A river cross-section flow field reconstruction method based on entropy model and nearshore flow velocity points

Abstract

The application discloses a river cross-section flow field reconstruction method based on an entropy model and a near-shore flow speed point, relates to the field of hydrological measurement and digital twinning, and comprises the following steps: determining entropy parameters of a river cross-section according to terrain data and historical hydraulic parameters; acquiring single-point surface flow speed of a near-shore side of the river; fitting surface flow speed data of the whole cross-section of the river according to a preset surface flow speed distribution model and the single-point surface flow speed; determining longitudinal flow speed distribution of the river cross-section; obtaining flow speed field data of the river cross-section by adopting a two-dimensional griddata interpolation algorithm according to the longitudinal flow speed distribution of the river cross-section; and determining the flow of the river cross-section by adopting the velocity-area method according to the flow speed field data. The application can make full use of the monitoring capacity of the near-shore side of a hydrological station, is helpful to solve the problems of flow speed field and flow of medium and large rivers, greatly improves the measurement efficiency and accuracy, and effectively reduces the consumption of manpower and material resources.

Description

Technical Field

[0001] This application relates to the fields of hydrological measurement and digital twins, and in particular to a method for reconstructing the flow field of a river cross section based on an entropy model and near-shore velocity points. Background Technology

[0002] River velocity and flow rate are essential foundational data for flood control and disaster reduction, water resource management, and water ecosystem protection. With the deepening of digital twin river basin construction, building high-precision, real-time updated digital models of river hydrodynamics has become crucial for improving water security capabilities and the level of refined water resource management. Digital twin systems require real-time mapping and dynamic simulation of real physical rivers, and one of their core inputs is the velocity field and flow rate data across the entire river cross-section.

[0003] Currently, with the construction of modern hydrological monitoring systems, non-contact measurement equipment such as video surveillance and radar current meters have been widely deployed. Among them, hydrological monitoring technology based on video images has become an important means of monitoring near-shore water levels, surface flow velocities, and ice conditions at hydrological stations due to its advantages of real-time operation, intuitiveness, and low cost. Through cameras fixed on the shore, continuous and automated surface flow velocity identification and tracking can be performed in local near-shore waters, accumulating massive amounts of real-time near-shore data.

[0004] However, for large rivers with considerable width (such as the Yangtze, Yellow, and Pearl Rivers), which can reach hundreds of meters or even kilometers in width, the monitoring capabilities of existing hydrological stations face fundamental limitations: shore-based video monitoring equipment can only effectively cover a limited width of water near the shore (usually tens of meters). For the hydrological dynamics of the main river channel and the opposite bank, effective measurements are difficult to achieve due to excessive line-of-sight, image distortion, and insufficient surface tracers. If drones or shipborne equipment are used for full-section mobile surveys, the risks are extremely high during flood seasons with high flow velocities and severe weather conditions, and continuous, real-time online monitoring cannot be achieved.

[0005] Therefore, the current actual monitoring system of hydrological stations has a prominent contradiction of "abundant near-shore data but lack of full-section information" - the massive amount of real-time near-shore video and radar data only represents the local hydrodynamic characteristics of the river edge and cannot directly meet the input requirements of digital twin watershed for full-section and distributed hydrodynamic data.

[0006] Traditional hydrological flow measurement methods, such as the mobile acoustic Doppler current profiler (ADCP), can obtain the velocity distribution across the entire cross-section, but they rely on manual, boat-based operations, resulting in high costs and poor timeliness. Especially during high flood seasons, the lives of measurement personnel are severely threatened, often forcing the interruption of measurements. Empirical formula methods based on statistical analysis (such as the index velocity method) lack physical mechanism support, and their empirical coefficients have poor applicability across different rivers and water levels, and similarly cannot output cross-sectional velocity field information. All these methods struggle to achieve the high-frequency, continuous, full-section hydrodynamic monitoring required for digital twins.

[0007] In summary, how to fully utilize real-time data such as near-shore video monitoring widely deployed at hydrological stations to overcome the limitations of river width on full-section hydrological monitoring, and how to accurately reconstruct the two-dimensional velocity field of the entire river cross-section and calculate the flow rate using only limited observation information from the near-shore side, thereby providing real-time, full-section hydrodynamic data support for digital twin watersheds, has become a key technical challenge that urgently needs to be solved in the field of hydrological monitoring and smart water conservancy. Summary of the Invention

[0008] The purpose of this application is to provide a method for reconstructing the flow field of a river cross section based on an entropy model and near-shore velocity points. This method can make full use of the near-shore monitoring capabilities of hydrological stations, help solve the problems of velocity field and flow rate in medium and large rivers, greatly improve measurement efficiency and accuracy, and effectively reduce the consumption of manpower and material resources.

[0009] To achieve the above objectives, this application provides the following solution: This application provides a method for reconstructing the flow field of a river cross section based on an entropy model and near-shore velocity points, including: Obtain topographic data and historical hydraulic parameters of the river channel cross section; The entropy parameters of the river channel cross section are determined based on topographic data and the historical hydraulic parameters. Using non-contact observation equipment at various hydrological stations in a digital twin context, the surface velocity at a single point on the near-bank side of the river channel is obtained; Based on the preset surface velocity distribution model and the surface velocity at a single point, the surface velocity data of the entire cross section of the river channel are fitted to obtain the surface velocity data of the entire cross section of the river channel; the preset surface velocity distribution model includes a parabolic surface velocity distribution model and an elliptical surface velocity distribution model. Based on the entropy parameter and the surface velocity data, the longitudinal velocity distribution of the river channel cross section is determined by using the entropy theory velocity distribution model and combining iterative optimization algorithms. Based on the longitudinal velocity distribution of the river channel cross section, the velocity field data of the river channel cross section is reconstructed using a two-dimensional griddata interpolation algorithm. Based on the velocity field data, the flow rate of the river cross section is determined using the velocity area method.

[0010] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a method for reconstructing the flow field of a river cross section based on an entropy model and near-shore velocity points. It measures the surface velocity on the near-bank side of the river channel using non-contact measurement equipment, and constructs a cross-sectional surface velocity distribution model using parabolic and elliptical surface velocity distribution models. Utilizing formulas based on entropy theory (entropy theory velocity distribution model) and combining them with the velocity-area method, it solves the problems of river velocity field and flow rate calculation, significantly improving measurement efficiency and accuracy while effectively reducing the consumption of manpower and resources. This application can help improve the comprehensive monitoring, intelligent sensing, and refined management capabilities of watersheds, serving the construction of smart twin watersheds and providing more comprehensive, accurate, perceptible, and intelligent information support for improving watershed governance and management capabilities. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of a method for reconstructing the flow field of a river cross section based on an entropy model and near-shore velocity points in one embodiment of this application. Figure 2 This is a schematic diagram illustrating a method for reconstructing the flow field of a river cross section based on an entropy model and nearshore velocity points, as described in one embodiment of this application. Figure 3 A functional fitting diagram of the surface velocity of the river cross section; Figure 4 A comparison diagram of the measured flow field at a river cross section and the calculated flow field in the embodiments of this application; Figure 5 A comparison diagram of the measured vertical flow velocity in the river channel and the calculated vertical flow velocity in the embodiments of this application; Figure 6 This is a comparison chart of the measured flow rates at various cross-sections of the river and the calculated flow rates in the embodiments of this application. Detailed Implementation

[0013] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0014] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0015] In one exemplary embodiment, such as Figure 1 and Figure 2 As shown, a method for reconstructing the flow field of a river cross section based on an entropy model and nearshore velocity points is provided. This method is executed by a computer device, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is described using a server as an example, including the following steps S101 to S107. Wherein: S101, obtain topographic data and historical hydraulic parameters of the river channel cross section; The topographic data includes: measurement data of riverbank surface topography and underwater topography taken at certain intervals along the river channel cross section, coordinates of measuring points, and relative elevation data; the historical river section hydraulic parameters include: hydraulic radius of the river channel cross section, maximum flow velocity, and average flow velocity. S102, Determine the entropy parameters of the river channel cross section based on the topographic data and the historical hydraulic parameters; S102 specifically includes: S21, Determine the three-dimensional cross-sectional topography of the river channel and the location of topographic measurement points based on topographic data; As a specific embodiment, S21 specifically includes: S211, using ultrasonic probes or mobile Doppler profilers, underwater topography is measured at certain intervals along the cross-section of the river channel to obtain underwater topography measurement data. S212, using a level and a distance measuring instrument, along the cross-section of the river channel, with the relative elevation zero coordinate point, measure the relative elevation and distance between the two riverbanks, up to the fixed posts on both banks, to obtain the measurement data of the riverbank surface topography; the relative elevation zero coordinate point is the fixed post on one side of the riverbank of the cross-section of the river channel. S213, using the relative elevation zero coordinate point to convert relative elevation data, and determining the three-dimensional cross-sectional topography of the river channel and the location of topographic measurement points (X) based on underwater topographic measurement data and riverbank surface topographic measurement data. i ,Y i Z i ).

[0016] Based on the existence of historical river flow velocity data at the topographic survey points, the topographic survey points are classified into survey stations and non-survey stations. Based on the soil quality of the river channel cross section, the river channel is classified into erodible and non-erodible channels. The survey cross section is then preliminarily classified based on the attributes.

[0017] S22, If historical river velocity data exists at the topographic survey points, then use the formula... Determine the entropy parameter M; where Φ(M) is the entropy function, M is the entropy parameter, and U m U is the average flow velocity across the river cross section. max denoted as the maximum flow velocity in the cross-section of the river channel, and e is the natural logarithm. S23, If historical river velocity data for the topographic survey point is unavailable, then the flow velocity data should be determined based on historical hydraulic parameters using the formula... Determine the entropy parameter M; where y max The maximum flow velocity U on the vertical line of the river channel cross section max The distance from the bed surface, y0 is the reference plane assuming zero velocity, k is the von Kármán parameter, R is the hydraulic radius, D is the flow depth, and h is the maximum flow velocity U on the vertical line of the channel cross section. max The distance downwards from the water surface, g is the acceleration due to gravity.

[0018] S103 utilizes non-contact observation equipment at various hydrological stations under a digital twin background to obtain single-point surface velocity on the near-bank side of the river channel; As a specific implementation, non-contact measurement equipment is used to acquire the surface velocity of the river near the bank (within 20% of the river width from the bank), obtaining its single-point surface velocity time-series data. Considering the basic conditions of the river measurement section (such as air visibility, river particle composition, etc.) and the difficulty of equipment deployment in the measurement area, non-contact measurement equipment such as radar velocity measuring instruments or particle image velocimeters are comprehensively selected. Based on the selection of non-contact measurement equipment, the measurement of river surface velocity and water level can be carried out near the bank, and the location and surface velocity data (X) are recorded. i D i U i ); S104. Based on the preset surface velocity distribution model and the single-point surface velocity, the surface velocity data of the entire cross section of the river channel is fitted to obtain the surface velocity data of the entire cross section. The preset surface velocity distribution model includes a parabolic surface velocity distribution model and an elliptical surface velocity distribution model. S104 specifically includes: S41, when the preset surface velocity distribution model is a parabolic surface velocity distribution model, use the formula Ax 2 +Bxy+Cy 2 +Dx+Ey+F=0, combined with the single-point surface velocity fitting on the near bank side of the river, the surface velocity data of the entire cross section of the river is obtained. S42, when the preset surface velocity distribution model is an elliptical surface velocity distribution model, use the formula The surface velocity data of the entire cross section of the river is obtained by fitting the surface velocity at a single point on the near bank side of the river. Where x is the distance from the river channel to the bank, y is the flow velocity, and A, B, C, D, E, and F are the shape parameters of the parabolic function. a c are the morphological parameters of the elliptic function.

[0019] S105, Based on the entropy parameter and the surface velocity data, the longitudinal velocity distribution of the river cross section is determined by using the entropy theory velocity distribution model and combining it with the optimization algorithm for iteration. Using formula Determine the location of topographic survey points (x) i Flow velocity data at the river cross section at (y, y) ; in, x is the vertical line of the river channel cross section i The maximum flow velocity at that location, x is the vertical line of the river channel cross section i The water depth at that location, M is the entropy parameter. For x i The distance from the water surface where the maximum flow velocity is located on the vertical line. Points in the vertical direction This represents the total number of vertical lines in the cross-section of the river channel.

[0020] Based on the flow velocity formula of entropy theory, using the formula... Determine the vertical lines x of each section of the river channel cross-section i Maximum vertical velocity U maxv (x i ); Among them, U surf (x) i ,D(x i )) is x i Surface velocity at the measuring line, δ(x) i D(x) represents the maximum downward displacement of the flow velocity at the location of the measuring line. i () represents the water depth at the location of the survey line.

[0021] Using formula Determine the maximum downward displacement of the vertical velocity along each vertical line xi in the river channel cross section. ; Where, x i It is the position of the i-th survey line from the left bank, D(x) i β is the water depth at the location of the survey line. i It corresponds to the downward shift of the maximum flow velocity along the vertical line. The correction factor.

[0022] The iterative calculation process for the flow field is unfolded. Each iteration yields a calculated entropy parameter value. The calculation process is complete when the difference between the calculated entropy parameter value and the theoretical entropy parameter value conforms to the following formula: Where ε is the difference between the entropy parameter value and the theoretical entropy parameter value, Φ(M p ) is the calculated value of the entropy function, i.e., the entropy parameter value; Φ(M) obs ) is the measured value of the entropy function, i.e., the theoretical entropy parameter value.

[0023] Construct the objective function by minimizing the difference between the entropy parameter value and the theoretical entropy parameter value. Where F(β) is the objective function to be optimized; Based on the objective function, the longitudinal velocity distribution of the river channel cross section is determined by iteratively using the particle swarm optimization algorithm. The particle swarm optimization algorithm is used to find the minimum value of the objective function, so as to make the calculated entropy parameter value as close as possible to the theoretical entropy parameter value.

[0024] Through formula Perform particle velocity updates.

[0025] Where particle i is the correction coefficient matrix β, β=[β1, β2, …, β i ], i∈[1,N v ];N v The total number of particles, It is a particle; P is the position of the i-th particle in generation k; w is the inertial weight, which controls the particle's ability to maintain its current flight direction; c1 and c2 are cognitive and social constants; r1 and r2 are random numbers, taking values ​​between [0,1]; b It is the historical optimal position of the particle; G b It is the global optimal position of the population.

[0026] S106. Based on the longitudinal velocity distribution of the river cross section, the velocity field data of the river cross section is reconstructed using a two-dimensional griddata interpolation algorithm. Using formula Perform two-dimensional griddata interpolation; Where, x i ,y i Let x be the coordinate of the i-th data point. i+1 ,y i+1 Let z be the coordinate of the (i+1)th data point. i,j For data point (x) i ,y i The velocity value at point (x, y) is the coordinate of the point to be interpolated; z is the function value of the interpolation point. i,j+1 For data points (x)i ,y i+1 The flow velocity value at point z i+1,j For data points (x) i+1 ,y i The flow velocity value at point z i+1,j+1 For data points (x) i+1 ,y i+1 The flow velocity value at ().

[0027] Finally, the velocity field data of the river channel cross section were obtained. for: ; in, x is the vertical line of the river channel cross section i The water depth at that location, M is the entropy parameter. The distance of maximum flow velocity downwards. Vertical position The number of perpendicular lines.

[0028] S107. Based on the velocity field data, the flow rate of the river cross section is determined using the velocity area method.

[0029] S107 specifically includes: S71, based on the velocity field data (V(x) i ,1)...V(x i Determine the vertical average flow velocity V(x) along each survey line of the river channel cross section at the topographic survey point. i ); V(x i )=[V(x i ,1)+...+V(x i [,j)] / j; where j is the number of vertical points on the survey line; S72, determine the weighted average flow velocity of the corresponding vertical line of the river cross section based on the average flow velocity between the vertical lines of every two adjacent river cross sections; The vertical line of the river channel cross section x i Average flow velocity V(x) i ) and the vertical line x of the river channel cross section i+1 The average flow velocity V(x) on the surface i+1 Take the weighted average to obtain the weighted average flow velocity. , =[V(x i )+V(x i+1 ] / 2 S73, determine the area of ​​the local region between the vertical lines of the river channel cross section, and use the velocity measurement vertical line as the boundary for dividing the sub-regions to divide the open channel cross section into multiple sub-regions, and calculate the cross-sectional area S of each sub-region. i ; Si =∑(b i+1 -b i )×(h i+1 -h i ); where b i+1 Let b be the width of the river at position i+1. i Let h be the width of the river at position i. i+1 Let h be the water depth at position i+1. i Let i be the width of the river at position i.

[0030] S74. Based on the cross-sectional area of ​​each sub-region and the weighted average velocity along the vertical line, the velocity-area method is used to determine the flow rate of the river cross section.

[0031] Based on the principle of calculating the flow rate of natural river channels in hydraulics, the velocity-area method is used. This method first uses the velocity measurement vertical line as the boundary to divide the open channel cross-section into several sub-regions. Then, based on the measured flow velocity and water depth, the cross-sectional area, average flow velocity, and flow rate of each sub-region are calculated. Finally, the flow rates of each sub-region are summed to obtain the result.

[0032] Using formula Q =∑S i × V (x i Determine the flow rate of the river cross section. Q ; Among them, S i V(x) represents the cross-sectional area of ​​each sub-region. i ) represents the weighted average velocity along the vertical line.

[0033] This application has the following effects: (1) This application provides a method for reconstructing the flow field of a river cross section based on an entropy model and near-shore velocity points. The main purpose is to solve the problems of high difficulty, high cost, poor accuracy, and difficulty in real-time online monitoring of hydrodynamic measurement of large rivers. The method described in this application has high accuracy in hydrodynamic monitoring calculation of natural rivers and is applicable to large and medium-sized rivers. It can realize real-time online synchronous monitoring of velocity field and flow rate. (2) The method provided in this application has a theoretical basis in hydraulics and probability theory. It can accurately identify the velocity distribution of each vertical line of a river through surface velocity measurement and adaptive adjustment of entropy parameters. It is effective in different river types and river sections. Compared with traditional calculation methods, it has more physical mechanism, strong interpretability, convenient application, wide applicability, and high accuracy and reliability of calculation. (3) The method provided in this application is based on non-contact measurement of the river channel, which has the advantages of high automation, strong adaptability to complex environments, and high measurement safety, and can ensure safety and avoid safety hazards to hydrological surveyors. At the same time, it makes full use of surface velocity data to realize the entire river channel and can be applied to different river types and river sections. Compared with traditional calculation methods, it has hydraulic and river dynamics mechanisms, and is convenient to use, has wide applicability, and high accuracy and reliability of calculation. (4) The method provided in this application can perform flow field calculations at multiple cross sections and flow field modeling for the entire river section. By making full use of real-time data such as the topography of the river cross section and the measured surface velocity, the flow velocity field of each cross section of the river is calculated through the algorithm of this model. The flow field of the entire river section is reconstructed by interpolation and fitting using computer software. The calculation efficiency is high, and it can accurately depict the flow velocity distribution of the river channel and describe the hydrological conditions of the river channel in real time, which greatly improves the accuracy of the flow measurement of the river cross section.

[0034] (5) The method provided in this application can not only obtain the flow rate of the river cross section, but also reconstruct the velocity field of the entire river cross section, which solves the problems of difficulty in measuring underwater velocity in natural rivers and the shortage of continuous data. It can also provide more comprehensive data support for understanding river hydrodynamics. At the same time, real-time monitoring of the velocity field of the entire cross section helps to identify adverse flow regimes in a timely manner, assess their impact on river evolution, and provide data support for decision-making in water resource management and river management.

[0035] (6) The precise calculation method provided in this application is highly operable, can be programmed, and has portability and nestability. It only requires the measured cross-sectional topography and measured cross-sectional flow velocity data of the river channel as input data. Through the built-in model algorithm of this application, it can realize automatic and rapid precise calculation of the cross-sectional flow field of the river channel and output the real-time online full-section flow velocity and river flow. It provides technical support for intelligent river sensing and comprehensive watershed monitoring, and also helps to improve the level of refined river management and watershed governance.

[0036] The following is a specific embodiment for illustration. The river section studied in this embodiment is a wide and shallow river section with a straight channel and stable riverbed. Surface velocity and water level of the river cross section are obtained through automatic control devices and radar flow measurement equipment. Basic data such as cross-sectional velocity, flow rate (for verification), and water depth are measured along the river cross section using a mobile Doppler current profiler. Computer software is used to fit the river cross section topography with the horizontal axis as the variable. Considering the large size of the river, a river section with a width exceeding 1 km is selected for example analysis, where the river width is set at 1.0 m intervals between each segment.

[0037] The measurement cross-section is classified as a data-rich measurement station, representing an erosive soil river channel. The theoretical entropy function value is 0.48, calculated using the formulas for the maximum and average flow velocities of the cross-section. Based on field conditions, a hydrological station radar velocimeter is used as a non-contact measurement device to obtain the surface flow velocity and water level on the near-bank side of the river channel. Figure 3 As shown, the surface velocity of the entire river cross-section is modeled by fitting a surface velocity distribution model of the river cross-section. Then, using the entropy theory formula model and surface velocity data, the point velocity values ​​of the entire cross-section are calculated using the particle swarm optimization algorithm. Finally, the total cross-sectional discharge is obtained using hydraulic methods for calculating natural river channel discharge. Figure 4 As shown, the results indicate that the average relative error between the calculated and measured velocity fields across the entire cross-section is 15.60%. To further verify the accuracy of this application, the measured velocity vertical distribution on the cross-section is compared with the calculated velocity vertical distribution, and the results are as follows. Figure 5 As shown. A comparison and analysis of the measured and calculated flow rates at the cross-section shows that the calculated cross-sectional flow rate is 14642 m³ / s, while the measured cross-sectional flow rate is 15888 m³ / s. 3 / s, with a relative error of only 8.51%; to further verify the beneficial effects of this application, the measured flow and calculated flow at each cross-section of the study area were compared and analyzed. During periods of high flood flow, the maximum relative error of the flow was only 9.67%, and the errors at each cross-section were all within 10%. A comparison of the measured flow and calculated flow at each cross-section is shown below. Figure 6 .

[0038] This application can make full use of the emerging non-contact measurement technologies of many hydrological stations. For large rivers with wide channels, real-time monitoring of river velocity field and flow can be achieved by using only the measured surface velocity on the near bank side. It is particularly suitable for real-time hydrodynamic monitoring of river sections with high flow velocity during floods and inaccessible to personnel, which greatly improves measurement safety and efficiency, effectively reduces the consumption of manpower and material resources, provides real-time data support for the construction of digital twin watersheds, and provides important support for strengthening water security and water resource management.

[0039] In an exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is connected to the system bus via the I / O interfaces. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The I / O interfaces of the computer device are used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for reconstructing the flow field of a river cross-section based on an entropy model and near-shore velocity points.

[0040] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0041] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0042] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0043] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0044] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0045] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0046] In this application, all actions to acquire signals, information, or data are carried out in compliance with the relevant data protection laws and policies of the country where the location is situated, and with the authorization granted by the owner of the relevant device.

[0047] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0048] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for reconstructing the flow field of a river cross section based on an entropy model and near-shore velocity points, characterized in that, include: Obtain topographic data and historical hydraulic parameters of the river channel cross section; The entropy parameters of the river channel cross section are determined based on topographic data and the historical hydraulic parameters. Using non-contact observation equipment at various hydrological stations in a digital twin context, the surface velocity at a single point on the near-bank side of the river channel is obtained; Based on the preset surface velocity distribution model and the surface velocity at a single point, the surface velocity data of the entire cross section of the river channel are fitted to obtain the surface velocity data of the entire cross section of the river channel; the preset surface velocity distribution model includes a parabolic surface velocity distribution model and an elliptical surface velocity distribution model. Based on the entropy parameter and the surface velocity data, the longitudinal velocity distribution of the river channel cross section is determined by using the entropy theory velocity distribution model and combining iterative optimization algorithms. Based on the longitudinal velocity distribution of the river channel cross section, the velocity field data of the river channel cross section is reconstructed using a two-dimensional griddata interpolation algorithm. Based on the velocity field data, the flow rate of the river cross section is determined using the velocity area method.

2. The method for reconstructing the river cross-section flow field based on the entropy model and near-shore velocity points according to claim 1, characterized in that, The determination of the entropy parameters of the river channel cross-section based on topographic data and historical hydraulic parameters specifically includes: The three-dimensional cross-sectional topography of the river channel and the location of topographic measurement points are determined based on the topographic data. If historical river velocity data for a given section exists at the topographic survey point, then the formula can be used. Determine the entropy parameter M; where Φ(M) is the entropy function, M is the entropy parameter, and U m U is the average flow velocity across the river cross section. max denoted as the maximum flow velocity in the cross-section of the river channel, and e is the natural logarithm. If historical flow velocity data for the river section is unavailable at the topographic survey point, then the historical hydraulic parameters are used, employing the formula... Determine the entropy parameter M; where y max The maximum flow velocity U on the vertical line of the river channel cross section max The distance from the bed surface, y0 is the reference plane assuming zero velocity, k is the von Kármán parameter, R is the hydraulic radius, D is the flow depth, and h is the maximum flow velocity U on the vertical line of the channel cross section. max The distance downwards from the water surface, g is the acceleration due to gravity.

3. The method for reconstructing the river cross-section flow field based on the entropy model and near-shore velocity points according to claim 1, characterized in that, The process of fitting surface velocity data of the entire cross-section of the river channel based on a preset surface velocity distribution model and the surface velocity at a single point specifically includes: When the preset surface velocity distribution model is a parabolic surface velocity distribution model, the formula Ax is used. 2 +Bxy+Cy 2 +Dx+Ey+F=0, combined with the single-point surface velocity fitting on the near bank side of the river, the surface velocity data of the entire cross section of the river is obtained. When the preset surface velocity distribution model is an elliptical surface velocity distribution model, the formula is used. The surface velocity data of the entire cross section of the river is obtained by fitting the surface velocity at a single point on the near bank side of the river. Where x is the distance from the river channel to the bank, y is the flow velocity, and A, B, C, D, E, and F are the shape parameters of the parabolic function. a c are the morphological parameters of the elliptic function.

4. The method for reconstructing the river cross-section flow field based on the entropy model and near-shore velocity points according to claim 1, characterized in that, The process of determining the longitudinal velocity distribution of the river channel cross-section by using an entropy theory velocity distribution model based on the entropy parameter and the surface velocity data, combined with an optimization algorithm for iteration, specifically includes: use Determine the difference between the entropy parameter value and the theoretical entropy parameter value; The objective function is constructed by minimizing the difference between the entropy parameter value and the theoretical entropy parameter value. Based on the objective function, the longitudinal velocity distribution of the river channel cross section is determined by iteratively using the particle swarm optimization algorithm. Where ε is the difference between the entropy parameter value and the theoretical entropy parameter value, Φ(M p ) is the entropy parameter value, Φ(M obs ) is the theoretical entropy parameter value.

5. The method for reconstructing the river cross-section flow field based on the entropy model and near-shore velocity points according to claim 1, characterized in that, The process involves reconstructing the velocity field data of the river cross-section using a two-dimensional griddata interpolation algorithm based on the longitudinal velocity distribution of the river cross-section. Specifically, this includes: Using formula Perform two-dimensional griddata interpolation; Where, x i ,y i Let x be the coordinate of the i-th data point. i+1 ,y i+1 Let z be the coordinate of the (i+1)th data point. i,j For data point (x) i ,y i The velocity value at point (x, y) is the coordinate of the point to be interpolated; z is the function value of the interpolation point. i,j+1 For data points (x) i ,y i+1 The flow velocity value at point z i+1,j For data points (x) i+1 ,y i The flow velocity value at point z i+1,j+1 For data points (x) i+1 ,y i+1 The flow velocity value at ().

6. The method for reconstructing the river cross-section flow field based on the entropy model and near-shore velocity points according to claim 1, characterized in that, The determination of the flow rate at the river cross-section using the velocity area method based on the velocity field data specifically includes: Determine the vertical average velocity along each measuring line of the river channel cross section at the topographic measurement point based on the velocity field data. The weighted average velocity of the corresponding vertical line of the river cross section is determined based on the average velocity between the vertical lines of every two adjacent river cross sections. Determine the area of ​​the local region between the vertical lines of the river channel cross section, and use the velocity measurement vertical line as the boundary for dividing the sub-regions. Divide the open channel cross section into multiple sub-regions and calculate the cross-sectional area of ​​each sub-region. The flow rate of the river cross section is determined by using the velocity-area method based on the cross-sectional area of ​​each sub-region and the weighted average velocity along the vertical.

7. The method for reconstructing the river cross-section flow field based on the entropy model and near-shore velocity points according to claim 1, characterized in that, The flow rate of the river channel cross section is determined using the velocity-area method based on the cross-sectional area of ​​each sub-region and the weighted average velocity along the vertical line. Specifically, this includes: Using formula Q =∑S i × V (x i Determine the flow rate of the river cross section. Q ; Among them, S i V(x) represents the cross-sectional area of ​​each sub-region. i ) represents the weighted average velocity along the vertical line.

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