Seawall overtopping amount and overtopping risk calculation method considering mangrove forest wave dissipation effect

Abstract

The invention discloses a seawall overtopping amount and overtopping risk calculation method considering a mangrove forest wave dissipation effect, and relates to the technical field of coast engineering. The method comprises the following steps: acquiring typhoon path data, inputting the typhoon path data into a Holland typhoon empirical model, and accurately generating a typhoon wind field; calculating coastal site tide level data in combination with a coastal storm surge numerical model; obtaining wave data during a typhoon by using a storm surge typhoon wave forecasting model based on the SWAN; historical typhoon data and relevant information of the seawall and the mangrove forest are collected, a water level-wave-vegetation-seawall coupling model is constructed, the wave dissipation effect of the mangrove forest is accurately simulated, and wave characteristic calculation is optimized; constructing a database, training the database through a CNN neural network model, and improving the prediction precision of seawall front wave height and wave force parameters; the wave overtopping amount is calculated based on the prediction parameters, a scientific basis is provided for wave overtopping risk assessment, it is ensured that real-time assessment of the wave overtopping risk is more accurate and efficient, and the disaster prevention and reduction capacity is effectively improved.

Description

Technical Field

[0001] The invention relates to the technical field of coastal engineering, and in particular to a method for calculating the overtopping amount and overtopping risk of a seawall taking into account the wave-breaking effect of mangroves. Background Art

[0002] The occurrence of extreme weather events such as typhoons and storm surges has brought great challenges to coastal protection. As an important coastal defense project, seawalls have long played a vital role in preventing seawater intrusion and protecting coastal areas from flood threats. Traditional seawall protection design mainly relies on engineering means, and the protection effect is limited for the risk of overtopping in extreme weather. Seawall overtopping not only increases the risk of damage to coastal infrastructure, but also threatens the stability of the coastal ecological environment.

[0003] In recent years, mangroves, as a natural ecological barrier, have attracted widespread attention due to their significant wave-breaking effect. Mangroves can effectively mitigate the energy of waves through complex root systems and vegetation structures, reduce the direct impact of waves on seawalls, and thus reduce the amount of overtopping. Therefore, fully considering the ecological role of mangroves and combining them with seawall protection design can significantly improve the protection capacity of seawalls. However, there are currently few studies on the application of mangroves' wave-breaking effect in seawall protection, and there is a lack of systematic calculation methods to evaluate their mitigation effect on overtopping risks under different conditions. Summary of the invention

[0004] In response to the above problems, the present invention proposes a method for calculating the overtopping amount and overtopping risk of seawalls that takes into account the wave-breaking effect of mangroves. The method aims to provide a more effective coastal protection solution by combining the natural disaster reduction function of mangroves with seawall engineering design, thereby enhancing the ability of coastal areas to cope with extreme climates.

[0005] In order to achieve the above object, the present invention is implemented by the following technical solutions:

[0006] A method for calculating seawall overtopping and overtopping risk considering the wave-breaking effect of mangroves, the method comprising:

[0007] Acquire typhoon path data according to the typhoon number, wherein the typhoon path data includes the longitude, latitude, minimum air pressure at the typhoon center, and maximum wind speed at the typhoon center at each time point;

[0008] The typhoon path data is input into the Holland typhoon empirical model to generate a corresponding typhoon wind field, and the typhoon wind field data is used to drive the coastal storm surge numerical model to obtain the tide level data of the nearshore location;

[0009] Inputting typhoon wind field data into the storm surge typhoon wave forecast model based on SWAN to obtain wave data of the research site during the typhoon period, wherein the wave data includes significant wave height, wave period, wavelength and wave direction;

[0010] Collect historical typhoon data, seawall information and mangrove related information in the sea area where the research site is located;

[0011] Construct a coupled model of water level-wave-vegetation-seawall, simulate the wave-reducing effect of mangroves, and calculate wave data;

[0012] Build a database to store the output results of the coupling model, and store typhoon path data, typhoon wind field data, nearshore tide data, wave data, historical typhoon data, seawall information, and mangrove related information. Train the data in the database based on the CNN neural network model to obtain the predicted values ​​of wave height and wave force parameters in front of the seawall.

[0013] Combining the predicted values ​​of wave height and wave force parameters in front of the seawall, the seawall overtopping amount is calculated using the formula;

[0014] Assess the overtopping risk based on the calculated seawall overtopping amount.

[0015] As a preferred solution of the present invention, the Holland typhoon empirical model consists of an air pressure model and a wind field model, wherein the expression of the air pressure model is:

[0016] ;

[0017] In the formula, Indicates the distance from the typhoon center under the influence of the typhoon The air pressure at is the distance from the calculation point to the typhoon center; is the maximum wind speed radius, is the Holland pressure profile parameter; The lowest air pressure in the center of a typhoon; is the outer pressure of the typhoon;

[0018] The expression of the wind field model is:

[0019] ;

[0020] In the formula, Indicates distance The gradient wind speed at is the air density; is the Coriolis force;

[0021] The coastal storm surge numerical model is constructed based on ADCIRC;

[0022] The nearshore tidal data are specifically real-time tidal data at locations 1-2 km from the shore, which is achieved by screening grid points within a distance range of 1-2 km from the shore of the target area and aggregating the tidal data within the grid points.

[0023] As a preferred solution of the present invention, the storm surge typhoon wave forecast model based on SWAN is expressed in a rectangular coordinate system as follows:

[0024] ;

[0025] In the formula, is the wave action density; For time, , is the geographic coordinate, is the relative wave frequency, is the wave direction; and is the component of wave propagation velocity in direction and , and For the waves and The speed of propagation in space, is the wave energy density;

[0026] The wave energy density It is expressed as:

[0027] ;

[0028] In the formula, represents the input of wind energy, , They represent the wave energy exchange caused by the third and fourth order nonlinear interactions, , , They represent the wave energy dissipation caused by whitecaps, bottom friction and wave breaking respectively.

[0029] As a preferred solution of the present invention, the historical typhoon data includes: typhoon number, occurrence time, duration, longitude and latitude information, minimum air pressure at the typhoon center, maximum wind speed at the typhoon center, typhoon path, affected area, and wave parameters of the corresponding wave field;

[0030] The seawall information includes: seawall location, historical flood control records, cross-section structure type, face protection type, and design parameters of the seawall top elevation, seawall top width, face protection structure, slope, slope shoulder width, and bottom slope;

[0031] The mangrove-related information includes: canopy size, canopy density, root diameter, root height, root density, stem diameter, stem height, stem density and the integrity of the three parts of roots, stems and leaves.

[0032] As a preferred solution of the present invention, the water level-wave-vegetation-seawall coupling model is constructed based on the SWASH model;

[0033] The SWASH model uses nonlinear shallow water equations, which are derived directly from the incompressible Reynolds-averaged Navier-Stokes equations and include non-hydrostatic pressure terms; for the propagation of waves in the vertical two-dimensional xz plane, the expression of the nonlinear shallow water equations is as follows:

[0034] Continuity equation:

[0035] ;

[0036] The momentum equation in the x direction is:

[0037] ;

[0038] Momentum equation in z direction:

[0039] ;

[0040] In the formula, is the velocity component in the x direction; is the velocity component in the z direction; Indicates time; Indicates the water density; , represent the components of the turbulent stress in the x direction and the z direction respectively; , denote the components of the turbulent stress in the z direction in the x and z directions, respectively; is the pressure item;

[0041] The hydrostatic pressure is expressed as a function of the free surface, so the pressure term It is expressed as:

[0042] ;

[0043] In the formula, represents the hydrostatic pressure, represents the free surface, represents the acceleration due to gravity, represents non-hydrostatic pressure;

[0044] The SWASH model generalizes vegetation into a rigid cylinder and calculates the drag force exerted by vegetation on the water body through the Morrison equation. The horizontal component of the drag force acting on the unit volume of vegetation is expressed as:

[0045] ;

[0046] In the formula, is the plant drag coefficient; is the plant height; is the plant diameter; is the number of plants per unit area;

[0047] Among them, the plant drag coefficient Directly set by humans.

[0048] As a preferred solution of the present invention, considering the influence of wave period, the plant drag force coefficient It can also be derived through the following expression:

[0049] ;

[0050] In the formula, Indicated by characteristic diameter The calculated Keuglan-Carpenter number.

[0051] As a preferred solution of the present invention, the CNN neural network is used to train the data in the database to obtain the predicted values ​​of the wave height and wave force parameters in front of the seawall. The method specifically includes:

[0052] Preprocess the input data to ensure that all input data have consistent dimensions through normalization, standardization, and missing value processing;

[0053] Initialize the CNN neural network architecture, including convolutional layers, pooling layers, and fully connected layers, and use the deep learning framework to automatically initialize the weight parameters of the convolution kernel and fully connected layers;

[0054] The preprocessed data is input into the CNN neural network, which is sequentially passed through the convolution layer to extract local features, the pooling layer to perform downsampling, and the fully connected layer to perform feature combination, and finally the predicted values ​​of the wave height and wave force parameters in front of the seawall are output;

[0055] Compare the predicted value output by the CNN neural network model with the true observed value, select the mean square error MSE as the loss function, calculate the error between the predicted value and the true observed value, calculate the gradient through the back propagation algorithm, use the gradient descent method to update the model weight parameters, gradually reduce the loss value, and after each training round, evaluate the generalization ability of the model through the validation set to ensure that the model will not overfit;

[0056] After completing the predetermined number of iterations, the performance of the model is evaluated using the validation set and the test set, and the mean square error (MSE) and correlation coefficient (CC) between the predicted value and the true observed value are calculated to quantify the model performance.

[0057] As a preferred solution of the present invention, the calculation of seawall overtopping amount by using a formula specifically includes:

[0058] When the working conditions meet the following 6 applicable conditions at the same time:

[0059] ,in For water depth, is the effective wave height;

[0060] ,in Indicated by the peak period Calculated deep water wavelength, , is the average wave period;

[0061] ,in is the slope of the seawall;

[0062] ,in is the shoulder width;

[0063] ,in It is the height of the seawall crest above the still water level;

[0064] ,in It represents the bottom slope ratio;

[0065] For a slope embankment without a wave-breaking wall, the calculation formula for the seawall overtopping is:

[0066] ;

[0067] In the formula, It indicates the amount of seawall overtopping; is the empirical coefficient, is the influence coefficient of the protective structure; represents the acceleration due to gravity;

[0068] For a slope embankment with a wave-breaking wall, the calculation formula for the seawall overtopping is:

[0069] ;

[0070] In the formula, is the empirical coefficient, It is the height of the top of the wave-breaking wall above the still water surface;

[0071] For a composite slope embankment with a straight wall at the bottom, a slope at the top and a platform in the middle, the calculation formula for the seawall overtopping is:

[0072] ;

[0073] In the formula, to is the correction factor function, which is defined as follows:

[0074] ;

[0075] ;

[0076] ;

[0077] ;

[0078] ;

[0079] ;

[0080] In the formula, , are the slopes below and above the platform, respectively, and satisfy , ; is the water depth on the platform, which takes a positive value when the platform is below the static water level and a negative value when the platform is above the static water level;

[0081] When the working conditions cannot meet the above 6 conditions at the same time, and the seawall slope When considering the safety of the project, the method with a confidence level of 95% is used to calculate the seawall overtopping amount. The formula is:

[0082] ;

[0083] In the formula, is the pressure item; The wave height is 13% of the cumulative amount;

[0084] The seawall slope The waves rise Depend on =1.25 and =1.5 at both ends The values ​​are determined by interpolation:

[0085] =1.25, ;

[0086] =1.5, , , is the wave breaking parameter with a cumulative rate of 1%, is the wave height with an accumulation rate of 1%;

[0087] When the working conditions cannot meet the above 6 conditions at the same time and the seawall slope is not satisfied hour:

[0088] The calculation formula for the seawall overtopping of the slope embankment is:

[0089] ;

[0090] In the formula, , b, c are fitting coefficients; is super high, and 0;

[0091] For both cases without wave breaking and with wave breaking, use the following modified formula for calculation:

[0092] With breaking wave: ;

[0093] Unbroken Waves: ;

[0094] In the formula, is the wave breaking coefficient, ; is the front slope; is the deep water wavelength; The factors affecting the platform are: is the influencing factor of slope roughness, is the influence factor of oblique incident wave, Factors affecting breast wall: It is a comprehensive influencing factor;

[0095] For the two types of seawalls, straight slope and impermeable slope, the wave overrunning behavior is affected by surface roughness, shallow water, oblique waves and short-peak waves. The wave overtopping and breaking modes are classified to calculate the seawall overtopping amount:

[0096] When the wave breaking coefficient When , the calculation formula is:

[0097] ;

[0098] In the formula, For steep slopes, , the scope of application is: ;

[0099] When the wave breaking coefficient When , the calculation formula is:

[0100] ;

[0101] The calculation formula for the seawall overtopping of a straight wall seawall is:

[0102] ;

[0103] The small platform built at the toe of the dike will change the breaking characteristics of the waves. The overtopping of the seawall with this structure is calculated in the following two cases:

[0104] when hour, ;

[0105] when hour, ;

[0106] In the formula, is the height of the embankment crest;

[0107] Considering the influence of oblique incident waves on the overtopping of straight-wall seawalls, the calculation formula for the overtopping of non-broken seawalls is:

[0108] ;

[0109] The calculation formula for the overtopping of a broken seawall is:

[0110] ;

[0111] In the formula, is the oblique incidence factor, is the incident wave angle The impact of the wave is greater than the is the breaking overtopping amount of the normal incident wave;

[0112] The water depth is shallow at the foreshore, In the case of , at this time, the calculation formula for the seawall overtopping is:

[0113] ;

[0114] This formula applies to the wave breaking coefficient And the slope is steep situation;

[0115] The overflow phenomenon in the case of negative superelevation requires further consideration of the overflow volume, the total amount of water flowing to the land side of the structure Overflow and seawall overtopping , for wide top structure, the overflow The calculation formula is:

[0116] ;

[0117] In the formula, It is negative super high;

[0118] Calculate seawall overtopping When, super high The value is 0. Value, and overflow Add together to get the total amount of water flowing to the land side of the structure , expressed as:

[0119] .

[0120] As a preferred solution of the present invention, the method for assessing the overtopping risk based on the calculated seawall overtopping amount comprises:

[0121] The dimensionless overtopping amount and dimensionless seawall superelevation are calculated for the sloped seawall section overtopping test data set, respectively, using the formula:

[0122] ;

[0123] ;

[0124] In the formula, is the dimensionless overtopping amount; is the dimensionless seawall superelevation; It indicates the amount of seawall overtopping; is the deep water wavelength; is the front slope; represents the acceleration due to gravity; is the effective wave height; The factors that influence the platform; is super high; is the wave breaking coefficient; is the influencing factor of slope roughness; is the factor affecting the oblique incident wave; Factors affecting breast wall;

[0125] Combined with the European Overtopping Manual, the single value forecast is calculated using the formula:

[0126]

[0127] Dimensionless overtopping and dimensionless seawall superelevation Substitute into the single-value prediction formula, and the dimensionless overtopping amount calculated value is The calculation formula is:

[0128] ;

[0129] Dimensionless overtopping amount calculated from the overtopping test data set of the sloped seawall section , dimensionless seawall superelevation and dimensionless overtopping discharge calculation value The regularity and divergence shown are used to establish the empirical distribution of overtopping probability and introduce the coefficient ,make ,in represents any dimensionless overtopping value;

[0130] Utilization coefficient Any dimensionless overtopping value Expressed as dimensionless overtopping amount calculation value of After times, establish the coefficient and overtopping probability The relationship between and dimensionless overtopping discharge calculation value Corresponding Value, calculation The exceedance probability of the value distribution is arranged in order from large to small, and the following function is fitted:

[0131] ;

[0132] Calculate the overtopping exceedance probability When The value is obtained using the following formula:

[0133] ;

[0134] In the formula, It indicates the seawall overtopping capacity standard specified when designing the seawall.

[0135] The beneficial effects of the present invention are as follows: by acquiring typhoon path data and inputting the Holland typhoon empirical model, the typhoon wind field is accurately generated to provide basic data support for subsequent analysis; in combination with the coastal storm surge numerical model, the tide level data of nearshore locations is calculated to accurately reflect the sea level change; using the storm surge typhoon wave forecast model based on SWAN, wave data during the typhoon is obtained to lay a foundation for wave impact analysis; historical typhoon data, seawall and mangrove related information are collected to ensure the comprehensiveness and accuracy of the data; a water level-wave-vegetation-seawall coupling model is constructed to accurately simulate the wave-breaking effect of mangroves and optimize the calculation of wave characteristics; a comprehensive database is constructed, and the database is trained through a CNN neural network model to improve the prediction accuracy of wave height and wave force parameters before the seawall; compared with the traditional model method, the CNN neural network can quickly learn complex nonlinear relationships, improve the accuracy and efficiency of the model in overtopping amount prediction, and greatly shorten the training time of the model; the overtopping amount is calculated based on the predicted parameters to provide a scientific basis for overtopping risk assessment, and ensure that the real-time assessment of overtopping risk is more accurate and efficient. Through multi-model, multi-data fusion and deep learning technology, this technical solution achieves high-precision simulation and risk assessment of the wave-breaking effect of mangroves and the overtopping of seawalls, providing scientific guidance for coastal protection design and disaster warning, and effectively improving disaster prevention and mitigation capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0136] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0137] Figure 1 is a flow chart of the method of the present invention;

[0138] Figure 2 A schematic diagram of an unstructured grid used in a storm surge typhoon wave forecast model based on SWAN in an embodiment of the present invention;

[0139] Figure 3 Schematic diagram of the calculation domain of the water level-wave-vegetation-seawall coupling model in an embodiment of the present invention. DETAILED DESCRIPTION

[0140] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0141] like Figure 1-Figure 3 FIG. 1 is an embodiment of the present invention, which provides a method for calculating the overtopping amount and overtopping risk of a seawall taking into account the wave-breaking effect of mangroves, comprising the following steps:

[0142] S1: Obtain typhoon path data according to the typhoon number, including the longitude, latitude, minimum air pressure at the typhoon center, and maximum wind speed at the typhoon center at each time point;

[0143] In one embodiment, step S1 specifically includes:

[0144] S11: Obtain JSON data containing all tropical cyclone information by accessing the URL interface of the Central Meteorological Observatory;

[0145] S12: Obtain the typhoon number, typhoon name (in Chinese and English) and typhoon status information of all active typhoons by parsing JSON data;

[0146] S13: According to the obtained typhoon number, further access the specific typhoon data interface provided by the Central Meteorological Observatory, and obtain JSON data containing detailed information of the typhoon at different time points by constructing the corresponding URL, and parse to obtain multiple time point information of the typhoon path, including the longitude, latitude, minimum air pressure at the typhoon center, maximum wind speed at the typhoon center and other parameters of the typhoon at each time point;

[0147] S14: Convert the UTC (Universal Time Coordinated) corresponding to the typhoon path data into CST (China Standard Time), and combine the real-time data with the forecast data to form a detailed information table containing the typhoon path, and mark the time point information as existing data or predicted data. The preparation data can be directly input into the Holland typhoon empirical model later.

[0148] S2: Input typhoon path data into the Holland typhoon empirical model to generate the corresponding typhoon wind field, use the typhoon wind field data to drive the coastal storm surge numerical model, and obtain the tide level data of nearshore locations;

[0149] Specifically, the Holland typhoon empirical model consists of a pressure model and a wind field model, where the pressure model is expressed as:

[0150] ;

[0151] In the formula, Indicates the distance from the typhoon center under the influence of the typhoon The air pressure at is the distance from the calculation point to the typhoon center; is the maximum wind speed radius, is the Holland pressure profile parameter; The lowest air pressure in the center of a typhoon; is the outer pressure of the typhoon;

[0152] The expression of the wind field model is:

[0153] ;

[0154] In the formula, Indicates distance The gradient wind speed at is the air density; is the Coriolis force.

[0155] Furthermore, the numerical model of coastal storm surge is constructed based on ADCIRC (An Advanced Circulation ModelFor Oceanic, Coastal and Estuarine Waters);

[0156] The tide data for nearshore locations refers to the real-time tide data for locations 1-2 km from the shore. This is achieved by screening grid points within a distance of 1-2 km from the shore in the target area and aggregating their water level (tide) data. One specific implementation method includes:

[0157] SMS software was used to build an unstructured grid with a grid range of 105.0°E-121.0°E, 12.0°N-25.0°N, and about 37,000 grids.

[0158] Combined with the grid-driven coastal storm surge numerical model built based on ADCIRC, tide level data of all nodes are obtained;

[0159] Specify the ID and offshore distance range of the target point on the shoreline, and use the Geopy library to calculate the geographic distance between each grid point and the target point;

[0160] During the screening process, ensure that the distance between each grid point and all designated shoreline target points meets the distance requirement of 1-2 km;

[0161] Finally, the ID, longitude, latitude and water depth information of the filtered grid points are obtained.

[0162] S3: Input the typhoon wind field data into the storm surge typhoon wave forecast model based on SWAN (Simulating Waves Nearshore) to obtain the wave data of the research site during the typhoon, including significant wave height, wave period, wavelength, wave direction, etc.; like Figure 2 As shown in the figure, an unstructured grid was built using SMS software. The grid range is 105.0°E-121.0°E, 12.0°N-25.0°N, and the number of grids is about 37,000. It can accurately simulate the complex interaction process between rivers and oceans in the core area. The grid division along the coastline and in areas with complex terrain is relatively fine, and the unit scale is small, aiming to improve local accuracy. In deep sea areas far from the coast, the grid cells are relatively large, thereby reducing the computational load.

[0163] In a specific embodiment, the storm surge typhoon wave forecast model based on SWAN is expressed in a rectangular coordinate system as follows:

[0164] ;

[0165] In the formula, is the wave action density; For time, , is the geographic coordinate, is the relative wave frequency, is the wave direction; and The wave propagation speed is and The weight in direction, and For the waves and The speed of propagation in space, is the wave energy density;

[0166] The wave energy density It is expressed as:

[0167] ;

[0168] In the formula, represents the input of wind energy, , They represent the wave energy exchange caused by the third and fourth order nonlinear interactions, , , They represent the wave energy dissipation caused by whitecaps, bottom friction and wave breaking respectively.

[0169] S4: Collect historical typhoon data, seawall information and mangrove related information in the sea area where the research site is located;

[0170] Specifically, historical typhoon data include: typhoon number, occurrence time, duration, longitude and latitude information, minimum air pressure at the typhoon center, maximum wind speed at the typhoon center, typhoon path, affected area, and wave parameters of the corresponding wave field;

[0171] Seawall information includes: seawall location, historical flood control records, cross-section structure type, face protection type, and design parameters such as levee crest elevation, crest width, face protection structure, slope, shoulder width, and bottom slope;

[0172] Information related to mangroves includes: canopy size, canopy density, root diameter, root height, root density, stem diameter, stem height, stem density, and the integrity of the three parts of roots, stems and leaves.

[0173] S5: Construct a coupled model of water level-wave-vegetation-seawall, simulate the wave-reducing effect of mangroves, and calculate wave data;

[0174] In one of the embodiments, the coupled model of water level-wave-vegetation-seawall is constructed based on the SWASH model (Simulating WAves till Shore, non-hydrostatic equation model); like Figure 3 As shown in the figure, the left side is the open-boundary wave-making area, which is used to generate the wave input conditions in the simulation, so that the waves propagate to the right to the inner area of ​​the calculation domain; the vegetation area is between the wave-making area and the foot of the seawall, which is used to simulate the reduction effect of coastal vegetation on wave propagation; the foot of the seawall is located between the vegetation area and the seawall, and is the key transition area before the wave reaches the seawall; the seawall area is located on the far right of the calculation domain, which is used to simulate the response of the seawall structure to waves.

[0175] The SWASH model uses nonlinear shallow water equations, which are derived directly from the incompressible Reynolds-averaged Navier-Stokes (RANS) equations and include non-hydrostatic pressure terms; for the propagation of waves in the vertical two-dimensional xz plane, the expression of the nonlinear shallow water equations is as follows:

[0176] Continuity equation:

[0177] ;

[0178] The momentum equation in the x direction is:

[0179] ;

[0180] Momentum equation in z direction:

[0181] ;

[0182] In the formula, is the velocity component in the x direction; is the velocity component in the z direction; Indicates time; Indicates the water density; , represent the components of the turbulent stress in the x direction and the z direction respectively; , denote the components of the turbulent stress in the z direction in the x and z directions, respectively; is the pressure item;

[0183] The hydrostatic pressure is expressed as a function of the free surface, so the pressure term It is expressed as:

[0184] ;

[0185] In the formula, represents the hydrostatic pressure, represents the free surface, represents the acceleration due to gravity, represents non-hydrostatic pressure;

[0186] The SWASH model generalizes vegetation into a rigid cylinder and calculates the drag force exerted by vegetation on the water body through the Morison equation. The horizontal component of the drag force acting on the unit volume of vegetation is expressed as:

[0187] ;

[0188] In the formula, is the plant drag coefficient; is the plant height; is the plant diameter; is the number of plants per unit area;

[0189] Among them, the plant drag coefficient Directly set by humans.

[0190] Further, in a specific embodiment, the plant drag coefficient and Reynolds number Compared with the relationship between The relationship with the Keuglan-Carpenter (KC) number takes into account the influence of wave period and is more suitable for reciprocating flow. Calculated and plant drag coefficient The correlation is better.

[0191] According to Kobayashi et al. Empirical formula: (Parameters A, B and E are constants). In this embodiment, the parameters A, B and E are continuously modified and adjusted during the fitting process to obtain the following plant drag coefficient that is more suitable for the mangrove model: The expression is:

[0192] ;

[0193] In the formula, Indicated by characteristic diameter The calculated Keuglan-Carpenter number.

[0194] S6: Build a database, train the data in the database based on the CNN neural network model, and obtain the predicted values ​​of wave height and wave force parameters in front of the seawall;

[0195] The database is used to store the output results of the coupling model, as well as typhoon path data, typhoon wind field data, nearshore tide data, wave data, as well as historical typhoon data, seawall information and mangrove related information;

[0196] The data structure of the database includes:

[0197] Table structure: It adopts relational database design and is divided into multiple tables (such as typhoon data table, wave data table, environmental parameter table, etc.), and is associated through foreign keys to facilitate query and data integration;

[0198] Time series: Ensure that historical data is arranged in chronological order to facilitate model training and time series analysis.

[0199] In one embodiment, the data in the database are trained based on the CNN neural network model to obtain the predicted values ​​of wave height and wave force in front of the seawall. The method specifically includes:

[0200] S61: Preprocess the input data to ensure the consistency of dimensions of all input data through normalization, standardization and missing value processing;

[0201] S62: Initialize the CNN neural network architecture, including convolutional layers, pooling layers, and fully connected layers, and use the deep learning framework to automatically initialize the weight parameters of the convolution kernel and fully connected layers;

[0202] S63: The preprocessed data is input into the CNN neural network, and the convolution layer is used to extract local features, the pooling layer is used for downsampling, and the fully connected layer is used for feature combination, and finally the predicted values ​​of the wave height and wave force parameters in front of the seawall are output;

[0203] S64: Compare the predicted value output by the CNN neural network model with the true observed value, select the mean square error MSE as the loss function, calculate the error between the predicted value and the true observed value, calculate the gradient through the back propagation algorithm, use the gradient descent method (Adam optimizer) to update the model weight parameters, gradually reduce the loss value, and evaluate the generalization ability of the model through the validation set after each training round to ensure that the model will not overfit;

[0204] S65: After completing the predetermined number of iterations, the performance of the model is evaluated using the validation set and the test set, and the mean square error (MSE) and correlation coefficient (CC) between the predicted value and the true observed value are calculated to quantify the model performance.

[0205] S7: Combine the predicted values ​​of wave height and wave force parameters in front of the seawall and use the formula to calculate the seawall overtopping, including:

[0206] S71: When the operating conditions meet the following 6 applicable conditions at the same time:

[0207] ,in For water depth, is the effective wave height;

[0208] ,in Indicated by the peak period Calculated deep water wavelength, , is the average wave period;

[0209] ,in is the slope of the seawall;

[0210] ,in is the shoulder width;

[0211] ,in It is the height of the seawall crest above the still water level;

[0212] ,in It represents the bottom slope ratio;

[0213] There are three situations for discussion:

[0214] 1) For a slope embankment without a wave-breaking wall, the calculation formula for the seawall overtopping is:

[0215] ;

[0216] In the formula, It indicates the amount of seawall overtopping; is the empirical coefficient, is the influence coefficient of the protective structure; represents the acceleration due to gravity;

[0217] 2) For a slope embankment with a wave-breaking wall, the calculation formula for the seawall overtopping is:

[0218] ;

[0219] In the formula, is the empirical coefficient, It is the height of the top of the wave-breaking wall above the still water surface;

[0220] 3) For specific composite cases, such as a composite slope embankment with a straight wall at the bottom, a slope at the top and a platform in the middle, the calculation formula for the seawall overtopping is:

[0221] ;

[0222] In the formula, is the overtopping amount; to is the correction factor function, which is defined as follows:

[0223] ;

[0224] ;

[0225] ;

[0226] ;

[0227] ;

[0228] ;

[0229] In the formula, , are the slopes below and above the platform, respectively, and satisfy , ; is the water depth on the platform, which takes a positive value when the platform is below the static water level and a negative value when the platform is above the static water level;

[0230] S72: If the conditions in S71 cannot be met, that is, the working condition cannot meet the above 6 conditions at the same time, and the seawall slope hour:

[0231] Considering the safety of the project, the 95% confidence level method is used to calculate the seawall overtopping amount. The formula is:

[0232] ;

[0233] In the formula, is the pressure item; The wave run-up is 13% of the cumulative amount and is calculated as follows:

[0234] When the seawall slope hour, ;

[0235] When the seawall slope hour, , , is the wave breaking parameter with a cumulative rate of 1%, is the wave height with an accumulation rate of 1%;

[0236] The seawall slope The waves rise Depend on =1.25 and =1.5 The value is determined by interpolation, that is, according to =1.25 and =1.5 , The two values ​​are determined by interpolation;

[0237] S73: If the conditions in S72 cannot be met, that is, the working condition cannot simultaneously meet the above 6 conditions and does not meet the seawall slope hour:

[0238] The discussion is divided into the following four situations:

[0239] 1) The calculation formula for the seawall overtopping of a sloped seawall is:

[0240] ;

[0241] In the formula, , b, c are fitting coefficients, and the fitting coefficients are determined by various influencing factors; is super high, and 0;

[0242] For both cases without wave breaking and with wave breaking, use the following modified formula for calculation:

[0243] With breaking wave: ;

[0244] Unbroken Waves: ;

[0245] In the formula, is the wave breaking coefficient, is the front slope; is the deep water wavelength; Factors affecting the platform (such as berm), is the influencing factor of slope roughness, is the factor affecting the oblique incident wave, Factors affecting breast wall: is a comprehensive influencing factor (used for breastwork, trail, hawk beak and other combinations);

[0246] For the two types of seawalls, straight slope and impermeable slope, the wave overrunning behavior is affected by surface roughness, shallow water, oblique waves and short-peak waves. The wave overtopping and breaking modes are classified to calculate the seawall overtopping amount:

[0247] When the wave breaking coefficient When , the calculation formula is:

[0248] ;

[0249] In the formula, For steep slopes, , the scope of application is: ;

[0250] When the wave breaking coefficient When , the calculation formula is:

[0251] ;

[0252] At the same time, the reduction parameters of the two can be used uniformly;

[0253] 2) The calculation formula for the seawall overtopping of a straight wall seawall is:

[0254] ;

[0255] The original calculation formulas for straight-wall seawalls and sloped seawalls are the same, but the fitting coefficients will change after correction in different situations. Building a small platform at the toe of the seawall will change the breaking characteristics of the waves. The overtopping of the seawall with this structure is calculated in the following two cases:

[0256] when hour, ;

[0257] when hour, ;

[0258] In the formula, is the height of the embankment crest;

[0259] Considering the influence of oblique incident waves on the overtopping of the straight-wall seawall, the calculation formula for the overtopping of the non-broken seawall is:

[0260] ;

[0261] The calculation formula for the overtopping of a broken seawall is:

[0262] ;

[0263] In the formula, is the oblique incidence factor, is the incident wave angle The impact of the wave is greater than the is the breaking overtopping amount of the normal incident wave;

[0264] 3) The water depth is shallow at the foreshore, i.e. In the case of , at this time, the calculation formula for the seawall overtopping is:

[0265] ;

[0266] This formula applies to the wave breaking coefficient And the slope is steep situation;

[0267] 4) When overflow occurs under negative superelevation, the overflow volume needs to be further considered, that is, the total amount of water flowing to the land side of the structure. Overflow and seawall overtopping , for wide top structure, the overflow The calculation formula is:

[0268] ;

[0269] In the formula, It is negative super high;

[0270] Calculate seawall overtopping When, super high The value is 0. Value, and overflow Add together to get the total amount of water flowing to the land side of the structure , expressed as:

[0271] .

[0272] S8: Assess the overtopping risk based on the calculated seawall overtopping volume, including:

[0273] S81: Calculate the dimensionless overtopping amount and dimensionless seawall superelevation for the sloped seawall section overtopping test data set, respectively, using the formula:

[0274] ;

[0275] ;

[0276] In the formula, is the dimensionless overtopping amount; is the dimensionless seawall superelevation; It indicates the amount of seawall overtopping; is the deep water wavelength; is the front slope; represents the acceleration due to gravity; is the effective wave height; The factors that influence the platform; is super high; is the wave breaking coefficient; is the influencing factor of slope roughness; is the factor affecting the oblique incident wave; Factors affecting breast wall;

[0277] S82: Calculate single value forecasts in conjunction with the European Overtopping Manual using the formula:

[0278]

[0279] S83: Dimensionless overtopping and dimensionless seawall superelevation Substitute into the single-value prediction formula, and the dimensionless overtopping amount calculated value is The calculation formula is:

[0280] ;

[0281] S84: Dimensionless overtopping load calculated from an experimental dataset of overtopping on a sloped seawall section , dimensionless seawall superelevation and dimensionless overtopping discharge calculation value The regularity and divergence shown are used to establish the empirical distribution of overtopping probability and introduce the coefficient ,make ,in represents any dimensionless overtopping value;

[0282] S85: Utilization coefficient Any dimensionless overtopping value Expressed as dimensionless overtopping amount calculation value of After times, establish the coefficient and overtopping probability The relationship between and dimensionless overtopping discharge calculation value Corresponding Value, calculation The exceedance probability of the value distribution is arranged in order from large to small, and the following function is fitted:

[0283] ;

[0284] Calculate the overtopping exceedance probability When The value is obtained using the following formula:

[0285] ;

[0286] In the formula, It indicates the seawall overtopping capacity standard specified when designing the seawall.

[0287] In summary, the present invention obtains typhoon path data and inputs the Holland typhoon empirical model to accurately generate a typhoon wind field, providing basic data support for subsequent analysis; combines the coastal storm surge numerical model to calculate the tide data of nearshore locations, accurately reflecting the sea level changes; uses the storm surge typhoon wave forecast model based on SWAN to obtain wave data during the typhoon, laying the foundation for wave impact analysis; collects historical typhoon data, seawall and mangrove related information to ensure the comprehensiveness and accuracy of the data; constructs a water level-wave-vegetation-seawall coupling model to accurately simulate the wave-breaking effect of mangroves and optimize the calculation of wave characteristics; constructs a comprehensive database, trains the database through the CNN neural network model, and improves the prediction accuracy of wave height and wave force parameters before the seawall; compared with the traditional model method, the CNN neural network can quickly learn complex nonlinear relationships, improve the accuracy and efficiency of the model in overtopping amount prediction, and greatly shorten the training time of the model; calculates the overtopping amount based on the predicted parameters, provides a scientific basis for overtopping risk assessment, and ensures that the real-time assessment of overtopping risk is more accurate and efficient. Through multi-model, multi-data fusion and deep learning technology, this technical solution achieves high-precision simulation and risk assessment of the wave-breaking effect of mangroves and the overtopping of seawalls, providing scientific guidance for coastal protection design and disaster warning, and effectively improving disaster prevention and mitigation capabilities.

[0288] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for calculating seawall overtopping and overtopping risk considering the wave-breaking effect of mangroves, characterized in that: The method comprises: Acquire typhoon path data according to the typhoon number, wherein the typhoon path data includes the longitude, latitude, minimum air pressure at the typhoon center, and maximum wind speed at the typhoon center at each time point; The typhoon path data is input into the Holland typhoon empirical model to generate a corresponding typhoon wind field, and the typhoon wind field data is used to drive the coastal storm surge numerical model to obtain the tide level data of the nearshore location; Inputting typhoon wind field data into the storm surge typhoon wave forecast model based on SWAN to obtain wave data of the research site during the typhoon period, wherein the wave data includes significant wave height, wave period, wavelength and wave direction; Collect historical typhoon data, seawall information and mangrove related information in the sea area where the research site is located; Construct a coupled model of water level-wave-vegetation-seawall, simulate the wave-reducing effect of mangroves, and calculate wave data; Build a database to store the output results of the coupling model, and store typhoon path data, typhoon wind field data, nearshore tide data, wave data, historical typhoon data, seawall information, and mangrove related information. Train the data in the database based on the CNN neural network model to obtain the predicted values ​​of wave height and wave force parameters in front of the seawall. Combining the predicted values ​​of wave height and wave force parameters in front of the seawall, the seawall overtopping amount is calculated using the formula; Assess the overtopping risk based on the calculated seawall overtopping amount.

2. The method for calculating seawall overtopping and overtopping risk considering the wave-breaking effect of mangroves according to claim 1 is characterized in that: The Holland typhoon empirical model consists of a pressure model and a wind field model, wherein the pressure model is expressed as: ； In the formula, Indicates the distance from the typhoon center under the influence of the typhoon The air pressure at is the distance from the calculation point to the typhoon center; is the maximum wind speed radius, is the Holland pressure profile parameter; The lowest air pressure in the center of a typhoon; is the outer pressure of the typhoon; The expression of the wind field model is: ； In the formula, Indicates distance The gradient wind speed at is the air density; is the Coriolis force; The coastal storm surge numerical model is constructed based on ADCIRC; The nearshore tidal data are specifically real-time tidal data at locations 1-2 km from the shore, which is achieved by screening grid points within a distance range of 1-2 km from the shore of the target area and aggregating the tidal data within the grid points.

3. The method for calculating seawall overtopping and overtopping risk considering the wave-breaking effect of mangroves according to claim 1 is characterized in that: The storm surge typhoon wave forecast model based on SWAN is expressed in the rectangular coordinate system as follows: ； In the formula, is the wave action density; For time, , is the geographic coordinate, is the relative wave frequency, is the wave direction; and The wave propagation speed is and The weight in direction, and For the waves and The speed of propagation in space, is the wave energy density; The wave energy density It is expressed as: ； In the formula, represents the input of wind energy, , They represent the wave energy exchange caused by the third and fourth order nonlinear interactions, , , They represent the wave energy dissipation caused by whitecaps, bottom friction and wave breaking respectively.

4. The method for calculating seawall overtopping and overtopping risk considering the wave-breaking effect of mangroves according to claim 1, characterized in that: The historical typhoon data include: typhoon number, occurrence time, duration, longitude and latitude information, minimum air pressure at the typhoon center, maximum wind speed at the typhoon center, typhoon path, affected area, and wave parameters of the corresponding wave field; The seawall information includes: seawall location, historical flood control records, cross-section structure type, face protection type, and design parameters of the seawall top elevation, seawall top width, face protection structure, slope, slope shoulder width, and bottom slope; The mangrove-related information includes: canopy size, canopy density, root diameter, root height, root density, stem diameter, stem height, stem density and the integrity of the three parts of roots, stems and leaves.

5. The method for calculating seawall overtopping and overtopping risk considering the wave-breaking effect of mangroves according to claim 1, characterized in that: The water level-wave-vegetation-seawall coupling model is constructed based on the SWASH model; The SWASH model uses nonlinear shallow water equations, which are derived directly from the incompressible Reynolds-averaged Navier-Stokes equations and include non-hydrostatic pressure terms; for the propagation of waves in the vertical two-dimensional xz plane, the expression of the nonlinear shallow water equations is as follows: Continuity equation: ； The momentum equation in the x direction is: ； Momentum equation in z direction: ； In the formula, is the velocity component in the x direction; is the velocity component in the z direction; Indicates time; Indicates the water density; , represent the components of the turbulent stress in the x direction and the z direction respectively; , denote the components of the turbulent stress in the z direction in the x and z directions, respectively; is the pressure item; The hydrostatic pressure is expressed as a function of the free surface, so the pressure term It is expressed as: ； In the formula, represents the hydrostatic pressure, represents the free surface, represents the acceleration due to gravity, represents non-hydrostatic pressure; The SWASH model generalizes vegetation into a rigid cylinder and calculates the drag force exerted by vegetation on the water body through the Morrison equation. The horizontal component of the drag force acting on the unit volume of vegetation is expressed as: ； In the formula, is the plant drag coefficient; is the plant height; is the plant diameter; is the number of plants per unit area; Among them, the plant drag coefficient Directly set by humans.

6. The method for calculating seawall overtopping and overtopping risk considering the wave-breaking effect of mangroves according to claim 5 is characterized in that: Considering the influence of wave period, the plant drag coefficient It can also be derived through the following expression: ； In the formula, Indicated by characteristic diameter The calculated Keuglan-Carpenter number.

7. The method for calculating seawall overtopping and overtopping risk considering the wave-breaking effect of mangroves according to claim 1, characterized in that: The method of training the data in the database based on the CNN neural network to obtain the predicted values ​​of the wave height and wave force parameters in front of the seawall specifically includes: Preprocess the input data to ensure that all input data have consistent dimensions through normalization, standardization, and missing value processing; Initialize the CNN neural network architecture, including convolutional layers, pooling layers, and fully connected layers, and use the deep learning framework to automatically initialize the weight parameters of the convolution kernel and fully connected layers; The preprocessed data is input into the CNN neural network, which is sequentially passed through the convolution layer to extract local features, the pooling layer to perform downsampling, and the fully connected layer to perform feature combination, and finally the predicted values ​​of the wave height and wave force parameters in front of the seawall are output; Compare the predicted value output by the CNN neural network model with the true observed value, select the mean square error MSE as the loss function, calculate the error between the predicted value and the true observed value, calculate the gradient through the back propagation algorithm, use the gradient descent method to update the model weight parameters, gradually reduce the loss value, and after each training round, evaluate the generalization ability of the model through the validation set to ensure that the model will not overfit; After completing the predetermined number of iterations, the performance of the model is evaluated using the validation set and the test set, and the mean square error (MSE) and correlation coefficient (CC) between the predicted value and the true observed value are calculated to quantify the model performance.

8. The method for calculating seawall overtopping and overtopping risk considering the wave-breaking effect of mangroves according to claim 1, characterized in that: The formula used to calculate the seawall overtopping specifically includes: When the working conditions meet the following 6 applicable conditions at the same time: ,in For water depth, is the effective wave height; ,in Indicated by the peak period Calculated deep water wavelength, , is the average wave period; ,in is the slope of the seawall; ,in is the shoulder width; ,in It is the height of the seawall crest above the still water level; ,in It represents the bottom slope ratio; For a slope embankment without a wave-breaking wall, the calculation formula for the seawall overtopping is: ； In the formula, It indicates the amount of seawall overtopping; is the empirical coefficient, is the influence coefficient of the protective structure; represents the acceleration due to gravity; For a slope embankment with a wave-breaking wall, the calculation formula for the seawall overtopping is: ； In the formula, is the empirical coefficient, It is the height of the top of the wave-breaking wall above the still water surface; For a composite slope embankment with a straight wall at the bottom, a slope at the top and a platform in the middle, the calculation formula for the seawall overtopping is: ； In the formula, to is the correction factor function, which is defined as follows: ； ； ； ； ； ； In the formula, , are the slopes below and above the platform, respectively, and satisfy , ; is the water depth on the platform, which takes a positive value when the platform is below the static water level and a negative value when the platform is above the static water level; When the working conditions cannot meet the above 6 conditions at the same time, and the seawall slope When considering the safety of the project, the method with a confidence level of 95% is used to calculate the seawall overtopping amount. The formula is: ； In the formula, is the pressure item; The wave height is 13% of the cumulative amount; The seawall slope The waves rise Depend on =1.25 and =1.5 at both ends The values ​​are determined by interpolation: =1.25, ; =1.5, , , is the wave breaking parameter with a cumulative rate of 1%, is the wave height with an accumulation rate of 1%; When the working conditions cannot meet the above 6 conditions at the same time and the seawall slope is not satisfied hour: The calculation formula for the seawall overtopping of the slope embankment is: ； In the formula, , b, c are fitting coefficients; is super high, and 0; For both cases without wave breaking and with wave breaking, use the following modified formula for calculation: With breaking wave: ; Unbroken Waves: ; In the formula, is the wave breaking coefficient, ; is the front slope; is the deep water wavelength; The factors affecting the platform are: is the influencing factor of slope roughness, is the influence factor of oblique incident wave, Factors affecting breast wall: It is a comprehensive influencing factor; For the two types of seawalls, straight slope and impermeable slope, the wave overrunning behavior is affected by surface roughness, shallow water, oblique waves and short-peak waves. The wave overtopping and breaking modes are classified to calculate the seawall overtopping amount: When the wave breaking coefficient When , the calculation formula is: ； In the formula, For steep slopes, , the scope of application is: ; When the wave breaking coefficient When , the calculation formula is: ； The calculation formula for the seawall overtopping of a straight wall seawall is: ； The small platform built at the toe of the dike will change the breaking characteristics of the waves. The overtopping of the seawall with this structure is calculated in the following two cases: when hour, ； when hour, ； In the formula, is the height of the embankment crest; Considering the influence of oblique incident waves on the overtopping of straight-wall seawalls, the calculation formula for the overtopping of non-broken seawalls is: ； The calculation formula for the overtopping of a broken seawall is: ； In the formula, is the oblique incidence factor, is the incident wave angle The impact of the wave is greater than the is the breaking overtopping amount of the normal incident wave; The water depth is shallow at the foreshore, In the case of , at this time, the calculation formula for the seawall overtopping is: ； This formula applies to the wave breaking coefficient And the slope is steep situation; The overflow phenomenon in the case of negative superelevation requires further consideration of the overflow volume, the total amount of water flowing to the land side of the structure Overflow and seawall overtopping , for wide top structure, the overflow The calculation formula is: ； In the formula, It is negative super high; Calculate seawall overtopping When, super high The value is 0. Value, and overflow Add together to get the total amount of water flowing to the land side of the structure , expressed as: 。 9. The method for calculating seawall overtopping and overtopping risk considering the wave-breaking effect of mangroves according to claim 1, characterized in that: The method for assessing the overtopping risk based on the calculated seawall overtopping amount includes: The dimensionless overtopping amount and dimensionless seawall superelevation are calculated for the sloped seawall section overtopping test data set, respectively, using the formula: ； ； In the formula, is the dimensionless overtopping amount; is the dimensionless seawall superelevation; It indicates the amount of seawall overtopping; is the deep water wavelength; is the front slope; represents the acceleration due to gravity; is the effective wave height; The factors that influence the platform; is super high; is the wave breaking coefficient; is the influencing factor of slope roughness; is the factor affecting the oblique incident wave; Factors affecting breast wall; Combined with the European Overtopping Manual, the single value forecast is calculated using the formula: ； Dimensionless overtopping and dimensionless seawall superelevation Substitute into the single-value prediction formula, and the dimensionless overtopping amount calculated value is The calculation formula is: ； Dimensionless overtopping amount calculated from the overtopping test data set of the sloped seawall section , dimensionless seawall superelevation and dimensionless overtopping discharge calculation value The regularity and divergence shown are used to establish the empirical distribution of overtopping probability and introduce the coefficient ,make ,in represents any dimensionless overtopping value; Utilization coefficient Any dimensionless overtopping value Expressed as dimensionless overtopping amount calculation value of After times, establish the coefficient and overtopping probability The relationship between and dimensionless overtopping discharge calculation value Corresponding Value, calculation The exceedance probability of the value distribution is arranged in order from large to small, and the following function is fitted: ； Calculate the overtopping exceedance probability When The value is obtained using the following formula: ； In the formula, It indicates the seawall overtopping capacity standard specified when designing the seawall.

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