Hydrodynamic model system based on MIKE 21FM model and automatic parameter judging, setting, selecting and testing method

Abstract

The invention discloses a hydrodynamic model system based on an MIKE 21FM model and an automatic parameter judging, setting, selecting and testing method, and belongs to the technical field of hydrodynamic simulation. In order to solve the problems that in the prior art, MIKE 21FM model parameters are complex to set, difficult to select and tedious in verification process, an automatic parameter judging and setting system is constructed; the system can automatically judge and set model parameters according to model characteristics and hydrological conditions of a research area, and meanwhile, automatically select proper parameters and verify and check the parameters, so that the rationality and reliability of the parameters are ensured. By means of the method, the efficiency and accuracy of MIKE 21FM model parameter setting can be remarkably improved, and powerful support is provided for hydrodynamic simulation; in addition, the method is also combined with a machine learning technology to further optimize a parameter selection process and improve a simulation effect; the method is widely applied to hydrodynamic simulation of rivers, lakes, offshore water areas and the like, and has remarkable practical application value.

Description

Technical Field

[0001] The present invention relates to the technical field of ocean hydrology and ocean wind energy resource utilization, and in particular to a hydrodynamic model system based on a MIKE 21FM model and a parameter automatic judgment setting, selection and testing method. Background Art

[0002] In the field of ocean hydrology and utilization of marine wind energy resources, the study of the temporal and spatial distribution of ocean dynamic factors such as wind, waves and currents has far-reaching significance. These dynamic factors not only affect the marine environment, but are also closely related to sea-air interaction, disaster prevention and mitigation, and the development and utilization of marine energy. Traditionally, people rely on physical model experiments or field measurements to obtain relevant data, but these methods are not only expensive and time-consuming, but also in my country, due to the relative scarcity of actual marine meteorological observation data and the lack of temporal and spatial consistency, the application of these methods is subject to certain limitations.

[0003] With the rapid development of computer technology, the use of mathematical models to analyze the changing laws of marine hydrological elements has gradually become an important research method. However, marine hydrology is affected by many factors, and there are many methods for numerical simulation research, and each method has a certain scope of application due to different physical assumptions. In practical applications, researchers often need to choose appropriate methods based on the specific research area and purpose. This process is not only cumbersome, but also easy to cause confusion or inconvenience.

[0004] At present, although some ocean hydrological numerical simulation methods based on mathematical models have been proposed, these methods still have some problems in practical application. For example, some methods may be too simplified and cannot accurately reflect the complex changes in ocean hydrology; while other methods may be too complicated, resulting in low computational efficiency and difficult to be widely used in practical engineering. In addition, the setting and selection of model parameters often rely on the experience and subjective judgment of researchers, lacking an automated and objective method.

[0005] Especially for the widely used hydrodynamic model MIKE 21FM, its parameter setting and selection are crucial to the accuracy of simulation results. However, most of the existing parameter setting methods rely on manual operation and empirical judgment, which is not only inefficient but also easily affected by human factors, resulting in inaccurate parameter selection, which in turn affects the simulation effect.

[0006] In summary, the prior art lacks a method that can automatically determine, set, select and verify hydrodynamic model parameters to solve the problems of low efficiency and insufficient accuracy in parameter selection. Therefore, the present invention aims to provide a method for automatically determining, setting, selecting and verifying hydrodynamic model parameters based on the MIKE 21FM model to improve the efficiency and accuracy of model parameter selection and provide more reliable technical support for marine hydrological numerical simulation research. Summary of the invention

[0007] The technical problem to be solved by the present invention is to provide a hydrodynamic model system based on the MIKE 21FM model and a parameter automatic judgment setting, selection and verification method, so as to solve the technical problems of low efficiency and insufficient accuracy in setting and selecting hydrodynamic model parameters in the field of marine hydrology and marine wind energy resource utilization.

[0008] In order to solve the above technical problems, the technical solution adopted by the present invention is: an automatic judgment setting, selection and inspection method of hydrodynamic model parameters based on the MIKE 21FM model, comprising the following steps: Step 1: Build an automated parameter judgment and setting system that can automatically judge and set model parameters based on the characteristics of the MIKE 21FM model and the hydrological conditions of the study area; Step 2: Input the hydrological condition data of the study area through the system and automatically select appropriate model parameters; Step 3: Verify and check the selected model parameters to ensure the rationality and reliability of the parameters.

[0009] In a preferred solution, the automated parameter judgment and setting system in Step 1 has built-in multiple parameter selection algorithms, which can intelligently select the optimal parameter combination based on the input data and conditions.

[0010] In a preferred solution, in the process of parameter determination and setting in Step 1, the geographical characteristics, climatic conditions and historical hydrological data of the study area are also considered to further optimize the parameter selection.

[0011] In a preferred solution, Step 1 also includes combining machine learning technology to learn and identify optimal parameters under different hydrological conditions through training models to improve the accuracy and efficiency of parameter selection.

[0012] In a preferred solution, the parameter verification and calibration step in Step 3 includes using a simulation experiment to input the set parameters into the MIKE 21FM model for simulation, and comparing and analyzing the simulation results with the measured data.

[0013] In a preferred embodiment, the MIKE 21 FM model is based on the two-dimensional incompressible Reynolds averaged NS equations based on Boussinesq and fluid static pressure assumptions, and its basic principles are as follows: Continuity equation: (1) Momentum equation: (2) (3) In the formula, For time; , It is a right-handed Cartesian coordinate system; for water depth; , The flow rates are , Directional weight; is the local atmospheric pressure; is the water density, is the reference water density; is the Coriolis force parameter; and is the acceleration caused by the rotation of the Earth; , , , is the radiation stress component; , , , is the horizontal viscous stress term; The source-sink term indicates whether there is external injection, i.e. source, or outflow, i.e. sink, in the fluid system; , They are , Directional source and sink flow velocity, , for , The average flow velocity of water in the direction; is the acceleration due to gravity; is the unit volume of water.

[0014] In a preferred embodiment, the turbulence modeling of the MIKE 21 FM model adopts the Smagorinsky subgrid scale model in the large eddy simulation method. The model uses an effective eddy viscosity value related to the characteristic length scale to describe the subgrid scale transport. The subgrid scale eddy viscosity value is given by the following formula: (4) In the formula, is a fixed value, is the characteristic length, is the sub-grid scale eddy viscosity value, is the deformation rate; The deformation rate is given by: (5) Bottom stress: Bottom stress Following the law of quadratic friction: (6) in is the drag coefficient, is the bottom flow slip velocity, is the bottom stress; For two-dimensional calculations, is the average velocity with respect to water depth, and the drag coefficient can be given by the Manning coefficient get: (7) Manning coefficient It can be obtained from the bottom bed roughness length: (8).

[0015] In the preferred solution, the verification and calibration of the selected model parameters in Step 3 is carried out by introducing , and Parameters are used to quantitatively detect the deviation between the simulated values ​​and the measured values ​​of the numerical model constructed in this study, where Root mean square error The function calculation formula is as follows: (9) Skewness The calculation formula is as follows: (10) Correlation coefficient The calculation formula is as follows: (11) In the formula, is the total number of test samples, is the measured value, Calculate values ​​for the model, is the average of the measured values, The mean of the values ​​calculated for the model.

[0016] In a preferred embodiment, the method further comprises performing a sensitivity analysis on the selected model parameters to determine the degree of influence of the parameters on the simulation results, and adjusting the parameter settings accordingly.

[0017] A hydrodynamic simulation system based on the MIKE 21FM model that applies any of the above-mentioned methods for automatically judging, setting, selecting and verifying the hydrodynamic model parameters based on the MIKE 21FM model, comprises a data input module, a parameter judgment and setting module, a simulation module and a verification module, wherein: the data input module is used to input the hydrological condition data of the study area; the parameter judgment and setting module is used to automatically judge and set the model parameters according to the input data and the characteristics of the MIKE 21FM model; the simulation module is used to perform hydrodynamic simulation according to the set parameters; and the verification module is used to verify and check the simulation results.

[0018] In a preferred solution, the parameter judgment and setting module also has a parameter optimization function, which automatically adjusts the parameter value to achieve the best simulation effect according to the comparison between the simulation results and the measured data.

[0019] The hydrodynamic model system based on the MIKE 21FM model and the parameter automatic judgment setting, selection and inspection method provided by the present invention have the following beneficial effects: 1. The present invention solves the technical problems of low efficiency and insufficient accuracy in setting and selecting parameters of hydrodynamic models in the field of marine hydrology and marine wind energy resource utilization; 2. Through the long-term research and publicity of the marine hydrological and physical conditions in different sea areas of my country by professionals, combined with the characteristics of the hydrodynamic model itself, this invention has designed a method for automatically judging, setting and selecting model parameters according to the actual needs of simulation, solving the problems of high cost, long time and scarce observation data of physical experiments and field measurements in the field of marine hydrology, and limited and confusing scope of application caused by different physical assumptions of different methods; 3. The present invention constructs an automated parameter judgment and setting system, which can automatically judge and set model parameters according to the characteristics of the MIKE 21FM model and the hydrological conditions of the study area. The system has built-in multiple parameter selection algorithms, which can intelligently select the optimal parameter combination according to the input data and conditions; 4. The present invention introduces , and Parameters such as the model simulation value and the measured value are used to quantitatively detect the deviation between them, so as to more accurately verify the accuracy of parameter selection and improve the accuracy and efficiency of hydrodynamic model parameter selection. 5. The present invention further verifies the accuracy of parameter selection by introducing a quantitative parameter verification method, making the model simulation results more reliable; 6. The present invention combines machine learning technology to learn and identify the optimal parameters under different hydrological conditions through training models, thereby further improving the accuracy and efficiency of parameter selection; 7. The present invention also designs a parameter verification mechanism to verify and check the set and selected parameters to ensure the rationality and reliability of the parameters; 8. The present invention improves the efficiency and accuracy of the selection and setting of hydrodynamic model parameters, reduces the influence of human factors, and thus improves the simulation effect of the MIKE 21FM model; 9. The conclusions of the present invention have been fully verified through actual simulation experiments and comparative analysis. The experimental results show that the method provided by the present invention can significantly shorten the time for parameter selection and improve the accuracy and stability of simulation results, providing more reliable technical support for marine hydrological numerical simulation research; 10. The present invention is also highly scalable and can be customized and expanded according to different research needs, providing a solid foundation for the in-depth research and application of hydrodynamic models, and is expected to play an important role in water resources management and environmental protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention will be further described below in conjunction with the accompanying drawings and implementation examples: Figure 1 It is a technical flow chart of the method of the present invention. DETAILED DESCRIPTION

[0021] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments: Example 1 like Figure 1 As shown, the method for automatically determining, setting, selecting and verifying the parameters of a hydrodynamic model is based on the MIKE 21FM model, and includes the following steps: Step 1: Build an automated parameter judgment and setting system that can automatically judge and set model parameters based on the characteristics of the MIKE 21FM model and the hydrological conditions of the study area; Step 2: Input the hydrological condition data of the study area through the system and automatically select appropriate model parameters; Step 3: Verify and check the selected model parameters to ensure the rationality and reliability of the parameters.

[0022] In this embodiment, the automated parameter judgment and setting system in Step 1 has built-in multiple parameter selection algorithms, which can intelligently select the optimal parameter combination according to the input data and conditions.

[0023] Furthermore, in the process of parameter determination and setting in Step 1, the geographical characteristics, climate conditions and historical hydrological data of the study area are also considered to further optimize the parameter selection.

[0024] Furthermore, the Step 1 also includes combining machine learning technology to learn and identify the optimal parameters under different hydrological conditions through training models to improve the accuracy and efficiency of parameter selection.

[0025] Furthermore, the parameter verification and calibration step in Step 3 includes using a simulation experiment to input the set parameters into the MIKE 21FM model for simulation, and comparing and analyzing the simulation results with the measured data.

[0026] Furthermore, the MIKE 21 FM model is based on the two-dimensional incompressible Reynolds-averaged Navier-Stokes equations (Navier-Stokes equations) of Boussinesq and hydrostatic pressure assumptions, and its basic principle is as follows: Continuity equation: (1) Momentum equation: (2) (3) In the formula, For time; , It is a right-handed Cartesian coordinate system; for water depth; , The flow rates are , Directional weight; is the local atmospheric pressure; is the water density, is the reference water density; is the Coriolis force parameter; and is the acceleration caused by the rotation of the Earth; , , , is the radiation stress component; , , , is the horizontal viscous stress term; The source-sink term indicates whether there is external injection, i.e. source, or outflow, i.e. sink, in the fluid system; , They are , Directional source and sink flow velocity, , for , The average flow velocity of water in the direction; is the acceleration due to gravity; is the unit volume of water.

[0027] Furthermore, the turbulence modeling of the MIKE 21 FM model adopts the Smagorinsky (1963) subgrid scale model in the large eddy simulation method. This model uses an effective eddy viscosity value related to the characteristic length scale to describe the subgrid scale transport. The subgrid scale eddy viscosity value is given by the following formula: (4) In the formula, is a fixed value, is the characteristic length, is the sub-grid scale eddy viscosity value, is the deformation rate; The deformation rate is given by: (5) Bottom stress: Bottom stress Following the law of quadratic friction: (6) in is the drag coefficient, is the bottom flow slip velocity, is the bottom stress; For two-dimensional calculations, is the average velocity with respect to water depth, and the drag coefficient can be given by the Manning coefficient get: (7) Manning coefficient It can be obtained from the bottom bed roughness length: (8).

[0028] Furthermore, the verification and calibration of the selected model parameters in Step 3 is carried out by introducing , and Parameters are used to quantitatively detect the deviation between the simulated values ​​and the measured values ​​of the numerical model constructed in this study, where The calculation formula of the root mean square error (Root Mean Square Error) function is as follows: (9) Skewness The Skewness calculation formula is as follows: (10) Correlation coefficient The calculation formula of (Correlation Coefficients) is as follows: (11) In the formula, is the total number of test samples, is the measured value, Calculate values ​​for the model, is the average of the measured values, The average of the values ​​calculated for the model; Furthermore, the method also includes performing a sensitivity analysis on the selected model parameters to determine the degree of influence of the parameters on the simulation results and adjusting the parameter settings accordingly.

[0029] Example 2 In another preferred embodiment, based on Example 1, Figure 1 As shown, a hydrodynamic simulation system based on the MIKE21FM model that applies any of the above-mentioned methods for automatically judging, setting, selecting and verifying the hydrodynamic model parameters based on the MIKE 21FM model includes a data input module, a parameter judgment and setting module, a simulation module and a verification module, wherein: the data input module is used to input the hydrological condition data of the study area; the parameter judgment and setting module is used to automatically judge and set the model parameters according to the input data and the characteristics of the MIKE 21FM model; the simulation module is used to perform hydrodynamic simulation according to the set parameters; and the verification module is used to verify and check the simulation results.

[0030] In this embodiment, the parameter judgment and setting module also has a parameter optimization function, which automatically adjusts the parameter value to achieve the best simulation effect according to the comparison between the simulation results and the measured data.

[0031] Example 3 In another preferred embodiment, based on embodiments 1 and 2, Figure 1 As shown, the technical solution and implementation methods of the present invention will be described in detail below in conjunction with specific embodiments.

[0032] The specific implementation method of the automatic judgment setting, selection and verification method of the hydrodynamic model parameters based on the MIKE 21FM model: First, an automated parameter judgment and setting system is constructed; the system includes a data input module, a parameter judgment module, a parameter setting module and an output module; the data input module is used to receive hydrological condition data of the study area, such as water depth, flow velocity, wind direction, etc. The parameter judgment module has built-in multiple parameter selection algorithms, which can automatically judge and select appropriate model parameters based on the input data and the characteristics of the MIKE 21FM model; the parameter setting module sets the parameters of the MIKE 21FM model according to the results of the parameter judgment module; the output module is used to output the set model parameters, as well as the relevant parameter descriptions and setting basis.

[0033] In the specific operation, the hydrological condition data of the study area is first input through the data input module; then, the parameter judgment module starts to work, analyzes and processes the input data according to the preset algorithm and logic, and selects the model parameters that best suit the current hydrological conditions; the parameter setting module then sets the corresponding parameters of the MIKE 21FM model according to the results of the parameter judgment module; finally, the set model parameters are output through the output module for subsequent simulation use.

[0034] In order to further improve the accuracy and efficiency of parameter selection, this embodiment also combines machine learning technology; specifically, by collecting a large amount of hydrological condition data and corresponding model parameter data, a machine learning model is trained; the model can learn and identify the optimal parameters under different hydrological conditions, so that under new hydrological conditions, it can quickly and accurately give optimal parameter selection suggestions.

[0035] In addition, this embodiment also designs a parameter verification mechanism; after the parameter setting is completed, the set and selected parameters are verified and checked through this mechanism; specifically, a simulation experiment can be used to input the set parameters into the MIKE 21FM model for simulation, and then the simulation results are compared and analyzed with the measured data; if the simulation results are consistent with the measured data, it means that the parameter setting is reasonable; if there is a large difference between the simulation results and the measured data, it is necessary to readjust the parameters and perform verification and verification again.

[0036] Example 4 In another preferred embodiment, based on embodiments 1, 2, and 3, Figure 1 As shown, this embodiment provides another specific implementation method of the automatic judgment setting, selection and verification method of the hydrodynamic model parameters based on the MIKE 21FM model. Different from Example 3, this embodiment focuses more on the optimization of the parameter selection method.

[0037] In the specific implementation, a parameter database is first constructed, which stores a large amount of hydrological condition data and corresponding model parameter data; then, through data mining and machine learning techniques, the data in the database are analyzed and processed to extract the selection rules of the optimal parameters under different hydrological conditions.

[0038] When selecting parameters, we first search for similar historical cases in the parameter database based on the hydrological conditions data of the study area; then, based on the optimal parameter selection rules in historical cases and combined with the current hydrological conditions, we select the most suitable model parameters.

[0039] In order to improve the accuracy and reliability of parameter selection, this embodiment also designs a parameter optimization algorithm; the algorithm can continuously adjust the parameter values ​​through iterative optimization according to the selected initial parameters, so that the degree of consistency between the simulation results and the measured data is optimal.

[0040] Similarly, after the parameter setting is completed, this embodiment also adopts a set of parameter verification mechanisms to verify and check the parameters; by comparing simulation experiments with actual measured data, the rationality and reliability of the parameter setting are ensured.

[0041] Example 5 In another preferred embodiment, based on embodiments 1, 2, 3, and 4, taking the Guangdong waters as an example, the specific implementation method of the automatic judgment setting, selection, and inspection method of the hydrodynamic model parameters based on the MIKE 21FM model is described in detail: 1. Different settings according to the simulation area There are many factors affecting ocean dynamics in different sea areas. The combined effects of tides, circulation, monsoons and other factors form a complex and changeable hydrodynamic change process in the sea area, resulting in unsatisfactory numerical simulation results in subdivided sea areas. Therefore, the hydrodynamic numerical model of provincial subdivided sea areas needs to be meshed to improve the precision and accuracy of the simulated target sea area. The grid is set to triple encryption, with a triangular grid side length of about 8km in the nearshore sea area and a minimum triangular grid side length of about 0.5km.

[0042] 2. Selection of boundary-driven data The scope of China's coastal waters is relatively small compared to the Pacific Ocean, and the tides generated by the tidal force of celestial bodies in the sea area itself are very small; it is calculated that the independent tide of the Yellow Sea is about 3% of the Yellow Sea tide; the amplitude of the high tide generated by the tidal force of the South China Sea at dawn is only 8 cm; it can be seen that the tides in China's coastal waters are mainly the coordinated vibration of the Pacific Ocean tidal waves transmitted to this sea area, and the sea area itself has no independent tidal wave system; based on this, the hydrodynamic model of the Chinese sea area targeted by the present invention can directly use the DTU10 global tidal model data as the offshore tidal boundary driver. DTU 10 is a tidal model established by the Technical University of Denmark (DTU) based on FES2004, with a spatial resolution of 0.125°.

[0043] 3. Choice of adjustment according to terrain The spatial scale of the Reynolds stress caused by the fluid is much smaller than the above-mentioned grid scale, which can easily cause model data overflow. This is because it is necessary to consider the influence of the bottom bed (ocean topography) on the movement of water flow and introduce the eddy viscosity coefficient to calculate the corresponding Reynolds stress.

[0044] In this embodiment, the Smagorinsky formula is used to calculate the eddy viscosity coefficient: (4) The deformation rate is given by: (5) In the formula, the Smagorinsky coefficient needs to be determined according to different terrain conditions (optional values ​​are between 0.25 and 1.0). The underwater terrain in the South my country Sea is relatively flat, so it can be set to 0.28. The Bohai Sea and the Yellow Sea are greatly affected by the continental shelf and river estuaries, so they can be set to 0.35. The East China Sea region is based on the model simulation range. If the nearshore area is large, it can refer to the Bohai Sea and the Yellow Sea. If the offshore distance is greater than 50km, it can be set to 0.30.

[0045] 4. Adjustment based on water depth Manning coefficient To reflect the influence of the bottom bed on the water flow at different depths, the unit is , adjusted according to the water depth. If the offshore distance is less than 30km, set it to 25; if the offshore distance is between 30km and 50km, set it to 32; if the offshore distance is greater than 50km, set it to 36.

[0046] 5. Inspection methods After the parameters are adjusted and the model is simulated, the following method is used for verification: In order to further verify the accuracy of parameter selection, this study introduces , and Parameters such as ΔE and ΔV are used to quantitatively detect the deviation between the simulated values ​​and the measured values ​​of the numerical model constructed in this study.

[0047] Root mean square error The function calculation formula is as follows: (9) Skewness The calculation formula is as follows: (10) Correlation coefficient The calculation formula is as follows: (11); use It reflects the degree of deviation between the actual value and the predicted value. The smaller it is, the better the quality of model parameter selection is and the more accurate the prediction is. The value range divides the quality of the simulation effect. [0.5, 0.6) means very good, [0.2, 0.5) means fair, According to the results of the test method, the parameter values ​​of steps 1 to 4 are adjusted, and further verification is performed to obtain the optimal result. The hydrodynamic model parameters are shown in Table 1: Table 1 Hydrodynamic model parameter settings

[0048] Using the collected on-site hydrological tests of tide stations, the tidal characteristics of Zhuhai Port were verified according to step 5. The time and accuracy of model parameter selection were improved, thereby further improving the simulation effect of the hydrodynamic model.

[0049] The specific implementation of the present invention fully demonstrates the technical solution and implementation process of the automatic judgment setting, selection and verification method of the hydrodynamic model parameters based on the MIKE 21FM model through detailed description and demonstration of multiple embodiments. These embodiments not only explain various aspects of the invention in detail, but also demonstrate the diversity and practicality of the invention through different implementation methods and optimization algorithms; at the same time, the reliability and stability of the invention are further enhanced through the introduction of the parameter verification mechanism.

[0050] In the preferred solution, the automated parameter judgment setting system in Step 1 has built-in multiple parameter selection algorithms, which can intelligently select the optimal parameter combination based on the input data and conditions; the above settings greatly improve the efficiency and accuracy of data processing, making the entire process smoother and more reliable; at the same time, the system also supports user-defined parameters to meet the personalized needs of different projects and scenarios.

[0051] In the preferred scheme, in the process of parameter judgment and setting in Step 1, the geographical characteristics, climatic conditions and historical hydrological data of the study area are also considered to further optimize the parameter selection; the above settings are intended to ensure that the model can more accurately reflect the actual situation and improve the accuracy and reliability of the flood early warning system; at the same time, the preliminary prediction results will be dynamically corrected in combination with real-time monitoring data.

[0052] In the preferred scheme, Step 1 also includes combining machine learning technology to learn and identify the optimal parameters under different hydrological conditions through training models to improve the accuracy and efficiency of parameter selection; the above settings can automatically adjust the working mode of the monitoring equipment to ensure high-precision hydrological data collection in various complex environments, thereby providing a more reliable scientific basis for water resources management and flood prevention and disaster reduction.

[0053] In the preferred solution, the parameter verification and calibration step in Step 3 includes using a simulation experiment to input the set parameters into the MIKE 21FM model for simulation, and comparing and analyzing the simulation results with the measured data; the above settings ensure the rationality and accuracy of the parameter settings; if it is found that there is a significant difference between the simulation results and the measured data, the parameters are adjusted and the simulation is repeated until the simulation results are basically consistent with the measured data, thereby ensuring the prediction accuracy of the model.

[0054] In the preferred solution, the method also includes performing a sensitivity analysis on the selected model parameters to determine the degree of influence of the parameters on the simulation results and adjusting the parameter settings accordingly; the above settings can greatly improve the prediction accuracy and stability of the model; in addition, the solution also introduces a real-time feedback mechanism to dynamically fine-tune the parameters according to the deviation between the simulation results and the actual data to ensure that the model is always close to the actual situation.

[0055] In the preferred scheme, the parameter judgment and setting module also has a parameter optimization function, which automatically adjusts the parameter value to achieve the optimal simulation effect according to the comparison between the simulation results and the measured data; the above settings not only improve the accuracy of the simulation, but also greatly shorten the time for parameter adjustment, so that the entire system can run more efficiently; in addition, the module also has self-learning ability, which can further improve the optimization efficiency in continuous iteration.

[0056] In summary, the hydrodynamic model system based on the MIKE 21FM model and the method for automatic judgment, setting, selection and verification of parameters proposed in the present invention solve the technical problems of low efficiency and insufficient accuracy in the setting and selection of hydrodynamic model parameters in the field of marine hydrology and marine wind energy resource utilization; the technical solution of the present invention proposes a new method for automatic parameter setting and selection, which is based on the physical framework and calculation equation group of the hydrodynamic model MIKE 21FM, combined with the research of professionals on the marine hydrological and physical conditions of different sea areas in my country, and realizes the automatic judgment, setting and selection of model parameters. Compared with the traditional manual parameter setting, this method greatly improves the efficiency and accuracy of parameter selection; in terms of parameter verification, the scheme introduces (Root Mean Square Error), (skewness) and (correlation coefficient) and other parameters are used to quantitatively detect the deviation between the model simulation value and the measured value; the introduction of these parameters makes the parameter verification process more scientific and accurate, and can more effectively verify the accuracy of parameter selection; in the process of parameter setting and selection, multiple factors such as simulation area, grid accuracy, boundary driving data, terrain conditions and water depth conditions are comprehensively considered to ensure that the selection of model parameters is more in line with the actual situation and improve the simulation effect of the model; the present invention combines the research of professionals on the marine hydrophysical conditions in different sea areas of my country with the characteristics of the hydrodynamic model MIKE 21FM, and designs a new method for automatic parameter judgment, setting, selection and verification; this method not only improves the efficiency and accuracy of parameter selection, but also makes the selection of model parameters more in line with the actual situation; it introduces , and The scheme provides a new and more scientific method for testing the parameters of the hydrodynamic model by taking parameters such as the surface area, depth, and depth of the water as the test criteria. The introduction of these parameters not only makes the parameter testing process more accurate and reliable, but also provides strong support for the subsequent optimization and improvement of the model. The present invention realizes the refined setting of the model parameters by comprehensive consideration of grid encryption, terrain conditions and water depth conditions. This refined setting not only improves the simulation effect of the model, but also provides more accurate and reliable data support for the simulation and evaluation of the marine hydrophysical conditions. The present invention also realizes the intelligent optimization of the model parameters by integrating advanced algorithms and data processing technologies, which significantly improves the accuracy and efficiency of marine environment simulation and provides strong technical support for the development of marine resources and environmental protection.

Claims

1. The method for automatically determining, setting, selecting and testing the parameters of the hydrodynamic model based on the MIKE 21FM model is characterized by: The method comprises the following steps: Step 1: Build an automated parameter determination and setting system, which automatically determines and sets model parameters based on the characteristics of the MIKE 21FM model and the hydrological conditions of the study area; Step 2: Input the hydrological condition data of the study area through the system and automatically select appropriate model parameters; Step 3: Verify and check the selected model parameters to ensure the rationality and reliability of the parameters.

2. The method for automatically determining, setting, selecting and testing hydrodynamic model parameters based on the MIKE 21FM model according to claim 1, characterized in that: The automated parameter judgment and setting system in Step 1 has built-in multiple parameter selection algorithms, which can intelligently select the optimal parameter combination based on the input data and conditions.

3. The method for automatically determining, setting, selecting and testing hydrodynamic model parameters based on the MIKE 21FM model according to claim 2, characterized in that: In the process of parameter determination and setting in Step 1, the geographical characteristics, climatic conditions and historical hydrological data of the study area are also considered to further optimize the parameter selection.

4. The method for automatically determining, setting, selecting and testing hydrodynamic model parameters based on the MIKE 21FM model according to claim 3 is characterized in that: The Step 1 also includes combining machine learning technology to learn and identify optimal parameters under different hydrological conditions by training models to improve the accuracy and efficiency of parameter selection.

5. The method for automatically determining, setting, selecting and testing hydrodynamic model parameters based on the MIKE 21FM model according to claim 4 is characterized in that: The parameter verification and calibration step in Step 3 includes using a simulation experiment to input the set parameters into the MIKE 21FM model for simulation, and comparing and analyzing the simulation results with the measured data.

6. The method for automatically determining, setting, selecting and testing hydrodynamic model parameters based on the MIKE 21FM model according to claim 5 is characterized in that: The MIKE 21 FM model is based on the two-dimensional incompressible Reynolds-averaged NS equations with Boussinesq and hydrostatic pressure assumptions. The basic principle is as follows: Continuity equation: （1）； Momentum equation: （2）； （3）； In the formula, For time; , It is a right-handed Cartesian coordinate system; for water depth; , The flow rates are , Directional weight; is the local atmospheric pressure; is the water density, is the reference water density; is the Coriolis force parameter; and is the acceleration caused by the rotation of the Earth; , , , is the radiation stress component; , , , is the horizontal viscous stress term; The source-sink term indicates whether there is external injection, i.e. source, or outflow, i.e. sink, in the fluid system; , They are , Directional source and sink flow velocity, , for , The average flow velocity of water in the direction; is the acceleration due to gravity; is the unit volume of water.

7. The method for automatically determining, setting, selecting and testing hydrodynamic model parameters based on the MIKE 21FM model according to claim 6 is characterized in that: The turbulence modeling of the MIKE 21 FM model adopts the Smagorinsky subgrid scale model in the large eddy simulation method. The model uses an effective eddy viscosity value related to the characteristic length scale to describe the subgrid scale transport. The subgrid scale eddy viscosity value is given by the following formula: （4）； In the formula, is a fixed value, is the characteristic length, is the sub-grid scale eddy viscosity value, is the deformation rate; The deformation rate is given by: （5）； Bottom stress: Bottom stress Following the law of quadratic friction: （6）； in is the drag coefficient, is the bottom flow slip velocity, is the bottom stress; For two-dimensional calculations, is the average velocity with respect to water depth, and the drag coefficient can be given by the Manning coefficient get: （7）； Manning coefficient It can be obtained from the bottom bed roughness length: （8）。 8. The method for automatically determining, setting, selecting and testing hydrodynamic model parameters based on the MIKE 21FM model according to claim 7 is characterized in that: The verification and calibration of the selected model parameters in Step 3 is carried out by introducing , and Parameters are used to quantitatively detect the deviation between the simulated values ​​and the measured values ​​of the numerical model constructed in this study, where Root mean square error The function calculation formula is as follows: （9）； Skewness The calculation formula is as follows: （10）； Correlation coefficient The calculation formula is as follows: （11）； In the formula, is the total number of test samples, is the measured value, Calculate values ​​for the model, is the average value of the measured values, The mean of the values ​​calculated for the model.

9. The method for automatically determining, setting, selecting and testing hydrodynamic model parameters based on the MIKE 21FM model according to claim 8, characterized in that: The method also includes performing a sensitivity analysis on the selected model parameters to determine the degree of influence of the parameters on the simulation results and adjusting the parameter settings accordingly.

10. A hydrodynamic simulation system based on the MIKE 21FM model using the method for automatically determining, setting, selecting and verifying hydrodynamic model parameters based on the MIKE 21FM model as described in any one of claims 1 to 9, characterized in that: The system includes a data input module, a parameter judgment and setting module, a simulation module and a verification module, wherein: the data input module is used to input the hydrological condition data of the study area; the parameter judgment and setting module is used to automatically judge and set the model parameters according to the input data and the characteristics of the MIKE 21FM model; the simulation module is used to perform hydrodynamic simulation according to the set parameters; and the verification module is used to verify and check the simulation results.

11. The hydrodynamic simulation system based on the MIKE 21FM model according to claim 10, characterized in that: The parameter judgment and setting module also has a parameter optimization function, which automatically adjusts the parameter value to achieve the best simulation effect according to the comparison between the simulation results and the measured data.

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