Maximum wave surge prediction method and related device on natural beach

Abstract

The present application provides a method and related device for predicting the maximum wave surge on a natural beach, the method comprising: obtaining the foreshore slope of the forecast coast, the median particle size of the beach, the effective wave height collected at the wave buoy, the spectrum peak period, and the water depth data at the wave buoy; according to the spectrum peak period and water depth data, the wavelength data at the wave buoy is calculated by a linear wave theory algorithm and a Newton iteration algorithm; according to the effective wave height, the spectrum peak period and the wavelength data, the deep water wavelength and the deep water effective wave height are calculated by a linear wave theory algorithm; according to the deep water wavelength, the deep water effective wave height, the foreshore slope, and the median particle size of the beach, the predicted value of the maximum wave surge on the natural beach is calculated; the measured values ​​of the maximum wave surge on the natural beaches in different regions are collected, and the measured values ​​and the predicted values ​​are subjected to error analysis to evaluate the accuracy of the prediction of the maximum wave surge. The present application significantly improves the prediction accuracy of the maximum wave surge on the natural beach.

Description

Technical Field

[0001] The present application belongs to the field of coastal dynamics technology, and in particular relates to a method for predicting the maximum wave surge on a natural beach and a related device. Background Art

[0002] Against the backdrop of global climate change, coastal flood disasters are becoming more frequent, which has a huge impact on the natural environment and social economy of coastal areas. Wave surge is the average water level rise caused by wave propagation and is an important component of coastal floods. The maximum wave surge value on natural beaches is a key parameter in coastal engineering design, coastal flood forecasting and other processes. Rapid and accurate prediction of it has important scientific significance and engineering practical value.

[0003] A deep understanding of the nearshore wave propagation and breaking process is crucial for calculating wave surge. However, the detailed characteristics of the complex underwater topography in coastal areas are usually unknown, which makes nearshore wave motion difficult to predict. Therefore, the current maximum wave surge is mostly predicted using empirical formulas, which are based on simple environmental parameters (such as shore slope, deep water wave height and wavelength, etc.). Compared with physical models and mathematical models, they have the advantages of high computational efficiency and low cost, and are widely used.

[0004] At present, scholars at home and abroad have proposed many formulas to achieve rapid prediction of maximum wave surge. However, the existing formulas usually do not take into account the difference in wave surge under different sediment particle size conditions on natural beaches, resulting in poor prediction accuracy of wave surge. The prediction accuracy needs to be improved.

[0005] References:

[0006] [1] Stockdon HF, Holman RA, Howd PA, et al. Empirical parameterization of setup, swash, and runup [J]. Coastal engineering, 2006, 53(7): 573-588.

[0007] [2] Medellín G, Brinkkemper JA, Torres-Freyermuth A, et al. Run-upparameterization and beach vulnerability assessment on a barrier island: adownscaling approach [J]. Natural Hazards and Earth System Sciences, 2016, 16(1): 167-180.

[0008] [3]Ji C, Zhang Q, Wu Y. An empirical formula for maximum wave setupbased on a coupled wave-current model[J]. Ocean Engineering, 2018, 147: 215-226.

[0009] [4]O'Grady JG,McInnes KL,Hemer MA,et al.Extreme water levels for Australian beaches using empirical equations for shoreline wave setup[J].Journal of Geophysical Research:Oceans,2019,124(8):5468-5484.

[0010] [5]Dalinghaus C,Coco G,Higuera PA predictive equation for wave setupusing genetic programming[J].Natural Hazards and Earth System SciencesDiscussions,2023,23(6):2157-2169. Summary of the invention

[0011] In view of this, the present application aims to propose a maximum wave rise prediction method and related devices on natural beaches to solve the problem of poor prediction accuracy of the maximum wave rise prediction method on natural beaches.

[0012] To achieve the above purpose, the technical solution of this application is implemented as follows:

[0013] In a first aspect, the present application provides a method for predicting the maximum wave surge on a natural beach, comprising:

[0014] Obtaining the foreshore slope, median particle size of the shore and wave data of the forecast coast, wherein the wave data at least includes the effective wave height and spectrum peak period collected at the wave buoy, and the water depth data at the wave buoy;

[0015] According to the spectrum peak period and the water depth data, the wavelength data at the wave buoy is calculated by a linear wave theory algorithm and a Newton iteration algorithm;

[0016] According to the significant wave height, the spectrum peak period and the wavelength data, the deep water wavelength and the deep water significant wave height are calculated by a linear wave theory algorithm;

[0017] The predicted value of the maximum wave rise on the natural beach is calculated based on the deep water wavelength, the deep water effective wave height, the foreshore slope, and the median particle size of the beach;

[0018] The measured values ​​of the maximum wave water rise on natural beaches in different areas are collected, and error analysis is performed between the measured values ​​and the predicted values ​​to evaluate the accuracy of the maximum wave water rise prediction.

[0019] In the second aspect, based on the same inventive concept, the present application also provides a device for predicting the maximum wave surge on a natural beach, comprising:

[0020] A data acquisition module is configured to acquire the foreshore slope, median particle size of the shore and beach, and wave data of the forecast coast, wherein the wave data at least includes the effective wave height and spectrum peak period collected at the wave buoy, and the water depth data at the wave buoy;

[0021] A first calculation module is configured to calculate the wavelength data at the wave buoy according to the spectrum peak period and the water depth data through a linear wave theory algorithm and a Newton iteration algorithm;

[0022] A second calculation module is configured to calculate the deep water wavelength and the deep water effective wave height according to the effective wave height, the spectrum peak period and the wavelength data through a linear wave theory algorithm;

[0023] A prediction module is configured to calculate a predicted value of the maximum wave rise on a natural beach based on the deep water wavelength, the deep water effective wave height, the foreshore slope, and the median particle size of the beach;

[0024] The error analysis module is configured to collect measured values ​​of maximum wave water rise on natural beaches in different areas, and perform error analysis between the measured values ​​and the predicted values ​​to evaluate the accuracy of the maximum wave water rise prediction.

[0025] In the third aspect, based on the same inventive concept, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for predicting the maximum wave rise on a natural beach as described in the first aspect is implemented.

[0026] In a fourth aspect, based on the same inventive concept, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method for predicting the maximum wave rise on a natural beach as described in the first aspect.

[0027] Compared with the prior art, the maximum wave surge prediction method and related device on the natural beach described in this application have the following beneficial effects:

[0028] The maximum wave water rise prediction method and related devices on natural beaches described in this application, the prediction method quickly and accurately predicts the maximum wave water rise on natural beaches based on only a few simple data such as the beach foreshore slope, the median particle size of the beach sediment, and the wave height collected by the wave buoy. Compared with previous methods, this embodiment takes into account the influence of the beach sediment particle size on the wave water rise. The prediction method described in this embodiment can effectively improve the prediction accuracy of the maximum water rise value. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0030] Figure 1 This is a flow chart of the method for predicting the maximum wave surge on a natural beach described in an embodiment of the present application;

[0031] Figure 2 A comparison chart of the maximum wave surge prediction value and the measured value described in the embodiment of the present application;

[0032] Figure 3 A comparison chart of the maximum wave surge predicted by the formula of Stockdon et al. (2006) described in the embodiment of the present application and the measured value;

[0033] Figure 4 This is a comparison chart of the maximum wave surge predicted by the formula of Medellín et al. (2016) described in the embodiment of the present application and the measured value;

[0034] Figure 5 A comparison chart of the maximum wave surge predicted by the formula of Ji et al. (2018) described in the embodiment of the present application and the measured value;

[0035] Figure 6 A comparison chart of the maximum wave surge predicted by the O'Grady et al. (2019) formula described in the embodiment of the present application and the measured value;

[0036] Figure 7A comparison chart of the maximum wave surge predicted by the Dalinghaus et al. (2023) formula described in the embodiment of the present application and the measured value;

[0037] Figure 8 A comparison diagram of the relative root mean square error between the maximum wave surge prediction method on a natural beach described in an embodiment of the present application and other prediction methods;

[0038] Fig. 9 A comparison chart of the determination coefficients predicted by the maximum wave surge prediction method on a natural beach described in an embodiment of the present application and other prediction methods;

[0039] Fig.10 This is a schematic diagram of the structure of a device for predicting maximum wave surge on a natural beach according to an embodiment of the present application;

[0040] Fig.11 This is a schematic diagram of the hardware structure of the electronic device described in the embodiment of the present application. DETAILED DESCRIPTION

[0041] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0042] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like 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.

[0043] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0044] See also Figure 1 As shown, a method for predicting the maximum wave surge on a natural beach according to an embodiment of the present application specifically includes the following steps:

[0045] Step S101, obtaining the foreshore slope, median particle size of the shore and wave data of the forecast coast, wherein the wave data at least includes the effective wave height and spectrum peak period collected at the wave buoy, and the water depth data at the wave buoy.

[0046] Specifically, in this embodiment, 10 groups of field test data on 6 prototype coasts are included, namely: 4 groups of field tests on the Duck coast of the United States, the test times are October 1982, October 1990, October 1994, and October 1997 respectively; the field test on the Scripps coast of the United States, the test time is June 1989; the field test on the San Onofre coast of the United States, the test time is October 1993; the field test on the Gleneden coast of the United States, the test time is February 1994; the field test on the Agate coast of the United States, the test time is February 1996; and 2 groups of field tests on the Terschelling coast of the Netherlands, the test times are April and October 1994 respectively.

[0047] Step S102: According to the spectrum peak period and the water depth data, the wavelength data at the wave buoy is calculated by using a linear wave theory algorithm and a Newton iteration algorithm.

[0048] Specifically, in this embodiment, based on the effective wave height and spectrum peak period collected at the wave buoy set on the forecast coast in step S101, the wavelength data at the wave buoy is calculated by the linear wave theory algorithm and the Newton iteration algorithm, and the calculation formula is:

[0049]

[0050] Where L is the wavelength, g is the acceleration due to gravity, and T p is the spectrum peak period collected by the wave buoy, and h is the water depth at the wave buoy.

[0051] The Newton iteration algorithm is used to iteratively solve the above formula, which specifically includes the following steps:

[0052] (1) Order but

[0053] (2) Calculate the initial value of L0 as (equal to the wavelength of deep water);

[0054] (3) The first approximation of L is

[0055] (4) The second approximation of L is

[0056] (5) Repeat step (4) to obtain the mth approximation of L: Until |L m -L m-1 |<0.001m when the iteration ends, L m This is the wavelength L obtained by solution.

[0057] Step S103, calculating the deep-water wavelength and deep-water effective wave height according to the effective wave height, spectrum peak period and wavelength data by using a linear wave theory algorithm.

[0058] Specifically, in this embodiment, the calculation formula for the deep water wavelength is:

[0059]

[0060] Where L0 is the deep water wavelength;

[0061] The calculation formula for deep water effective wave height is:

[0062]

[0063]

[0064]

[0065]

[0066] In the formula, H s,0 is the deep water effective wave height, H s is the effective wave height collected by the wave buoy, k s is the shallow water deformation coefficient, n is the wave energy transmission rate, and k is the wave number.

[0067] Step S104: Calculate the predicted value of the maximum wave rise on the natural beach according to the deep water wavelength, deep water effective wave height, foreshore slope, and beach median particle size.

[0068] Specifically, in this embodiment, the calculation formula for the predicted value of the maximum wave surge on the natural beach is:

[0069]

[0070] Where η max is the predicted value of the maximum wave surge on the natural beach, β s is the foreshore slope angle, D 50 is the median particle size on the beach.

[0071] Step S105: collect the measured values ​​of the maximum wave water rise on natural beaches in different areas, and perform error analysis between the measured values ​​and the predicted values ​​to evaluate the accuracy of the maximum wave water rise prediction.

[0072] In this example, the maximum wave rise data of 10 sets of field tests on 6 prototype coasts were collected. The specific test and data processing methods are shown in reference [1]. Figure 2 The figure shows the comparison between the maximum wave rise value on the natural beach predicted by the method described in this embodiment and the measured value.

[0073] Specifically, in this embodiment, the relative root mean square error formula (RRMSE) and the determination coefficient (R 2 ) formula as an evaluation index, and performing error analysis on the measured value and the predicted value, including:

[0074]

[0075]

[0076] Where N is the number of samples, x i and i They represent the predicted value and measured value of the maximum wave surge on the natural beach, is the average value of the measured maximum wave surge, RRMSE is the relative root mean square error, R 2 is the coefficient of determination. The smaller the RRMSE, the higher the R 2 The closer it is to 1, the higher the prediction accuracy.

[0077] The method for predicting the maximum wave water rise on a natural beach described in this embodiment quickly and accurately predicts the maximum wave water rise on a natural beach based on only a few simple data such as the beach foreshore slope, the median particle size of the sediment on the beach, and the wave height collected by the wave buoy. Compared with previous methods, this embodiment takes into account the influence of the particle size of the beach sediment on the wave water rise. The prediction method described in this embodiment can effectively improve the prediction accuracy of the maximum water rise value.

[0078] In this embodiment, the existing maximum wave surge calculation methods of the same type used for prediction effect comparison include: Stockdon et al. (2006) formula (reference [1]), Medellín et al. (2016) formula (reference [2]), Ji et al. (2018) formula (reference [3]), O'Grady et al. (2019) formula (reference [4]), Dalinghaus et al. (2023) formula (reference [5]).

[0079] Figures 3 to 7 To compare the maximum wave surge prediction value and the measured value obtained by the above calculation method of the embodiment, Figure 8 The relative root mean square error (RRMSE) of the maximum wave surge value predicted by the method described in this embodiment is compared with that of the existing method. Fig. 9 is the maximum wave rise value determination coefficient (R 2 ) compared with existing methods.

[0080] According to statistics, the relative root mean square error (RRMSE) of the method described in this embodiment in this embodiment is 0.29, which is 22.0% lower than the formula of Stockdon et al. (2006), 53.7% lower than the formula of Medellín et al. (2016), 10.5% lower than the formula of Ji et al. (2018), 16.5% lower than the formula of O'Grady et al. (2019), and 10.6% lower than the formula of Dalinghaus et al. (2023); the coefficient of determination (R 2 ) is 0.66, which is 0.22 higher than the formula of Stockdon et al. (2006), 1.26 higher than the formula of Medellín et al. (2016), 0.09 higher than the formula of Ji et al. (2018), 0.15 higher than the formula of O'Grady et al. (2019), and 0.09 higher than the formula of Dalinghaus et al. (2023).

[0081] In summary, the results of the above two evaluation indicators show that the method described in this embodiment significantly improves the prediction accuracy of the maximum wave surge on the natural beach.

[0082] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0083] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application also provides a device for predicting the maximum wave surge on a natural beach.

[0084] like Fig.10 As shown, the maximum wave surge prediction device on the natural beach includes:

[0085] The data acquisition module 11 is configured to acquire the foreshore slope, the median particle size of the shore and the wave data of the forecast coast, wherein the wave data at least includes the effective wave height and the spectrum peak period collected at the wave buoy, and the water depth data at the wave buoy;

[0086] The first calculation module 12 is configured to calculate the wavelength data at the wave buoy according to the spectrum peak period and the water depth data through a linear wave theory algorithm and a Newton iteration algorithm;

[0087] The second calculation module 13 is configured to calculate the deep water wavelength and the deep water effective wave height according to the effective wave height, the spectrum peak period and the wavelength data and through a linear wave theory algorithm;

[0088] The prediction module 14 is configured to calculate the predicted value of the maximum wave surge on the natural beach according to the deep water wavelength, the deep water effective wave height, the foreshore slope, and the median particle size of the beach;

[0089] The error analysis module 15 is configured to collect the measured values ​​of the maximum wave water rise on natural beaches in different areas, and perform error analysis between the measured values ​​and the predicted values ​​to evaluate the accuracy of the maximum wave water rise prediction.

[0090] For the convenience of description, the above devices are described in terms of functions and are divided into various modules. Of course, when implementing the embodiments of the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0091] The device of the above embodiment is used to implement the corresponding maximum wave rise prediction method on the natural beach in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0092] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for predicting the maximum wave rise on a natural beach as described in any of the above embodiments is implemented.

[0093] Fig.11 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 in the device.

[0094] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0095] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0096] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0097] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0098] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0099] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0100] The electronic device of the above embodiment is used to implement the corresponding maximum wave surge prediction method on the natural beach in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0101] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the maximum wave rise prediction method on the natural beach as described in any of the above embodiments.

[0102] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0103] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the maximum wave rise prediction method on the natural beach as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0104] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0105] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0106] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0107] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of the present application.

Claims

1. A method for predicting the maximum wave surge on a natural beach, characterized in that: include: Obtaining the foreshore slope, median particle size of the shore and wave data of the forecast coast, wherein the wave data at least includes the effective wave height and spectrum peak period collected at the wave buoy, and the water depth data at the wave buoy; According to the spectrum peak period and the water depth data, the wavelength data at the wave buoy is calculated by a linear wave theory algorithm and a Newton iteration algorithm; According to the significant wave height, the spectrum peak period and the wavelength data, the deep water wavelength and the deep water significant wave height are calculated by a linear wave theory algorithm; The predicted value of the maximum wave rise on the natural beach is calculated based on the deep water wavelength, the deep water effective wave height, the foreshore slope, and the median particle size of the beach; The measured values ​​of the maximum wave water rise on natural beaches in different areas are collected, and error analysis is performed between the measured values ​​and the predicted values ​​to evaluate the accuracy of the maximum wave water rise prediction.

2. The method for predicting the maximum wave surge on a natural beach according to claim 1, characterized in that: The wavelength data calculation formula at the wave buoy is: Where L is the wavelength at the wave buoy, g is the gravitational acceleration, T p is the spectrum peak period collected at the wave buoy, and h is the water depth at the wave buoy.

3. The method for predicting the maximum wave surge on a natural beach according to claim 2, characterized in that: The calculation formula for the deep water wavelength is: Where L0 is the deep water wavelength.

4. The method for predicting the maximum wave surge on a natural beach according to claim 3, characterized in that: The calculation formula for the deep water significant wave height is: In the formula, H s,0 is the deep water effective wave height, H s is the effective wave height collected at the wave buoy, k s is the shallow water deformation coefficient, n is the wave energy transmission rate, and k is the wave number.

5. The method for predicting the maximum wave surge on a natural beach according to claim 4, characterized in that: The calculation formula for the predicted value of the maximum wave surge on the natural beach is: Where η max is the predicted value of the maximum wave surge on the natural beach, β s is the foreshore slope angle, D 50 is the median particle size on the beach.

6. The method for predicting the maximum wave surge on a natural beach according to claim 1, characterized in that: By using the relative root mean square error formula and the determination coefficient formula as evaluation indicators, the error analysis of the measured value and the predicted value is performed, including: Where N is the number of samples, x i and i They represent the predicted value and measured value of the maximum wave surge on the natural beach, is the average value of the measured maximum wave surge, RRMSE is the relative root mean square error, R 2 is the determination coefficient.

7. A device for predicting maximum wave surge on a natural beach, characterized in that: include: A data acquisition module is configured to acquire the foreshore slope, median particle size of the shore and beach, and wave data of the forecast coast, wherein the wave data at least includes the effective wave height and spectrum peak period collected at the wave buoy, and the water depth data at the wave buoy; A first calculation module is configured to calculate the wavelength data at the wave buoy according to the spectrum peak period and the water depth data through a linear wave theory algorithm and a Newton iteration algorithm; A second calculation module is configured to calculate the deep water wavelength and the deep water effective wave height according to the effective wave height, the spectrum peak period and the wavelength data through a linear wave theory algorithm; A prediction module is configured to calculate a predicted value of the maximum wave rise on a natural beach based on the deep water wavelength, the deep water effective wave height, the foreshore slope, and the median particle size of the beach; The error analysis module is configured to collect measured values ​​of maximum wave water rise on natural beaches in different areas, and perform error analysis between the measured values ​​and the predicted values ​​to evaluate the accuracy of the maximum wave water rise prediction.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method for predicting the maximum wave rise on a natural beach according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium, characterized in that: in, The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for predicting the maximum wave rise on a natural beach according to any one of claims 1 to 6.

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