

[0072] Combined with appendix Figure 2This figure is divided into three sub-figures: Figure (a), Figure (b), and Figure (c), which simulate sediment transport processes for three different historical northwest-trending tropical cyclone cases. The vertical axis is labeled 32°N, 30°N, 28°N, and 26°N, and the horizontal axis is labeled 120°E and 122°E. White isobaths represent water depth variations in the seabed topography, and red arrows represent the net direction of sediment transport. Different colors indicate the magnitude of sediment transport rate (unit: kg·m³). -1 ·s -1 The values ​​range from 0 (blue) to 5 (yellow), with higher values ​​indicating higher sediment transport rates. Specifically, Figure (a) shows the direction and size distribution of sediment transport under the first representative tropical cyclone-driven event, with the black dashed box marking areas of significant variation; Figure (b) shows the sediment transport characteristics under the second representative tropical cyclone-driven event; and Figure (c) shows the sediment transport under the third representative tropical cyclone-driven event. By comprehensively comparing and extracting the outermost edge of the affected grid points marked by the black dashed boxes on the seaward side in Figures (a), (b), and (c), the sediment transport boundary range under the influence of historical typhoons is defined.

[0073] Next, the boundary of the future scenario for siltation warning is extrapolated. A scenario parameter of a 2°C increase in temperature driving a 5% increase in wind speed is preset. The intensity parameters of representative tropical cyclones are adjusted accordingly, and the centroid of the tropical cyclone sample is calculated using the mass moment method. Latitude and longitude translation rules for spatial paths are set, and corresponding migration schemes are configured for typhoons with different orientations. Specifically, taking Typhoon 9711 as an example to represent a northwest-bound typhoon trajectory, a Class A northwest-bound latitudinal migration scheme is set, employing multiple tiers of latitudinal migration schemes including A1 (original scheme), A2 (latitude +1), A3 (latitude +2), A4, A5, and so on. Taking Typhoon 1509 as an example to represent a northwest-northeast trajectory, a Class B northwest-northeast longitude migration scheme is set, employing multiple tiers of longitude migration schemes including B1 (original scheme), B2 (longitude -0.5), B3 (longitude -1), B4, B5, and so on.

[0074] Combined with appendix Figure 3This figure, based on the erosion changes of Typhoon 9711 moving northwest, is divided into five sub-figures: Figure (a), Figure (b), Figure (c), Figure (d), and Figure (e), corresponding to different scenarios of latitudinal shift and intensity changes. Specifically, Figure (a) shows the spatial distribution of the maximum seabed erosion depth when using the original A1 path (brown line); Figure (b) shows the erosion and deposition changes when using the A2 path with increased latitude (the typhoon path shifts northward); Figure (c) shows the erosion and deposition changes when using the A3 path with further increased latitude; Figure (d) shows the erosion and deposition changes when using the A4 path with increased latitude; and Figure (e) shows the erosion and deposition changes when using the A5 highest latitude migration tiered scenario. As the typhoon path moves northward from Figure (a) to Figure (e), significant seabed erosion areas (blue corresponding to negative values ​​representing erosion) and localized deposition areas (red corresponding to positive values ​​representing deposition) also exhibit corresponding spatial polar response characteristics.

[0075] Combined with appendix Figure 4 This figure, based on the scouring changes of Typhoon No. 1509 (northwest-northeast), is also divided into five sub-figures: Figure (a), Figure (b), Figure (c), Figure (d), and Figure (e), corresponding to different scenarios of longitude shift and intensity change. Specifically, Figure (a) shows the scouring and sedimentation distribution when using the original B1 path (brown line); Figure (b) shows the scouring and sedimentation changes when using the B2 path with reduced longitude (the typhoon path shifts westward towards the coast); Figure (c) shows the scouring and sedimentation changes when using the B3 path with further westward shift; Figure (d) shows the scouring and sedimentation changes when using the B4 path with reduced longitude; and Figure (e) shows the scouring and sedimentation changes when using the B5 westernmost longitude shift tiered path. As the path gradually approaches the shore from Figure (a) to Figure (e), the dynamic impact on the nearshore shallow waters intensifies, and the area of ​​significant scouring and sedimentation changes expands significantly inland.

[0076] exist Figure 3 and Figure 4 In the diagram, the vertical axis ranges from 32°N to 26°N, and the horizontal axis ranges from 120°E to 122°E. Color bars indicate the maximum erosion depth (unit: m, numerical range -0.05 to 0.05). The scour and deposition change distribution data are obtained by subtracting the original simulation results from the simulation results after changing the position and intensity parameters for each of the above translation scenarios. The outermost contour of the area where the scour and deposition change is greater than 0 (i.e., representing a deposition response and subsurface disturbance and reshaping) is extracted (e.g., ...). Figure 3 and Figure 4 (As shown in the outer extreme value envelope of the relevant subgraph), the fusion is used to define the boundary for future scenario scour and siltation early warning. Figure 3 and Figure 4 The gray area represents land, and the white area represents ocean.

[0077] Subsequently, the constraints on the preservation potential of sedimentary records were quantified. Storm sedimentary record data were collected from nearshore cores, and the number of tropical cyclone depositional events was identified through geological dating, grain size indices, and elemental composition indices. The core recording time was then aligned with the instrumental recording time span of regional wind field data. (This is combined with...) Figure 5 The percentage of preservation potential is calculated based on the following formula: ; in, This indicates the percentage of potential for preservation of tropical cyclone sedimentary records; This indicates the number of tropical cyclone deposits identified in the core sedimentary record; This indicates the number of times the wind speed at the specific latitude and longitude coordinates of the collected rock core sample corresponds to a tropical cyclone with a wind speed of 10 or higher. Figure 5 The black contour lines are distributed sequentially from nearshore to offshore to indicate water depths of 10m, 20m, 30m, 40m, 50m, and 60m. The nearshore area is shallower, while the offshore area is deeper. Each black triangle represents a core sample, distributed along different water depths in the nearshore region. This embodiment collected five core samples, with corresponding preservation percentages of 33%, 15.4%, 29.4%, 31.6%, and 8.3%, respectively. By collecting a sufficient number of core records using this method, a more refined distribution of preservation potential percentages can be obtained. Figure 5 The gray area represents the land area, and the white area represents the ocean area. By standardizing the acquired percentages, spatial distribution data on the preservation potential of nearshore sedimentary records are output.

[0078] Finally, a comprehensive result of the multi-dimensional sea-direction influence boundary is generated. The sediment transport boundary range obtained above is used as the current baseline boundary, the scour and deposition early warning boundary is used as the future planning early warning boundary, and areas with standardized values ​​greater than 0.5 in the spatial distribution data of nearshore sedimentary record preservation potential are defined as key protection boundaries. Through unified spatial coordinate registration and layer mapping fusion, the comprehensive sea-direction influence boundary result is output.

[0079] The method for determining the influence boundary of typhoon spatiotemporal variations in nearshore waters proposed in this invention breaks through the limitations of past methods that relied on a single theoretical model or a single geological survey. In practical implementation, the model grid used for calculation transitions in spatial resolution from approximately 500m nearshore to 10km offshore, ensuring the accuracy of hydrodynamic evolution analysis under complex nearshore topography while suppressing unnecessary consumption of computational resources.

[0080] Combined with appendix Figure 5The distribution characteristics of core sampling data presented in the data (with preservation percentages of 33%, 15.4%, 29.4%, 31.6%, and 8.3%, respectively) show that the sediment retention probability varies under different water depths and distances from the shore within a water depth range of 10m to 60m. The standardized percentages converted from the above core sampling data are introduced into the numerical dynamics extrapolation process. Combined with the extracted sediment transport boundary range and the future scenario erosion and deposition warning boundary, the spatial distribution data of the impact boundary, including the current baseline boundary, the future planning warning boundary, and the key protection boundary, are output.

Claims

1. A method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters, characterized in that, Includes the following steps: Historical tropical cyclone track data and regional wind field data of the study area were obtained, tropical cyclone center data were extracted, and a representative tropical cyclone sample set was generated by combining the marine spatial grid matrix and the disaster-causing wind speed threshold. Establish an unstructured mesh finite volume ocean model and construct a hydrodynamic-sediment coupled numerical model. The representative tropical cyclone sample set is input into the hydrodynamic sediment coupled numerical model to obtain basic operational data. Based on the basic operational data, the spatial distribution of net sediment transport is calculated, and the sediment transport boundary range is delineated. The representative tropical cyclone sample set is adjusted in parameters and its path is shifted to obtain the shift path. Based on the adjusted parameters and the shift path, the hydrodynamic and sediment coupling numerical model is used to obtain the scour and sedimentation change distribution data and extract the scour and sedimentation early warning boundary for future scenarios. Based on the collected nearshore marine core storm sedimentary record data, the number of tropical cyclone depositions was determined, the percentage of sedimentary record preservation potential was generated, and high-potential areas were extracted. By integrating the sediment transport boundary, the future scenario erosion and sedimentation warning boundary, and the high-potential area, the influence boundary of typhoon spatiotemporal changes in nearshore waters is constructed.

2. The method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters according to claim 1, characterized in that, The extracted tropical cyclone center data is as follows: The tropical cyclone center data is extracted from the historical tropical cyclone track data. The tropical cyclone center data includes longitude, latitude, central pressure, maximum wind speed near the center, and radius of maximum wind speed. The specific steps for generating a representative tropical cyclone sample set include: Using the wind field formula, the theoretical wind speed at each grid point in the spatial grid matrix of the sea area is calculated based on the obtained tropical cyclone center data; A preset wind speed threshold is obtained as the disaster-causing wind speed threshold. Each target grid point in the spatial wind speed distribution field is traversed to determine whether the theoretical wind speed at the location of the target grid point is greater than or equal to the preset wind speed threshold. If a historical tropical cyclone has a target grid point in the spatial grid matrix of the sea area with a theoretical wind speed greater than or equal to the disaster-causing wind speed threshold, the corresponding historical tropical cyclone is extracted, and all the extracted corresponding historical tropical cyclones are combined to generate the representative tropical cyclone sample set.

3. The method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters according to claim 1, characterized in that, The steps for establishing an unstructured mesh finite volume ocean model and constructing a hydrodynamic-sediment coupled numerical model specifically include: Establish a model computation domain covering the nearshore waters of the target area, and configure the model range to cover the coastal boundary of the area to be studied; According to the grid size distribution rule that gradually increases from the nearshore area to the offshore area, an unstructured triangular grid is divided in the computational domain of the model; Based on the divided unstructured triangular mesh, the operation mechanism of the ocean model in the finite volume region of the unstructured mesh is configured to perform calculations by solving the three-dimensional Navier-Stokes equations and coupling a wave model. Configure open boundary conditions and environmental forcing field data into the unstructured mesh finite volume region ocean model to drive the operation of the unstructured mesh finite volume region ocean model; The parameters of the unstructured grid finite volume marine model were validated by combining measured hydrological and sediment data after operation, and the hydrodynamic and sediment coupled numerical model suitable for the target sea area was generated.

4. The method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters according to claim 3, characterized in that, The operational mechanism of the unstructured mesh finite volume ocean model is to perform calculations by solving the three-dimensional Navier-Stokes equations and coupling them with a wave model. The specific steps include: The core computing engine of the configuration model system solves the three-dimensional Navier-Stokes equations, adopts the hydrostatic pressure approximation mechanism and uses σ coordinate system transformation to process vertical terrain; Based on the processed vertical terrain, the governing equations of the three-dimensional hydrodynamic model are configured, and the parameters of the vertical mixing process are calculated by coupling a turbulent closed model in the vertical dimension. At the level of sediment dynamics, the suspended sediment transport and diffusion equations are configured to deduce the dynamic process of sediment suspension and sedimentation in water bodies, and the SWAN wave model is coupled to calculate the evolution of wave energy spectrum and the generation and dissipation process of wind waves.

5. The method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters according to claim 3, characterized in that, The representative tropical cyclone sample set is input into the hydrodynamic-sediment coupled numerical model to obtain the basic operational data. Based on the basic operational data, the spatial distribution of net sediment transport is calculated. The specific steps include: The hydrodynamic-sediment coupling numerical model was used to simulate the basic environment without tropical cyclone wind field and the representative tropical cyclone sample set with tropical cyclone wind field, respectively, and the corresponding flow velocity data, sediment concentration data, bed shear stress data and foundation scour and deposition change distribution data were obtained as the basic operation data. For the acquired flow velocity data, a low-pass filter is used to eliminate the periodic tidal effects in the flow velocity data and extract the residual flow vector; The residual flow vector at each time point is decomposed into mutually perpendicular horizontal orthogonal components of the residual flow. Execute the time node alignment logic of multi-source data to extract the sediment content data that has a synchronous timestamp with the residual flow vector; The extracted horizontal orthogonal components of the residual flow at each time point are multiplied with the corresponding sediment concentration data; Within the set typhoon impact period, the product results obtained from the multiplication calculation are accumulated and synthesized to obtain the sediment transport volume corresponding to the horizontal orthogonal component of the residual flow. The set typhoon impact period covers the complete meteorological record time span from the tropical cyclone entering the model calculation domain to leaving or dissipating. The sediment transport amounts of each of the orthogonal components of the residual flow level are vector synthesized to calculate the spatial distribution of the net sediment transport amount.

6. The method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters according to claim 1, characterized in that, The specific steps for delineating the sediment transport boundary are as follows: By comparing the sediment transport direction and magnitude of each grid point in the marine spatial grid matrix under simulated conditions without and with tropical cyclone wind fields, the outermost envelope of the grid points whose sediment transport magnitude under the tropical cyclone wind field condition is greater than that under the condition without tropical cyclone wind field is extracted and defined as the sediment transport boundary range.

7. The method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters according to claim 2, characterized in that, The specific steps for adjusting parameters and shifting the path of the representative tropical cyclone sample set to obtain the shift path include: Obtain the preset wind speed increase ratio corresponding to the preset temperature increase value; Extract the maximum wind speed near the center from the representative tropical cyclone sample set, and adjust the maximum wind speed near the center by combining it with the preset wind speed increase ratio to obtain the adjusted maximum wind speed of the tropical cyclone. The adjusted tropical cyclone center pressure is calculated using the following empirical correspondence to complete the parameter adjustment: the adjusted maximum wind speed of the tropical cyclone is equal to the first fitting coefficient multiplied by the second fitting coefficient power of the pressure difference between the preset background atmospheric pressure and the adjusted tropical cyclone center pressure. The spatial distribution centroid of each tropical cyclone sample within the tropical cyclone sample set was calculated using the mass moment method. The average value of the latitude and longitude variation data of the centroid over a long time series is used as the translation step size. Tropical cyclones with latitudinal or longitude migration as the main migration trajectory are taken as the migration research objects of the corresponding dimensions. Based on the calculated translation step size, multiple different translation tier scenarios including the original path are configured. The translation tier scenarios are obtained by increasing the translation step size step by step. Based on the multiple translation tier scenarios, spatial coordinate translation operations are performed on the original path to obtain the translation path corresponding to each translation scenario.

8. The method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters according to claim 7, characterized in that, The steps for obtaining scour and deposition change distribution data using the hydrodynamic-sediment coupling numerical model based on the adjusted parameters and the translation path, and extracting future scenario scour and deposition early warning boundaries, are as follows: The adjusted maximum wind speed of the tropical cyclone, the adjusted central pressure of the tropical cyclone, and the obtained translation path are sequentially imported into the hydrodynamic sediment coupling numerical model to drive the hydrodynamic sediment coupling numerical model to simulate the scour and sedimentation depth of the sea area. The scour and sedimentation change distribution data are obtained by subtracting the scour and sedimentation depth simulation results before parameter adjustment and path translation from the simulation results after parameter adjustment and path translation. The outer contour of the region where the scour and siltation change distribution data is greater than 0 or the preset effective scour and siltation tolerance value is extracted as the future scenario scour and siltation early warning boundary.

9. The method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters according to claim 1, characterized in that, Based on the collected nearshore marine core storm sedimentary record data, the number of tropical cyclone depositions is determined, the percentage of the sedimentary record preservation potential is generated, and the high-potential areas are extracted. The specific steps include: Align the time span corresponding to the core storm deposition record data with the time span of the instrument recording in the acquired regional wind field data; Based on the alignment of time spans, and combined with the specific latitude and longitude coordinates of the core storm sedimentary records collected in the nearshore sea area, the number of instrument measurement records that the wind speed at the specific latitude and longitude coordinates reached the disaster-causing wind speed threshold is extracted from the regional wind field data. Core stratigraphic units are divided according to a preset thickness standard, and grain size index data and elemental material index data are extracted from each core stratigraphic unit. Identify and determine that the layers with coarsening grain size and the layers with abrupt changes in the elemental material index data are tropical cyclone sedimentary layers, obtain the number of tropical cyclone sediments per year, and count the number of tropical cyclone sediments identified within the stratigraphic year. Calculate the ratio of the number of tropical cyclone depositions to the number of instrumental records to generate the percentage of the deposition record preservation potential; The percentage of sediment record preservation potential is standardized, and the sea areas with standardized values ​​greater than a set benchmark value are defined as high-potential areas.

10. The method for determining the boundary of the impact of typhoon spatiotemporal variations on nearshore waters according to claim 1, characterized in that, The steps of integrating the sediment transport boundary, the future scenario erosion and deposition warning boundary, and the high-potential area to construct the impact boundary of typhoon spatiotemporal changes in nearshore waters specifically include: The spatial distribution data of the sediment transport boundary, the future scenario erosion and deposition warning boundary, and the high-potential area are uniformly converted to the same standard geographic coordinate projection system to perform spatial coordinate registration and layer overlay. The influence boundary is constructed by taking the sediment transport boundary as the current baseline boundary, the future scenario erosion and sedimentation early warning boundary as the future planning early warning boundary, and the outer edge of the high-potential area as the key protection boundary.

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