A method and system for simulating sediment erosion and deposition considering meteorological forcing and multi-source tracing

Abstract

This invention discloses a method and system for simulating sediment erosion and deposition considering meteorological forcing and multi-source tracing. It relates to the fields of sedimentary dynamics and numerical simulation in estuarine delta rivers, estuarine and coastal areas. The method includes the following steps: Step 1: Acquire driving data and measured data; Step 2: Establish a wave model for the target area; Step 3: Establish a hydrodynamic-wave model for the target area; Step 4: Set sediment composition classifications for the target area: inflow boundary sediment is classified as Class I, channel bed sediment as Class II, and estuarine and coastal bed sediment as Class III; Step 5: Establish a hydrodynamic-wave-sediment model for the target area; Step 6: Validate the coupled model based on measured data; Step 7: Quantitatively output the multi-source sediment distribution, suspended sediment content distribution, and bed sediment erosion and deposition changes throughout the entire river-estuary-coastal process. This invention can reflect the transport paths and dynamic changes in source-sink fluxes of sediments from different sources.

Description

Technical Field

[0001] This invention relates to the field of sedimentary dynamics and numerical simulation technology of estuary delta rivers flowing into the sea, estuaries and coasts, and particularly to a method and system for simulating sediment erosion and deposition that considers meteorological forcing and multi-source tracing. Background Technology

[0002] The estuary-coastal region is the core area of ​​land-sea dynamic interaction, and the suspension, transport, and deposition processes of sediment are the fundamental driving forces shaping the evolution of estuarine delta landforms. In recent years, with the frequent occurrence of extreme weather and climate events, the impact of large-scale meteorological forcing such as strong winds, precipitation, air pressure, and radiation on the complex multiphysics dynamic response of the estuarine and coastal zones has become increasingly significant. Traditional numerical models usually only consider the unidirectional or bidirectional effects of water flow and sediment, or only introduce a single wind field drive, making it difficult to accurately characterize the baroclinic effect and real response mechanism of large-scale hydrodynamics in the estuary under meteorological stress.

[0003] Furthermore, sediment sources in estuarine and coastal areas are complex, typically including riverine sediment transport, resuspended sediment from the riverbed, and offshore sediment from shallow waters. In previous sediment simulations, sediment from different sources was often treated uniformly during mixing, transport, and alternating scouring and deposition. Traditional transport models struggled to rigorously distinguish and trace the specific sources and transport paths of each sediment component within the system, leading to a "vague labeling" problem. This simplistic approach significantly limits the precise quantification of dynamic fluxes between sediment sources and sinks, failing to meet the in-depth analytical needs of modern coastal engineering for source-tracing scouring and deposition mechanisms.

[0004] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a sediment erosion and deposition simulation method that considers meteorological forcing and multi-source tracing. This method is applicable to river channels, estuaries, and coastlines, and solves the labeling ambiguity problem in the mixed transport and interactive erosion and deposition process of multi-source sediments. It can reflect the transport paths and dynamic changes in source-sink flux of sediments from different sources.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A method for simulating sediment erosion and deposition considering meteorological forcing and multi-source tracing includes the following steps: Step 1: Obtain the driving data and measured data of the target area, and preprocess the driving data; Step 2: Establish a wave model for the target area based on the WWM model, drive and run the wave model, and calculate the wave parameters for the target area by combining the offshore boundary conditions; Step 3: Establish a hydrodynamic-wave model for the target area based on the SCHISM-WWM two-way coupling model. Combine the influence of meteorological factors on hydrodynamics and the wave-current coupling effect to calculate the hydrodynamic parameters of the target area. Step 4: Based on the requirements of multi-source tracing, set the sediment composition classification of the target area: sediment at the inflow boundary is classified as Class I, sediment at the riverbed is classified as Class II, and sediment at the estuary and coast is classified as Class III, with 3 particle sizes set for each. Step 5: Based on the SCHISM-WWM-SED3D model, establish a hydrodynamic-wave-sediment model for the target area, and calculate the sediment parameters of the target area by combining the measured data. Step 6: Validate the coupled model based on measured data to obtain the hydrodynamic-wave-sediment model affected by meteorological forcing; Step 7: Input the initial data into the hydrodynamic-wave-sediment model and run it to quantitatively output the multi-source sediment distribution, suspended sediment content distribution, and bed sediment erosion and deposition changes throughout the entire process of river channel-estuary-coast.

[0007] Furthermore, in step 1, the riverbanks and coastlines of the target area are extracted using the GEE platform, attributes are defined, and river inflow boundaries, ocean open boundaries, land boundaries, and island boundaries are set. Then, unstructured triangular meshes are generated using mesh generation software, with the mesh resolution smoothly transitioning from meter-level for rivers, estuaries, and coastlines to hundred-meter-level to kilometer-level for the open sea.

[0008] Furthermore, in step 2, wind field data provided by ERA5 global meteorological reanalysis data is used as the driving force, combined with open boundary conditions in the open sea, to run a wave model and calculate the wave parameters of the target area; specifically, the basic governing equations of the wave model in the Cartesian coordinate system are: ; in, N(x,y,fru,θ,t) The wave action spectral density is defined as N = E / fru. Let fru be the wave energy spectral density, and fru be the natural frequency. For wave direction, x The x-axis is... y The vertical axis is , t For time, These represent the propagation speeds of waves in the x and y directions, respectively, in geographic space. c gx For wave speed at The directional component, U, is the water flow velocity in The velocity component in the direction, c gy For the wave speed at The directional component, V, is the water flow velocity in... The velocity component in the direction, cfru c θ These represent the propagation speeds in the frequency and directional domains of the spectral space, respectively, which control the frequency shift caused by changes in water depth and the flow field, as well as wave refraction. The total source and sink terms are calculated using the following formula: ; in, For wind energy input, This is a nonlinear wave-wave interaction term. For whitening dissipation term, For shallow water wave-breaking dissipation term, This is a low-friction dissipation term.

[0009] Furthermore, in step 3, considering the forcing effect of meteorological factors, wave parameters are used to drive waves, and water depth data is combined with the SCHISM model to... Configure the hydrodynamic-wave model in coordinate system, solve the continuity and momentum equations of the hydrodynamic-wave model, and simulate the tidal propagation and wave-current coupling processes; specifically, the continuity equation of the hydrodynamic-wave model is: ; ; in, For the Hamiltonian operator on the horizontal plane, U and v are the fluid velocities in the x and y directions, respectively. For fluid in Flow velocity in the direction; The momentum equation for the hydrodynamic-wave model is: ; ; in, The mass derivative represents the total acceleration of the fluid particles. For combined external force terms; It is a positive pressure gradient force. For vertical mixing / viscous terms, It is a nonlinear quadratic resistance term; Coriolis force, It is the baroclinic pressure gradient force. This is the atmospheric pressure gradient force. For tidal force, For horizontal viscosity, "other" includes wave radiation stress; Wave radiation stress is: ; ; in, The total mass of the water column per unit horizontal surface area. These represent the effects caused by wave motion along the coast. and Additional normal stress flux in the direction, For shear stress flux; In step 3, the SCHISM model uses a unified three-dimensional convection-diffusion conservative equation to solve for seawater temperature and salinity; specifically, its standard governing equations are as follows: Temperature equation: ; Salinity equation: ; Equations of state: ; in, For seawater temperature, For seawater salinity, The vertical heat / salt diffusion coefficient is... For the temperature-salinity level diffusion term, For radiative heat source term, The density of seawater, seawater salinity Seawater temperature Seawater pressure The function.

[0010] Furthermore, in step 4, component I represents the inflow boundary sediment, which includes fine particles, medium particles, and coarse particles in the inflow. Fine, medium, and coarse particles are classified according to their radius. In terms of boundary control, concentration curves of these three types of sediment over time need to be set at the inflow boundary of the upstream river. In terms of bed control, the mass fraction of these three types of sediment in the initial matrix of the entire bed needs to be set to 0. Class II components represent riverbed sediments, including fine sand, medium sand, and coarse sand. The fine, medium, and coarse sands are classified according to their radius. For boundary control, the concentration of these three types of sediments at the inflow boundary must be kept constant at 0. For bed control, the mass fraction of these three types of sediments is initialized only within the grid in the river region, while in the estuary and marine areas, the mass fraction of these three types of sediments must be set to 0. Class III components represent sediments in the estuary and marine areas, including fine sand, medium sand, and coarse sand in marine shoals. The fine, medium, and coarse sands are classified according to their radius. In terms of boundary control, the concentration of these three types of sediments at the inflow boundary must be kept constant at 0. In terms of substrate control, the mass fraction of these three types of sediments is initialized only in the grid area of ​​the estuary and coastline, while in inland waterways, the mass fraction of these three types of sediments must be set to 0.

[0011] Furthermore, in step 5, hydrodynamic parameters considering the effects of meteorological forcing and wave-current coupling are used as the hydrodynamic driver. Combined with the sediment concentration at the inflow boundary and the sediment mass fraction at the bottom surface as defined in step 4, the model configuration is completed based on SCHISM-WWM-SED3D. Specifically, the suspended volume fraction of various sediment components... The three-dimensional convection-diffusion transport equations satisfied are as follows: ; in, C i For the first i Instantaneous concentration of sediment-like components, u,v,w For fluid in x,y,z Flow velocity in direction For the first i The settling velocity of sediment-like materials, K h ,K v denoted as the turbulent eddy diffusion coefficient in the horizontal and vertical directions. Q si For source and sink items.

[0012] Furthermore, in step 5, at the substrate boundary, the erosion flux... E i The calculation formula is as follows: ; in, E 0,i This is the substrate stripping rate coefficient. For the bed porosity, bed_frac i,l For the first i The percentage by mass of sediment in the outermost layer of the substrate. For the first i Critical erosion shear stress for silt-like sediments The actual shear stress at the bottom layer generated by wave-current coupling or pure flow; sedimentation flux D i The calculation formula is as follows: ; in, Ci,b For the bottom water body grid i Calculated concentration of sediment-like material; Vertical net sedimentation flux between bottom water and the substrate J net,i The calculation formula is as follows: .

[0013] Furthermore, in step 6, the measured data includes measured wave data, measured tidal level and flow velocity and direction data, measured suspended sediment concentration and bed scouring and deposition data; the wave parameters output by the wave model are compared with the measured wave data to complete the parameter calibration of the wave model; the hydrodynamic parameters output by the hydrodynamic model are compared with the measured tidal level and flow velocity and direction data to complete the parameter calibration of the hydrodynamic model; the sediment parameters output by the sediment model are compared with the measured suspended sediment concentration and bed scouring and deposition data to complete the parameter calibration of the sediment model.

[0014] Furthermore, in step 7, the initial conditions of the hydrodynamic-wave-sediment model are determined, including meteorological forcing factors, initial water depth, initial suspended sediment concentration field, initial temperature and salinity field, initial bed composition, and bed surface roughness. After preprocessing the data of the initial conditions, they are input into the hydrodynamic-wave-sediment model to drive the model to run and output the multi-source sediment distribution, suspended sediment content distribution, and bed sediment erosion and deposition changes of the entire process from river channel to estuary to coastline. This provides a basis for clarifying the transport paths of sediment from different sources and the dynamic changes of source-sink flux, and improving the simulation accuracy of sediment erosion and deposition in river deltas.

[0015] To achieve the above objectives, the present invention adopts the following technical solution: A sediment erosion and deposition simulation system considering meteorological forcing and multi-source tracing, used to execute the method provided by this invention, includes: Module 1: Acquire the driving data and measured data of the target area, and preprocess the driving data; The second module: Based on the WWM model, a wave model of the target area is established, the wave model is driven and run, and the wave parameters of the target area are calculated by combining the offshore boundary conditions; The third module: Based on the SCHISM-WWM two-way coupling model, a hydrodynamic-wave model of the target area is established. Combining the influence of meteorological factors on hydrodynamics and the wave-current coupling effect, the hydrodynamic parameters of the target area are calculated. Module 4: Based on the requirements of multi-source tracing, the sediment composition of the target area is classified as follows: sediment at the inflow boundary is classified as Class I, sediment at the riverbed is classified as Class II, and sediment at the estuary and coast is classified as Class III, with three particle sizes set for each. Module 5: Based on the SCHISM-WWM-SED3D model, establish a hydrodynamic-wave-sediment model for the target area, and calculate the sediment parameters of the target area by combining measured data. Module 6: Based on measured data, the coupled model is validated to obtain a hydrodynamic-wave-sediment model affected by meteorological forcing; Module 7: Input the initial data into the hydrodynamic-wave-sediment model for operation, and quantitatively output the multi-source sediment distribution, suspended sediment content distribution, and bed sediment erosion and deposition changes throughout the entire process of river channel-estuary-coast.

[0016] Compared with the prior art, the beneficial effects of this invention are as follows: 1. A deeply coupled driving framework encompassing seven key elements—wind, pressure, temperature, humidity, radiation, and precipitation—was constructed, significantly improving the model's simulation accuracy of meteorological dynamic responses. Compared to traditional methods relying solely on a single wind field, this approach transforms various meteorological elements into baroclinic gradient forces, atmospheric pressure gradient forces, and surface shear stresses within the hydrodynamic equations, achieving real-time coordination between meteorological stress and tides and circulation. This all-physics-driven mechanism effectively captures the complex nonlinear dynamic responses of estuarine and coastal zones under extreme weather conditions, reducing simulation errors caused by missing driving information.

[0017] 2. An innovative multi-source tracing mechanism covering the entire process from river channel to estuary to coastline was constructed. By rigorously labeling sediments from different sources into three categories and nine independent tracer components, and maintaining the independence of their dynamic properties during parallel computation, the "label ambiguity" problem of tracing the source of multi-source sediments during mixing, transport, and interactive scouring and deposition was completely solved. This mechanism enables refined quantification of the transport paths, proportions, and dynamic fluxes of sediments from different sources, providing a scientific basis for source tracing in marine engineering planning and environmental governance.

[0018] 3. A fully coupled two-way dynamic feedback mechanism integrating meteorological forcing, hydrodynamics, waves, and sediment has been achieved. The dynamic bed elevation changes caused by the calculated sediment scouring and deposition flux can be fed back to the hydrodynamic and wave models in real time as bottom boundary conditions, forming a physically closed-loop feedback mechanism. This mechanism ensures the consistency between the dynamic field and the material field during the evolution process, overcomes the limitation of traditional one-way coupled models in reproducing the sediment evolution process under complex and highly disturbed environments, and significantly improves the stability and reliability of long-term simulations. Attached Figure Description

[0019] Figure 1 A flowchart of a sediment erosion and deposition simulation method that considers weather forcing and multi-source tracing; Figure 2The tide level verification results for Station 1 (located at Dayao Bay, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 3 The results of tide level verification at two tide gauge stations (located at Tiger Beach, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 4 The results of tide level verification at three tide gauge stations (located in Bayuquan, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 5 The results of tide level verification at four tide gauge stations (located in Jinzhou Bay, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 6 The results of tide level verification at 5 tide gauge stations (located in Qinhuangdao, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 7 The results of tide level verification at 6 tide gauge stations (located in Tanggu, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 8 The results of tide level verification at 7 tide gauge stations (located in the outer sea of ​​Chengkou, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 9 The results of tide level verification at 8 tide gauge stations (located at Wong Wah Port, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 10 The results of tide level verification at 9 tide gauge stations (located at the mouth of Wanwangou, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 11 The results of tide level verification at 10 tide gauge stations (located in Dongying Port, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 12 The results of tide level verification at 11 tide gauge stations (located in Weifang Port, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 13 The results of tide level verification at 12 tide gauge stations (located in Laizhou Port, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 14The results of tide level verification at 13 tide gauge stations (located in Longkou, with a correlation coefficient r = 0.9800 and a time range of 2018.11.01-00 to 2018.11.04-23); Figure 15 The results of tide level verification at 14 tide gauge stations (located in Penglai, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 16 The results of tide level verification at 15 tide gauge stations (located on Tuoji Island, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 17 The results of tide level verification at 16 tide gauge stations (located on Beihuangcheng Island, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 18 The results of tide level verification at 17 tide gauge stations (located in Yantai, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 19 The results of tide level verification at 18 tide gauge stations (located in Weihai, with a time range of 2018.11.01-00 to 2018.11.04-23); Figure 20 The flow rate verification result for site A; Figure 21 The flow verification results for site A; Figure 22 The flow rate verification result for site B; Figure 23 The flow verification result for site B; Figure 24 The flow rate verification result for site C; Figure 25 The flow verification result for site C; Figure 26 This is the result of valid wave height verification; Figure 27 The results are used to verify the average wave height. Figure 28 Results for suspended sediments driven by different dynamic forces; Figure 29 The simulation results and overall distribution results of sediment source erosion and deposition transport are presented. Detailed Implementation

[0020] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0021] Example 1: A method for simulating sediment erosion and deposition that considers meteorological forcing and multi-source tracing, such as Figure 1 As shown, it includes the following steps: Step 1: Obtain the driving data and measured data of the target area, and preprocess the driving data.

[0022] In this embodiment, in step 1, the driving data may include: water depth data, bed elevation, and meteorological reanalysis data; the offshore water depth data uses ETOPO data; the river and nearshore water depth data uses self-measured data; the bed elevation mainly includes offshore water depth data and coastal river channel data, wherein the offshore water depth data uses ETOPO data, and the coastal river channel data uses measured data interpolation. The elevation data can be interpolated to the unstructured grid nodes of the study area for use in the three-dimensional hydrodynamic calculation of the study area; the meteorological reanalysis data uses the ERA5 reanalysis dataset provided by ECMWF, which includes: 10 meters The data includes seven meteorological factors: zonal and meridional wind components, mean sea level pressure correction, air temperature at 2 meters above the surface, specific humidity at 2 meters above the surface, long / shortwave radiation flux downwards from the surface, and surface precipitation rate. Measured data may include: measured inflow flow at the open boundary, measured sediment content, measured tidal level, measured flow velocity and direction, measured suspended sediment concentration, and sediment scouring and deposition data from the bed. Since the collected driving data may not be in grid coordinates, step 1 involves preprocessing the driving data using Kriging interpolation to interpolate the data to the coordinates of unstructured grid nodes.

[0023] In this embodiment, in step 1, the riverbanks and coastlines of the target area are extracted using the GEE (Google Earth Engine) platform, and attributes are defined, setting river inflow boundaries, ocean open boundaries, land boundaries, and island boundaries. Then, grid generation software (such as SMS) is used to generate unstructured triangular grids. The grid resolution smoothly transitions from meter-level for rivers, estuaries, and coastlines to hundred-meter-level to kilometer-level for the open sea. Unstructured grids can better fit the coastline distribution and improve the resolution of the shoreline.

[0024] Step 2: Establish a wave model for the target area based on the WWM model (third-generation spectral wave model), drive and run the wave model, and calculate the wave parameters of the target area in combination with the offshore boundary conditions.

[0025] The WWM model can simulate wind-generated surface gravity waves and their interaction with ocean currents and the environment. It solves the wave action equilibrium equations and provides wave parameters and wave-induced forces for the components of the hydrodynamic model. In this embodiment, in step 2, a wave model of the target region is constructed by integrating the WWM model into the SCHISM model (semi-implicit multi-scale ocean model) framework. Waves are generated through wind-wave interaction. The WWM model is configured via a file, mainly including: basic parameters, coupling options, mesh settings, initial and boundary conditions, source terminology selection, numerical scheme, and output control.

[0026] In this embodiment, in step 2, the wind field data (including zonal and meridional wind components at 10-meter height, pressure correction at mean sea level, air temperature at 2-meter height, specific humidity at 2-meter height, long / shortwave radiation flux downwards from the surface, and surface precipitation rate) provided by ERA5 global meteorological reanalysis data is used as the driving force. Combined with the open boundary conditions of the open sea (the open sea boundary conditions refer to a section of the open sea boundary line, not a region, but a parameterized wave spectrum applied at the open sea boundary, which is the driving wave boundary forcing condition), the wave model is run to calculate the wave parameters of the target area.

[0027] In this embodiment, in step 2, the basic governing equations of the wave model in the Cartesian coordinate system are: ; in, N(x,y,fru,θ,t) The wave action spectral density is defined as N = E / fru. Let fru be the wave energy spectral density, and fru be the natural frequency. The x-axis represents the wave direction, the y-axis represents the horizontal axis, and the t-axis represents time. These represent the propagation speeds of waves in the x and y directions in geographic space (including the superposition of group velocity and flow velocity). c gx For wave speed at The directional component, U, is the water flow velocity in The velocity component in the direction, c gy For the wave speed at The directional component, V, is the water flow velocity in... The velocity component in the direction, c fru c θ These represent the propagation speeds in the frequency and directional domains of the spectral space, respectively, which control the frequency shift caused by changes in water depth and the flow field, as well as wave refraction. The total source and sink term represents the generation, dissipation, and transfer of wave energy. The calculation formula is: ; in, For wind energy input, This is a nonlinear wave-wave interaction term. For whitening dissipation term, For shallow water wave-breaking dissipation term, This represents the low-friction dissipation term. Solving this term yields the effective wave height, wave period, wave direction, radiation stress tensor, and bottom friction forcing of the target region.

[0028] Step 3: Establish a hydrodynamic-wave model for the target area based on the SCHISM-WWM two-way coupling model. Combine the influence of meteorological factors on hydrodynamics and the wave-current coupling effect to calculate the hydrodynamic parameters of the target area.

[0029] In this embodiment, in step 3, a hydrodynamic-wave model of the target area is constructed by integrating the WWM model into the SCHISM model framework.

[0030] In this embodiment, in step 3, the seven meteorological factors of the meteorological reanalysis data are embedded into the continuity equation and momentum equation through the water surface boundary and the internal source term depth to construct a momentum, heat and mass synergistic coupling network. Specifically: In the momentum-driven layer, the zonal and meridional wind components at a height of 10 meters are transformed into surface wind stress through air-water interface friction and nonlinearly transfer momentum. The mean sea level pressure correction value induces the inverse barometer effect through the horizontal pressure gradient force, synergistically driving macroscopic wind currents and storm surges. In the thermodynamic baroclinic layer, the air temperature at a height of 2 meters above the ground, the specific humidity at a height of 2 meters above the ground, and the long / shortwave radiation flux downward from the surface jointly determine the net heat flux. Shortwave radiation also decays exponentially with depth to construct a non-uniform temperature field, which is transformed into a spatial density difference through the equation of state, forming a baroclinic gradient force in the gravity field to drive stratified flow and density current. In the mass and composition regulation layer, the precipitation rate, as the boundary material flux, enters the continuity equation to fine-tune the water level and dilute the surface component concentration to trigger density stratification and regulate sediment settling velocity. Finally, the nonlinear full coupling of momentum, heat, and mass is achieved in a unified numerical discrete solution matrix.

[0031] In this embodiment, in step 3, the wave is driven by wave parameters, taking into account the forcing effect of meteorological factors, and based on the SCHISM model using water depth data, in... Configure the hydrodynamic-wave model in coordinate system, solve the continuity and momentum equations of the hydrodynamic-wave model, and simulate the tidal propagation and wave-current coupling processes; specifically, the continuity equation of the hydrodynamic-wave model is: ; ; in, The Hamiltonian operator (gradient / divergence operator) on the horizontal plane. U and v are the fluid velocities in the x and y directions, respectively. For fluid in Flow velocity in the direction.

[0032] The momentum equation for the hydrodynamic-wave model is: ; ; in, The mass derivative represents the total acceleration of the fluid particles. For combined external force terms; It is a positive pressure gradient force. For vertical mixing / viscous terms, It is a nonlinear quadratic resistance term; Coriolis force, It is the baroclinic pressure gradient force. This is the atmospheric pressure gradient force. For tidal force, For horizontal viscosity, "other" includes wave radiation stress. It should be noted that, depending on the meaning of the applicable module, if there is vegetation influence, "other" may also include vegetation resistance.

[0033] Wave radiation stress is: ; ; in, The total mass of the water column per unit horizontal surface area. These represent the effects caused by wave motion along the coast. and Additional normal stress flux in the direction, This represents the shear stress flux.

[0034] In this embodiment, in step 3, the SCHISM model solves for seawater temperature and salinity using a unified three-dimensional convection-diffusion conservative equation; specifically, its standard governing equations are as follows: Temperature equation: ; Salinity equation: ; Equations of state: ; in, For seawater temperature, For seawater salinity, The vertical heat / salt diffusion coefficient is... For the temperature-salinity level diffusion term, For radiative heat source term, The density of seawater, seawater salinity Seawater temperature Seawater pressure The function.

[0035] In this embodiment, in step 3, the SCHISM model employs a set of rigorous three-dimensional equations that conform to the laws of conservation of matter and energy. By simulating the "forced displacement (convection)" of water flow and the "natural mixing (diffusion)" of water, it achieves the monitoring of the overall water temperature. and salinity Highly accurate calculation of succession.

[0036] Step 4: Based on the requirements of multi-source tracing, set the sediment composition classification of the target area: sediment at the inflow boundary is classified as Class I, sediment at the riverbed is classified as Class II, and sediment at the estuary and coast is classified as Class III, with three particle sizes set for each.

[0037] In this embodiment, in step 4, for each of the three source / region types (inflow boundary, channel bed, and estuary coast), a scheme with three particle size options is implemented. This requires setting the total sediment component count to NST = 9 (i.e., 9 tracer components) in the code and input file (sediment.in). Specifically: Class I components represent inflow boundary sediment, including fine inflow particles (ised=1), medium inflow particles (ised=2), and coarse inflow particles (ised=3). Fine, medium, and coarse particles are classified according to their radius. For boundary control, it is necessary to set the concentration curves of these three types of sediment over time at the inflow boundary in the upper reaches of the river (i.e., set the time series values ​​of sediment concentration at the inflow boundary, and C1, C2, C3>0, where C1 is fine particles, C2 is medium particles, and C3 is coarse particles). For bed control, the mass fractions of these three types of sediment in the initial matrix of the entire bed should all be set to 0 [i.e., bed_frac(1:3,:,:) = 0].

[0038] Class II components represent channel bed sediments, including fine channel bed sediments (ised=4), medium channel bed sediments (ised=5), and coarse channel bed sediments (ised=6). Fine, medium, and coarse sediments are classified according to their radius. For boundary control, the concentrations of these three types of sediments at the inflow boundary must be constantly set to 0 (i.e., C4=C5=C6=0, where C4 is fine sediment, C5 is medium sediment, and C6 is coarse sediment). For bed control, the mass fractions of these three types of sediments are initialized only within the grid of the channel area [e.g., bed_frac(4:6, ele) > 0, and the sum of the proportions of each particle size is 1]. In the estuary and marine areas, the mass fractions of these three types of sediments must be set to 0.

[0039] Class III components represent sediments in the estuarine and marine seabed, including fine sand (ised=7), medium sand (ised=8), and coarse sand (ised=9) in marine shoals. The fine, medium, and coarse sands are classified according to their radii. For boundary control, the concentrations of these three types of sediments at the inflow boundary must be kept constant at 0 (i.e., C7=C8=C9=0, where C7 is fine sand, C8 is medium sand, and C9 is coarse sand). For bed control, the mass fractions of these three types of sediments are initialized only in the grid areas of the estuary and coastline [e.g., bed_frac(7:9, ele) > 0], while in inland waterways, the mass fractions of these three types of sediments must be set to 0.

[0040] In this embodiment, the specific discretization and code configuration implementation steps in step 4 are as follows: (1) Modify the basic control numbers in sediment.in: Set the total number of components to 9 (if distinguishing between viscous and non-viscous, set NCS = 3 for viscous, NNS = 6 for non-viscous, and the total number of components NST = 9). For these 9 components, give 9 sedimentation velocities WSED, 9 critical stresses TAU_CE, and 9 peel rates E_RDR respectively.

[0041] (2) Spatial region initialization (modify sed_init.F90 or use an external input file): In the loop that reads the bed initialization code (usually within the sed_init subroutine), establish conditional branches using the coordinates of the grid cells or the region ID: "do ie = 1, ne if (in_river_domain(ie)) then bed_frac(1:3, 1, ie) = 0.0_rkind bed_frac(4:6, 1, ie) = [0.3_rkind, 0.4_rkind, 0.3_rkind] ! Example: Percentage of three particle sizes in Class II bed_frac(7:9, 1, ie) = 0.0_rkind else if (in_estuary_coast_domain(ie)) then bed_frac(1:6, 1, ie) = 0.0_rkind bed_frac(7:9, 1, ie) = [0.2_rkind, 0.5_rkind, 0.3_rkind] ! Example: Percentage of three particle sizes in Class III endif enddo".

[0042] Step 5: Based on the SCHISM-WWM-SED3D model, establish a hydrodynamic-wave-sediment model for the target area, and calculate the sediment parameters of the target area by combining the measured data.

[0043] In this embodiment, in step 5, SED3D refers to a three-dimensional sediment transport model; the measured data includes measured suspended sediment concentration data and sediment scouring and deposition data of the bed.

[0044] In this embodiment, in step 5, hydrodynamic parameters considering the effects of meteorological forcing and wave-current coupling are used as the hydrodynamic driver. Combined with the sediment concentration at the inflow boundary and the sediment mass fraction at the bottom as defined in step 4, the model configuration is completed based on SCHISM-WWM-SED3D. Specifically, the suspended volume fraction (or mass concentration) of various sediment components is used. The three-dimensional convection-diffusion transport equations satisfied are as follows: ; in, C i For the first i Instantaneous concentration of sediment-like components, u,v,w For fluid in x,y,z Flow velocity in direction For the first i The settling velocity of sediment-like materials, K h ,K v denoted as the turbulent eddy diffusion coefficient in the horizontal and vertical directions. Q si For source and sink items.

[0045] In this embodiment, in step 5, the erosion flux at the substrate boundary... E i The calculation formula is as follows: ; in, E 0,i This is the substrate stripping rate coefficient. For the bed porosity, bed_frac i,l For the first i The percentage by mass of sediment in the outermost layer of the substrate. For the first i Critical erosion shear stress for silt-like sediments This refers to the actual shear stress at the bottom layer generated by wave-current coupling or pure flow.

[0046] sedimentation flux Di The calculation formula is as follows: ; in, C i,b For the bottom water body grid i Calculated concentration of sediment-like material.

[0047] In this embodiment, in step 5, the sediment flux depends entirely on the sediment concentration within the water grid cells immediately adjacent to the bottom bed. C i,b With settling velocity; erosion flux E i With sedimentation flux D i The difference determines the flux of sediment.

[0048] Vertical net sedimentation flux between bottom water and the substrate J net,i The calculation formula is as follows: .

[0049] Step 6: Validate the coupled model based on measured data to obtain the hydrodynamic-wave-sediment model affected by meteorological forcing.

[0050] In this embodiment, in steps 2-5, the wind field, air pressure, and thermal parameters output from the reanalysis meteorological data are respectively input into the wave model and the hydrodynamic model. The wave parameters output by the wave model and the hydrodynamic parameters output by the hydrodynamic model are bidirectionally coupled to calculate the combined wave-current bed shear stress, which is then input into the sediment model. The sediment model introduces three types of nine-component multi-source tracer sand boundary conditions and independently calculates the suspended and bedload fluxes of each tracer component. In each calculation time step, the sediment model calculates the bed scour rate, suspended sediment deposition rate, and bedload transport gradient based on the current water flow shear force and wave force. Subsequently, the model calls the classical bed evolution equation (Exner equation) to update the bed elevation. Then, the dynamic bed elevation caused by scour and deposition is fed back to the hydrodynamic model and the wave model in real time as the bottom boundary condition.

[0051] The Exner equation is as follows: ; in, The porosity of the sediment. This refers to the dynamic bed elevation. This refers to the net settling or net flushing flux of suspended matter. The divergence of bedload transport rate.

[0052] In this embodiment, step 6 includes measured wave data, measured tidal level and flow velocity and direction data, measured suspended sediment concentration and bed scouring and deposition data; the wave parameters (effective wave height, wave period) output by the wave model are compared with the measured wave data to complete the parameter calibration of the wave model; the hydrodynamic parameters (tidal level, flow velocity, flow direction) output by the hydrodynamic model are compared with the measured tidal level and flow velocity and direction data to complete the parameter calibration of the hydrodynamic model; the sediment parameters (suspended sediment concentration, bed scouring and deposition changes) output by the sediment model are compared with the measured suspended sediment concentration and bed scouring and deposition data to complete the parameter calibration of the sediment model.

[0053] In this embodiment, in step 6, calibration refers to using measured data and employing correlation coefficients and determination coefficients to determine the goodness of fit between simulated values ​​and measured values, and repeatedly performing parameter calibration until the parameters make the simulation results conform to the actual situation.

[0054] Step 7: Input the initial data into the hydrodynamic-wave-sediment model and run it to quantitatively output the multi-source sediment distribution, suspended sediment content distribution, and bed sediment erosion and deposition changes throughout the entire process of river channel-estuary-coast.

[0055] In this embodiment, step 7 determines the initial conditions of the hydrodynamic-wave-sediment model, including meteorological forcing factors (7 meteorological factors: zonal and meridional wind components at 10-meter height of wind field data, pressure correction value at mean sea level, air temperature at 2-meter height of ground, specific humidity at 2-meter height of ground, long / shortwave radiation flux downward from the surface, and surface precipitation rate), initial water depth, initial suspended sediment concentration field, initial temperature and salinity field, initial bed composition, and bed surface roughness. After preprocessing the initial condition data (interpolation processing), the data is input into the hydrodynamic-wave-sediment model to drive the model operation. The model outputs the multi-source sediment distribution, suspended sediment content distribution, and bed sediment erosion and deposition changes throughout the entire process from river channel to estuary to coastline. This provides a basis for clarifying the transport paths and dynamic changes of source and sink fluxes of sediment from different sources, and improving the simulation accuracy of sediment erosion and deposition in river deltas.

[0056] The working principle of the sediment erosion and deposition simulation method considering meteorological forcing and multi-source tracing in this embodiment is as follows: By introducing meteorological forcing and sediment classification definitions, and based on the SCHISM-WWM-SED3D three-dimensional coupled model, a full-process sediment transport simulation system covering the river channel-estuary-coastal region was constructed. At the dynamic driving level, it overcomes the limitation of traditional models relying solely on a single wind field. By integrating high-precision ERA5 reanalysis data, it integrates seven key elements—wind field, sea-level pressure, surface temperature and humidity, downward shortwave / longwave radiation, and surface precipitation rate—into a dynamic spatiotemporal boundary condition. Through real-time calculation of the interactions between various meteorological elements and the water body, thermal and dynamic stresses are transformed into baroclinic gradient force, atmospheric pressure gradient force, and surface shear stress in the hydrodynamic equations, thus accurately reproducing the nonlinear response mechanism of multi-physics fields in the estuarine and coastal zones under extreme weather conditions. At the transport simulation level, it not only achieves fully coupled real-time bidirectional feedback between wave radiation stress, tidal circulation, and sediment transport, but also innovatively introduces a multi-source sediment tracing mechanism. By "labeling" sediments from different spatial sources (inflow, channel bed, and coastal bed) and setting them as independent tracer components, the system can strictly maintain the source attributes of sediment components during the parallel solution of the three-dimensional convection-diffusion equations, completely solving the "label ambiguity" problem of multi-source sediments in the mixing, transport, and interactive scouring and deposition processes. Through a closed-loop feedback mechanism of "meteorological forced drive - hydrodynamic multi-field coupling - sediment source tracing," it can not only dynamically capture the real-time evolution of bed elevation with sediment flux, but also achieve refined analysis from macroscopic dynamic fields to microscopic sediment source-sink fluxes, significantly eliminating systematic biases caused by parameter simplification or missing tracers. This provides highly reliable numerical simulation support for the forecasting and source tracing analysis of scouring and deposition evolution in estuaries and coastlines under complex dynamic environments.

[0057] The sediment erosion and deposition simulation method of this embodiment, which considers meteorological forcing and multi-source tracing, has the following beneficial effects: 1. A deeply coupled driving framework encompassing seven key elements—wind, pressure, temperature, humidity, radiation, and precipitation—was constructed, significantly improving the model's simulation accuracy of meteorological dynamic responses. Compared to traditional methods relying solely on a single wind field, this approach transforms various meteorological elements into baroclinic gradient forces, atmospheric pressure gradient forces, and surface shear stresses within the hydrodynamic equations, achieving real-time coordination between meteorological stress and tides and circulation. This all-physics-driven mechanism effectively captures the complex nonlinear dynamic responses of estuarine and coastal zones under extreme weather conditions, reducing simulation errors caused by missing driving information.

[0058] 2. An innovative multi-source tracing mechanism covering the entire process from river channel to estuary to coastline was constructed. By rigorously labeling sediments from different sources into three categories and nine independent tracer components, and maintaining the independence of their dynamic properties during parallel computation, the "label ambiguity" problem of tracing the source of multi-source sediments during mixing, transport, and interactive scouring and deposition was completely solved. This mechanism enables refined quantification of the transport paths, proportions, and dynamic fluxes of sediments from different sources, providing a scientific basis for source tracing in marine engineering planning and environmental governance.

[0059] 3. A fully coupled two-way dynamic feedback mechanism integrating meteorological forcing, hydrodynamics, waves, and sediment has been achieved. The dynamic bed elevation changes caused by the calculated sediment scouring and deposition flux can be fed back to the hydrodynamic and wave models in real time as bottom boundary conditions, forming a physically closed-loop feedback mechanism. This mechanism ensures the consistency between the dynamic field and the material field during the evolution process, overcomes the limitation of traditional one-way coupled models in reproducing the sediment evolution process under complex and highly disturbed environments, and significantly improves the stability and reliability of long-term simulations.

[0060] Example 2: A sediment erosion and deposition simulation system considering meteorological forcing and multi-source tracing, for performing the method of Example 1, includes: Module 1: Acquire the driving data and measured data of the target area, and preprocess the driving data; The second module: Based on the WWM model, a wave model of the target area is established, the wave model is driven and run, and the wave parameters of the target area are calculated by combining the offshore boundary conditions; The third module: Based on the SCHISM-WWM two-way coupling model, a hydrodynamic-wave model of the target area is established. Combining the influence of meteorological factors on hydrodynamics and the wave-current coupling effect, the hydrodynamic parameters of the target area are calculated. Module 4: Based on the requirements of multi-source tracing, the sediment composition of the target area is classified as follows: sediment at the inflow boundary is classified as Class I, sediment at the riverbed is classified as Class II, and sediment at the estuary and coast is classified as Class III, with three particle sizes set for each. Module 5: Based on the SCHISM-WWM-SED3D model, establish a hydrodynamic-wave-sediment model for the target area, and calculate the sediment parameters of the target area by combining measured data. Module 6: Based on measured data, the coupled model is validated to obtain a hydrodynamic-wave-sediment model affected by meteorological forcing; Module 7: Input the initial data into the hydrodynamic-wave-sediment model for operation, and quantitatively output the multi-source sediment distribution, suspended sediment content distribution, and bed sediment erosion and deposition changes throughout the entire process of river channel-estuary-coast.

[0061] Verification Example: To verify the accuracy of the river-estuary-coastal sediment erosion and deposition simulation method of the present invention, which considers meteorological forcing and multi-source tracing, this embodiment selects the Yellow River Delta as the study area, uses measured flow and sediment data from the Lijin section to drive the river boundary, and uses the FES2022 tidal model to drive the open sea boundary.

[0062] To verify the reliability of the three-dimensional wave-current coupled hydrodynamic model constructed in Example 1, tide level data from 18 tide gauge stations around the Bohai Sea were selected in the study area and compared with the simulated values ​​for verification. Three observation points, A, B, and C, were selected in the study area to verify the flow velocity and direction. Figure 2-19 , Figure 20-25 , Figure 26-27 The verification results for tidal level, flow velocity, flow direction, and wave parameters are presented, demonstrating the simulation accuracy of the three-dimensional hydrodynamic model.

[0063] Figure 2-19 The fitting results of 18 tide gauge stations show that the calculated tide levels and the measured tide levels generally have good consistency. The simulated and observed tide levels at each station exhibit good consistency in overall trend, rise and fall processes, and phase changes, with correlation coefficients (r) all above 0.94. For most stations, the (r) value exceeds 0.98, and for some stations it even reaches above 0.99, indicating that the model can accurately reproduce the temporal variation characteristics of tide levels in the study area. Overall, all tide gauge stations show high correlation, indicating that the established hydrodynamic model has high accuracy in tidal level simulation and good stability, and can reliably reflect the tidal propagation and tidal level change processes in the study area. This provides a reliable hydrodynamic basis for subsequent flow field analysis, sediment transport simulation, and estuarine hydrodynamic process research.

[0064] Figure 20-25 The fitting results of velocity and direction show that the model captures the periodic variation of the tidal flow very well. In the surface, middle, and bottom layers of the three stations (A, B, and C), the peaks (maximum velocities) and troughs (minimum velocities) of the simulated velocity curves occurred at times that were basically consistent with the actual observation points, with no significant phase lag or lead. The velocity correlation coefficient r reached 0.85–0.93 (mean 0.88), and the skill score s was 0.59–0.85 (mean 0.73). For most of the time period, the simulated curves passed through the observed scatter plots, indicating good overall numerical agreement. The simulation accuracy of the flow direction is even better, with a correlation coefficient r as high as 0.75~0.98 (mean 0.93, and most levels exceeding 0.90), and a skill score s of 0.51~0.94 (mean 0.84). The abrupt change in flow direction between the flood tide and the ebb tide (shown as an almost vertical jump line in the figure) is highly consistent with the turning point of the actual observation point, indicating that the model has extremely accurately grasped the turning point and flow field dynamics of the water area.

[0065] Figure 26-27 The given wave fitting results show that the model is accurate for significant wave heights ( ) and mean wave period ( The simulation yielded excellent results in reproducing the wave's evolution, accurately capturing the complete dynamic characteristics of the wave throughout the 145-hour simulation sequence, from a calm background (0–30 h), growth (30–35 h), peak sustaining (35–75 h), to gradual decay (75–145 h). Specifically, the significant wave height ( The burst growth response was rapid, with extremely high agreement in the peak range (3.0~3.5 m), only slightly overestimated during the decay phase (75~100 h), after which it closely matched the low-wave observations again; the mean wave period ( The starting phase of the rise was accurately captured, and the peak segment (6.5~7.0 s) highly coincided with the measured value. The overall evolution trend was highly consistent with the actual observation.

[0066] To verify the meteorological forcing effect of the method in Example 1, a control simulation was set up, and the simulated values ​​of suspended sediment concentration at three observation points (A, B, and C) within the study area were compared with the observed values ​​for verification. Figure 28 A comparison of results considering and not considering weather forcing is presented, showing that the simulation effect considering weather forcing is better.

[0067] Figure 28 The simulation results of sediment concentration in the bottom layer indicate that meteorological factors play a crucial role in reproducing the spatiotemporal distribution of sediment concentration in water bodies. Without considering meteorological conditions (non-meteorological), the simulated concentrations at all three stations were significantly lower than the observed values; however, the simulation accuracy was greatly improved after introducing meteorological factors. Among them, station B in the bottom layer showed the best fit, with the simulated curve highly overlapping with the observed scatter plots, accurately capturing the concentration of 2.2 kg / m³ around 09:00. 3 The peak concentration; the simulated values ​​at the bottom layer A site (1.0~2.5 kg / m³). 3 The observed pulsation trend is consistent with the observed trend; the bottom-level C station exhibits a clear bimodal variation characteristic under meteorological influence, except for a single observed extreme value (7.3 kg / m³) at 07:00. 3 In addition, the simulated curves reflect the background evolution of sediment concentration in the water body quite well. Overall, the model that takes meteorological conditions into account can accurately reproduce the order of magnitude and dynamic changes of sediment concentration in the bottom layer.

[0068] To verify the multi-source sediment tracing technology of the method in Example 1, a simulated working condition was set up, and the inflow boundary and the sediment composition of the substrate were defined. Figure 29Simulation results and overall distribution results of sediment transport from different sources are presented, which can quantitatively show the distribution composition of sediment from different sources and clarify the source composition of sediment.

[0069] Figure 29 The simulation results tracing sediment sources clearly reveal the spatial differentiation characteristics of inflow sediment and local channel sediment at the mouth. Measurement points 1 and 2 are both located near the mouth, and their sediment source compositions are very similar. At measurement point 1, the inflow boundary accounts for 55.00%, the original channel bed accounts for 20.20%, and the original estuary bed accounts for 24.80%; at measurement point 2, these figures are 54.50%, 19.90%, and 25.60%, respectively. The small difference between the two points indicates that the suspended sediment source structure near the mouth is relatively consistent, still mainly controlled by upstream river sediment transport, while channel bed scouring and estuary bed resuspension also contribute to some extent.

[0070] In contrast, monitoring point 3, located outside the mouth of the river, showed a more pronounced change in sediment source. The proportion of sediment source at the river inflow boundary decreased to 50.50%, the proportion from the original channel bed decreased to 15.30%, while the proportion from the original estuary bed increased to 34.20%. Compared to monitoring point 1, the proportion of river inflow boundary source at monitoring point 3 decreased by 4.50 percentage points, the proportion from the original channel bed decreased by 4.90 percentage points, and the proportion from the original estuary bed increased by 9.40 percentage points. This indicates that during sediment transport from the mouth of the river, the relative influence of direct river input and channel scouring gradually weakens, while the contribution of existing sediment in the estuary region to suspended sediment composition increases after being resuspended by hydrodynamic forces. This suggests that upstream inflow sediment is the dominant source controlling the diffusion of suspended sediment in the open sea, while channel sediment mainly influences the sedimentation evolution of the estuary barrier sand area.

[0071] In view of this, this embodiment discloses a river-estuary-coastal sediment scouring and deposition simulation method that considers meteorological forcing and multi-source tracing. This method integrates the influence of meteorological factors on the momentum equation, transport equation, and state equation to accurately simulate the scouring and deposition transport process of multi-source sediments in river channels, estuaries, and coastlines. It improves the accuracy of suspended sediment concentration simulation, solves the "label ambiguity" problem of difficulty in tracing the source of multi-source sediments in the process of mixed transport and interactive scouring and deposition, and realizes the refined quantification of the transport paths, proportions, and dynamic fluxes of sediments from different sources, providing a scientific source tracing basis for marine engineering planning and environmental governance.

[0072] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for simulating sediment erosion and deposition considering meteorological forcing and multi-source tracing, characterized in that, Includes the following steps: Step 1: Obtain the driving data and measured data of the target area, and preprocess the driving data; Step 2: Establish a wave model for the target area based on the WWM model, drive and run the wave model, and calculate the wave parameters for the target area by combining the offshore boundary conditions; Step 3: Establish a hydrodynamic-wave model for the target area based on the SCHISM-WWM two-way coupling model. Combine the influence of meteorological factors on hydrodynamics and the wave-current coupling effect to calculate the hydrodynamic parameters of the target area. Step 4: Based on the requirements of multi-source tracing, set the sediment composition classification of the target area: sediment at the inflow boundary is classified as Class I, sediment at the riverbed is classified as Class II, and sediment at the estuary and coast is classified as Class III, with 3 particle sizes set for each. Step 5: Establish a hydrodynamic-wave-sediment model for the target area based on the SCHISM-WWM-SED3D model, and calculate the sediment parameters of the target area by combining the measured data. Step 6: Validate the coupled model based on measured data to obtain the hydrodynamic-wave-sediment model affected by meteorological forcing; Step 7: Input the initial data into the hydrodynamic-wave-sediment model and run it to quantitatively output the multi-source sediment distribution, suspended sediment content distribution, and bed sediment erosion and deposition changes throughout the entire process of river channel-estuary-coast.

2. The sediment erosion and deposition simulation method considering meteorological forcing and multi-source tracing as described in claim 1, characterized in that, In step 1, the riverbanks and coastlines of the target area are extracted using the GEE platform, and their attributes are defined. The river inflow boundary, ocean open boundary, land boundary, and island boundary are set. Then, unstructured triangular meshes are generated using mesh generation software. The mesh resolution smoothly transitions from meters for rivers, estuaries, and coastlines to hundreds of meters to kilometers for the open sea.

3. The sediment erosion and deposition simulation method considering meteorological forcing and multi-source tracing as described in claim 1, characterized in that, In step 2, wind field data provided by ERA5 global meteorological reanalysis data is used as the driving force, combined with open boundary conditions in the open sea, to run a wave model and calculate the wave parameters of the target area; specifically, the basic governing equations of the wave model in the Cartesian coordinate system are: ； in, N(x,y,fru,θ,t) The wave action spectral density is defined as N = E / fru. Let fru be the wave energy spectral density, and fru be the natural frequency. For wave direction, x The x-axis is... y The vertical axis is , t For time, These represent the propagation speeds of waves in the x and y directions, respectively, in geographic space. c gx For wave speed at The directional component, U, is the water flow velocity in The velocity component in the direction, c gy For the wave speed at The directional component, V, is the water flow velocity in... The velocity component in the direction, c fru c θ These represent the propagation speeds in the frequency and directional domains of the spectral space, respectively, which control the frequency shift caused by changes in water depth and the flow field, as well as wave refraction. The total source and sink terms are calculated using the following formula: ； in, For wind energy input, This is a nonlinear wave-wave interaction term. For whitening dissipation term, For shallow water wave-breaking dissipation term, This is a low-friction dissipation term.

4. The sediment erosion and deposition simulation method considering meteorological forcing and multi-source tracing as described in claim 1, characterized in that, In step 3, considering the forcing effect of meteorological factors, wave parameters are used to drive waves. Combined with water depth data, and based on the SCHISM model, in... Configure the hydrodynamic-wave model in coordinate system, solve the continuity and momentum equations of the hydrodynamic-wave model, and simulate the tidal propagation and wave-current coupling processes; specifically, the continuity equation of the hydrodynamic-wave model is: ； ； in, For the Hamiltonian operator on the horizontal plane, U and v are the fluid velocities in the x and y directions, respectively. For fluid in Flow velocity in the direction; The momentum equation for the hydrodynamic-wave model is: ； ； in, The mass derivative represents the total acceleration of the fluid particles. For combined external force terms; It is a positive pressure gradient force. For vertical mixing / viscous terms, It is a nonlinear quadratic resistance term; Coriolis force, It is the baroclinic pressure gradient force. This is the atmospheric pressure gradient force. For tidal force, For horizontal viscosity, "other" includes wave radiation stress; Wave radiation stress is: ； ； in, The total mass of the water column per unit horizontal surface area. These represent the effects caused by wave motion along the coast. and Additional normal stress flux in the direction, For shear stress flux; In step 3, the SCHISM model uses a unified three-dimensional convection-diffusion conservative equation to solve for seawater temperature and salinity; specifically, its standard governing equations are as follows: Temperature equation: ； Salinity equation: ； Equations of state: ； in, For seawater temperature, For seawater salinity, The vertical heat / salt diffusion coefficient is... For the temperature-salinity level diffusion term, For radiative heat source term, The density of seawater, seawater salinity Seawater temperature Seawater pressure The function.

5. The sediment erosion and deposition simulation method considering meteorological forcing and multi-source tracing as described in claim 1, characterized in that, In step 4, component I represents the inflow boundary sediment, which includes fine particles, medium particles, and coarse particles in the inflow. Fine, medium, and coarse particles are classified according to their radius. In terms of boundary control, concentration curves of these three types of sediment over time need to be set at the inflow boundary of the upstream river. In terms of bed control, the mass fraction of these three types of sediment in the initial matrix of the entire bed needs to be set to 0. Class II components represent riverbed sediments, including fine sand, medium sand, and coarse sand. The fine, medium, and coarse sands are classified according to their radius. For boundary control, the concentration of these three types of sediments at the inflow boundary must be kept constant at 0. For bed control, the mass fraction of these three types of sediments is initialized only within the grid in the river region, while in the estuary and marine areas, the mass fraction of these three types of sediments must be set to 0. Class III components represent sediments in the estuary and marine areas, including fine sand, medium sand, and coarse sand in marine shoals. The fine, medium, and coarse sands are classified according to their radius. In terms of boundary control, the concentration of these three types of sediments at the inflow boundary must be kept constant at 0. In terms of substrate control, the mass fraction of these three types of sediments is initialized only in the grid area of ​​the estuary and coastline, while in inland waterways, the mass fraction of these three types of sediments must be set to 0.

6. The sediment erosion and deposition simulation method considering meteorological forcing and multi-source tracing according to claim 5, characterized in that, In step 5, hydrodynamic parameters considering the effects of meteorological forcing and wave-current coupling are used as the hydrodynamic driver. Combined with the sediment concentration at the inflow boundary and the sediment mass fraction at the bottom surface as defined in step 4, the model configuration is completed based on SCHISM-WWM-SED3D. Specifically, the suspended volume fraction of various sediment components is... The three-dimensional convection-diffusion transport equations satisfied are as follows: ； in, C i For the first i Instantaneous concentration of sediment-like components, u,v,w For fluid in x,y,z Flow velocity in direction For the first i The settling velocity of sediment-like materials, K h ,K v denoted as the turbulent eddy diffusion coefficient in the horizontal and vertical directions. Q si For source and sink items.

7. The sediment erosion and deposition simulation method considering meteorological forcing and multi-source tracing as described in claim 6, characterized in that, In step 5, at the substrate boundary, the erosion flux... E i The calculation formula is as follows: ； in, E 0,i This is the substrate stripping rate coefficient. For the bed porosity, bed_frac i,l For the first i The percentage by mass of sediment in the outermost layer of the substrate. For the first i Critical erosion shear stress for silt-like sediments The actual shear stress at the bottom layer generated by wave-current coupling or pure flow; sedimentation flux D i The calculation formula is as follows: ； in, C i,b For the bottom water body grid i Calculated concentration of sediment-like material; Vertical net sedimentation flux between bottom water and the substrate J net,i The calculation formula is as follows: 。 8. The sediment erosion and deposition simulation method considering meteorological forcing and multi-source tracing as described in claim 1, characterized in that, In step 6, the measured data include measured wave data, measured tidal level and flow velocity and direction data, measured suspended sediment concentration and bed scouring and deposition data; the wave parameters output by the wave model are compared with the measured wave data to complete the parameter calibration of the wave model; the hydrodynamic parameters output by the hydrodynamic model are compared with the measured tidal level and flow velocity and direction data to complete the parameter calibration of the hydrodynamic model; the sediment parameters output by the sediment model are compared with the measured suspended sediment concentration and bed scouring and deposition data to complete the parameter calibration of the sediment model.

9. A method for simulating sediment erosion and deposition considering meteorological forcing and multi-source tracing as described in claim 1, characterized in that, In step 7, the initial conditions of the hydrodynamic-wave-sediment model are determined, including meteorological forcing factors, initial water depth, initial suspended sediment concentration field, initial temperature and salinity field, initial bed composition, and bed surface roughness. After preprocessing the data of the initial conditions, they are input into the hydrodynamic-wave-sediment model to drive the model to run. The model outputs the distribution of multi-source sediments, the distribution of suspended sediment content, and the changes in bed sediment scouring and deposition throughout the entire process from river channel to estuary to coastline. This provides a basis for clarifying the transport paths of sediments from different sources and the dynamic changes in source-sink fluxes, and improving the simulation accuracy of sediment scouring and deposition in river deltas.

10. A sediment erosion and deposition simulation system considering meteorological forcing and multi-source tracing, characterized in that, For performing the method according to any one of claims 1 to 9, comprising: Module 1: Acquire the driving data and measured data of the target area, and preprocess the driving data; The second module: Based on the WWM model, a wave model of the target area is established, the wave model is driven and run, and the wave parameters of the target area are calculated by combining the offshore boundary conditions; The third module: Based on the SCHISM-WWM two-way coupling model, a hydrodynamic-wave model of the target area is established. Combining the influence of meteorological factors on hydrodynamics and the wave-current coupling effect, the hydrodynamic parameters of the target area are calculated. Module 4: Based on the requirements of multi-source tracing, the sediment composition of the target area is classified as follows: sediment at the inflow boundary is classified as Class I, sediment at the riverbed is classified as Class II, and sediment at the estuary and coast is classified as Class III, with three particle sizes set for each. Module 5: Based on the SCHISM-WWM-SED3D model, establish a hydrodynamic-wave-sediment model for the target area, and calculate the sediment parameters of the target area by combining measured data. Module 6: Based on measured data, the coupled model is validated to obtain a hydrodynamic-wave-sediment model affected by meteorological forcing; Module 7: Input the initial data into the hydrodynamic-wave-sediment model for operation, and quantitatively output the multi-source sediment distribution, suspended sediment content distribution, and bed sediment erosion and deposition changes throughout the entire process of river channel-estuary-coast.

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