A method for estimating bed load transport rate based on surface velocity

Abstract

The present invention discloses a method for estimating the bedload sediment transport rate in an open channel based on surface velocity. By exploring the correlation between the surface velocity of the water flow and the movement of bedload sediment, the underwater bedload sediment transport rate is evaluated through surface flow field information. The present invention analyzes and obtains a reliable correlation between the surface velocity of the open channel and the profile distribution of the bedload sediment velocity from test data and numerical calculation results. Based on these correlations, the bedload sediment transport rate in the open channel can be effectively estimated using surface velocity information and water depth information. In actual engineering, surface velocity information is easier to obtain than bedload sediment movement, and has higher measurement accuracy. The surface velocity information can be obtained by obtaining images from drones or other devices, and then surface velocity data can be obtained through image processing. The technology is mature and has high measurement efficiency. Therefore, the method for estimating the bedload sediment transport rate in an open channel based on surface velocity disclosed by the present invention has the advantages of high universality, high accuracy, high efficiency, and low cost.

Description

Technical Field

[0001] The invention belongs to the field of hydraulics and river dynamics, relates to the study of hydrodynamic characteristics and riverbed evolution of erodible open channels, and specifically relates to a method for estimating bed load and sediment transport rate based on open channel surface velocity. Background Art

[0002] In engineering scenarios such as water resources management, flood prediction and prevention, environmental monitoring, hydraulic engineering design, and water supply and drainage systems, it is crucial to accurately measure and calculate bedload sediment in open channels. The evolution of the riverbed caused by the movement of bedload sediment will directly affect the flood prediction and prevention work in the basin. In this dynamic process, bedload sediment often carries a large amount of organic matter and inorganic salts, which has a profound impact on the ecological and environmental health of the river network. In dam and levee projects, accurate estimation of open channel sediment transport rate is crucial to assessing the safety and stable operation of engineering structures. The movement of bedload sediment also greatly affects the design, planning and operation of urban water supply and drainage systems. Therefore, in the field of water conservancy engineering, accurate measurement and estimation of bedload sediment transport rate is regarded as a prerequisite for assessing the safety and stable operation of water conservancy engineering facilities, disaster prevention and mitigation, predicting river network evolution, and optimizing water resources management. The commonly used methods for measuring and estimating open channel bedload sediment transport rate are:

[0003] 1) Instrumental measurement method

[0004] The bed load sampler is placed directly on the open channel bed to collect bed load samples, and the sediment transport rate is estimated by collecting bed load. This method has low sampling efficiency, interferes with the flow field, and the data obtained depends on the local water flow and riverbed conditions, with poor stability and reliability.

[0005] 2) Radioactive tracer sand method

[0006] This method releases radioactive isotope tracers in open channels, uses the tracers to detect the movement of sediment and deduce the bedload sediment transport rate. This method may pose a threat to human health and the ecological environment, so it is not universal.

[0007] 3) Empirical sediment transport formula estimation method

[0008] In engineering, empirical sediment transport rate formulas are often used for estimation. This method often uses bed load balance sediment transport formulas (such as Meyer-Peter and Müller formula and Bagnold formula) based on energy conservation and experimental data analysis, or bed load transport formulas based on probability theory (such as Einstein formula) to estimate open channel bed load sediment transport rate. This method is widely used, low cost, and high efficiency, but the calculation accuracy is poor, and the calculation results often depend on the selected formula and the selection of empirical coefficients.

[0009] In general, there is no efficient and accurate method to estimate the bed load and sediment transport rate in an open channel. In practical engineering applications, the surface velocity of an open channel is often the easiest information to obtain. Estimating the bed load and sediment transport rate with the help of open channel surface flow field information has become a potential research direction and a powerful means. In practical engineering, with the widespread application of drone technology, the method of obtaining the surface water velocity field of the river channel by taking images with drones and combining image processing technology is becoming more and more popular. However, these methods can only reflect the surface flow field and cannot directly obtain the complex underwater bed load and sediment movement. How to infer the underwater bed load and sediment movement through surface flow field information has become a new difficulty and challenge. Summary of the invention

[0010] The purpose of the present invention is to address the deficiencies in the prior art and provide a method for estimating the open channel bed load sediment transport rate based on surface flow velocity. By exploring the correlation between the surface velocity of the water flow and the movement of sediment in the bed load layer, the water surface flow field information and water depth information captured by an unmanned aerial vehicle can be used to effectively estimate the bed load sediment transport rate in the open channel, thereby achieving a more efficient and accurate estimation of the open channel bed load sediment transport rate.

[0011] The present invention explores the correlation between the surface velocity of water flow and the movement of bedload sediment, and realizes the inference of underwater bedload sediment movement through surface flow field information. For example, the bedload sediment transport rate of an open channel can be inferred with the help of surface flow field image data. In view of the problem that the images taken by drones can only reflect the surface of the water flow, and cannot directly obtain the profile information of the water flow along the water depth direction, and cannot obtain the complex underwater bedload sediment movement conditions, it is proposed that: if a reliable correlation between the surface velocity of water flow and the movement and distribution of bedload sediment in the bedload layer can be obtained from the test data and numerical simulation results, then these relationships can be analyzed to infer the bedload sediment transport rate of the open channel based on the surface flow field information obtained by drone photography. The method of the present invention uses the water surface flow field information and water depth information taken by drones to effectively estimate the bedload sediment transport rate in the open channel. While ensuring the estimation accuracy, it has the advantages of convenience, high efficiency and low cost.

[0012] The method for estimating the open channel bed load sediment transport rate based on surface velocity provided by the present invention comprises the following steps:

[0013] (1) Obtaining the basic physical parameters of open channel bedload sediment, including sediment density ρ s , particle size D, internal friction angle and the volume concentration of riverbed sediment c0; the open channel water depth H and riverbed gradient θ were measured;

[0014] (2) Estimate the thickness of the bedrock layer according to the following formula;

[0015]

[0016]

[0017] Where δ is the thickness of the bedrock layer; is the Shear Force; D is the effective particle size of sediment in the open channel; κ and λ are coefficients, κ = 8.37, λ = 0.72; H is the water depth of the open channel; is the internal friction angle of bed load; S = tanθ, θ is the riverbed gradient; s = ρ s / ρ w is the bed load density ρ s and water density ρ w ratio.

[0018] (3) Use drone flow measurement technology or high-speed camera flow measurement technology to obtain the surface flow velocity of the open channel According to formula (3), the bed load transport rate q is estimated b .

[0019]

[0020] Where W is the width of the open channel water section; c0 is the volume concentration of riverbed sediment; is the surface velocity of the open channel; z is the height of any point in the bedload layer; c is the volume concentration of sediment at the height z; u s is the corresponding sediment movement velocity; z0 is the height of the lower surface of the bedload layer; δ is the thickness of the bedload layer; the values ​​of coefficients α and β are obtained by finding their correlation with the surface velocity of the open channel. The dimensionless Schertz number Θ is related to:

[0021]

[0022] β=1.40 (5)

[0023]

[0024] Where g is the acceleration due to gravity.

[0025] Furthermore, in the above method, the drone flow measurement technology is a method of obtaining the surface velocity field of the open channel through image processing technology based on the open channel river channel image taken by the drone. Compared with other flow measurement technologies, such as current meters, acoustic Doppler current profilers (ADCP) and ultrasonic instruments, drone flow measurement technology has the advantages of high efficiency and low cost.

[0026] Furthermore, in the above method, the steps of the drone flow measurement technology are as follows: a) setting reference points, releasing tracer particles, and using drones to collect river images at different times; b) based on the reference point coordinates, denoising and correcting the acquired images; c) calculating the surface flow field according to the positions of the tracer particles at different times.

[0027] Furthermore, in the above method, the high-speed camera flow measurement technology is similar to the drone flow measurement technology in principle and steps. The high-speed camera flow measurement technology is more suitable for open channel surface flow velocity measurement in flume tests.

[0028] Furthermore, in the above method, the sediment velocity in the bed load layer presents a power function distribution form, and the power function formula is as follows:

[0029]

[0030] In the formula, u s is the velocity of sediment movement in the bed load layer; is the surface velocity of the open channel; z is the height of any point in the bed load layer; z0 is the height of the lower surface of the bed load layer; δ is the thickness of the bed load layer; β and β are the coefficients of the power function.

[0031] Furthermore, in the above method, the values ​​of the power function coefficients in formulas (7) and (3) are determined by establishing the relationship between α and α and the surface velocity of the open channel. The dimensionless Schertz number θ is determined by the following method: the velocity profiles obtained by numerical calculation of the four working conditions (see Table 1) and the corresponding open channel surface velocity The data is extracted, and the corresponding dimensionless Schertz number θ is calculated using formula (6); then all velocity profiles are fitted with the power function form of formula (7) to obtain β and α of each velocity profile; the correlation between all data points α and β and the corresponding dimensionless Schertz number θ is found to obtain:

[0032]

[0033] β=1.40 (5)

[0034]

[0035] In formula (6), g is the acceleration due to gravity. The dimensionless Schertz number is a common index used to describe the movement of bed load and sediment. It is usually defined as the ratio of the bed shear stress to the underwater gravity of the bed sand. where u * is the shear velocity. In order to highlight the importance of the surface velocity of the open channel, a dimensionless Schertz number based on the surface velocity is defined. In order to consider the effect of riverbed gradient on bed load movement, the cosine of riverbed gradient is added to the denominator of equation (6).

[0036] Furthermore, in the above method, step (1) uses an unmanned aerial vehicle equipped with a laser radar or a depth sounder to measure the open channel water depth H and the riverbed gradient θ.

[0037] Furthermore, in the above method, step (1) obtains the basic physical parameters of open channel bedload sediment by geological survey or querying basin river network data.

[0038] In the above method of the present invention, the derivation process of formula (3) is as follows:

[0039] The water tank test was carried out in a glass water tank with a width of 0.25m, a height of 0.7m and a length of 6.0m. The schematic diagram of the water tank test and numerical modeling is shown in the figure. Figure 1 As shown. Before the start, there is a gate in the middle of the flume. The erosion bed height h upstream of the gate s1 , covered with clear water high h w1 The erodible bed height downstream of the gate is h s2 At the beginning of the experiment, the middle gate was quickly removed, and the upstream water flowed downstream under the action of gravity, while driving the sediment particles on the erodible bed surface to be transported downstream. A bedload sediment transport layer was formed between the clear water layer and the erodible bed surface. The test included a total of 4 groups of working conditions, using different layout forms to characterize different water flow conditions and riverbed topography in natural open channels. The specific parameters are shown in Table 1.

[0040] Table 1. Summary of test conditions

[0041]

[0042] In the test, only the sediment concentration and velocity of the bedload layer were measured, and other information such as the surface velocity of the open channel could not be provided. Therefore, the present invention uses a smoothed particle model (Smoothed Particle Hydrodynamics, SPH for short) suitable for water-sand two-phase flow to simulate the test process to provide more flow field information and make up for the shortcomings of the test measurement. Numerical calculations are performed for the above four working conditions, and analysis is performed in combination with the test measurement data.

[0043] The purpose of numerical calculation is to verify the reliability of numerical calculation by comparing the calculation results with the experimental measurement data; to provide more flow field information to make up for the shortcomings of experimental measurement. The numerical model adopts a smooth particle model suitable for water-sand two-phase flow that has been published in the literature (Shi, H., Yu, X., & Dalrymple, RA (2017). Development of a two-phase SPH model for sediment laden flows. Computer Physics Communications, 221, 259-272.). The model independently solves the mass conservation equation and momentum conservation equation of water and sediment, and fully considers the relative motion and interaction between water and sediment. The model uses gridless technology (i.e., a set of discrete numerical smooth particles, referred to as SPH particles) to discretize water and sediment in the calculation domain. Therefore, this numerical model is particularly suitable for solving the problem of sediment movement under the action of violent water flow. In addition, the numerical model has verified its ability to accurately capture the movement of sediment in water in problems such as riverbed evolution, submarine landslides, and underwater soil collapse.

[0044] The numerical calculation process and steps are shown in Figure 2 , as follows: a) set the initial calculation domain according to each working condition and discretize it into a group of SPH particles carrying flow field information; b) update the position of each SPH particle and the flow field information it carries at different times according to the mass conservation equation and momentum conservation equation of water and sediment; c) compare the numerical calculation results with the experimental measurement results to verify the reliability of the numerical model; d) use the numerical calculation results as reliable data to supplement more flow field information to make up for the shortcomings of experimental measurement.

[0045] Figure 3 The velocity profile comparison results of working condition P01 are shown. In the figure, the black dots represent the test measurement values; the blue dotted line represents the water velocity obtained by numerical simulation; the red solid line represents the sediment movement velocity obtained by numerical simulation. The black solid line represents the free water surface of the dam break flow. The black dotted line represents the upper surface of the bedload layer. The black dotted line represents the lower surface of the bedload layer. The area below the black dotted line represents the immovable bed. Figure 3 It can be seen that the results of numerical simulation are in good agreement with the experimental measurements, indicating that the mathematical model can well simulate the movement of water flow and sediment in the open channel. It is worth noting that the sediment velocity in the bedload layer presents a power function distribution ( Figure 3 It can be seen that in the bedload layer (between the black dashed line and the black dotted line), both the experimental value (black dots) and the calculated value (curve) are more in line with the power function distribution), which is different from the linear distribution form mentioned in previous studies. Therefore, the power function formula is proposed as follows:

[0046]

[0047] In this formula, u s is the velocity of sediment movement in the bed load layer; is the surface velocity of the open channel; z is the height of any point in the bed load layer; z0 is the height of the lower surface of the bed load layer; δ is the thickness of the bed load layer; α and β are the coefficients of the power function.

[0048] According to existing research, the concentration of sediment in the bedload layer is linearly distributed as follows:

[0049] c=c0+(c1-c0)(z-z0) / δ (8)

[0050] Where z is the height of any point in the bedload layer; c is the sediment volume concentration corresponding to the height z in the bedload layer; c0 is the sediment volume concentration in the riverbed; c1 is the sediment volume concentration on the upper surface of the bedload layer; z0 is the height of the lower surface of the bedload layer; δ is the thickness of the bedload layer.

[0051] According to the definition of bedload sediment transport, the bedload sediment transport rate per unit area per unit time can be obtained as s and the bed load q per unit time flowing through the flow section b They are as follows:

[0052]

[0053]

[0054] Ignoring the small amount of suspended sediment that may appear, the sediment concentration on the bed load surface is defined as 0, that is, c1 = 0, then:

[0055]

[0056] According to existing research, the thickness of the bedrock layer is estimated using the following formula:

[0057]

[0058]

[0059] in is the Shear Force; D is the effective particle size of sediment in the open channel; κ and λ are coefficients, κ = 8.37, λ = 0.72; H is the water depth of the open channel; is the internal friction angle of bed load; S = tanθ, θ is the riverbed gradient; s = ρ s / ρ w is the bed load density ρ s and water density ρ w ratio; W is the width of the open channel water flow section.

[0060] In order to determine the value of the power function coefficient in formula (3), the present invention discusses the relationship between α and β and the surface velocity of the open channel. The dimensionless Schertz number Θ is related to the following method: the velocity profiles (similar to Figure 3 The red curve in the figure) and the corresponding open channel surface velocity The data is extracted; the dimensionless Schertz number θ corresponding to each data point is calculated using formula (6); then all velocity profiles are fitted using the power function form of formula (7) to obtain α and β of each velocity profile; the correlation between all data points α and β and the corresponding dimensionless Schertz number θ is found, as follows: Figure 4 As shown in the figure, the black dots correspond to the numerical calculation results of the four working conditions; it can be seen from the figure that the coefficients basically conform to the following relationship:

[0061]

[0062] β=1.40 (5)

[0063]

[0064] Most of the data points fall within the above relationship and its ±25% error range, indicating that the power function coefficient α is related to the surface velocity of the open channel. There is a stable correlation between the dimensionless Schertz number θ and the dimensionless Schertz number θ. Therefore, it is feasible to deduce the bedload sediment transport rate by measuring the surface velocity of the open channel.

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] 1. The method of the present invention proposes a method for estimating bed load sediment transport rate based on surface velocity. This method, combined with drone flow measurement technology, can efficiently and conveniently estimate the bed load sediment transport rate in an open channel and reduce engineering measurement costs.

[0067] 2. Compared with other measurement methods, the present invention does not require additional measurement equipment to be installed in the open channel and does not interfere with the flow field.

[0068] 3. Compared with other existing empirical sediment transport rate estimation formulas, the open channel bedload sediment transport estimation formula proposed in the present invention has clear physical meaning and improved calculation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 A schematic diagram of a water tank test and numerical modeling involving data sources in the analysis process of the method of the present invention;

[0070] Figure 2 The process and steps for numerical calculation;

[0071] Figure 3 Comparison between the velocity profile test data and numerical calculation results for the working condition P01 mentioned in the analysis process.

[0072] The black dots in the figure represent the experimental measurement values. The blue dotted line represents the water flow velocity obtained by numerical simulation. The red solid line represents the sediment movement velocity obtained by numerical simulation. The black solid line represents the free water surface of the dam break flow. The black dotted line represents the upper surface of the bedload layer. The black dotted line represents the lower surface of the bedload layer. The area below the black dotted line represents the immobile bed. This figure is intended to prove the reliability of the numerical method and to demonstrate the rationality of the invention.

[0073] Figure 4 The power function coefficients proposed by the method of the present invention are based on the surface velocity of the open channel. The dimensionless Schertz number Θ is related to . DETAILED DESCRIPTION

[0074] The following is a further explanation of the method for estimating the bed load sediment transport rate based on surface velocity described in the present invention in conjunction with a specific implementation manner.

[0075] Example 1

[0076] Test A was conducted in a rectangular glass flume of sufficient length. The flume was 0.2 m wide and the bottom was covered with polyvinyl chloride (PVC) particles to achieve a riverbed sediment volume concentration of c0 = 0.66. A water-PVC mixture with a total flow rate of 10.9 L / s was continuously delivered upstream through pipes and pumps to supplement the downstream outflow flow, of which the PVC flow rate was 0.192 L / s. The flume test was carried out by adjusting the flume slope to 0.8° to meet the open channel uniform constant flow conditions. The equivalent diameter of the PVC particles is D = 3.35 mm and the density is ρ s =1510kg / m 3 , the internal friction angle is The water depth in the open channel is H = 0.064m (based on the surface of the stationary bed), and the density of water is ρ w =1000kg / m 3 Based on the images taken by a high-speed camera (in actual engineering environments, drones can be used to efficiently obtain data), the surface flow velocity of the open channel is measured using the particle tracking velocimetry method (in actual engineering environments, the corresponding drone flow measurement technology is used).

[0077] Substituting the above parameters into formula (2), the Shear stress is calculated as Substituting into formula (1), we get the bed load thickness δ = 17.9 mm. According to formula (6), we get the surface velocity of the open channel The dimensionless Schertz number Θ = 112.69. According to formula (4-5), the power function coefficients α = 0.531 and β = 1.40 are calculated. Substituting these parameters into formula (3), the open channel bed load sediment transport rate q is calculated. b =0.211L / s.

[0078] The relative error of the open channel bedload sediment transport rate estimated by the invention is 9.90% compared with the bedload sediment transport rate actually measured in the experiment (in the experiment, the sediment discharged at the downstream outlet of the open channel was collected and the sediment transport rate was measured by weighing and conversion). The error of the estimation method proposed by the present invention is lower than the error estimated by the estimation formula proposed in the literature (Capart, H., & Fraccarollo, L. (2011). Transport layer structure in intense bed-load. Geophysical Research Letters, 38 (20).) and the commonly used Meyer-Peter and Müller formula. The relative errors of the sediment transport rate estimates of the two are 22.61% and 121.85% respectively.

[0079] Example 2

[0080] Test B was conducted in the same rectangular flume. The bottom of the flume was covered with PVC particles to reach a riverbed sediment volume concentration of c0 = 0.66. The upstream was continuously supplied with a water-PVC mixture with a total flow rate of 8.9 L / s through pipes and pumps to supplement the downstream outflow flow, of which the PVC flow rate was 0.862 L / s. The flume test was carried out by adjusting the flume slope to 3.2° to meet the open channel uniform constant flow conditions. The equivalent diameter of the PVC particles is D = 3.35 mm and the density is ρ s =1510kg / m 3 , the internal friction angle is The water depth in the open channel is H = 0.046m, and the water density is ρ w =1000kg / m 3 Based on the images taken by the high-speed camera, the particle tracking velocimetry method was used to measure the surface velocity of the open channel:

[0081] Substituting the above parameters into formula (2), the Shear stress is calculated as Substituting into formula (1), we get the bed load thickness = 40.4 mm. According to formula (6), we get the surface velocity of the open channel The dimensionless Schertz number Θ = 227.59. According to formula (4-5), the power function coefficients α = 0.754 and β = 1.40 are calculated. Substituting these parameters into formula (3), the open channel bed load sediment transport rate q is calculated. b=0.962L / s.

[0082] The relative error of the open channel bedload sediment transport rate estimated by the invention is 11.60% compared with the bedload sediment transport rate (0.862L / s) actually measured in the test. The error of the estimation method proposed by the invention is lower than the error estimated by the estimation formula proposed in the literature (Capart, H., & Fraccarollo, L. (2011). Transport layer structure in intense bed-load. Geophysical Research Letters, 38 (20).) and the commonly used Meyer-Peter Muller formula, the relative errors of which are 24.86% and 295.61% respectively.

Claims

1. A method for estimating the sediment transport rate of an open channel bed load based on surface velocity, characterized in that: The following steps are involved: (1) Obtaining the basic physical parameters of open channel bedload sediment, including sediment density ρ s , particle size D, internal friction angle and the volume concentration of riverbed sediment c0; the open channel water depth H and riverbed gradient θ were measured; (2) Estimate the thickness of the bedrock layer according to the following formula; Where δ is the thickness of the bedrock layer; is the Shear Force; D is the effective particle size of sediment in the open channel; κ and λ are coefficients, κ = 8.37, λ = 0.72; H is the water depth of the open channel; is the internal friction angle of bed load; S = tanθ, θ is the riverbed gradient; s = ρ s / ρ w is the bed load density ρ s and water density ρ w The ratio of (3) Use drone flow measurement technology or high-speed camera flow measurement technology combined with image processing technology to obtain the surface flow velocity of the open channel According to formula (3), the bed load transport rate q is estimated b , Where W is the width of the open channel water section; c0 is the volume concentration of riverbed sediment; is the surface velocity of the open channel; z is the height of any point in the bedload layer; c is the volume concentration of sediment at the height z; u s is the corresponding sediment movement velocity; z0 is the height of the lower surface of the bedload layer; δ is the bed load thickness; the coefficients α and β are chosen by finding their relationship with the surface velocity of the open channel. The dimensionless Schertz number Θ is related to: β＝1.40 (5) Where g is the acceleration due to gravity.

2. The method according to claim 1, characterized in that: The steps of the drone flow measurement technology are as follows: a) setting reference points, releasing tracer particles, and using drones to collect river images at different times; b) based on the reference point coordinates, denoising and correcting the acquired images; c) calculating the surface flow field according to the positions of the tracer particles at different times.

3. The method according to claim 1, characterized in that: The sediment velocity in the bedload layer presents a power function distribution, and the power function formula is as follows: In the formula, u s is the velocity of sediment movement in the bed load layer; is the surface velocity of the open channel; z is the height of any point in the bed load layer; z0 is the height of the lower surface of the bed load layer; δ is the thickness of the bed load layer; α and β are the coefficients of the power function.

4. The method according to claim 3, characterized in that: The values ​​of the power function coefficients in formulas (3) and (7) are determined by establishing the relationship between α and β and the surface velocity of the open channel. The dimensionless Schertz number Θ is related to the relationship between the velocity profiles obtained by numerical calculation of the four working conditions and the corresponding open channel surface velocity. The data is extracted; the corresponding dimensionless Schertz number θ is calculated using formula (6); then all velocity profiles are fitted using the power function form of formula (7) to obtain α and β for each velocity profile; the correlation between all data points α and β and the corresponding dimensionless Schertz number θ is found to obtain: β＝1.40 (5) In formula (6), g is the acceleration due to gravity.

5. The method according to claim 1, characterized in that: Step (1) Use a drone equipped with a laser radar or depth sounder to measure the open channel water depth H and riverbed gradient θ.

6. The method according to claim 1, characterized in that: Step (1) Obtain the basic physical parameters of open channel bedload sediment through geological survey or query of river network data.

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