A method and device for predicting the height of a coastal incident wave current, an electronic device and a storage medium

Abstract

The application discloses a kind of coast incident wave scouring height prediction method, device, electronic equipment and storage medium, belong to the field of coastal dynamics, including the following steps: obtaining the wave data and beach parameters of the coast to be predicted;According to the effective wave height in deep water, spectral peak period, and sediment settling velocity, the dimensionless settling velocity parameter is calculated, the dimensionless settling velocity parameter represents the dimensionless ratio relationship between the effective wave height in deep water and the sediment settling distance within the spectral peak period;According to the wave spectral peak period, the deep water wavelength is calculated by linear wave theory;The effective wave height in deep water, deep water wavelength, the foreslope angle of the coast to be predicted and the dimensionless settling velocity parameter are input into the incident wave scouring height prediction model, and the prediction value of the coast incident wave scouring height is output.The present application aims to improve the problems of the prior art, such as insufficient prediction adaptability under different beach medium conditions, difficult to balance prediction accuracy and stability, and difficult to realize reliable prediction under the condition of available engineering data.

Description

Technical Field

[0001] This invention belongs to the field of coastal dynamics technology, and in particular relates to a method, device, electronic device and storage medium for predicting the height of incident waves on the coast. Background Technology

[0002] As nearshore waves propagate, deform, and act on the shoreline, they cause significant changes in shoreline water levels and water movement. The shoreline water level response caused by wave action can generally be divided into two main components: one is wave setup, which generally refers to the time-averaged water level rise caused by wave breaking and the resulting changes in radiation stress; the other is swash, which generally refers to the periodic uplift and receding of waves on the shoreline, reflecting the direct effect of wave energy on the shoreline.

[0003] Because slick flows can involve water level oscillations caused by components of different frequencies, engineering and academic research typically classify slicks into two categories based on frequency: incident swashes and infrared swashes. Incident swashes usually correspond to higher frequency components (e.g., often distinguished by a boundary of approximately 0.05 Hz). Under certain shoreline types and sea conditions, incident swashes can significantly impact shoreline dynamic processes and engineering safety assessments. The height of the incident swash characterizes the amplitude of vertical water level fluctuations caused by high-frequency shortwave action (often expressed as a statistical measure). Its magnitude is influenced by multiple factors, including wave characteristic parameters, shoreline topography (such as foreshore slope), and shoreline medium properties. Reasonable prediction of the incident swash height helps provide fundamental parameter support for coastal flood forecasting, shoreline erosion assessment, and coastal protection engineering design.

[0004] In existing technologies, methods for predicting incident wave surge height mostly employ empirical models, typically using parameters such as wave height, period, and slope as primary inputs to obtain predictive results suitable for engineering calculations. While these methods are convenient for calculation and application, their applicability and prediction accuracy may still be limited under different shoreline conditions. On the one hand, shoreline media (such as sediment particle size or settling velocity) may affect the nearshore wave-shoal interaction process, thus influencing the surge response; on the other hand, some schemes' prediction targets or parameterization methods are not constructed specifically for incident wave surge height, potentially leading to insufficient adaptability in describing the incident wave surge response.

[0005] For example, existing technologies include schemes for predicting wave rise, such as the Chinese invention patent – ​​Method and Device for Predicting Maximum Wave Rise on Natural Banks (CN118051705B), which predicts wave rise based on the influence of sediment particle size. However, wave rise and incident wave surge differ in physical mechanisms, characteristic quantity definitions, and parametric modeling methods. The prediction objectives and parametric methods described above for wave rise are not applicable to the description and prediction of incident wave surge height. Therefore, a prediction technology for incident wave surge height is still needed to achieve reasonable calculation and output of incident wave surge height under engineering-available input data conditions.

[0006] References:

[0007] [1] Holman RA, Sallenger Jr A H. Setup and swash on a natural beach[J]. Journal of Geophysical Research: Oceans, 1985, 90(C1): 945-953(Wave rise and swash process on a natural beach).

[0008] [2] Ruggiero P, Holman RA, Beach RA. Wave run-up on a high-energy dissipative beach[J]. Journal of Geophysical Research: Oceans, 2004, 109(C6):C06025(High-energy dissipative beach wave run-up).

[0009] [3] Stockdon HF, Holman RA, Howd PA, et al. Empirical parameterization of setup, swash, and runup[J]. Coastal engineering, 2006, 53(7): 573-588 (Empirical parameterization of wave rise, swash and runup).

[0010] [4] Brinkkemper JA, Torres-Freyermuth A, Mendoza ET, et al. Parameterization of wave run-up on beaches in Yucatan, Mexico: A numerical study[C] / / Proceedings of the 7th International Conference on CoastalDynamics, 2013: 225-234(MXC Yucatan Beaches Wave Run-up Parameterization: A Numerical Study). Summary of the Invention

[0011] The purpose of this invention is to provide a method, apparatus, electronic device, and storage medium for predicting the height of incident waves on the coast, in order to solve the technical problem mentioned in the background art that the existing technology has insufficient adaptability and prediction accuracy for different beach media conditions, and it is difficult to reliably predict the height of incident waves under the condition of available engineering data.

[0012] To achieve the above objectives, the present invention provides the following technical solution:

[0013] In a first aspect, the present invention provides a method for predicting the height of incident waves on a coast, comprising the following steps:

[0014] Acquire wave data and shoreline parameters of the coastline to be predicted; wherein the wave data includes at least the deep-water significant wave height and spectral peak period; and the shoreline parameters include at least the foreshore slope angle and the shoreline sediment settling velocity.

[0015] Based on the significant wave height, spectral peak period, and sediment settling velocity in deep water, a dimensionless settling velocity parameter is calculated. This dimensionless settling velocity parameter characterizes the dimensionless ratio between the significant wave height and the sediment settling distance within the spectral peak period. The calculation formula is as follows:

[0016] ;

[0017] In the formula, This is a dimensionless sinking velocity parameter; This refers to the significant wave height in deep water. For sediment settling speed; The periodicity of the spectral peak;

[0018] The deep-water wavelength is calculated using linear wave theory based on the wave spectrum peak period.

[0019] The deep-water significant wave height, deep-water wavelength, foreshore slope angle, and dimensionless settling velocity parameters are input into the incident wave surge height prediction model, which outputs the predicted value of the incident wave surge height. The incident wave surge height prediction model is as follows:

[0020] ;

[0021] In the formula, This is the predicted value for the height of the incident wave impact on the coast. The foreshore slope angle, ; For deep water wavelength; This is a dimensionless settling velocity parameter.

[0022] Preferably, the wave data of the coastline to be predicted is obtained from numerical model output, reanalysis dataset, engineering database, and historical data file queries.

[0023] Preferably, acquiring the wave data of the coastline to be predicted includes:

[0024] The spectral peak period, water depth, and significant wave height at the measurement point are collected by wave sensors or wave buoys near the coastline to be predicted; the spectral peak period at the measurement point is used as the spectral peak period of the incident wave.

[0025] The deep-water wavelength is calculated using a linear wave theory algorithm based on the spectral peak period.

[0026] Based on the spectral peak period and the water depth at the measuring point, a dispersion equation at the measuring point is established based on linear wave theory. The wavelength at the measuring point is obtained by iteratively solving the dispersion equation using the Newton iteration algorithm.

[0027] The significant wave height at the measuring point, the wavelength at the measuring point, the deep-water wavelength, and the water depth at the measuring point are used to calculate the significant wave height in deep water using a linear wave theory algorithm.

[0028] Preferably, the iteration termination condition for using the Newton-Raphson iteration algorithm to iteratively solve the dispersion equation and obtain the wavelength at the measurement point is that the absolute value of the difference between the wavelengths at the measurement point obtained from two adjacent iterations is less than a preset threshold or the number of iterations reaches the upper limit.

[0029] Preferably, the settling velocity of the shoreline sediment is obtained by sampling the shoreline sediment on-site and then conducting a settling test; or it is calculated based on the median particle size of the shoreline sediment using an empirical formula for settling velocity.

[0030] ;

[0031] ;

[0032] In the formula, For sediment settling speed; The median particle size of sediment on the shoreline; The kinematic viscosity coefficient of the water body; Dimensionless particle size; Dimensionless particle size cubed; The relative density of the sediment; This is the acceleration due to gravity.

[0033] Preferably, after obtaining the wave data and shore parameters of the coastline to be predicted, the method further includes preprocessing the wave data and shore parameters, wherein the preprocessing includes one or more of timestamp alignment, outlier removal, and missing value imputation.

[0034] Preferably, the method further includes: collecting measured values ​​of incident wave surge heights on different coastlines, performing error analysis between the measured values ​​and the predicted values, and evaluating the accuracy of the coastline incident wave surge height prediction.

[0035] Secondly, based on the same inventive concept, the present invention also provides a device for predicting the height of coastal incident wave currents, comprising the following modules:

[0036] The data acquisition module is used to acquire wave data and shore parameters of the coastline to be predicted; wherein, the wave data includes at least the deep-water significant wave height and spectral peak period; the shore parameters include at least the foreshore slope angle and the shore sediment settling velocity;

[0037] The dimensionless settling velocity parameter calculation module is used to calculate the dimensionless settling velocity parameter based on the significant wave height, spectral peak period, and sediment settling velocity in deep water. The dimensionless settling velocity parameter represents the dimensionless ratio between the significant wave height and the sediment settling distance within the spectral peak period. The calculation formula is as follows:

[0038] ;

[0039] In the formula, This is a dimensionless sinking velocity parameter; This refers to the significant wave height in deep water. For sediment settling speed; The periodicity of the spectral peak;

[0040] The deep-water wavelength calculation module is used to calculate the deep-water wavelength based on the spectral peak period using linear wave theory, and then output it to the surge height prediction module.

[0041] The surge height prediction module is used to input the significant deep-water wave height, deep-water wavelength, foreshore slope angle, and dimensionless settling velocity parameters into the incident wave surge height prediction model, and output the predicted value of the incident wave surge height. The incident wave surge height prediction model is as follows:

[0042] ;

[0043] In the formula, This is the predicted value for the height of the incident wave impact on the coast. The foreshore slope angle, This refers to the significant wave height in deep water. For deep water wavelength; This is a dimensionless sinking velocity parameter;

[0044] The output module is used to output the predicted value of the incident wave surge height and provide the prediction result to the upper-level application; the upper-level application includes: early warning threshold judgment, coastal engineering design parameter output, and numerical simulation boundary condition input.

[0045] Thirdly, based on the same inventive concept, the present invention also provides an electronic device for performing the above-described method, the electronic device comprising: a processor, a memory, and a communication interface, wherein the processor, memory, and communication interface are connected via a bus, wherein:

[0046] The memory is used to store computer programs and runtime data;

[0047] The processor is electrically connected to the memory. The processor is used to call and execute the computer program to realize the following processing flow: acquiring wave parameters and beach parameters, calculating dimensionless sinking velocity parameters, calculating deep water wavelength, and calculating and outputting the predicted value of incident wave surge height.

[0048] The communication interface is used to receive data input from wave sensors, wave buoys or databases, and / or output the predicted height of the incident wave surge to external application systems.

[0049] Fourthly, based on the same inventive concept, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0050] Compared with the prior art, the beneficial effects of the present invention are:

[0051] This invention provides a method, device, and electronic equipment for predicting the height of incident waves on the coast. It aims to improve upon existing technologies by addressing their shortcomings in predicting adaptability under different shoreline media conditions, the difficulty in balancing prediction accuracy and stability, and the challenge of achieving reliable predictions when engineering data is available. By acquiring and processing key physical parameters such as deep-water significant wave height, spectral peak period, foreshore slope angle, and sediment settling velocity, a dimensionless settling velocity parameter is constructed to characterize the relationship between sediment deposition and wave action over time. This parameter, along with wave elements such as deep-water wavelength, is input into the incident wave height prediction model to achieve a predicted output of the coastal incident wave height. This provides crucial parameter support for coastal protection, port and shoreline engineering design, and disaster early warning.

[0052] To address the significant impact of different shoreline sediment conditions on the flow process and the difficulty of using traditional empirical formulas to characterize the differences in shoreline conditions, this invention introduces shoreline sediment settling velocity and constructs a dimensionless settling velocity parameter. The ratio between the effective deep-water wave height and the sediment settling distance within the spectral peak period is then dimensionlessly characterized. This parameter is used as one of the inputs to the prediction model, enabling the model to explicitly reflect the influence of shoreline medium differences on the incident wave flow height. This reduces systematic bias under different shoreline conditions and improves the transferability of the results.

[0053] To address the challenges of long-term on-site observation or full-parameter measurement in engineering scenarios, which hinders the implementation of prediction methods, this invention allows wave parameters such as deep-water effective wave height and spectral peak period to be obtained from wave sensor / buoy observation data, or from numerical model output, reanalysis datasets, engineering databases, and historical data file queries. The sediment settling velocity of shoreline sediments can also be measured through settling tests or calculated from the median particle size using empirical formulas. This satisfies the need for rapid prediction under conditions where engineering data is available, without adding extra complexity to the measurement process.

[0054] To address the issue of unstable predictions caused by time asynchrony, outliers, and missing values ​​in input data, this invention performs preprocessing on wave data and shoreline parameters, including timestamp alignment, outlier removal, and missing value completion, thereby improving input data quality. Furthermore, based on linear wave theory, it calculates necessary parameters such as deep-water wavelength, enabling the prediction process to be automatically executed on servers, industrial control computers, or edge computing nodes. The output predicted incident wave surge height is used for early warning threshold judgment, engineering design parameter output, or numerical simulation boundary condition input, improving the response efficiency and decision consistency of engineering applications.

[0055] The input data required for this invention consists of readily available wave data and basic shoreline parameters such as foreshore slope, facilitating automated calculations and rapid output of results in early warning systems, engineering calculation systems, or coastal engineering design software. This improves the efficiency of engineering applications in scenarios such as coastal flood forecasting, shoreline erosion assessment, and protection engineering design. While ensuring the availability of engineering data, this invention enhances adaptability to different shoreline conditions and the stability of prediction results, reducing the cost of field testing and repeated verification, and improving the efficiency and reliability of early warning and design parameter determination. Attached Figure Description

[0056] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0057] Figure 1 This is a flowchart of the coastal incident wave surge height prediction method according to an embodiment of the present invention;

[0058] Figure 2 This is a comparison chart of the predicted and measured values ​​of the coastal incident wave surge height according to an embodiment of the present invention;

[0059] Figure 3 This is a comparison chart of the coastal incident wave surge height predicted by the Holman and Sallenger (1985) formula described in the embodiments of the present invention and the measured value;

[0060] Figure 4 This is a comparison chart of the coastal incident wave surge height predicted by the formula of Ruggiero et al. (2004) as described in the embodiments of the present invention and the measured value;

[0061] Figure 5 This is a comparison chart of the coastal incident wave surge height predicted by the Stockdon et al. (2006) formula described in the embodiments of the present invention and the measured value;

[0062] Figure 6 This is a comparison chart of the coastal incident wave surge height predicted by the formula of Brinkkemper et al. (2013) as described in the embodiments of the present invention and the measured value;

[0063] Figure 7 This is a comparison chart of the root mean square error of the coastal incident wave surge height prediction method described in this embodiment of the invention with other prediction methods.

[0064] Figure 8 This is a comparison of the coefficients of determination between the coastal incident wave surge height prediction method described in this embodiment of the invention and other prediction methods.

[0065] Figure 9This is a schematic diagram of the coastal incident wave surge height prediction device according to an embodiment of the present invention;

[0066] Figure 10 This is a schematic diagram of the electronic device structure according to an embodiment of the present invention. Detailed Implementation

[0067] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0068] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this invention should have the ordinary meaning understood by those skilled in the art. The terms "first," "second," and similar terms used in the embodiments of this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word covers the element or object listed after the word and its equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0069] like Figures 1-10 As shown:

[0070] First embodiment:

[0071] This embodiment provides a method for predicting the height of incident wave surges along a coast. The method can be deployed as an independent workflow in an early warning system, engineering calculation system, or coastal engineering design software. Wave data can be collected and transmitted by conventional wave sensors / wave buoys, or imported from an engineering database. This method achieves rapid prediction based solely on data such as deep-water wave height, spectral peak period, foreshore slope (or slope angle), and sediment settling velocity. Furthermore, by introducing a dimensionless settling velocity parameter to reflect the shoreline condition, it improves the prediction accuracy of the incident wave surge height.

[0072] Please see Figure 1 As shown, it includes the following steps:

[0073] S100, acquire wave data and shore parameters of the coastline to be predicted; wherein, the wave data includes at least the deep-water significant wave height and spectral peak period; the shore parameters include at least the foreshore slope angle and the shore sediment settling velocity.

[0074] In one alternative implementation, the wave data for predicting the coastline based on the significant wave height and spectral peak period in deep water are obtained from the numerical model output, reanalysis datasets, engineering databases, and historical data file queries.

[0075] In another alternative implementation:

[0076] The spectral peak period, water depth, and significant wave height at the measurement point are obtained by using wave sensors or wave buoys at measurement points near the coastline to be predicted; the spectral peak period at the measurement point is used as the spectral peak period of the incident wave in subsequent calculations.

[0077] The deep-water wavelength is calculated using a linear wave theory algorithm based on the spectral peak period.

[0078] ;

[0079] In the formula, For deep water wavelength, For the spectral peak period, This is the acceleration due to gravity.

[0080] Based on the spectral peak period and the water depth at the measuring point, a dispersion equation is established using linear wave theory:

[0081] ;

[0082] In the formula, The wavelength at the measurement point is... It is the acceleration due to gravity. For the spectral peak period, This represents the water depth at the measuring point.

[0083] The above equation is solved iteratively using Newton's iteration algorithm, let ,

[0084] calculate ;

[0085] Take deep water wavelength Used as the initial value for iteration; updated according to the following iteration format:

[0086] ,

[0087] Until satisfied The iteration stops when the value is less than the preset value or the maximum number of iterations is reached, and the converged result is obtained. Wavelength at the measurement point ;

[0088] Then, based on the significant wave height at the measuring point, the wavelength at the measuring point, the deep-water wavelength, and the water depth at the measuring point, the significant wave height in deep water is calculated using a linear wave theory algorithm.

[0089] ;

[0090] in,

[0091] ;

[0092] ;

[0093] ;

[0094] In the formula, For the significant wave height in deep water, The effective wave height at the measuring point. The coefficient of deformation in shallow water. The ratio of group velocity to phase velocity. For wave number.

[0095] The foreshore slope angle can be determined based on shoreline profile measurement data, topographic data, or digital elevation model data of the coastline to be predicted; for example, the foreshore slope angle can be calculated based on the elevation-horizontal distance relationship of the foreshore area.

[0096] The settling velocity of the shoreline sediment is obtained by sampling the shoreline sediment on-site and then conducting a settling test; or it can be calculated based on the median particle size of the shoreline sediment using an empirical formula for settling velocity.

[0097] ;

[0098] ;

[0099] In the formula, For sediment settling speed; The median particle size of sediment on the shoreline; The kinematic viscosity coefficient of the water body; Dimensionless particle size; Dimensionless particle size cubed; This represents the relative density of the sediment.

[0100] Optionally, after obtaining the wave data and beach parameters of the coastline to be predicted, the wave data and beach parameters are preprocessed, including one or more of timestamp alignment, outlier removal and missing value imputation, to ensure the stability of subsequent calculations.

[0101] S200, based on the deep-water significant wave height, spectral peak period, and sediment settling velocity, a dimensionless settling velocity parameter is calculated. The dimensionless settling velocity parameter characterizes the dimensionless ratio between the deep-water significant wave height and the sediment settling distance within the spectral peak period.

[0102] Specifically, in this embodiment, the formula for calculating the dimensionless settling velocity parameter is:

[0103] ;

[0104] In the formula, This is a dimensionless settling velocity parameter.

[0105] S300 calculates the deep-water wavelength based on the wave spectrum peak period using linear wave theory.

[0106] Specifically, in this embodiment, the formula for calculating the deep-water wavelength is:

[0107] ;

[0108] In one alternative implementation, if the deep-water wavelength has already been calculated based on the spectral peak period during the process of converting the deep-water significant wave height from observation data in S100... In this step, the function is called directly. Otherwise, calculate according to the above formula. .

[0109] S400, inputs the deep-water wavelength, significant deep-water wave height, foreshore slope angle, and dimensionless settling velocity parameters into the incident wave surge height prediction model, and outputs the predicted value of the incident wave surge height; the incident wave surge height prediction model is as follows:

[0110] ;

[0111] In the formula, This is the predicted value for the height of the incident wave impact on the coast. The slope angle of the foreshore.

[0112] The S500 collects measured values ​​of incident wave surge heights on different coastlines, performs error analysis between the measured and predicted values, and evaluates the accuracy of the coastal incident wave surge height prediction.

[0113] As an example, the dataset used for validation includes 14 sets of field trial data from 10 prototype coasts: 4 sets from the Duck coast (October 1982, October 1990, October 1994, and October 1997) in the United States; the Scripps coast (June 1989) in the United States; the San-Onofre coast (October 1993) in the United States; the Gleneden coast (February 1994) in the United States; the Agate coast (February 1996) in the United States; 2 sets from the Terschelling coast (April 1994 and October 1994) in the Netherlands; the Truc-Vert coast (March 2008) in France; the Tairoua coast (July 2008) in New Zealand; the Ngarunui coast (November 2010) in New Zealand; and the Somo and El-Puntal coasts in Spain (May 2016). The above data is used to validate and compare the effectiveness of the method in this embodiment and does not constitute a limitation on the scope of application of the method.

[0114] Specifically, in this embodiment, the root mean square error formula ( ) and coefficient of determination ( The formula is used as an evaluation index to perform error analysis between measured and predicted values, including:

[0115] ;

[0116] ;

[0117] In the formula, For the sample size, and These represent the predicted and measured values ​​of the incident wave height on the coast, respectively. This represents the average of the measured values ​​of the incident wave height on the coast. The root mean square error, The coefficient of determination. The smaller and The closer the value is to 1, the higher the accuracy of the prediction.

[0118] In this embodiment, the existing methods for calculating the height of the incident wave on the coast of the same type used for comparison of prediction effects include: Holman and Sallenger (1985) formula (reference [1]), Ruggiero et al. (2004) formula (reference [2]), Stockdon et al. (2006) formula (reference [3]), and Brinkkemper et al. (2013) formula (reference [4]).

[0119] Figure 2 This is a comparison chart of the predicted and measured values ​​of the incident wave height on the coast, as described in an embodiment of the present invention. Figures 3 to 6 To compare the predicted and measured values ​​of the incident wave surge height obtained using the calculation method described in the embodiment, Figure 7 To compare the root mean square error (RMSE) of the incident wave jet height predicted using the method described in this embodiment with existing methods, Figure 8 The incident wave jet height determination coefficient predicted using the method described in this embodiment ( Comparison with existing methods.

[0120] According to statistics, the relative root mean square error (RMSE) of the method described in this embodiment is 0.415 m, which is 24.6% lower than the Holman and Sallenger (1985) formula, 58.6% lower than the Ruggiero et al. (2004) formula, 16.5% lower than the Stockdon et al. (2006) formula, and 35.7% lower than the Brinkkemper et al. (2013) formula; the coefficient of determination of the method described in this embodiment in this embodiment is ( The value is 0.465, which is 0.406 higher than the Holman and Sallenger (1985) formula, 2.587 higher than the Ruggiero et al. (2004) formula, 0.231 higher than the Stockdon et al. (2006) formula, and 0.759 higher than the Brinkkemper et al. (2013) formula.

[0121] Second embodiment:

[0122] This embodiment provides a device for predicting the height of coastal incident waves, which is used to implement the method for predicting the height of coastal incident waves described in the first embodiment. The device can be deployed on the server / local side of an early warning system, engineering calculation system, or coastal engineering design software, and is used to process input wave parameters and shoreline parameters and output predicted values ​​of the incident wave height. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0123] The device includes the following modules:

[0124] Includes the following modules:

[0125] The data acquisition module is used to acquire wave data and shoreline parameters of the coastline to be predicted. The wave data includes at least the significant deep-water wave height and wave spectrum peak period; the shoreline parameters include at least the foreshore slope angle and the sediment settling velocity. The wave data comes from wave numerical model output, reanalysis dataset, engineering database, historical data files, or is obtained directly or by conversion from observation data of wave sensors or wave buoys. The sediment settling velocity is measured by sedimentation tests or calculated from the median particle size of the sediment.

[0126] The dimensionless settling velocity parameter calculation module is used to calculate the dimensionless settling velocity parameter based on the deep-water significant wave height, spectral peak period, and sediment settling velocity, and output it to the surge height prediction module. The dimensionless settling velocity parameter represents the dimensionless ratio between the deep-water significant wave height and the sediment settling distance within the spectral peak period. The calculation formula is as follows:

[0127] ;

[0128] In the formula, This is a dimensionless sinking velocity parameter; This refers to the significant wave height in deep water. For sediment settling speed; The periodicity of the spectral peak;

[0129] The deep-water wavelength calculation module is used to calculate the deep-water wavelength based on the spectral peak period using linear wave theory, and then output it to the surge height prediction module.

[0130] The surge height prediction module is used to input the significant deep-water wave height, deep-water wavelength, foreshore slope angle, and dimensionless settling velocity parameters into the incident wave surge height prediction model, and output the predicted value of the incident wave surge height. The incident wave surge height prediction model is as follows:

[0131] ;

[0132] In the formula, This is the predicted value for the height of the incident wave impact on the coast. The foreshore slope angle, This refers to the significant wave height in deep water. For deep water wavelength; This is a dimensionless sinking velocity parameter;

[0133] The output module is used to output the predicted value of the incident wave surge height and provide the prediction result to the upper-level application; the upper-level application includes: early warning threshold judgment, coastal engineering design parameter output, numerical simulation boundary condition input, etc.

[0134] In one implementation, the above modules can be implemented by a program executed by the same processor; in another implementation, the above modules can be implemented collaboratively by multiple processors / threads or distributed computing nodes.

[0135] Third embodiment:

[0136] In this embodiment, an electronic device is provided for performing the method described in the first embodiment, or implementing the device function described in the second embodiment.

[0137] The electronic device includes: a processor, a memory, and a communication interface, wherein the processor, memory, and communication interface are connected via a bus, wherein:

[0138] The memory is used to store computer programs and runtime data;

[0139] The processor is electrically connected to the memory. The processor is used to call and execute the computer program to realize the following processing flow: acquiring wave parameters and beach parameters, calculating dimensionless sinking velocity parameters, calculating deep water wavelength, and calculating and outputting the predicted value of incident wave surge height.

[0140] The communication interface is used to receive data input from wave sensors / wave buoys / databases, etc., and / or output the incident wave surge height prediction results to external application systems.

[0141] In one alternative implementation, the electronic device is a server, an industrial control computer, an edge computing node, or a terminal device with data processing capabilities; the processor can be a general-purpose processor, a digital signal processor, or other programmable chips; and the memory can be volatile memory, non-volatile memory, or a combination of both.

[0142] Fourth embodiment:

[0143] In this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it implements the coastal incident wave surge height prediction method described in the first embodiment.

[0144] The computer-readable storage media include: read-only memory, random access memory, hard disk, solid-state drive, USB flash drive, memory card, etc.

[0145] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented, in whole or in part, as a computer program product, the computer program product includes one or more computer instructions. When the computer program instructions are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0146] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for predicting the height of incident waves on a coast, characterized in that, Includes the following steps: Acquire wave data and shoreline parameters of the coastline to be predicted; wherein the wave data includes at least the deep-water significant wave height and spectral peak period; and the shoreline parameters include at least the foreshore slope angle and the shoreline sediment settling velocity. Based on the significant wave height, spectral peak period, and sediment settling velocity in deep water, a dimensionless settling velocity parameter is calculated. This dimensionless settling velocity parameter characterizes the dimensionless ratio between the significant wave height and the sediment settling distance within the spectral peak period. The calculation formula is as follows: ； In the formula, This is a dimensionless sinking velocity parameter; This refers to the significant wave height in deep water. For sediment settling speed; The periodicity of the spectral peak; The deep-water wavelength is calculated based on the wave spectrum peak period using linear wave theory. The deep-water significant wave height, deep-water wavelength, foreshore slope angle, and dimensionless settling velocity parameters are input into the incident wave surge height prediction model, which outputs the predicted value of the incident wave surge height. The incident wave surge height prediction model is as follows: ; In the formula, This is the predicted value for the height of the incident wave impact on the coast. The foreshore slope angle, This refers to the significant wave height in deep water. For deep water wavelength; This is a dimensionless settling velocity parameter.

2. The method according to claim 1, characterized in that, The wave data for the coastline to be predicted is obtained from numerical model output, reanalysis datasets, engineering databases, and historical data files.

3. The method according to claim 1, characterized in that, The acquisition of wave data for the coastline to be predicted includes: The spectral peak period, water depth, and significant wave height at the measurement point are collected by wave sensors or wave buoys near the coastline to be predicted; the spectral peak period at the measurement point is used as the spectral peak period of the incident wave. The deep-water wavelength is calculated using a linear wave theory algorithm based on the spectral peak period. Based on the spectral peak period and the water depth at the measuring point, a dispersion equation at the measuring point is established based on linear wave theory. The wavelength at the measuring point is obtained by iteratively solving the dispersion equation using the Newton iteration algorithm. The effective wave height in deep water is calculated using a linear wave theory algorithm based on the significant wave height at the measuring point, the wavelength at the measuring point, the wavelength in deep water, and the water depth at the measuring point.

4. The method according to claim 3, characterized in that, The iteration of the dispersion equation using the Newton-Raphson iteration algorithm terminates when the absolute value of the difference between the wavelengths at the measurement point obtained from two adjacent iterations is less than a preset threshold or the number of iterations reaches the upper limit.

5. The method according to claim 1, characterized in that, The settling velocity of the shoreline sediment is obtained by sampling the shoreline sediment on-site and then conducting a settling test; or it can be calculated based on the median particle size of the shoreline sediment using an empirical formula for settling velocity. ； ； In the formula, For sediment settling speed; The median particle size of sediment on the shoreline; The kinematic viscosity coefficient of the water body; Dimensionless particle size; Dimensionless particle size cubed; The relative density of the sediment; This is the acceleration due to gravity.

6. The method according to claim 1, characterized in that: After obtaining the wave data and shore parameters of the coastline to be predicted, the process further includes preprocessing the wave data and shore parameters. The preprocessing includes one or more of the following: timestamp alignment, outlier removal, and missing value imputation.

7. The method according to claim 1, characterized in that, Also includes: Measured values ​​of incident wave surge heights on different coastlines were collected, and error analysis was performed between the measured and predicted values ​​to evaluate the accuracy of the coastal incident wave surge height prediction.

8. A device for predicting the height of incident waves on a coast, characterized in that, Includes the following modules: The data acquisition module is used to acquire wave data and shore parameters of the coastline to be predicted; wherein, the wave data includes at least the deep-water significant wave height and spectral peak period; the shore parameters include at least the foreshore slope angle and the shore sediment settling velocity; The dimensionless settling velocity parameter calculation module is used to calculate the dimensionless settling velocity parameter based on the deep-water significant wave height, spectral peak period, and sediment settling velocity, and output it to the surge height prediction module. The dimensionless settling velocity parameter represents the dimensionless ratio between the deep-water significant wave height and the sediment settling distance within the spectral peak period. The calculation formula is as follows: ； In the formula, This is a dimensionless sinking velocity parameter; This refers to the significant wave height in deep water. For sediment settling speed; The period of the spectral peak; The deep-water wavelength calculation module is used to calculate the deep-water wavelength based on the spectral peak period using linear wave theory, and then output it to the surge height prediction module. The surge height prediction module is used to input the significant deep-water wave height, deep-water wavelength, foreshore slope angle, and dimensionless settling velocity parameters into the incident wave surge height prediction model, and output the predicted value of the incident wave surge height. The incident wave surge height prediction model is as follows: ; In the formula, This is the predicted value for the height of the incident wave impact on the coast. The foreshore slope angle, This refers to the significant wave height in deep water. For deep water wavelength; This is a dimensionless sinking velocity parameter; The output module is used to output the predicted value of the incident wave surge height and provide the prediction result to the upper-level application; the upper-level application includes: early warning threshold judgment, coastal engineering design parameter output, and numerical simulation boundary condition input.

9. An electronic device, characterized in that, The electronic device is used to perform the method according to any one of claims 1 to 7, comprising: a processor, a memory, and a communication interface, wherein the processor, memory, and communication interface are connected via a bus, wherein: The memory is used to store computer programs and runtime data; The processor is electrically connected to the memory. The processor is used to call and execute the computer program to realize the following processing flow: acquiring wave parameters and beach parameters, calculating dimensionless sinking velocity parameters, calculating deep water wavelength, and calculating and outputting the predicted value of incident wave surge height. The communication interface is used to receive data input from wave sensors, wave buoys or databases, and / or output the predicted height of the incident wave surge to external application systems.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1 to 7.

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