A method for predicting beach sediment transport volume

Abstract

A method for predicting the beach sediment transport volume proposed in this application relates to the technical field of sediment transport volume prediction. First, according to the first geological information of the first beach, determine the first sediment transport distance of the first beach within the first preset time period. Then, based on the two first shorelines of the first beach before and after the first preset time period and the first sediment transport distance, determine the first and second sediment lines to be transferred, and determine the spacing between the two sediment lines to be transferred. Finally, based on the determined spacing and the sediment accumulation rate of the first beach, obtain the predicted first sediment transport volume through a machine learning model. Through the technical solution of the present invention, the sediment lines to be transferred corresponding to the shoreline can be determined in combination with the geological information of the first beach, so that the predicted value of sediment accumulation after the preset time interval can be obtained according to the spacing between the sediment lines to be transferred before and after the preset time interval and the sediment accumulation rate.

Description

Technical Field

[0001] The present invention belongs to the technical field of sediment transport volume prediction, and particularly relates to a method for predicting beach sediment transport volume. Background Art

[0002] The prediction of beach sediment transport volume plays an important role in coastal engineering, environmental protection, disaster prevention, etc. However, the existing technologies usually can only predict the beach sediment transport volume after a preset time period based on expert experience, and the prediction accuracy is relatively low. Summary of the Invention

[0003] The purpose of the present invention is to provide a method for predicting beach sediment transport volume to solve the technical problem of low prediction accuracy of beach sediment transport volume in the existing technologies.

[0004] The present application proposes a method for predicting beach sediment transport volume, and the method includes:

[0005] S1: Determine a first sediment transport distance according to the first geological information of a first beach; the first sediment transport distance refers to the average sediment transport distance of the first beach within a first preset time period.

[0006] S2: Obtain a plurality of first marked points from a first coastline of the first beach, and obtain a first sediment line to be transferred according to the first coastline, the plurality of first marked points, and the first sediment transport distance; the first sediment line to be transferred refers to the probability that the sediment between the first sediment line to be transferred and the first coastline will be transferred from the sea to the shore or from the shore to the sea within the first preset time period.

[0007] S3: Repeat the steps in S2 to obtain a second sediment line to be transferred after the first preset time period.

[0008] S4: Obtain a first sediment transport volume according to the first sediment line to be transferred, the second sediment line to be transferred, and a first sediment accumulation rate.

[0009] Preferably, the S1 includes the following sub-steps:

[0010] S11: Determine the historical sediment transport distance of the first beach.

[0011] S12: Obtain first basic information of the first beach, and input the first basic information into a sediment transport distance prediction model to obtain a sediment transport distance prediction value; the first basic information includes one or more of the average hydrodynamic force value, the average tidal drop value, the geological structure type, the beach material type, and the vegetation coverage type.

[0012] S13: Obtain the first sediment transport distance based on the historical sediment transport distance and the predicted sediment transport distance.

[0013] Preferably, the S2 includes the following sub-steps:

[0014] S21: Select multiple first marked points on the first beach. For any one of the first marked points, draw a first analysis line; the first analysis line is along the horizontal direction.

[0015] S22: Denote the intersection point of the first analysis line and the first coastline as the second marked point.

[0016] S23: Determine the first sediment transport point based on the second marked point and the first sediment transport distance.

[0017] S24: Repeat the above steps S21 - S23 to obtain multiple first sediment transport points, and obtain the first sediment line to be transferred based on the multiple first sediment transport points.

[0018] Preferably, the S3 includes the following sub-steps:

[0019] S31: Obtain the second coastline after the first preset time period.

[0020] S32: Repeat the steps in S2 to obtain the second sediment line to be transferred corresponding to the second coastline.

[0021] Preferably, the S4 further includes:

[0022] Use the distance between the first and second sediment lines to be transferred to predict the first sediment transport volume.

[0023] Wherein the distance is obtained by the following method:

[0024] Fit two straight lines respectively according to the first and second sediment lines to be transferred, and take the average distance between the two straight lines as the spacing between the first and second sediment lines to be transferred.

[0025] Preferably, the S11 includes:

[0026] Determine multiple first historical sediment transport distances of the first beach at a predetermined time interval, and perform a weighted summation operation on the multiple first historical sediment transports to obtain the historical sediment transport distance.

[0027] Preferably, when determining the weights of the multiple first historical sediment transport distances, the greater the distance from the current time interval, the greater the weight of the first historical sediment transport distance.

[0028] A method for predicting beach sediment transport volume proposed in this application relates to the technical field of sediment transport volume prediction. First, determine the first sediment transport distance of the first beach within a first preset time period according to the first geological information of the first beach. Then, based on two first shorelines of the first beach before and after the first preset time period and the first sediment transport distance, determine the first and second sediment lines to be transferred, and determine the distance between the two sediment lines to be transferred. Finally, based on the determined distance and the sediment accumulation rate of the first beach, obtain the predicted first sediment transport volume through a machine learning model. Through the technical solution of the present invention, the sediment lines to be transferred corresponding to the shoreline can be determined in combination with the geological information of the first beach, so that the predicted value of sediment accumulation after the preset time interval can be obtained according to the distance between the sediment lines to be transferred before and after the preset time interval and the sediment accumulation rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only exemplary, and for those of ordinary skill in the art, without creative efforts, other implementation drawings can also be obtained based on the provided drawings.

[0030] Figure 1 is the execution flowchart of a method for predicting beach sediment transport volume in the present invention;

[0031] Figure 2 is the flowchart of the method for determining the second marked point on the shoreline of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present invention.

[0033] The present invention will be described in detail below in conjunction with the drawings and specific embodiments, and the illustrative embodiments and descriptions are only used to explain the present invention, but not to limit the present invention.

[0034] The following will detail a method for predicting beach sediment transport volume of the present invention.

[0035] This embodiment proposes a method for predicting beach sediment transport volume, and the specific method process is as Figure 1 shown, and specifically includes the following steps:

[0036] S1: Determine the first sediment transport distance based on the first geological information of the first beach.

[0037] The first sediment transport distance refers to the average sediment transport distance of the first beach within the first preset time period. The first sediment transport distance is affected by various factors such as hydrodynamic force, tidal action, geological structure, beach material, and vegetation coverage.

[0038] The first sediment transport distance can be specifically obtained by combining historical data and big data prediction.

[0039] The S1 includes the following sub-steps:

[0040] S11: Determine the historical sediment transport distance of the first beach.

[0041] In this step, multiple first historical sediment transport distances of the first beach can be determined at a predetermined time interval, and corresponding operations can be performed on the multiple first historical sediment transports to obtain the historical sediment transport distance.

[0042] For example, multiple first historical sediment transport distances within the past two years can be obtained at a time interval of 3 months, and then the average value of the multiple first historical sediment transport distances can be obtained as the historical sediment transport distance.

[0043] Preferably, a weighted average value of the multiple first historical sediment transport distances can be obtained with the time interval from the current time point as the weight. For example, the closer the first historical sediment transport distance is to the current time point, the greater the weight in obtaining the historical sediment transport distance, and vice versa.

[0044] S12: Obtain the first basic information of the first beach, and input the first basic information into the sediment transport distance prediction model to obtain a sediment transport distance prediction value.

[0045] The first basic information includes one or more of the average hydrodynamic force, average tidal drop value, geological structure type, beach material type, and vegetation coverage type.

[0046] The sediment transport distance prediction model is obtained by training a CNN model. During training, the first basic information and measured sediment transport distances of multiple beaches are selected as sample data through big data. For each piece of the sample data, its first basic information is used as input data, and the measured sediment transport distance is used as the output distance to train the CNN model to obtain the sediment transport distance prediction model.

[0047] S13: Obtain the first sediment transport distance based on the historical sediment transport distance and the sediment transport distance prediction value.

[0048] In this step, the historical sediment transport distance can be corrected by the predicted sediment transport distance to obtain the first sediment transport distance.

[0049] Preferably, the first sediment transport distance can be obtained by calculating the average value or weighted average value of the predicted sediment transport distance and the historical sediment transport distance.

[0050] S2: Obtain a plurality of first marked points from the first coastline of the first beach, and obtain a first sediment line to be transferred according to the first coastline, the plurality of first marked points, and the first sediment transport distance.

[0051] In this step, first obtain the first coastline by means of image recognition. Since the distance that sediment moves on the same beach within the same time interval is relatively fixed, the first sediment line to be transferred can be obtained by image fitting according to the obtained first coastline and the first sediment transport distance. The first sediment line to be transferred refers to the probability that the sediment between the first sediment line to be transferred and the first coastline will be transferred from the sea to the shore or from the shore to the sea within the first preset time period.

[0052] The S2 includes the following sub-steps:

[0053] S21: Arbitrarily select a plurality of first marked points on the first beach, and for any one of the first marked points, make a first analysis line.

[0054] Wherein, any one of the points to be measured is any pixel point on the first beach.

[0055] The first analysis line is along the horizontal direction.

[0056] S22: Denote the intersection point of the first analysis line and the first coastline as the second marked point.

[0057] As Figure 2 shown, in this step, it is necessary to mark the second marked point on the first coastline that is on the same horizontal line as each of the first marked points, so as to provide a basis for subsequently determining the first sediment transport point on the same horizontal line.

[0058] S23: Determine the first sediment transport point according to the second marked point and the first sediment transport distance.

[0059] In this step, taking the second marked point as the reference point, on the same horizontal line as the second marked point, offset the first sediment transport distance towards the shore direction or the seawater direction to obtain the first sediment transport point on the horizontal line.

[0060] S24: Repeat the above steps S21 - S23 to obtain multiple first sediment transport points, and obtain the first sediment line to be transferred based on the multiple first sediment transport points.

[0061] In this step, for each of the first marked points, obtain the corresponding first sediment transport point, and perform curve fitting on the multiple first sediment transport points to obtain the first sediment line to be transferred.

[0062] Among them, the first sediment line to be transferred is basically in a parallel position with the first coastline.

[0063] S3: Repeat the steps in S2 to obtain the second sediment line to be transferred after the first preset time period.

[0064] In this step, the second sediment line to be transferred needs to be obtained by the same method as in S2.

[0065] S3 includes the following sub - steps:

[0066] S31: Obtain the second coastline after the first preset time period.

[0067] In this step, the image recognition method needs to be used to obtain the second coastline of the first beach after the first preset time period. Due to the accumulation of sediment on the beach, there may be a difference in position between the first coastline and the second coastline.

[0068] S32: Repeat the steps in S2 to obtain the second sediment line to be transferred corresponding to the second coastline.

[0069] In this step, based on the same method steps as in S2, by selecting the first marked points on the beach, selecting the second marked points on the same horizontal line as the first marked points, and performing curve fitting on multiple second marked points, the second sediment line to be transferred corresponding to the second coastline can be obtained.

[0070] Among them, the second sediment line to be transferred is basically in a parallel position with the second coastline.

[0071] S4: Obtain the first sediment transport volume based on the first sediment line to be transferred, the second sediment line to be transferred, and the first sediment accumulation rate.

[0072] At the time interval of the first preset time period, the distance between the first and second sediment lines to be transferred can be used to estimate the first sediment transport volume at the first preset time period. When the sediment accumulation rate is determined, there is a certain correlation between the distance between the first and second sediment lines to be transferred and the first sediment transport volume.

[0073] Preferably, the first sediment accumulation rate is estimated based on the basic information of the first beach through expert experience and is used to characterize the sediment accumulation rate on the beach.

[0074] When predicting the first sediment transport volume, a machine learning model is required, preferably a CNN model. Using the relevant data of the historical beach sediment transfer volume as samples, the distance between the first and second sediment lines to be transferred at a preset time interval and the sediment accumulation rate are used as inputs, and the actual sediment transport volume is used as the output to train the CNN model to obtain a sediment transport volume prediction model.

[0075] Preferably, the distance between the first and second sediment lines to be transferred can be obtained in the following way. For example, two straight lines are respectively fitted according to the first and second sediment lines to be transferred, and the average distance between the two straight lines is used as the distance between the first and second sediment lines to be transferred.

[0076] A method for predicting beach sediment transport volume proposed in this application relates to the technical field of sediment transport volume prediction. First, the first sediment transport distance of the first beach within a first preset time period is determined according to the first geological information of the first beach. Then, based on two first shorelines of the first beach before and after the first preset time period and the first sediment transport distance, the first and second sediment lines to be transferred are determined, and the distance between the two sediment lines to be transferred is determined. Finally, based on the determined distance and the sediment accumulation rate of the first beach, the predicted first sediment transport volume is obtained through a machine learning model. Through the technical solution of the present invention, the sediment lines to be transferred corresponding to the shoreline can be determined in combination with the geological information of the first beach, so that the predicted value of sediment accumulation after the preset time interval can be obtained according to the distance between the sediment lines to be transferred before and after the preset time interval and the sediment accumulation rate.

[0077] The above is only a preferred embodiment of the present invention. Therefore, any equivalent changes or modifications made according to the structure, characteristics, and principles described in the scope of the present invention patent application are included in the scope of the present invention patent application.

Claims

1. A method for predicting beach sediment transport volume, characterized in that, The method includes: S1: Determine the first sediment transport distance according to the first geological information of the first beach; the first sediment transport distance refers to the average sediment transport distance of the first beach within the first preset time period; S2: Obtain a plurality of first marked points from the first coastline of the first beach, and obtain the first sediment line to be transferred according to the first coastline, the plurality of first marked points and the first sediment transport distance; S3: Repeat the steps in S2 to obtain the second sediment line to be transferred after the first preset time period; S4: Obtain the first sediment transport volume according to the first sediment line to be transferred, the second sediment line to be transferred and the first sediment accumulation rate; S2 includes the following sub-steps: S21: Arbitrarily select a plurality of first marked points on the first beach, and for any one of the first marked points, make a first analysis line; the first analysis line is along the horizontal direction; S22: Denote the intersection point of the first analysis line and the first coastline as the second marked point; S23: Determine the first sediment transport point according to the second marked point and the first sediment transport distance; S24: Repeat the above steps S21 - S23 to obtain a plurality of the first sediment transport points, and obtain the first sediment line to be transferred according to the plurality of the first sediment transport points; The first sediment transport volume is predicted by a sediment transport volume prediction model, and the sediment transport volume prediction model is obtained by training a CNN model. In the training sample data, the distance between the first and second sediment lines to be transferred at a preset time interval and the sediment accumulation rate are used as inputs, and the actual sediment transport volume is used as the output.

2. The prediction method of beach sediment transport volume according to claim 1, characterized in that S1 includes the following sub-steps: S11: Determine the historical sediment transport distance of the first beach; S12: Obtain the first basic information of the first beach, and input the first basic information into the sediment transport distance prediction model to obtain a sediment transport distance prediction value; The first basic information includes one or more of the average hydrodynamic force, the average tidal drop value, the geological structure type, the beach material type, and the vegetation coverage type; S13: Obtain the first sediment transport distance according to the historical sediment transport distance and the sediment transport distance prediction value.

3. A method for predicting beach sediment transport volume according to claim 2, characterized in that, S3 includes the following sub-steps: S31: Obtain the second coastline after the first preset time period; S32: Repeat the steps in S2 to obtain the second sediment line to be transferred corresponding to the second coastline.

4. A method for predicting beach sediment transport volume according to claim 3, characterized in that, S4 further includes: Using the distance between the first and second sediment lines to be transferred to predict the first sediment transport volume.

5. A method for predicting beach sediment transport volume according to claim 4, characterized in that, The distance between the first and second sediment lines to be transferred is obtained by the following method: Two straight lines are respectively fitted according to the first and second sediment lines to be transferred, and the average distance between the two straight lines is used as the distance between the first and second sediment lines to be transferred.

6. A method for predicting beach sediment transport volume according to claim 5, characterized in that, S11 includes: Determine a plurality of first historical sediment transport distances of the first beach at a predetermined time interval, and perform a weighted summation operation on the plurality of first historical sediment transports to obtain the historical sediment transport distance.

7. A method for predicting beach sediment transport volume according to claim 6, characterized in that, When determining the weights of multiple said first historical sediment transport distances, the weight of the first historical sediment transport distance with a greater time interval from the current time is greater.

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