An estuary sediment transport simulation method considering coupling of environmental factors

Abstract

The application discloses an estuary sediment transport simulation method considering environmental factor coupling and belongs to the technical field of near-shore ocean deposition dynamics, which comprises the following steps: processing target sea area geographic data, constructing a non-structure calculation grid area of the target sea area and generating an initial terrain field; setting boundary conditions and an initial field for the target sea area, and constructing a three-dimensional hydrodynamic numerical model; using multi-source observation data to systematically verify and parameterize the three-dimensional hydrodynamic numerical model of S2; based on the three-dimensional hydrodynamic numerical model verified in S3, a three-dimensional hydrodynamic-sediment coupling numerical model considering environmental factor driving is constructed; and using multi-source observation data to systematically verify and parameterize the three-dimensional hydrodynamic-sediment coupling numerical model of S4. The application establishes a real-time dynamic coupling relationship between environmental factors and sediment settling velocity by modifying the sediment settling velocity equation, represents the flocculation effect of high-concentration fine-grained sediment in an estuary, and improves the accuracy of suspended sediment concentration simulation.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of nearshore marine sediment dynamics, and relates to a river estuary sediment transport simulation method considering coupling of environmental factors. BACKGROUND

[0002] The estuary delta is one of the areas with the richest biodiversity and plays an important role in carbon sequestration and climate regulation. The estuary delta is a depositional landform formed by the river estuary sediment, and the suspension and deposition of the sediment are the fundamental driving force for the development of the estuary delta. The traditional observation methods of the river estuary sediment mainly include field measurement and remote sensing method. The field measurement can only obtain discrete spatial points and data points, and it is difficult to describe the accurate morphology of the delta. The remote sensing method can only observe the surface data of the sea surface and is subject to weather and access period. As a supplementary means, the numerical simulation of the river estuary sediment transport process is helpful to understand the long-term evolution trend of the estuary delta under the combined action of natural factors and human factors.

[0003] The fine-grained cohesive sediment in the river estuary will accelerate flocculation under the action of seawater temperature and salinity, resulting in the aggregation of the sediment into groups and the increase of the sediment settling velocity. In the current numerical simulation of the river estuary fine-grained cohesive sediment transport, the numerical model usually sets the sediment settling velocity as a fixed value, without considering the influence of the coupling of seawater temperature, salinity and other factors on flocculation, thereby ignoring the dynamic adjustment mechanism of the flocculation process on the sediment settling velocity. This simplification causes obvious deviation in the simulation, limits the applicability and prediction accuracy of the numerical model in the complex estuary environment; in addition, in general simulation, it is usually assumed that the water body is uniform, without fully considering the influence of environmental factors on the water density, which can simulate most cases, but when the river estuary inflow is large and the sediment concentration is high, such simplification will significantly amplify the error, resulting in the inability of the numerical model to accurately characterize the baroclinic effect driven by the density gradient and the estuary circulation structure, thereby fundamentally affecting the accuracy of the estuary sediment transport result. Therefore, when simulating the river estuary high-concentration sediment into the sea, considering the influence of environmental factors, improving the simulation accuracy and accurately describing the physical process are the main problems to be solved by the application. SUMMARY

[0004] In view of the problems existing in the existing numerical model, the application provides a river estuary sediment transport simulation method considering coupling of environmental factors, which improves the simulation accuracy and reliability under the condition of high-concentration sediment transport in the river estuary.

[0005] The technical scheme provided by the application is as follows:

[0006] A river estuary sediment transport simulation method considering coupling of environmental factors comprises the following steps:

[0007] S1: Process geographic data of the target sea area, construct an unstructured computational grid region of the target sea area and generate an initial topographic field;

[0008] S2: Set boundary conditions and initial field for the target sea area, and construct a three-dimensional hydrodynamic numerical model;

[0009] S3: The three-dimensional hydrodynamic numerical model in step S2 is systematically verified and its parameters are calibrated using multi-source observation data;

[0010] S4: Based on the three-dimensional hydrodynamic numerical model verified by S3, a three-dimensional hydrodynamic-sediment coupling numerical model considering environmental factors is constructed.

[0011] S5: The three-dimensional hydrodynamic-sediment coupling numerical model in S4 was systematically verified and its parameters were calibrated using multi-source observation data.

[0012] Preferably, step S1 includes:

[0013] S11. Extract the coastline features of the target sea area;

[0014] S12. Determine the numerical calculation area and set attributes for the shoreline of different areas, including river input boundary, open sea boundary, coastal boundary and island boundary;

[0015] S13. Define geometric constraints based on shoreline boundaries;

[0016] S14. Integrate nautical chart water depth data with nearshore measured topographic data to generate an initial scatter plot dataset of topography for the target sea area;

[0017] S15. Map the terrain scatter dataset onto unstructured grid nodes.

[0018] Preferred,

[0019] Step S11: Extract the coastline features of the target sea area using visual interpretation.

[0020] Step S13 employs the Constrained Delaunay Triangulation (CDT) algorithm to generate a high-quality unstructured mesh, and refines the mesh in key study areas to characterize the physical processes in detail and improve the accuracy of numerical calculations.

[0021] Step S15 uses interpolation to map the terrain scatter dataset onto unstructured grid nodes. Linear interpolation is used inside the target sea area, while inverse distance weighting (IDW) is used near the boundary of the target sea area to obtain the initial terrain field of the entire target sea area.

[0022] Preferably, step S2 includes: solving the Navier-Stokes equations based on hydrostatics and the Boussinesq approximation; using the σ coordinate system for vertical stratification to better fit the seabed topography; setting open boundary conditions and an initial field; wherein the open boundary conditions include: tidal harmonic constant and flow time series; and the initial field includes: temperature, salinity, friction coefficient, water level, and eddy viscosity; and calculating the friction coefficient n using the following formula:

[0023] ,

[0024] In the formula, For water depth;

[0025] Preferably, step S3 includes: comparing and verifying the key hydrodynamic elements output by the model simulation: tidal level, flow velocity, and flow direction with the measured data, selecting the Pearson correlation coefficient r as the verification index, and ensuring that the verification result is greater than 0.7. If the above accuracy requirements are not met, the key parameters of the model are adjusted and recalculated repeatedly until the model reaches the preset accuracy standard. The key parameters of the model include any one or a combination of bottom roughness, turbulence coefficient, and boundary condition settings.

[0026] Preferably, the specific formula for r is:

[0027] ,

[0028] In the formula, For the i-th measured value, This is the i-th simulated value; These are the average values ​​of the measured values ​​and the simulated values, respectively. This represents the number of sample points.

[0029] Ensure the validation result is greater than 0.7, i.e., reaching a moderate to high level of positive correlation, indicating that the model results have a significant positive correlation with the measured data and can effectively reflect the actual trend of change. If the above accuracy requirements are not met, repeatedly adjust and recalculate the model by adjusting key parameters (such as bed roughness, turbulence coefficient, or boundary condition settings) until the model reaches the preset accuracy standard.

[0030] Preferably, step S4 includes the following steps:

[0031] S41. Establish a real-time coupling relationship between environmental factors and settling velocity in the transport equation, and calculate the effects of salinity and temperature on sediment particle settling velocity using the following formula:

[0032] ,

[0033] In the formula, Equivalent particle size; Gravitational acceleration; The difference is the relative density. Seawater temperature; Seawater salinity; The kinematic viscosity of water; These are empirical constants;

[0034] S42. Introduce the density change caused by environmental factors into the gravity term of the momentum equation, and calculate the effects of temperature, salinity, and sediment particles on seawater density using the following formula:

[0035] ,

[0036] ,

[0037] In the formula, The initial seawater density, Seawater density taking into account the effects of temperature and salinity; To account for the effects of temperature, salinity, and sediment particle size on seawater density, For temperature coefficient, This is the salinity coefficient. For seawater temperature, For reference temperature, Seawater salinity For reference salinity, The concentration of sediment. This refers to the density of sediment particles;

[0038] S43. Set open boundary conditions and initial field. The open boundary conditions, based on those set in S2, also include the measured sediment concentration time series. The initial field, based on those set in S2, also includes: the critical initiation shear stress and clear water settling velocity of sediment in the study area, the initial thickness of the seabed, and the initial suspended sediment concentration in the ocean.

[0039] Preferably, step S5 includes: comparing and verifying the simulated suspended sediment concentration results with the measured data, selecting the Pearson correlation coefficient r as the verification index, ensuring that the verification result is greater than 0.7, and if the above accuracy requirements are not met, then readjusting the model parameters, such as the critical starting shear stress and settling velocity, and repeatedly adjusting and recalculating until the model reaches the preset accuracy standard.

[0040] Preferably, the specific formula for r is:

[0041] ,

[0042] In the formula, For the i-th measured value, This is the i-th simulated value; These are the average values ​​of the measured values ​​and the simulated values, respectively. This represents the number of sample points.

[0043] Ensure the validation result is greater than 0.7, i.e., reaching a moderate to high level of positive correlation, indicating that the model results have a significant positive correlation with the measured data and can effectively reflect the actual trend of change. If the above accuracy requirements are not met, readjust the model parameters, such as the critical starting shear stress and settling velocity, and perform repeated adjustments and recalculations until the model reaches the preset accuracy standard.

[0044] As can be seen from the above, the advantages of this invention are:

[0045] The proposed method for estuarine sediment transport simulation considering the coupling of environmental factors differs from the simplified approach of traditional methods that set the settling velocity as a constant and ignore flocculation. By modifying the sediment settling velocity equation, this method establishes a real-time dynamic coupling relationship between environmental factors and sediment settling velocity, characterizes the flocculation effect of high-concentration fine-particle sediment in estuaries, and improves the accuracy of suspended sediment concentration simulation.

[0046] The proposed method for estuarine sediment transport simulation that considers the coupling of environmental factors differs from traditional methods that ignore the influence of environmental factors on water density. By introducing a modified equation of state into the momentum equation, it significantly improves the simulation accuracy of complex flows under thermohaline circulation, baroclinic effects, and high-concentration sediment entering the sea, and can more realistically reflect the physical mechanism of water and sediment movement in the estuarine region.

[0047] 3. The estuarine sediment transport simulation method considering the coupling of environmental factors proposed in this invention is not only applicable to sandy beaches dominated by bedload, but also to simulating silty beaches dominated by fine-grained sediments such as silt and fine sand. It can characterize key physical phenomena such as density currents and feather currents in estuaries, providing accurate and reliable scientific basis and technical support for the prevention and control of siltation in ports and waterways, the protection and restoration of coastal ecological environment, and the planning and construction of marine engineering facilities. Attached Figure Description

[0048] Figure 1 A flowchart of a method for simulating estuarine sediment transport considering the coupling of environmental factors, according to an embodiment of the present invention, is presented.

[0049] Figure 2 The simulated and measured results of tide level, current velocity, and current direction at station Z1 were compared.

[0050] Figure 3 The simulated and measured results of tide level, flow velocity, and flow direction at station Z2 were compared.

[0051] Figure 4 The simulated and measured results of tide level, flow velocity, and flow direction at station Z3 were compared.

[0052] Figure 5The results of comparing suspended sediment concentration with measured values ​​at each station are presented to verify the accuracy of the three-dimensional hydrodynamic-sediment coupling numerical model that takes into account the coupling of environmental factors. Among them, Figure (a) compares the simulated and measured results of suspended sediment concentration at station Z4, and Figure (b) compares the simulated and measured results of suspended sediment concentration at station Z5.

[0053] Figure 6 A comparison of the results of high-concentration sediment entering the sea in estuaries using the method of the present invention and the traditional simulation method is presented; wherein, Figure (a) is the result of the method of the present invention, and Figure (b) is the result of the traditional simulation method. Detailed Implementation

[0054] To better illustrate the specific steps involved in this invention and the expected effects, an embodiment is provided below, along with the accompanying drawings.

[0055] Example 1

[0056] Please see Figure 1 , Figure 1 The implementation flowchart of the estuarine sediment transport simulation method considering the coupling of environmental factors in this embodiment is shown.

[0057] This embodiment provides a method for simulating estuarine sediment transport that considers the coupling of environmental factors, comprising the following steps:

[0058] Step S1: Process the geographic data of the target sea area, construct an unstructured computational grid for the target sea area, and generate an initial topographic field.

[0059] This embodiment extracts shoreline features of the target sea area through visual interpretation to determine the numerical calculation region and sets attributes for the shorelines of different regions, including river input boundaries, open sea boundaries, coastal boundaries, and island boundaries. Based on the geometric constraints defined by the shoreline boundaries, the Constrained Delaunay Triangulation (CDT) algorithm is used to generate a high-quality unstructured mesh. The mesh is densified in key study areas to characterize the physical processes in detail and improve the accuracy of numerical calculations. Nautical chart depth data and nearshore measured topographic data are fused to generate an initial topographic scatter plot dataset for the target sea area. This embodiment uses interpolation to map the topographic scatter plot dataset onto the unstructured mesh nodes. Linear interpolation is used within the target sea area, while inverse distance weighting (IDW) is used near the target sea area boundaries to obtain the initial topographic field for the entire target sea area.

[0060] Step S2: For the target sea area, set boundary conditions and initial field, and construct a three-dimensional hydrodynamic numerical model.

[0061] This embodiment uses hydrostatics and the Boussinesq approximation to solve the Navier-Stokes equations. To better fit the seabed topography and accurately depict the three-dimensional effect of fluids in the ocean, this embodiment uses a σ coordinate system to uniformly layer each grid cell according to water depth, generally setting 10-20 layers. The river flow velocity open boundary condition uses flow rate input, with values ​​being measured flow rate time series. This embodiment uses the TPXO7.2 global tidal model to drive the tide level to simulate the real ocean dynamic environment. The initial field settings include: temperature, salinity, water level, eddy viscosity, and friction coefficient. The formula used for the friction coefficient is:

[0062] ,

[0063] Step S3: Use multi-source observation data to systematically verify and calibrate the parameters of the three-dimensional hydrodynamic model in S2.

[0064] This embodiment compares the measured oceanographic data with the simulated output of tidal level, current velocity, and current direction, selecting the Pearson correlation coefficient (r) as the verification index. The specific formula is as follows:

[0065] ,

[0066] In the formula, For the i-th measured value, This is the i-th simulated value; These are the average values ​​of the measured values ​​and the simulated values, respectively. This represents the number of sample points.

[0067] Ensure the validation result is greater than 0.7, i.e., reaching a moderate to high level of positive correlation, indicating that the model results have a significant positive correlation with the measured data and can effectively reflect the actual trend of change. If the above accuracy requirements are not met, repeatedly adjust and recalculate the model by adjusting key parameters (such as bed roughness, turbulence coefficient, or boundary condition settings) until the model reaches the preset accuracy standard.

[0068] Step S4: Based on the three-dimensional hydrodynamic numerical model verified in S3, construct a three-dimensional hydrodynamic-sediment coupling numerical model that considers the coupling of environmental factors.

[0069] In this embodiment, S41, a solution for sediment transport is added to the transport equation, and the effects of temperature and salinity on settling velocity are considered in the calculation of the equation and the sedimentation amount of the bottom unit. A real-time coupling relationship between environmental factors and settling velocity is established to characterize the flocculation process of viscous fine-grained sediment. The effects of salinity and temperature on sediment particle settling velocity are calculated using the following formula:

[0070] ,

[0071] In the formula, Equivalent particle size; Gravitational acceleration; The difference is the relative density. Seawater temperature; Seawater salinity; The kinematic viscosity of water; This is an empirical constant.

[0072] S42. Introduce the density change caused by environmental factors into the gravity term of the momentum equation, and calculate the effects of temperature, salinity, and sediment particles on seawater density using the following formula:

[0073] ,

[0074] ,

[0075] The initial seawater density; Seawater density taking into account the effects of temperature and salinity; Seawater density taking into account the effects of temperature, salinity, and sediment particles; Temperature coefficient; Salinity coefficient; For seawater temperature, For reference temperature; Seawater salinity For reference salinity; The concentration of sediment. This refers to the density of sediment particles;

[0076] S43. The river open boundary condition was input using measured flow and sediment concentration time series, while the ocean open boundary condition was driven by the TPXO7.2 global tidal model. The initial field was based on S2, incorporating the critical initiation shear stress and clear water settling velocity parameters for sediment. These two parameters are determined by the sediment gradation of the seabed in the study area. Without considering the influence of extreme weather, the seabed thickness was generally set to 2 m, and the initial suspended sediment concentration in the ocean was set to 30 mg / L.

[0077] Step S5: Use multi-source observation data to systematically verify and calibrate the parameters of the three-dimensional hydrodynamic-sediment coupling numerical model in S4.

[0078] In this embodiment, the simulated suspended sediment concentration is compared and verified with the measured data. The Pearson correlation coefficient (r) is selected as the verification index, and the specific formula is as follows:

[0079] ,

[0080] In the formula, For the i-th measured value, This is the i-th simulated value; These are the average values ​​of the measured values ​​and the simulated values, respectively. This represents the number of sample points.

[0081] Ensure the validation result is greater than 0.7, i.e., reaching a moderate to high level of positive correlation, indicating that the model results have a significant positive correlation with the measured data and can effectively reflect the actual trend of change. If the above accuracy requirements are not met, readjust the model parameters (such as critical starting shear stress, settling velocity, etc.), and repeatedly adjust and recalculate until the model reaches the preset accuracy standard.

[0082] Example 2

[0083] To verify the reliability of the estuarine sediment transport simulation method considering the coupling of environmental factors in this invention, this embodiment selects the Bohai Sea as the study area. The marine boundary conditions are driven by the TPXO7.2 global tidal model, and the river boundary conditions are driven by the measured flow time series.

[0084] To verify the accuracy of the three-dimensional hydrodynamic numerical model constructed in Example 1, three observation points (Z1-Z3) were set up in the Bohai Sea. The specific latitude and longitude coordinates are shown in Table 1. The numerical simulation results of tidal level, current velocity, and current direction at the observation points were compared with the measured results for verification. Figures 2 to 4 A comparison chart of tidal levels, flow velocities, and flow directions at various stations was presented to verify the accuracy of the three-dimensional hydrodynamic numerical model. Figure 2 The simulated and measured values ​​of tide level, current velocity, and current direction at station Z1 were compared between 9:00 on October 10, 2018 and 10:00 on October 11, 2018. Figure 3 The simulated and measured values ​​of tide level, current velocity, and current direction at station Z2 were compared between 9:00 on October 10, 2018 and 10:00 on October 11, 2018. Figure 4 The simulated and measured values ​​of tidal level, flow velocity, and flow direction at station Z3 were compared between 9:00 AM on October 10, 2018 and 10:00 AM on October 11, 2018. It can be seen that the Pearson correlation coefficient (r) of the flow field simulation results constructed by the method of this invention is above 0.7, indicating that the model meets the accuracy requirements in hydrodynamic simulation.

[0085] Table 1 Coordinates of observation stations for tide level, current velocity, and current direction

[0086]

[0087] To verify the accuracy of the three-dimensional hydrodynamic-sediment coupling numerical model that takes into account the coupling of environmental factors, two observation points, Z4 and Z5, were set up in the Bohai Sea. The specific latitude and longitude coordinates are shown in Table 2.Figure 5 The simulated and measured values ​​of suspended sediment concentration in Z4-Z5 during the period from 00:00 to 21:00 on July 13, 2018 were compared. It can be seen that the Pearson correlation coefficient (r) of the simulation results is above 0.7, effectively simulating the initiation law of sediment. The three-dimensional hydrodynamic-sediment coupling numerical model considering environmental factors meets the accuracy requirements for water and sediment simulation.

[0088] Table 2 Coordinates of suspended sediment concentration monitoring stations

[0089]

[0090] To verify the accuracy of the model in the complex dynamic environment of the estuary, this embodiment compares... Figure 6 The simulation results were verified to determine whether environmental factors were considered in the simulation. All simulations were performed under the same conditions, location, and time. Figure 6 (a) shows the numerical simulation results without considering the coupling of environmental factors. Figure 6 (b) shows the results of the method of the present invention. It can be seen that the numerical model that does not consider the coupling of environmental factors cannot accurately depict the density current phenomenon in the estuary when simulating high concentration sediment entering the sea. The method of the present invention can truly reflect the physical mechanism of water and sediment movement in the estuary area.

[0091] In view of this, the present invention discloses a method for simulating estuarine sediment transport that considers the coupling of environmental factors. This method integrates the influence of environmental factors on seawater density, captures the phenomena of estuarine density currents and seawater stratification, accurately simulates the seaward transport process of high-concentration sediment, and realizes the real-time influence of temperature and salinity on sediment settling velocity, characterizing the physical process of sediment flocculation. This significantly improves the accuracy of simulating marine suspended sediment concentration, providing accurate and reliable scientific basis and technical support for the prevention and control of siltation in ports and waterways, the protection and restoration of coastal ecological environment, and the planning and construction of marine engineering facilities.

Claims

1. A method for simulating estuarine sediment transport considering the coupling of environmental factors, characterized in that: Includes the following steps: S1: Process geographic data of the target sea area, construct an unstructured computational grid region of the target sea area and generate an initial topographic field; S2: Set boundary conditions and initial field for the target sea area, and construct a three-dimensional hydrodynamic numerical model; S3: The three-dimensional hydrodynamic numerical model in step S2 is systematically verified and its parameters are calibrated using multi-source observation data; S4: Based on the three-dimensional hydrodynamic numerical model validated in S3, construct a three-dimensional hydrodynamic-sediment coupling numerical model considering environmental factors; including the following steps: S41. Establish a real-time coupling relationship between environmental factors and settling velocity in the transport equation, and calculate the effects of salinity and temperature on sediment particle settling velocity using the following formula: ， In the formula, Equivalent particle size; Gravitational acceleration; The difference is the relative density. Seawater temperature; Seawater salinity; The kinematic viscosity of water; These are empirical constants; S42. Introduce density changes caused by environmental factors into the gravity term of the momentum equation, and calculate the effects of temperature, salinity, and sediment particles on seawater density using the following formula: ， ， In the formula, The initial seawater density, Seawater density taking into account the effects of temperature and salinity; To account for the effects of temperature, salinity, and sediment particle size on seawater density, For temperature coefficient, This is the salinity coefficient. For seawater temperature, For reference temperature, Seawater salinity For reference salinity, The concentration of sediment. This refers to the density of sediment particles; S43. Set open boundary conditions and initial field. The open boundary conditions, based on those set in S2, also include the measured sediment concentration time series. The initial field, based on those set in S2, also includes: the critical initiation shear stress and clear water settling velocity of sediment in the study area, the initial thickness of the seabed, and the initial suspended sediment concentration in the ocean. S5: The three-dimensional hydrodynamic-sediment coupling numerical model in S4 was systematically verified and its parameters were calibrated using multi-source observation data.

2. The method for simulating estuarine sediment transport according to claim 1, characterized in that: Step S1 includes: S11. Extract the coastline features of the target sea area; S12. Determine the numerical calculation area and set attributes for the shoreline of different areas, including river input boundary, open sea boundary, coastal boundary and island boundary; S13. Define geometric constraints based on shoreline boundaries; S14. Integrate nautical chart water depth data with nearshore measured topographic data to generate an initial topographic scatter dataset of the target sea area; S15. Map the terrain scatter dataset onto unstructured grid nodes.

3. The method for simulating estuarine sediment transport according to claim 2, characterized in that: Step S11: Extract the coastline features of the target sea area using visual interpretation. Step S13 employs the constrained Delaunay triangulation algorithm to generate a high-quality unstructured mesh, and refines the mesh in key study areas to characterize the physical processes in detail and improve the accuracy of numerical calculations. Step S15 uses interpolation to map the terrain scatter dataset onto unstructured grid nodes. Linear interpolation is used inside the target sea area, while inverse distance weighting is used near the boundary of the target sea area to obtain the initial terrain field of the entire target sea area.

4. The method for simulating estuarine sediment transport according to claim 1, characterized in that: Step S2 includes: solving the Navier-Stokes equations based on hydrostatics and the Boussinesq approximation; using the σ coordinate system for vertical stratification to better fit the seabed topography; setting open boundary conditions and an initial field; where the open boundary conditions include: tidal harmonic constant and flow time series; and the initial field includes: temperature, salinity, friction coefficient, water level, and eddy viscosity. The friction coefficient n is calculated using the following formula: ， In the formula, The water is deep.

5. The method for simulating estuarine sediment transport according to claim 1, characterized in that: Step S3 includes: comparing and verifying the key hydrodynamic elements output by the model simulation: tidal level, flow velocity, and flow direction with the measured data. The Pearson correlation coefficient r is selected as the verification index to ensure that the verification result is greater than 0.

7. If the above accuracy requirements are not met, the key parameters of the model are adjusted and recalculated repeatedly until the model reaches the preset accuracy standard. The key parameters of the model include any one or a combination of the following: bed roughness, turbulence coefficient, and boundary condition settings.

6. The method for simulating estuarine sediment transport according to claim 5, characterized in that: The specific formula for r is: ， In the formula, For the i-th measured value, This is the i-th simulated value; These are the average values ​​of the measured values ​​and the simulated values, respectively. This represents the number of sample points.

7. The method for simulating estuarine sediment transport according to claim 1, characterized in that: Step S5 includes: comparing and verifying the simulated suspended sediment concentration results with the measured data, selecting the Pearson correlation coefficient r as the verification index, ensuring that the verification result is greater than 0.7, and if the above accuracy requirements are not met, then readjusting the model parameters, such as the critical starting shear stress and settling velocity, and repeatedly adjusting and recalculating until the model reaches the preset accuracy standard.

8. The method for simulating estuarine sediment transport according to claim 7, characterized in that: The specific formula for r is: ， In the formula, For the i-th measured value, This is the i-th simulated value; These are the average values ​​of the measured values ​​and the simulated values, respectively. This represents the number of sample points.

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