Long river reach beach trough evolution prediction method and system based on digital twinning

Abstract

The invention discloses a long-river-reach beach channel evolution prediction method and system based on digital twinning, mainly relates to the field of river water environments, and aims to solve the problem that the existing beach channel evolution prediction system usually analyzes the water flow near a river channel only by using a single monitoring instrument; the beach channel evolution prediction system comprises a data acquisition unit, a sediment content analysis unit, a water flow analysis unit, a sediment transport analysis unit, a time deduction unit, a feedback unit and a display terminal. According to the method, the surrounding environment information of each region of the river channel is collected, land selection and orientation evaluation analysis is carried out, the sediment transport amount condition of the water river channel is accurately analyzed in a formulated processing, normalized analysis and signal integration output mode, and the risk level of beach and trough evolution is output accordingly, so that the risk level of beach and trough evolution is improved. Therefore, a foundation is laid for efficient and scientific management according to soil and river states near a river channel while clear classification of beach channel risk levels is realized.

Description

Technical Field

[0001] The present invention relates to the field of river water environment technology, and more specifically, to a method and system for predicting the evolution of long river sections based on digital twins. Background Art

[0002] During the evolution of river channels, as water and sediment conditions and boundary conditions change, the morphology of river channels often changes as well, resulting in the maintenance of a certain stable channel distribution morphology being relative, while a long-term unstable channel distribution morphology being absolute.

[0003] The existing beach channel evolution prediction system often only uses a single monitoring instrument to analyze the water flow near the river channel. The prediction of beach channel evolution is inaccurate and superficial, making it difficult to achieve accurate prediction and regulation of beach channel evolution. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method and system for predicting the evolution of shoals and channels in long river sections based on digital twins. By collecting the surrounding environmental information of each area of ​​the river channel and conducting site selection directional evaluation and analysis, the sediment transport situation of the water channel is accurately analyzed by means of formulaic processing, normalized analysis and signal integration output. The risk level of shoal and channel evolution is output accordingly, thereby achieving a clear division of shoal and channel risk levels and laying the foundation for efficient and scientific management based on the soil and river conditions near the river channel, so as to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for predicting the evolution of long river channels based on digital twins includes the following steps:

[0007] Step S10, obtaining the soil compaction value Sh, rainfall value P, riverbed height value Rb and vegetation coverage value Gar of each area of ​​the river channel according to the formula:

[0008]

[0009] Obtain the river channel sediment content influence coefficient CS, where a1, a2, a3, and a4 are preset proportional coefficients of soil compaction value, rainfall value, riverbed height value, and vegetation coverage value, respectively, and i = {1, 2, 3...n}, and i represents the number of regions;

[0010] Step S20, obtaining the flow area value S, wind force value C and temperature value T of each area of ​​the river channel according to the formula:

[0011]

[0012] Obtain the river flow influence coefficient Q, where b1, b2, b3, and b4 are preset proportional coefficients of rainfall, flow area, wind force, and temperature, respectively;

[0013] Step S30, integrating and analyzing the river sediment content influence coefficient CS and the river flow influence coefficient Q, and generating a risk-free signal, a warning signal and an unstable signal accordingly.

[0014] In a preferred embodiment, after step S30, step S40 is further included;

[0015] Determine whether the ratio of the warning signal to the unstable signal in a unit time is greater than a set standard threshold;

[0016] If it is greater, a long-term risk signal is generated, otherwise no signal is generated.

[0017] In a preferred embodiment, after step S40, step S50 is further included;

[0018] Determine whether a long-term risk signal is generated. If a long-term risk signal is generated, analyze and mark the part of the river that needs to be adjusted, and display the marking results.

[0019] In a preferred embodiment, in step S30, the influence coefficient of the sediment content in the main channel is set to the gradient reference value R of CS0. V 1 and R V 2 and set the gradient reference value R of the main river flow influence coefficient Q0 V 3 and R V 4, where R V 1>R V 2. R V 3>R V 4;

[0020] Substitute the influence coefficient of sediment content in the main channel CS0 into the gradient reference value R V 1 and R V Comparison analysis of 2 in 1:

[0021] When the sediment content in the main channel is greater than R V 1, a high-risk level sediment content signal is generated;

[0022] When the sediment content in the main channel is greater than R V 2 is less than R V 1, a risk level sediment content signal is generated;

[0023] When the sediment content in the main channel is less than R V 2, a zero risk level sediment content signal is generated;

[0024] Substitute the main river flow influence coefficient Q0 into the gradient reference value R V 3 and R V Comparative analysis is performed in 4:

[0025] When the flow influence coefficient of the main river is Q0 greater than R V 3, a high-risk level water flow signal is generated;

[0026] When the flow influence coefficient of the main river is Q0 greater than R V 4 is less than R V 3, a risk level water flow signal is generated;

[0027] When the flow influence coefficient of the main river is Q0 less than R V 4, a zero risk level water flow signal is generated.

[0028] In a preferred embodiment, in step S30;

[0029] When both the sediment content analysis unit and the water flow analysis unit are zero risk level signals, a risk-free signal is generated;

[0030] When one of the sediment content analysis unit and the water flow analysis unit is a risk level signal and the other is a zero risk level, a prompt signal is generated;

[0031] When both the sediment content analysis unit and the water flow analysis unit send signals above the risk level, an unstable signal is generated;

[0032] In other cases, the gradient reference value is adjusted.

[0033] In a preferred embodiment, in step S30, the specific process of adjusting the gradient reference value is as follows:

[0034] When either the water flow or the sediment content is too large, the gradient reference value of the other needs to be adjusted downward, that is, the sediment content influence coefficient CS is inversely proportional to the water flow influence coefficient Q, and the formula is as follows:

[0035]

[0036] In the formula, c1 and c2 are the preset proportional coefficients of the sediment content influence coefficient CS, and c1>c2;

[0037] When the flow influence coefficient of the main river is Q0 greater than R V 3 o'clock, At this time, the influence coefficient of sediment content in the main channel is CS0 and R V 2, if CS0 is smaller than R V2, then the prompt signal is output, otherwise the unstable signal is output;

[0038] When the sediment content in the main channel is greater than R V 1 o'clock, At this time, the influence coefficient of water flow in the main river channel is determined as Q0 and R V 4, if Q0 is greater than or equal to R V 4, it outputs an unstable signal, otherwise it outputs a warning signal.

[0039] A long river section shoal channel evolution prediction system based on digital twin, used to implement the long river section shoal channel evolution prediction method based on digital twin as claimed in the above claims, comprising a data acquisition unit, a sediment content analysis unit, a water flow analysis unit, a sediment transport analysis unit, a time deduction unit, a feedback unit and a display terminal;

[0040] The data collection unit is used to collect the land and weather information of the river channel itself and the water flow and weather information of the river channel itself, and send them to the sediment content analysis unit and the water flow analysis unit respectively;

[0041] The sediment content analysis unit is used to receive the land and weather information of the river itself for directional evaluation and analysis, and send the analysis results to the sediment transport analysis unit;

[0042] The water flow analysis unit is used to receive the water flow and weather information of the river channel itself for directional evaluation and analysis, and send the analysis results to the sediment transport analysis unit;

[0043] The sediment transport analysis unit is used to receive the analysis results of the sediment content analysis unit and the water flow analysis unit and perform combined analysis and processing on them, thereby generating a beach channel risk-free signal, a warning signal and an unstable signal, and then sending the signal to the time deduction unit and the feedback unit;

[0044] The time deduction unit is used to receive the risk-free signal, warning signal and unstable signal of the beach channel generated by the sediment transport analysis unit, and calculate whether they exceed the set threshold ratio within a unit time, determine whether the beach channel has a long-term risk and send the generated result to the feedback unit;

[0045] The feedback unit is used to mark each risk area of ​​the river channel in a targeted manner when the beach channel has a long-term risk, and send the marking result to the display terminal;

[0046] The display terminal is used to display the river risk area marked by the feedback unit.

[0047] Technical effects and advantages of the present invention:

[0048] 1. The present invention collects the surrounding environment information of each area of ​​the river channel and conducts site selection and directional assessment and analysis. It uses formulaic processing, normalized analysis and signal integration output to accurately analyze the sediment transport situation of the water channel, and outputs the risk level of the beach channel evolution accordingly. While achieving a clear division of the beach channel risk level, it also lays a foundation for efficient and scientific management based on the soil and river conditions near the river channel;

[0049] 2. The present invention divides the river channel into several areas according to tributaries and main streams, and can accurately understand the sediment content and water flow status of each area of ​​the river channel. Therefore, when the shoal has long-term risks, each risk area of ​​the river channel can be targetedly marked based on the overall assessment and analysis, so as to facilitate subsequent overall or individual repair and reinforcement. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a schematic diagram of the structure of a long river section shoal evolution prediction system based on digital twins of the present invention;

[0051] Figure 2 This is a flow chart of a method for predicting the evolution of long river sections based on digital twins according to the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Digital twins are integrated with multi-disciplinary, multi-physical, multi-scale, and multi-probability simulation processes to make full use of physical models, sensor updates, operation history, and other data. In this invention, a physical model of the river and shoal channel is constructed, and multiple data are collected to predict the evolution of the shoal channel.

[0054] Example 1

[0055] The present invention provides a long river section shoal evolution prediction system based on digital twin, such as Figure 1 As shown, it includes a data acquisition unit, a sediment content analysis unit, a water flow analysis unit, a sediment transport analysis unit, a time deduction unit, a feedback unit and a display terminal.

[0056] The data collection unit is used to collect the land and weather information of the river channel itself and the water flow and weather information of the river channel itself, and send them to the sediment content analysis unit and the water flow analysis unit respectively. Among them, the land and weather information of the river channel itself is the soil compaction value, rainfall value, riverbed height value and vegetation coverage value of the river channel area.

[0057] It should be noted that the soil compaction value refers to the percentage of soil in a unit volume of the river bank that is bonded into blocks. The larger the compaction value, the more it means that the soil contains more bonded blocky soil, which also indicates that the looseness of the soil is worse, making it less likely to accumulate silt in the river channel. The rainfall value is the amount of rainfall in the area. The greater the rainfall, the easier it is to wash the silt on the river bank into the river channel. The riverbed height value refers to the drop value of the river. The greater the drop value of the river, the easier it is to wash the silt in the river channel along the water flow. The vegetation coverage value is the vegetation coverage rate of the river banks on both sides. The higher the vegetation coverage rate, the better the sand fixation ability of the river bank.

[0058] Therefore, the soil compaction value, rainfall value, riverbed height value and vegetation coverage value will all affect the sand content in the river channel. The soil compaction value and vegetation coverage value are inversely proportional to the sand content in the river channel, while the rainfall value and riverbed height value are directly proportional to the sand content in the river channel.

[0059] When the sediment content analysis unit receives the land and weather information of the river channel collected by the data collection unit, it performs a directional evaluation and analysis of the sediment content in the river channel based on the information. The specific analysis process is as follows:

[0060] The river is divided into n regions according to its tributaries and main stream, where n is a positive integer greater than or equal to 1. The soil compaction value, rainfall value, riverbed height value and vegetation coverage value in each region are obtained and calibrated as Sh, P, Rb and Gar respectively. The influence coefficient of river sediment content CS in each region is obtained according to the formula. The specific formula is as follows:

[0061]

[0062] Wherein, a1, a2, a3, and a4 are preset proportional coefficients of soil compaction value, rainfall value, riverbed height value, and vegetation coverage value, respectively, and a2>a3>a4>a1>0, a1+a2+a3+a4=8.613, where i={1, 2, 3...n}, and i represents the number of regions.

[0063] It should be noted that the larger the value of the river sediment content influence coefficient CS is, the greater the sediment content of the river is. After the sediment content analysis unit calculates the sediment content influence coefficient CS, it sends it to the sediment transport analysis unit for analysis and processing.

[0064] The water flow and weather information of the river itself includes rainfall, flow area value, wind force value and temperature value.

[0065] It should be noted that the rainfall value is the amount of rainfall in the area. The greater the rainfall, the greater the water flow in the river. The flow area value refers to the cross-sectional area through which the water in the river flows. The smaller the flow area value, the faster the water flow rate will be, and the more sediment at the bottom of the river will be driven. The wind force value is the wind force level in the area where the river is located. The greater the wind force value, the greater the evaporation of the river water and the smaller the water flow. The temperature value is the ambient temperature of the river. The greater the temperature value, the greater the evaporation of the river water and the smaller the water flow.

[0066] Therefore, rainfall, flow area, wind force and temperature will affect the sediment transport capacity of the river by changing the river flow. Moreover, rainfall and flow area are proportional to the water flow, while wind force and temperature are inversely proportional to the water flow.

[0067] When the water flow analysis unit receives the water flow and weather information of the river channel collected by the data acquisition unit, it performs directional evaluation and analysis on the water flow in the river channel according to the information. The specific analysis process is as follows:

[0068] According to the tributaries and main stream of the river, the whole river is divided into n n regions, where n is a positive integer greater than or equal to 1, and the rainfall, flow area value, wind force value and temperature value in each n region are obtained respectively. They are calibrated as P, S, C, and T respectively. Since the water flow and sediment content of the studied river are in the same area, the rainfall value P is universal for the i divided regions. And it is analyzed by formula, and the river water flow influence coefficient Q in each area is obtained according to the formula. The specific formula is as follows:

[0069]

[0070] Wherein, b1, b2, b3, b4 are preset proportional coefficients of rainfall, flow area value, wind force value and temperature value respectively, and b2>b1>b3>b4>0, wherein, i={1, 2, 3...n}, and i represents the number of regions.

[0071] It should be noted that the larger the value of the river water flow influence coefficient Q is, the greater the water flow in the river is. After the water flow analysis unit calculates the river water flow influence coefficient Q, it sends it to the sediment transport analysis unit for analysis and processing.

[0072] Among them, the amount of sediment transported per unit time in the river is mainly determined by the water flow and sediment content of the river. Since the beach channel is downstream of the main river channel, although the main river channel is gathered by several tributaries, when studying the evolution of the beach channel, the present invention only needs to study the water flow and sediment content of the main channel. Assuming that the influence coefficient of the sediment content of the main river channel is CS0 and the influence coefficient of the water flow of the main river channel is Q0, the present invention integrates the influence coefficient of the sediment content of the main river channel CS0 and the influence coefficient of the water flow of the main river channel Q0 for analysis and processing. The specific operation process is as follows:

[0073] Set the influence coefficient of sediment content in the main channel to CS0 as the gradient reference value R V 1 and R V 2 and set the gradient reference value R of the main river flow influence coefficient Q0 V 3 and R V 4, where R V 1>R V 2. R V 3>R V 4. The gradient reference value of the present invention is the risk threshold of the two.

[0074] Substitute the influence coefficient of sediment content in the main channel CS0 into the gradient reference value R V 1 and R V Comparison analysis of 2 in 1:

[0075] When the sediment content in the main channel is greater than R V 1, a high-risk level sediment content signal is generated;

[0076] When the sediment content in the main channel is greater than R V 2 is less than R V 1, a risk level sediment content signal is generated;

[0077] When the sediment content in the main channel is less than R V 2, a zero risk level sediment content signal is generated.

[0078] Substitute the main river flow influence coefficient Q0 into the gradient reference value R V 3 and R V Comparative analysis is performed in 4:

[0079] When the flow influence coefficient of the main river is Q0 greater than R V 3, a high-risk level water flow signal is generated;

[0080] When the flow influence coefficient of the main river is Q0 greater than R V 4 is less than R V 3, a risk level water flow signal is generated;

[0081] When the flow influence coefficient of the main river is Q0 less than R V 4, a zero risk level water flow signal is generated.

[0082] Therefore, when both the sediment content analysis unit and the water flow analysis unit send zero risk level signals, it means that the shoal will not generate evolution risk, its stability will not decrease, and the sediment transport analysis unit generates a risk-free signal; when one of the sediment content analysis unit and the water flow analysis unit sends a risk level signal and the other sends a zero risk level signal, it means that the shoal has a certain evolution risk. At this time, the sediment transport analysis unit generates a prompt signal and points out which of the sediment content and the water flow exceeds the set first gradient; when both the sediment content analysis unit and the water flow analysis unit send signals above the risk level, it means that the shoal has a greater evolution risk, and the sediment transport analysis unit generates an unstable signal; in other cases, that is, one of the sediment content analysis unit and the water flow analysis unit generates a high risk level signal and the other generates a zero risk level signal, further research is needed.

[0083] Since the sediment transport is mainly determined by the water flow and sediment content, when one of them is large enough, it exceeds the second gradient reference value R V 1 or R V 3, even if the other side does not reach the set first gradient reference value, it may cause excessive sediment transport. Therefore, when one of the sediment content analysis unit and the water flow analysis unit generates a high risk level signal, the gradient reference value set by the other side needs to be readjusted. The specific process is as follows:

[0084] When either the water flow or the sediment content is too large, the gradient reference value of the other needs to be adjusted downward, that is, the sediment content influence coefficient CS is inversely proportional to the water flow influence coefficient Q, and the formula is as follows:

[0085]

[0086] In the formula, c1 and c2 are the preset proportional coefficients of the sediment content influence coefficient CS, and c1>c2. Therefore, according to the above formula, when the main river water flow influence coefficient Q0 is greater than R V 3 o'clock, At this time, the influence coefficient of sediment content in the main channel is CS0 and R V 2, so as to determine whether the sediment transport analysis unit generates a warning signal or an unstable signal. If CS0 is less than R V 2, then the warning signal is output, otherwise the unstable signal is output. V 1 o'clock, At this time, the influence coefficient of water flow in the main river channel is determined as Q0 and R V4, so as to determine whether the sediment transport analysis unit generates a warning signal or an unstable signal. If Q0 is greater than or equal to R V 4, it outputs an unstable signal, otherwise it outputs a warning signal.

[0087] Therefore, the present invention makes the overall channel evolution prediction more accurate by dynamically adjusting the water flow and the sediment content gradient reference value.

[0088] Furthermore, the time deduction unit of the present invention receives the signal generated by the sediment transport analysis unit, which is used to determine whether the beach channel has a risk trend within a period of time. Since the duration of the sediment transport feedback by the sediment transport analysis unit is not fixed, it is difficult to perform long-term evolution analysis on the beach channel without monitoring it for a period of time through the time deduction unit. The present invention assumes that the unit time monitored by the time deduction unit is t, and the proportion of early warning is p. If the proportion of the prompt signal or unstable signal of the sediment transport analysis unit within the unit time t is greater than p, it means that the beach channel has a long-term risk, otherwise it means that it does not have a long-term risk.

[0089] If the proportion of warning signals or unstable signals of the sediment transport analysis unit within a unit time t is greater than p, the time deduction unit sends a long-term risk signal to the feedback unit. After receiving the long-term risk signal, the feedback unit analyzes and marks the part of the river that needs to be adjusted, and sends the marking result to the display terminal. The specific marking analysis process is as follows:

[0090] The feedback unit receives the query of the sediment content analysis unit and the water flow analysis unit to calculate the sediment content influence coefficient CS and the river water flow influence coefficient Q of all regions, and compares them with the gradient reference value R V 1 and R V 2 or gradient reference value R V 3 and R V 4. Compare and determine which river areas have sediment or water content exceeding the risk threshold, and sort them. The feedback unit marks the river areas where the sediment or water content exceeds the risk threshold and sends them to the display terminal, which displays them visually to facilitate subsequent staff to carry out targeted repairs and reinforcements.

[0091] Example 2

[0092] The difference between Example 2 and Example 1 of the present invention is that Example 1 mainly introduces a long river section shoal evolution prediction system based on digital twins, and based on this system, this embodiment introduces a long river section shoal evolution prediction method based on digital twins. Figure 2 As shown, the following steps are included:

[0093] A. Obtain the soil compaction value, rainfall value, riverbed height value and vegetation coverage value of each area of ​​the river channel, and calibrate them as Sh, P, Rb, Gar. According to the formula, the river channel sediment content influence coefficient CS in each area is obtained. The specific formula is as follows:

[0094]

[0095] Wherein, a1, a2, a3, and a4 are preset proportional coefficients of soil compaction value, rainfall value, riverbed height value, and vegetation coverage value, respectively, and a2>a3>a4>a1>0, a1+a2+a3+a4=8.613, where i={1, 2, 3...n}, and i represents the number of regions.

[0096] B. Obtain the rainfall, flow area, wind speed and temperature values ​​in each area of ​​the river; and calibrate them as P, S, C, T, and use the formula

[0097]

[0098] Where b1, b2, b3, and b4 are preset proportional coefficients of rainfall, flow area, wind force, and temperature, respectively, and b2>b1>b3>b4>0, where i={1, 2, 3...n}, and i represents the number of regions. Obtain the river flow influence coefficient Q.

[0099] C. Integrate and analyze the river channel sediment content influence coefficient CS and the river channel water flow influence coefficient Q, and generate risk-free signals, warning signals and unstable signals. The present invention determines the river channel sediment transport by the river channel sediment content and water flow. When the sediment transport is too large, the shoal will evolve with sediment, resulting in instability.

[0100] D. Determine whether the proportion of the warning signal and the unstable signal in a unit time is greater than the set standard threshold. If so, a long-term risk signal is generated, otherwise it is not generated. This is mainly to determine whether the duration of the sediment transport is sufficient, and to determine the overall sediment transport status in a unit time through its proportion time, so as to facilitate subsequent adjustments.

[0101] E. Determine whether a long-term risk signal is generated. If a long-term risk signal is generated, analyze and mark the part of the river that needs to be adjusted, and display the marking results. Remind the staff of follow-up work.

[0102] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by technicians in this field according to actual conditions;

[0103] Such as the formula:

[0104]

[0105] A number of groups of sample data are collected by technical personnel in this field, and corresponding weight factor coefficients are set for each group of sample data; the set weight factor coefficients and the collected sample data are substituted into the formula, and any four formulas constitute a set of four-variable linear equations. The calculated coefficients are screened and averaged to obtain the values ​​of a1, a2, a3, and a4: a1=0.609, a2=3.211, a3=2.836, and a4=1.957.

[0106] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding weight factor coefficient for each group of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0107] The present invention collects the surrounding environment information of each area of ​​the river channel and conducts site selection and directional assessment and analysis. It uses formulaic processing, normalized analysis and signal integration output to accurately analyze the sediment transport situation of the water channel, and outputs the risk level of the beach channel evolution accordingly. While achieving a clear division of the beach channel risk level, it also lays a foundation for efficient and scientific management based on the soil and river conditions near the river channel.

[0108] At the same time, the present invention divides the river channel into several areas according to tributaries and main streams, and can accurately understand the sediment content and water flow status of each area of ​​the river channel. Therefore, when the shoal has long-term risks, each risk area of ​​the river channel can be targetedly marked based on the overall assessment and analysis, so as to facilitate subsequent overall or individual repair and reinforcement.

[0109] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0110] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0111] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0112] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0113] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0114] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0115] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0116] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0117] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting the evolution of long river sections based on digital twins, characterized in that: The steps include: Step S10, obtaining the soil compaction value Sh, rainfall value P, riverbed height value Rb and vegetation coverage value Gar of each area of ​​the river channel according to the formula: Obtain the river channel sediment content influence coefficient CS, where a1, a2, a3, and a4 are preset proportional coefficients of soil compaction value, rainfall value, riverbed height value, and vegetation coverage value, respectively, and i = {1, 2, 3...n}, and i represents the number of regions; Step S20, obtaining the flow area value S, wind force value C and temperature value T of each area of ​​the river channel according to the formula: Obtain the river flow influence coefficient Q, where b1, b2, b3, and b4 are preset proportional coefficients of rainfall, flow area, wind force, and temperature, respectively; Step S30, integrating and analyzing the river sediment content influence coefficient CS and the river flow influence coefficient Q, and generating a risk-free signal, a warning signal and an unstable signal accordingly.

2. According to claim 1, a method for predicting the evolution of long river sections based on digital twins is characterized by: After step S30, step S40 is also included; Determine whether the ratio of the warning signal to the unstable signal in a unit time is greater than a set standard threshold; If it is greater, a long-term risk signal is generated, otherwise no signal is generated.

3. The method for predicting the evolution of long river sections based on digital twins according to claim 1 is characterized by: After step S40, the method further includes step S50; Determine whether a long-term risk signal is generated. If a long-term risk signal is generated, analyze and mark the part of the river that needs to be adjusted, and display the marking results.

4. The method for predicting the evolution of long river sections based on digital twins according to claim 1 is characterized by: In step S30, the influence coefficient of sediment content in the main channel is set to the gradient reference value R of CS0. V 1 and R V 2 and set the gradient reference value R of the main river flow influence coefficient Q0 V 3 and R V 4, where R V 1>R V 2. R V 3>R V 4; Substitute the influence coefficient of sediment content in the main channel CS0 into the gradient reference value R V 1 and R V Comparison analysis of 2 in 1: When the sediment content in the main channel is greater than R V 1, a high-risk level sediment content signal is generated; When the sediment content in the main channel is greater than R V 2 is less than R V 1, a risk level sediment content signal is generated; When the sediment content in the main channel is less than R V 2, a zero risk level sediment content signal is generated; Substitute the main river flow influence coefficient Q0 into the gradient reference value R V 3 and R V Comparative analysis is performed in 4: When the flow influence coefficient of the main river is Q0 greater than R V 3, a high-risk level water flow signal is generated; When the flow influence coefficient of the main river is Q0 greater than R V 4 is less than R V 3, a risk level water flow signal is generated; When the flow influence coefficient of the main river is Q0 less than R V 4, a zero risk level water flow signal is generated.

5. The method for predicting the evolution of long river sections based on digital twins according to claim 4 is characterized by: In step S30; When both the sediment content analysis unit and the water flow analysis unit are zero risk level signals, a risk-free signal is generated; When one of the sediment content analysis unit and the water flow analysis unit is a risk level signal and the other is a zero risk level, a prompt signal is generated; When both the sediment content analysis unit and the water flow analysis unit send signals above the risk level, an unstable signal is generated; In other cases, the gradient reference value is adjusted.

6. A method for predicting the evolution of long river sections based on digital twins according to claim 5, characterized in that: In step S30, the specific process of adjusting the gradient reference value is as follows: When either the water flow or the sediment content is too large, the gradient reference value of the other needs to be adjusted downward, that is, the sediment content influence coefficient CS is inversely proportional to the water flow influence coefficient Q, and the formula is as follows: In the formula, c1 and c2 are the preset proportional coefficients of the sediment content influence coefficient CS, and c1>c2; When the flow influence coefficient of the main river is Q0 greater than R V 3 o'clock, At this time, the influence coefficient of sediment content in the main channel is CS0 and R V 2, if CS0 is smaller than R V 2, then the prompt signal is output, otherwise the unstable signal is output; When the sediment content in the main channel is greater than R V 1 o'clock, At this time, the influence coefficient of water flow in the main river channel is determined as Q0 and R V 4, if Q0 is greater than or equal to R V 4, it outputs an unstable signal, otherwise it outputs a warning signal.

7. A long river section shoal channel evolution prediction system based on digital twin, used to implement any of the long river section shoal channel evolution prediction methods based on digital twin of claims 1-6 above, characterized in that: It includes a data acquisition unit, a sediment content analysis unit, a water flow analysis unit, a sediment transport analysis unit, a time deduction unit, a feedback unit and a display terminal; The data collection unit is used to collect the land and weather information of the river channel itself and the water flow and weather information of the river channel itself, and send them to the sediment content analysis unit and the water flow analysis unit respectively; The sediment content analysis unit is used to receive the land and weather information of the river itself for directional evaluation and analysis, and send the analysis results to the sediment transport analysis unit; The water flow analysis unit is used to receive the water flow and weather information of the river channel itself for directional evaluation and analysis, and send the analysis results to the sediment transport analysis unit; The sediment transport analysis unit is used to receive the analysis results of the sediment content analysis unit and the water flow analysis unit and perform combined analysis and processing on them, thereby generating a beach channel risk-free signal, a warning signal and an unstable signal, and then sending the signal to the time deduction unit and the feedback unit; The time deduction unit is used to receive the risk-free signal, warning signal and unstable signal of the beach channel generated by the sediment transport analysis unit, and calculate whether they exceed the set threshold ratio within a unit time, determine whether the beach channel has a long-term risk and send the generated result to the feedback unit; The feedback unit is used to mark each risk area of ​​the river channel in a targeted manner when the beach channel has a long-term risk, and send the marking result to the display terminal; The display terminal is used to display the river risk area marked by the feedback unit.

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