A wetland-seawall design parameter determination method based on equivalent recurrence period

Abstract

The application provides a wetland-seawall design parameter determination method based on equivalent recurrence period, and belongs to the technical field of coastal protection engineering based on computer data processing; design parameters of vegetation in front of the seawall are acquired, and open sea wave height and water level of the design recurrence period are calculated; the design parameters are used as model vegetation setting, the open sea wave height and water level of the design recurrence period are used as model open boundary, wave attenuation of the vegetation in front of the seawall is calculated through numerical simulation, and the wave height in front of the seawall is obtained; the wave height in front of the seawall is inversely calculated to the recurrence period through local historical wave water level monitoring data, and the vegetation equivalent recurrence period representing the protection capability of the vegetation in front of the seawall is calculated; according to the protection recurrence period requirement of the mixed protection engineering, the vegetation equivalent recurrence period is deducted, the protection recurrence period requirement of the seawall is obtained, and the selection of the seawall design parameter is guided. The method is aimed at the gray-green combined mixed protection problem of the vegetation and the seawall, breaks through the problem of quantifying the protection effect of the vegetation in front of the seawall, and realizes the safety standard evaluation problem of the mixed coastal protection.

Description

Technical Field

[0001] This invention belongs to the field of coastal protection engineering technology based on computer data processing, and particularly relates to a method for determining wetland-seawall design parameters based on equivalent return period. Background Technology

[0002] In recent years, coastal areas have faced extreme marine disasters such as typhoons and storm surges. Traditional coastal protection facilities have been continuously heightened and thickened, resulting in high construction and maintenance costs, disrupting ecosystem connectivity, and leading to coastal wetland degradation and coastline erosion. Against this backdrop, a proposed solution is to plant vegetation in front of traditional coastal protection facilities. This would utilize the frictional energy dissipation and siltation-promoting effects of the vegetation to weaken wave dynamics, while the subsequent seawall would safeguard against flooding, thus achieving a balance between safety and ecological function.

[0003] Currently, the design of laying vegetation in front of seawalls is quite common. A large number of coastal engineering projects are facing a shift from traditional pure seawall projects to coastal protection projects that combine seawall vegetation with seawalls. It is foreseeable that for a very long period in the future, coastal protection systems with coastal vegetation in front of seawalls will become the common form and mainstream trend in coastal engineering construction both domestically and internationally. This provides technical demand and room for the promotion and application of related supporting design methods.

[0004] While coastal protection engineering incorporating vegetation along seawalls holds great promise, it faces a technical bottleneck in practical engineering design and standardized operation due to a misalignment between ecological protection effects and engineering standards. Current industry standards rely on design return periods to determine hydrological parameters and guide structural design. However, current technologies primarily focus on assessing the wave height attenuation rate of vegetation, making it impossible for traditional engineers to directly convert this rate into compliant seawall design return period reductions. Lacking clear equivalent conversion standards, engineering designs often struggle to incorporate ecological protection effects into seawall disaster resistance indicators. This bottleneck prevents current engineering designs from quantifying the protective effects of vegetation along seawalls into engineering parameters applicable to the seawall design return period, thus hindering the realization of the core advantages of protection systems in saving engineering investment and reducing carbon emissions. Summary of the Invention

[0005] This invention addresses the aforementioned technical challenges by proposing a method for determining wetland-seawall design parameters based on equivalent return periods. This method creatively quantifies the protective capacity of front-wall vegetation for the coastline as an "equivalent return period," and further guides the structural design parameters of the seawall based on this "equivalent return period." This invention aims to break down the standard barriers between ecological dissipation and engineering return periods, incorporating vegetation protective capacity into the engineering return period system, and providing a quantitative basis for the design of gray-green integrated coastal protection projects.

[0006] This invention provides a method for determining wetland-seawall design parameters based on equivalent return periods, comprising the following steps: S1, obtain the design parameters of the vegetation in front of the embankment, including the length and width of the vegetation area in front of the embankment, the planting density of the vegetation, the vegetation coverage rate of the vegetation area, the vegetation height, the vegetation diameter, and the vegetation fragmentation of the vegetation area. S2, the offshore incident wave height and water level for the design return period are calculated using a one-dimensional composite extreme value distribution based on local historical wave and water level monitoring data; S3 uses the design parameters obtained in S1 as the model vegetation settings, and the ocean incident wave height and water level obtained in S2 as the open boundary of the model. The attenuation of waves by the vegetation in front of the dike is calculated by numerical simulation to obtain the wave height in front of the dike. S4, the wave height in front of the dike is inverted back to the return period using local historical wave water level monitoring data, and the equivalent return period of vegetation representing the protective capacity of vegetation in front of the dike is calculated. S5. Based on the protection return period requirements of the mixed protection project, the equivalent return period of vegetation is deducted to obtain the protection return period requirements of the seawall. These protection return period requirements guide the selection of seawall design parameters.

[0007] Preferably, in step S1, the vegetation design parameters are adjusted according to the specific design scheme. For example, the length and width of the vegetation area in front of the embankment can be replaced by the coordinates of the boundary points of the vegetation area; the planting density of the vegetation can be replaced by the planting spacing; if the vegetation height parameter is missing in the design scheme, the height of the vegetation can be collected from sample plots of planted vegetation and the average value can be taken; the vegetation diameter is calculated as the average diameter of the canopy and rootstock. The planting spacing is converted into planting density using the following formula: ; Where L is the planting density and L is the planting spacing.

[0008] The diameter of vegetation can be calculated using the following formula: ; in The diameter of the vegetation; Canopy height; The height of the stem; The diameter of the canopy; The diameter of the stem.

[0009] Preferably, the specific process of calculating the offshore incident wave height and water level for the design return period in S2 is as follows: S21, collect historical monitoring data on local wave height and water level, and statistically analyze the frequency of extreme events that have occurred over the years and the corresponding water level and wave height for each extreme event.

[0010] S22, Fit the frequency of extreme events over the years using a Poisson distribution, and calculate the Poisson distribution parameters; Poisson distribution probability distribution function. as follows: ; In the formula, e is the natural constant; k is the independent variable, representing the frequency of extreme events that occur over the years; Here are the parameters to be fitted, representing the average number of extreme events occurring per year. The calculation method is as follows: ; For the first i Frequency of extreme events per year; The year span of the observed data; S23, use the generalized Pareto distribution to fit the water level and wave height, and calculate the generalized Pareto distribution parameters. and The calculation method uses maximum likelihood estimation. Previous studies have shown that for random variables following any distribution, after setting a threshold to filter out all data exceeding the threshold, given a sufficiently large dataset, all data exceeding the threshold will follow a generalized Pareto distribution. The probability density function of the generalized Pareto distribution is as follows: ; In the formula, x is the independent variable, representing wave height in the extreme value calculation of wave height and water level in the extreme value calculation of water level; and These are also the parameters to be fitted, representing the dispersion of wave height and water level data, and the tail thickness of the extreme value distributions of water level and wave height, respectively. Maximum likelihood estimation is a classic parameter point estimation method. Its idea is that, given unknown parameters and a finite sample size, events that have already occurred can be considered the events with the highest probability. After drawing a specific sample, we need to find the parameter values ​​(likelihoods) that maximize the probability of these samples occurring. In other words, we want to maximize the posterior probability of the samples. It is generally assumed that the samples are independent and identically distributed, therefore the probability of the entire sample set is equal to the product of the probabilities of each individual sample. Since the analysis of multiple products is complex, the product of likelihood values ​​is usually transformed into a sum of probabilities by taking the logarithm, i.e., the sum of the logarithms of the probabilities of each sample. The likelihood function is constructed as follows: ; In the formula For water level and wave height data exceeding the threshold; M is the total number of data points; Let be the probability density function of the generalized Pareto distribution. The likelihood function represents the probability of drawing the current sample given specific parameter values. Since the posterior result is the observed value of the current sample, the parameter values ​​of the generalized Pareto distribution can be estimated by assuming that the parameter values ​​of the wave height probability distribution maximize the probability of obtaining these samples. ; S24 calculates the composite extreme value distribution using the fitted Poisson distribution and the generalized Pareto distribution, and then calculates the water level and wave height for the design return period. The parameters calculated in S23 are used... , and Calculate the water level during the return period. The expression for the composite extreme value distribution is as follows: ; The return period can be converted using the following formula: ; Let T be the probability of occurrence per year, and T be the design return period, such as 100 years; then the calculated... , , and Substituting these values ​​into the composite extreme value distribution expression, we can obtain the corresponding incident wave height and water level values ​​in the open sea. If the parameters substituted are calculated from wave height monitoring data... , and The result is The ocean incident wave height under the return period T If the parameters substituted are calculated from water level monitoring data; , and Then the result is The water level is the return period T.

[0011] Preferably, in step S3, the wave height in front of the dike is obtained by numerical simulation calculation of the attenuation of waves by the vegetation in front of the dike. The specific process is as follows: S31. Set the calculated incident wave height and water level of the outer sea as the open boundary conditions of the model, and set the vegetation parameters in the model's grid, including the vegetation height matrix, vegetation density matrix, and vegetation diameter matrix.

[0012] S32 simulates the wave dissipation and flow obstruction processes caused by vegetation. The wave propagation process is simulated by solving the following equations: ; In the formula, The wave speed, For the purpose of wave dissipation by vegetation, The energy of a wave and its relationship to wave height are as follows: ; In the formula, The wave height; The density of seawater; The acceleration due to gravity is typically taken as 9.8 m / s². 2 The flow obstruction process is simulated by solving the following equations: ; In the formula, The resistance of vegetation to water flow, This is the drag coefficient. The density of seawater, This refers to the number of plants per unit area. The diameter of the plant. The height of the plant submerged in water. Flow rate.

[0013] The wave dissipation process of vegetation is characterized by the following equation: ; In the formula, The wave energy reduction per unit area per unit time. The wave number. The wave frequency, The energy of the waves.

[0014] S33, extract the simulated wave height in front of the dike. S32, solve for the wave height of each grid cell. Then, all grids in the area from behind the vegetation zone to in front of the seawall were selected, and the wave height simulation results of these grids were averaged to obtain the wave height in front of the seawall. .

[0015] Preferably, in step S4, the wave height in front of the dike is inverted back to the return period using local historical wave level monitoring data. A previously fitted one-dimensional composite extreme value distribution is then used to calculate the probability and return period of the wave height. The vegetation equivalent return period is the return period corresponding to the wave height resisted by the vegetation in front of the dike alone. The vegetation equivalent return period is calculated by subtracting the return period of the incident wave height from the open sea from the return period of the wave height in front of the dike. It can be obtained using the following formula: ; In the formula, The equivalent return period for vegetation; The height of incident waves over the open sea; The waves are high in front of the dike; , and The composite extreme value distribution parameters are obtained by fitting wave height monitoring data.

[0016] Preferably, in step S5, the hybrid coastal protection project comprises two parts: vegetation in front of the dike and a seawall behind it. The overall hybrid coastal protection project needs to meet corresponding protection return period requirements, partly provided by the protective capacity of the vegetation in front of the dike and partly supplemented by the seawall behind it. The protective capacity of the vegetation in front of the dike is characterized by the "vegetation equivalent return period," and the protection requirement that the seawall behind it needs to meet is the remaining portion of the overall protection requirement of the hybrid coastal protection project after deducting the "vegetation equivalent return period."

[0017] After determining the required protection level of the seawall, parameters can be adjusted according to the seawall design. For example, if the seawall is a Class 1 seawall that does not allow wave run-through, the safety height increase is generally 1 m. Subsequently, the wave run-up can be calculated based on the seawall design standards, using the seawall's seaward slope ratio, surface roughness, and the protection requirements calculated by this invention, and then the top elevation of the seawall can be determined.

[0018] Compared with the prior art, the present invention has the following beneficial effects: 1. The protective capacity of vegetation was quantified; the concept of "equivalent return period of vegetation" was proposed. By combining composite extreme value analysis and vegetation dissipation simulation, the wave attenuation rate of vegetation was calculated as the equivalent return period of vegetation, overcoming the problem of difficulty in quantifying the protective effect of vegetation in front of dikes, and providing a basis for the design and planting of vegetation in front of dikes. It provides practical suggestions for the planting and design of vegetation in front of dikes in actual ecological coastal protection projects. 2. It breaks down the standard barriers between ecological dissipation and engineering return periods; by incorporating vegetation protection capacity into the engineering return period system, it overcomes the problem of the difficulty in co-designing front vegetation and rear seawalls in ecological coastal protection projects. Using the equivalent return period of vegetation as a bridge, it provides a quantitative value of the protection capacity of front vegetation for the design of rear seawalls, promoting the co-design of front vegetation and rear seawalls. It provides a more scientific and comprehensive design method for ecological coastal protection projects. Attached Figure Description

[0019] Figure 1 This is a flowchart of a standard design method for seawall protection that takes into account vegetation in front of the seawall, according to the present invention.

[0020] Figure 2 This is a schematic diagram illustrating the principle of a seawall protection standard design method that takes into account vegetation in front of the seawall, as proposed in this invention.

[0021] Figure 3 This is a schematic diagram illustrating the physical meaning of "vegetation equivalent return period" in this invention.

[0022] Figure 4 This is a schematic diagram illustrating the extraction of vegetation design parameters in front of the dike according to the present invention.

[0023] Figure 5 This is a schematic diagram illustrating the relationship between the return period and water level wave height in this invention.

[0024] Figure 6 This is a schematic diagram of the model setup for simulating the wave dissipation process of vegetation in this invention.

[0025] Figure 7 A schematic diagram illustrating the principle of using vegetation equivalent return period to guide seawall design.

[0026] Figure 8 The wave height simulation results are for the vegetation wave dissipation process in the case study.

[0027] Figure 9 This is a schematic diagram of the relevant design parameters for the seawall. Detailed Implementation

[0028] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. The specific process of calculating the equivalent return period of vegetation to guide the design of seawalls will be demonstrated. (Refer to the flowchart.) Figure 1 Schematic diagram Figure 2 .

[0029] This implementation scheme provides a relatively ideal case to demonstrate the feasibility of the invention. This case focuses on a rectangular area 61 km long and 4 km wide, as shown in the diagram. Figure 6 The vegetated area is located on the coastline extending 2 km inland, with a seawall behind it. Kandelia candel is planted evenly within the vegetated area. Water level and wave height monitoring data are based on data from strong wind events in Dapeng Bay from 1949 to 1999.

[0030] S1. Based on the mixed protection design, obtain the parameters of the vegetation in front of the dike, including the length and width of the vegetation zone, planting density, vegetation coverage, vegetation height, vegetation diameter, and vegetation fragmentation. See the schematic diagram. Figure 4 .

[0031] In this case, the planting area of ​​vegetation is in Figure 6 As indicated in the diagram. In the planting area, Kandelia candel is planned to be planted at a spacing of 0.7m. Based on the planting spacing, the area occupied by each Kandelia candel plant is calculated to be 0.49m². 2 Therefore, the number of Kandelia candel plants per square meter was determined to be 2. Additionally, the height, stem diameter, and canopy diameter of several mature Kandelia candel plants were measured. The data are summarized in the table below: Table 1 Statistics of indicators of mature Kandelia candel

[0032] The average of the canopy diameter and stem diameter was then used as the overall vegetation diameter of the Kandelia candel, which was 0.84 m. Since the planting area was entirely planted with Kandelia candel, the coverage rate was 100%, and the fragmentation rate was 0. The final parameters of the vegetation in front of the embankment are shown in Table 2.

[0033] Table 2 Vegetation parameter values

[0034] S2, calculate the wave height and water level for each return period. A schematic diagram of the technical route is shown below. Figure 6 In this example, the frequency of strong winds in the study area since 1949, as well as the water level and wave height observation records corresponding to each strong wind, were collected. The data were organized into the frequency of extreme events each year and the water level and wave height of each occurrence. A selection of the data is shown in Table 3.

[0035] Table 3 Historical observation data for the study area

[0036] Then, a composite extreme value distribution obtained by combining the Poisson and Pareto distributions is used to fit the observed data. This composite extreme value distribution filters out extreme values ​​from the observed data through a certain threshold or event. The known extreme value distribution is then used for fitting to estimate extreme values ​​at different return periods. Its advantage is that, compared to traditional generalized extreme value distribution analysis based on the block maximum method, this method does not require continuous observation data or the same amount of observation data each year. Only a certain threshold (e.g., wave height exceeding 1.5 meters) or a certain extreme event (e.g., observing a typhoon) needs to be set to filter out extreme value data under extreme events, thus avoiding the problem of excessive daily data affecting the estimation of extreme values ​​and leading to an underestimation of the extreme values.

[0037] The statistical data was processed into the number of extreme events that occurred each year (or the number of data points that exceeded the threshold each year) and extreme value data.

[0038] In this example, The average value in the second column of Table 3 is calculated as follows: The value is 3.5. The Pareto distribution is fitted using the wave height column in Table 3.

[0039] Excerpt and The values ​​of are used to illustrate the process of maximum likelihood estimation. Table 4 shows the likelihood function values ​​under different parameter values: Table 4. Likelihood function values ​​for different parameter values

[0040] Among the listed parameter values, the likelihood function is largest (-401.72) when σ is 3 and ξ is 0. Therefore, this set of parameter values ​​is selected. The table above only shows a portion of the parameter values. In the actual calculation process, more parameter values ​​were selected for comparison. Finally, it was calculated that the likelihood function is largest when σ is 5.4 and ξ is -0.62, with a value of -361.66. Therefore, this set of parameter values ​​is selected. The final calculated parameters for the composite extreme value distribution are shown in Table 5. Table 5. Values ​​of composite extreme value distribution parameters

[0041] In determining , and Subsequently, the composite extreme value distribution was calculated, and the wave heights for each return period calculated using this observation data are shown in Table 6. A schematic diagram of the principle is shown below. Figure 5 .

[0042] Table 6 Wave heights corresponding to each return period

[0043] The extreme value distribution probability calculated using the composite extreme value distribution is not significantly different from the sample frequency of the observed data. For example, the calculated 10-year return period wave height was predicted to occur 5 times in a 50-year span, and it actually occurred 5 times; the 20-year return period wave height was predicted to occur 2.5 times in a 50-year span, and it actually occurred 2 times; the 50-year return period wave height was predicted to occur once, and it actually occurred once; the 100-year return period wave height was predicted to occur no more than once, and it actually occurred once. Using the same method, the water level for each return period was calculated. Since typhoons increase wave height more significantly than water level, the water level for each return period is lower than the corresponding wave height. In this example, the protection return period requirement for the hybrid coastal protection project is designed based on a 20-year period, corresponding to a wave height of 8.07 m and a water level of 3 m.

[0044] S3: Input the vegetation parameters in front of the dike and the corresponding return period boundary into the numerical model to simulate the attenuation of waves by vegetation. See the schematic diagram below. Figure 7 The wave height of 8.07 m and the water level of 3 m are set as constant values ​​on the open boundary, with the wave direction being southeast and the wave period being 5 seconds. The vegetation parameters obtained from S1 are input into the model through the vegetation parameter matrix on each grid. The vegetation parameter matrix contains three matrices: vegetation height matrix, vegetation density matrix, and vegetation diameter matrix, defined as follows: ; Where m is the number of rows in the model mesh, and n is the number of columns in the model mesh. Let be the vegetation parameters within the grid in the i-th row and j-th column, when When it is a vegetation height matrix, The vegetation height of this grid; when When it is a vegetation density matrix, The vegetation density of this grid; when When it is a vegetation diameter matrix, This represents the vegetation diameter of the grid. The final input model consists of three matrices: the vegetation height matrix. Vegetation density matrix Vegetation diameter matrix .

[0045] The method for generating three vegetation matrices using vegetation parameters is as follows: First, select a grid within the vegetation zone. In this case, the grid is divided into 160 rows and 676 columns, and the vegetation zone is set as a rectangular area running vertically through the simulation area, i.e., columns 316 to 395 of the grid. Then, randomly select a grid within the vegetation zone, for example, the grid at row 90 and column 330; check if the grid has already been assigned vegetation parameters. If it has, select a new grid; if not, check if the surrounding grids have vegetation to simulate the patch growth process of vegetation. For the grid at row 90 and column 330, the four adjacent grids where vegetation needs to be determined are: row 89 and column 330, row 91 and column 330, row 90 and column 329, and row 90 and column 331. If at least one of the four adjacent grids has vegetation, directly assign the vegetation parameters to that grid, setting the vegetation height matrix... The value is 1.37; let the vegetation density matrix be... Let the value be 2; let the vegetation diameter matrix be... The value is 0.84; if none of the four adjacent grids have vegetation, the grid is assigned a value based on the set fragmentation level. For example, if the fragmentation level is set to 1, the grid will be set as vegetation regardless of whether it has adjacent vegetation; if the fragmentation level is 0, the grid without adjacent vegetation will definitely not be set as vegetation. Finally, check if the coverage rate meets the requirements. That is, count the number of grids set as vegetation. For example, if only one grid is set as vegetation in the first loop, divide the number of vegetation grids by the number of grids in the vegetation zone, i.e.: ; Determine if the current vegetation cover meets the requirement; at this point, 0.021% is far from 100%. Repeat the above steps until the coverage meets the requirement. Since the coverage in this instance is 100%, the final generated vegetation height matrix has columns 316 to 395 all having a value of 1.37, with the remaining columns having a value of 0. The vegetation density matrix is ​​generated similarly to the vegetation diameter matrix.

[0046] The above steps simulate the vegetation growth process. Fragmentation actually controls the probability of generating isolated vegetation patches. If the fragmentation is 0, the generated vegetation is a complete patch, with all vegetation points connected together. If the fragmentation is 1, the vegetation is randomly generated throughout the vegetation area, even if the selected grid is an isolated grid.

[0047] In this example, the wave-current coupling process is considered, where the vegetation in front of the dike participates in both the flow obstruction and wave dissipation processes. The flow obstruction effect of the vegetation is characterized by the following equation: The simulated wave height attenuation results are shown in Figure 8 The wave height in front of the dike was found to be 6.3 m, and the incident wave height was 8.07 m. The wave height attenuation caused by the vegetation in front of the dike was 1.77 m.

[0048] S4. After simulating the wave height in front of the dike, calculate the equivalent return period of vegetation. See the schematic diagram for the principle. Figure 3 The calculation equations used are those given in S4. , , , , Substitute and calculate to get The significance of vegetation equivalent return period is the amount of reduction in the return period of the seawall behind it caused by the wave height attenuation caused by the vegetation in front of the seawall.

[0049] S5, according to the return period requirement, remove the vegetation return period to obtain the required protection return period for the seawall. See Figure 7 In this case, the required return period for the rear seawall is: (Year). Use the required protection return period of the seawall to guide the design of the seawall, such as the crest elevation, etc. See [reference needed]. Figure 9 .

[0050] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0051] While the specific embodiments of the present invention have been described above, they are not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for determining wetland-seawall design parameters based on equivalent return periods, characterized in that, The process includes the following: S1, obtain the design parameters of the vegetation in front of the embankment, including the length and width of the vegetation area in front of the embankment, the planting density of the vegetation, the vegetation coverage rate of the vegetation area, the vegetation height, the vegetation diameter, and the vegetation fragmentation of the vegetation area. S2, based on local historical wave level monitoring data, uses a one-dimensional composite extreme value distribution to calculate the offshore incident wave height and water level for the design return period; the specific process includes: S21, collect historical monitoring data on local wave height and water level, and statistically analyze the frequency of extreme events that have occurred over the years and the corresponding water level and wave height for each extreme event; S22, Fit the frequency of extreme events over the years using a Poisson distribution, and calculate the Poisson distribution parameters; Poisson distribution probability distribution function. as follows: ； In the formula, e is the natural constant; k is the independent variable, representing the frequency of extreme events that occur over the years; Here are the parameters to be fitted, representing the average number of extreme events occurring per year. The calculation method is as follows: ； The frequency of extreme events in year i; The year span of the observed data; S23, use the generalized Pareto distribution to fit the water level and wave height, and calculate the generalized Pareto distribution parameters. and The calculation method uses maximum likelihood estimation; S24. The composite extreme value distribution is calculated using the fitted Poisson distribution and the generalized Pareto distribution. The offshore incident wave height and water level are calculated for the design return period. S3 uses the design parameters obtained in S1 as the model vegetation settings, and the ocean incident wave height and water level obtained in S2 as the open boundary of the model. The attenuation of waves by the vegetation in front of the dike is calculated by numerical simulation to obtain the wave height in front of the dike. S4. The wave height in front of the dike is retrieved back to its return period using local historical wave level monitoring data. The equivalent return period of vegetation, representing the protective capacity of the vegetation in front of the dike, is then calculated. Specifically, this includes: retrieving the wave height in front of the dike back to its return period using local historical wave level monitoring data; using a previously fitted one-dimensional composite extreme value distribution, the wave height in front of the dike is substituted into the extreme value distribution to calculate the probability and return period of the wave height occurrence; the equivalent return period of vegetation is the return period corresponding to the wave height resisted by the vegetation in front of the dike alone, calculated by subtracting the return period of the incident wave height from that of the open sea from the return period of the wave height in front of the dike; the calculation method is as follows: ； In the formula, The equivalent return period for vegetation; The height of incident waves over the open sea; The waves are high in front of the dike; , and These are the composite extreme value distribution parameters obtained by fitting wave height monitoring data; S5. Based on the protection return period requirements of the mixed protection project, the equivalent return period of vegetation is deducted to obtain the protection return period requirements of the seawall. These protection return period requirements guide the selection of seawall design parameters.

2. The method for determining wetland-seawall design parameters based on equivalent return period as described in claim 1, characterized in that: In S1, when the design parameters for the vegetation in front of the embankment are missing, the length and width of the vegetation area in front of the embankment are replaced by the coordinates of the boundary points of the vegetation area; the planting density of the vegetation is replaced by the planting spacing; the vegetation height parameter is calculated by collecting samples from planted vegetation and taking the average value; the vegetation diameter is calculated by taking the average diameter of the canopy and rootstock; the planting spacing is converted into the planting density of the vegetation using the following formula: ； N represents the planting density, and L represents the planting spacing.

3. The method for determining wetland-seawall design parameters based on equivalent return period as described in claim 1, characterized in that: In S23, the probability density function of the generalized Pareto distribution is as follows: ； In the formula, x is the independent variable, representing wave height in the extreme value calculation of wave height and water level in the extreme value calculation of water level; and These are also the parameters to be fitted, representing the dispersion of wave height and water level data, and the tail thickness of the extreme value distributions of water level and wave height, respectively. The likelihood function for maximum likelihood estimation is as follows: ； In the formula For water level and wave height data exceeding the threshold; M is the total number of data points; Let be the probability density function of the generalized Pareto distribution; the parameter values ​​of the generalized Pareto distribution are estimated by assuming the parameter values ​​of the wave height probability distribution to maximize the probability of obtaining the sample. In S24, the parameters calculated in S23 are used. , and The expression for the composite extreme value distribution for calculating the return period water level is as follows: ； The return period can be converted using the following formula: ； Let T be the annual probability of occurrence and T be the design return period; then the calculated... , , and Substituting these values ​​into the composite extreme value distribution expression, we can obtain the corresponding incident wave height and water level values ​​in the open sea. If the parameters substituted are the parameters to be fitted obtained from wave height monitoring data. , and The result is The ocean incident wave height under the return period T If the parameters substituted are the parameters to be fitted calculated from water level monitoring data. , and Then the result is The water level is the return period T.

4. The method for determining wetland-seawall design parameters based on equivalent return period as described in claim 1, characterized in that: The specific process of S3 is as follows: S31, set the calculated incident wave height and water level of the outer sea as the open boundary conditions of the model, and set the vegetation parameters in the model's mesh, including the vegetation height matrix, vegetation density matrix, and vegetation diameter matrix. S32 simulates the flow obstruction and wave dissipation processes caused by vegetation; the wave propagation process is simulated by solving the following equations: ； In the formula, The wave speed, For the purpose of wave dissipation by vegetation, The energy of a wave and its relationship to wave height are as follows: ； In the formula, The wave height; The density of seawater; It is the acceleration due to gravity; The flow obstruction process is simulated by solving the following equations: ； In the formula, The resistance of vegetation to water flow, This is the drag coefficient. The density of seawater, This refers to the number of plants per unit area. The diameter of the plant. The height of the plant submerged in water. For flow rate; The wave dissipation process of vegetation is characterized by the following formula: ； In the formula, The wave energy reduction per unit area per unit time. The wave number. The wave frequency, The energy of the waves; S33, extract the simulated wave height in front of the dike, and solve for the wave height of each grid in S32. Then, all grids in the area from behind the vegetation zone to in front of the seawall were selected, and the wave height simulation results of these grids were averaged to obtain the wave height in front of the seawall. .

5. The method for determining wetland-seawall design parameters based on equivalent return period as described in claim 1, characterized in that: In S5, the protective capacity of the vegetation in front of the dike is characterized by the equivalent return period of vegetation, and the protection requirements that the sea dike behind it needs to meet are the remaining part of the overall protection requirements of the mixed coastal protection project after deducting the equivalent return period of vegetation.

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