A calculation method suitable for extracting mixed tide type characteristic tide level values

Abstract

The application provides a calculation method suitable for mixed tide type characteristic tide level value extraction, and comprises the following steps: S1, obtaining original tide level data of consecutive years based on numerical simulation; S2, extracting high tide level data in a tidal period based on the original tide level data; S3, extracting high high tide level data which is greater than that on both sides among consecutive three high tide level data based on the high tide level data; S4, extracting ascending tide level data based on the high tide level data; and S5, calculating average high high tide level by combining the high high tide level and the ascending tide level data. The application is easy to program and realize by decomposing tide level characteristic value extraction steps, and has better applicability under the condition of large data compared with the traditional method. The rest tide level characteristic value extraction and average high tide level extraction ideas are the same, and will not be described here.

Description

Technical Field

[0001] This invention relates to the field of marine hydrodynamic numerical simulation, specifically to a calculation method for extracting characteristic tidal levels of mixed tidal patterns. Background Technology

[0002] Numerical simulation, relying on electronic computers and combining the concepts of finite element or finite volume, studies engineering problems, physical problems, and various natural problems through numerical calculation and image display. It is a low-cost, easy-to-operate, and highly portable research method. After more than half a century of development, this method has matured and become reliable, resulting in numerous representative commercial software programs with powerful pre- and post-processing capabilities. Delft3D software, developed by the Dutch company WL Delft Hydraulics, is widely used in various fields such as hydraulic engineering, coastal engineering, marine engineering, marine dynamic environment, storm surge, water and sediment transport, and pollution diffusion and migration, thanks to its rich functionality and open-source nature.

[0003] Tidal characteristic values ​​include multiple parameters such as mean high tide level, mean low tide level, mean high tide level of spring tides, mean low tide level of spring tides, mean high tide level of neap tides, mean low tide level of neap tides, mean tidal range, and mean spring tide range. These are important parameters reflecting the strength and nature of regional tidal dynamics. Among them, the mean high tide level and mean low tide level of spring tides are particularly important. In coastal zone scientific research, the mean high tide line and mean low tide line of spring tides are indicator lines for determining the intertidal zone. In marine engineering design, the design high and low tide levels are the high and low tide levels under normal operating conditions for marine structures. Some countries use the mean high and low tide levels of spring tides to determine the design tide level, while others use the cumulative frequency of tide duration. Therefore, the mean high / low tide level of spring tides is an important reference indicator in both academic research and practical engineering fields.

[0004] Current methods for calculating the average high tide level mainly rely on multi-year measured tide data or hourly measured tide data for a year. These methods only provide the average high tide level for the area where tide gauge stations are located. Numerical simulation technology, after verifying measured tide levels, can obtain continuous tide data for any point through long-term numerical simulation. However, the amount of tide data obtained from numerical simulation is enormous, and manual statistical methods are time-consuming and labor-intensive, failing to quickly obtain tide characteristic data. Therefore, it is necessary to design a time-efficient and easy-to-operate method for extracting tide characteristics. Summary of the Invention

[0005] To overcome the drawbacks of massive amounts of numerical simulation tidal data and the time-consuming and labor-intensive nature of manual statistical calculations, this invention proposes a calculation method suitable for extracting tidal level values ​​of mixed tidal types. This method calculates the original tidal level, high tidal level, intermediate high tidal level, and ascending tidal level step by step, and then statistically obtains the average high tidal level. This method is easy to program and can quickly and accurately derive the average high tidal level from years of simulated tidal data, thus solving the efficiency problem of tidal feature value extraction. The methods for extracting other tidal features are the same as those for the average high tidal level, and the extraction methods for other tidal features are still within the scope of the technical solutions protected by this invention.

[0006] To achieve the above objectives, this invention proposes a calculation method for extracting characteristic tidal levels of mixed tidal patterns, comprising the following steps:

[0007] S1: Construct a tidal dynamic numerical model based on Delft3D numerical calculation software, simulate tidal motion, and extract the original tidal level data of each observation point based on the numerical simulation results.

[0008] S2: Based on the original tide level data of the observation point, extract the high tide level data for each tidal cycle;

[0009] S3: Based on the high tide data of the observation point, extract the high tide data where the middle one is greater than the two sides from three consecutive high tide data;

[0010] S4: Extract ascending tide data based on the high tide data of the observation points;

[0011] S5: Combine high tide data and ascending tide data to calculate the average high tide level of the observation point.

[0012] Further, step S1 specifically includes:

[0013] A1: Based on the measured data, the Delft3D tidal current model is calibrated and corrected to ensure that the accuracy of the tidal level simulation meets the requirements, and the tidal level observation points and corresponding numbers are determined.

[0014] A2: Perform tidal level simulation based on the research content, set the tidal level output time interval, and generate simulation result files;

[0015] A3: Based on the tide observation point number in A1 and the result file in A2, extract the original tide data Y_tide for the corresponding tide observation point.

[0016] Further, step S2 specifically includes:

[0017] B1: Based on the original tide level data in A3, discrimination is performed on every three consecutive tide level data points Y_tide1, Y_tide2, and Y_tide3;

[0018] B2: Based on the characteristics of high tide, the high tide level is greater than the adjacent tide levels and greater than 0.

[0019] If the logical form is Y_tide2>=Y_tide1 and Y_tide2>=Y_tide3 and Y_tide2>0, then extract Y_tide2;

[0020] B3: Program B2 to read the raw tide data from A3 and extract the high tide data G_tide from the corresponding observation point;

[0021] Further, step S3 specifically includes:

[0022] C1: Based on the B3 high tide data, the judgment is made for every three consecutive tide data points G_tide1, G_tide2, and G_tide3;

[0023] C2: Define the climax as the climax within the climax, that is, the climax is greater than the climaxes on both sides. The logical form is: if G_tide2>=G_tide1 and G_tide2>=G_tide3, then extract G_tide2.

[0024] C3: Program C2, input the high tide level data B3, and extract the high tide level data GG_tide of the corresponding observation point;

[0025] Further, step S4 specifically includes:

[0026] D1: Based on the B3 high tide data, the distinction is made between every two adjacent tide data points G_tide1 and G_tide2;

[0027] D2: Define the ascending tide position as the tide position increases with the sequence number, that is, if the latter is greater than the former, then the latter is the ascending tide position. The logical form is: if G_tide2>G_tide1, then extract G_tide2.

[0028] D3: Program D2 to read the high tide data from B3 and extract the ascending tide data SX_tide from the corresponding observation point.

[0029] Further, step S5 specifically includes:

[0030] E1: Based on the high tide level C3 and the ascending tide level D3, merge the two into a high-high ascending tide level GGSX_tide;

[0031] E2: Based on the properties of the high tide level, namely that the high tide level is greater than the high tide level on both sides in ascending order, the high tide level D_tide is determined. The logical form is GGSX_tide2>GGSX_tide1 and GGSX_tide2>GGSX_tide3, then GGSX_tide2 is D_tide.

[0032] E3: The high tide level of a spring tide is usually the average of three consecutive tide levels during the spring tide period. Therefore, according to E2, the average of three consecutive tide levels including the large D_tide as the median is taken as DM_tide.

[0033] The logical form is GGSX_tide2>GGSX_tide1 and GGSX_tide2>GGSX_tide3.

[0034] Then GGSX_tide2 is D_tide.

[0035] DM_tide of D_tide=(GGSX_tide1+GGSX_tide2+GGSX_tide3) / 3;

[0036] E4: Repeat E3 to obtain a series of high tide positions DM_tide1, DM_tide2, DM_tide3, etc.;

[0037] E5: Based on E4, calculate the average high tide level of the corresponding observation point. Attached Figure Description

[0038] Figure 1 This is a flowchart illustrating an embodiment of the present invention.

[0039] Figure 2 This is a graph of the original tide level data according to an embodiment of the present invention, illustrating the high tide level.

[0040] Figure 3 This is a high tide data curve diagram according to an embodiment of the present invention, illustrating the high tide level.

[0041] Figure 4 This is a high tide data curve diagram according to an embodiment of the present invention, illustrating the ascending tide levels.

[0042] Figure 5 This is a high-high ascending tide level curve diagram according to an embodiment of the present invention, which illustrates the minimum value of the high tide level during spring tides.

[0043] Figure 6 This is a high-high ascending tide level curve diagram according to an embodiment of the present invention, illustrating the high tide level of spring tides.

[0044] Figure 7 This is a schematic diagram of the EXCEL filtering method according to an embodiment of the present invention. Detailed Implementation

[0045] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. After reading the present invention, any modifications of the present invention in various equivalent forms by those skilled in the art fall within the scope defined by the appended claims.

[0046] This invention uses Delft3D to build a tidal model for the South Yellow Sea, simulating tidal movements over a six-year period from 2015 to 2021. The output station is YC1_5, and the output time interval is 10 minutes. Matlab is used as the batch extraction tool for tidal data, and Excel is used as the statistical calculation tool. The process includes the following steps:

[0047] S1: Use Delft3D to perform tidal current simulation. Based on the numerical simulation results, extract the original tidal level data Y_tide for observation point YC1_5. The specific steps are as follows:

[0048] A1: Calibrate and verify the tidal current model, determine the tidal level observation points and their corresponding numbers, and use measured tidal current data to calibrate and verify the model; the location of the tidal level observation points can be determined using ArcGIS software (version 10.2 or higher), and then add the tidal level observation point file (.obs) in the Flow module of Delft3D; record the observation point number, for example, the number of YC1_5 is 123.

[0049] A2: Perform a tide level simulation, set the tide level output time interval, and generate a result file. Set the simulation period to 2014-12-30-00-00-00 to 2022-01-01-00-00-00, the tide level output time interval to 10 minutes, and generate a result file named trih-4.dat.

[0050] A3: Based on the tide observation point number in A1 and the result file in A2, extract the original tide data for the corresponding observation point. In Matlab software, use the qpfopen, vs_disp, and vs_get functions provided by Delft3D to extract the original tide data Y_tide for station YC1_5 from the simulation result file trih-4.dat, based on the station number 123. This data is then output to the "Original Tide" workbook in YC1_5_2015_2022.xlsx.

[0051] S2: Based on the original tide level data of observation point YC1_5, extract the high tide level data for each tidal cycle, such as... Figure 1 As shown. The specific steps are as follows:

[0052] B1: Based on the original tide level data Y_tide of station YC1_5 in A3 from 2015 to 2022, the data of each consecutive three tide level data Y_tide(1), Y_tide(2), and Y_tide(3) are judged;

[0053] B2: According to the definition of high tide, the high tide level is greater than the adjacent tide levels and greater than 0.

[0054] The logical form is Y_tide(2)>=Y_tide(1) and Y_tide(2)>=Y_tide(3) and Y_tide(2)>0;

[0055] B3: Program B2 to read the raw tide level data from A3 and extract the high tide level data G_tide from the corresponding observation point. The statement logic is as follows:

[0056]

[0057] S3: Based on the high tide position data G_tide from observation point YC1_5 from 2015 to 2022, extract the high tide position data, such as... Figure 3 As shown. The specific steps are as follows:

[0058] C1: Based on the high tide data G_tide of YC1_5 station in B3 from 2015 to 2022, the distinction is made for every three consecutive tide data G_tide(1), G_tide(2), G_tide(3);

[0059] C2: Define the climax as the climax within the climax, that is, the climax is greater than the climax on both sides of the adjacent climax. The logical form is G_tide(2)>=G_tide(1) and G_tide(2)>=G_tide(3);

[0060] C3: Program C2, input the high tide level data B3, and extract the corresponding high tide level data GG_tide from the observation point, as shown in the following statements:

[0061]

[0062]

[0063] S4: Based on the high tide data G_tide from observation point YC1_5 from 2015 to 2022, extract the ascending tide data from the high tide data, such as... Figure 4 As shown. The specific steps are as follows:

[0064] D1: Based on the high tide data G_tide of YC1_5 station in B3 from 2015 to 2022, the distinction is made between every two consecutive tide data G_tide(1) and G_tide(2);

[0065] D2: Define the ascending tide position as the tide position increases with the sequence number, that is, the latter is greater than the former, then the latter is the ascending tide position, and the logical form is G_tide(2)>G_tide(1);

[0066] D3: Program D2 to read the high tide data from B3 and extract the ascending tide data SX_tide for the corresponding observation point. The statements are as follows:

[0067]

[0068] S5: Based on the high tide data and ascending tide data of observation point YC1_5 extracted from C3 and D3 from 2015 to 2022, the average high tide level of the observation point is calculated. The specific method is as follows:

[0069] E1: Based on the high tide level C3 and the ascending tide level D3, merge the two into a high-high ascending tide level GGSX_tide; the statement is as follows:

[0070]

[0071]

[0072] E2, E3: Based on the property that the high tide level of the spring tide is greater than the high tide level on the adjacent two sides, use Excel to determine the high tide level D_tide from the "high tide level" in E1;

[0073] A scatter plot was used to create an ascending tide level map to determine the minimum high tide level for spring tides, which was then used as a filtering criterion. In this example, the minimum high tide level limit for YC1_5_2015_2022 is 1.25. Figure 5 As shown;

[0074] Statistically, the high tide level for a spring tide is the average of three consecutive tide levels during the spring tide period. Therefore, the average of three consecutive tide levels, including D_tide as the median, is taken as the high tide level for the spring tide (within three days before and after). Figure 6 As shown;

[0075] Excel filtering, such as Figure 7 As shown, the statement is as follows:

[0076] c2=IF((b2>b1)*AND(b2>b3)*AND(b2>1.25),(b1+b2+b3) / 3,0)

[0077] The high tide level used for the statistics is in column C2. Based on this, the average high tide level of YC1_5_2015_2022 can be calculated.

Claims

1. A calculation method for extracting characteristic tidal levels of mixed tidal patterns, characterized in that, Includes the following steps: S1: Construct a tidal dynamic numerical model based on Delft3D numerical calculation software, simulate tidal motion, and extract the original tidal level data of each observation point based on the numerical simulation results; S2: Extract high tide data from the tidal cycle based on the raw tide data of the observation point; S3: Based on the high tide data of the observation point, extract the high tide data where the middle one is greater than the two sides from three consecutive high tide data; S4. Extract ascending tide data based on the high tide data from the observation points; S5. Combine the ascending tide data to calculate the average high tide level of the observation point. Step S2 specifically involves: B1: Based on the original tide level data, distinguish between every three consecutive tide level data points Y_tide1, Y_tide2, and Y_tide3; B2: Based on the characteristics of high tide, the high tide level is greater than the adjacent tide levels and greater than 0. The logical form is Y_tide2>=Y_tide1 and Y_tide2>=Y_tide3 and Y_tide2>0; B3: Read the raw tide level data and extract the high tide level data G_tide of the corresponding observation point; Step S3 specifically involves: C1: Based on the B3 tidal level data, discriminate between every three consecutive tidal level data points G_tide1, G_tide2, and G_tide3; C2: Define the climax as the climax of the climax, that is, the climax is greater than the climaxes on both sides of the adjacent climax. The logical form is G_tide2>=G_tide1 and G_tide2>=G_tide3. C3: Read the high tide level data from B3 and extract the high tide level data GG_tide from the corresponding observation point; Step S4 specifically involves: D1: Based on the B3 high tide data, distinguish between two adjacent high tide data points G_tide1 and G_tide2; D2: Define the ascending tide position as the tide position increases with the sequence number. That is, if the latter is greater than the former, then the latter is the ascending tide position. The logical form is G_tide2>G_tide1. D3: Read the high tide data from B3 and extract the ascending tide data SX_tide from the corresponding observation points; Step S5 specifically involves: E1: Obtain the high-high ascending tide level GGSX_tide based on the ascending tide level of D3; E2: Determine the high tide level D_tide based on the fact that the high tide level of the spring tide is greater than the high tide levels on both sides of the adjacent high tide. E3: The average high tide level of spring tide is taken as the average of three consecutive tide levels during spring tide. Therefore, according to E2, the average of three consecutive high-high ascending tide levels DM_tide, which includes the high tide level D_tide of spring tide as the median, is taken. E4: Repeat E3 to obtain a series of average high tide levels; E5: Based on E4, calculate the average high tide level of the corresponding observation point.

2. The calculation method for extracting characteristic tidal levels of mixed tidal patterns according to claim 1, characterized in that, Step S1 specifically involves: A1: Based on the measured data, the model is calibrated and corrected to determine the tide level observation points and their corresponding numbers; A2: Perform tidal current simulation based on the parameters corrected in A1, set the tidal level output time interval, and generate the result file; A3: Based on the tide observation points and corresponding serial numbers in A1 and the result file generated in A2, extract the original tide data Y_tide for the corresponding observation points.

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