A system and method for determining effective diffusivity at a water-sand interface

Abstract

The application discloses a system and method for measuring effective diffusion coefficient of water-sand interface, which comprises a transparent annular water tank, a rotatable power control device arranged in the center of the annular water tank, a plurality of connecting pieces arranged uniformly on the periphery of the rotatable power control device, a shear plate installed at the end of each connecting piece, a plurality of shear plates vertically placed along the radial direction of the annular water tank, the plurality of shear plates being uniformly distributed along the circumferential direction of the annular water tank, the rotatable power control device being connected with a computer through a data acquisition system, a PIV particle image velocimetry arranged outside the annular water tank and facing the overlying water layer in the annular water tank, and a sensor connecting device arranged on the annular water tank and connected with the computer. The application can simulate the hydraulic environment of a river under dynamic water conditions, and realizes continuous, dynamic and accurate measurement of the effective diffusion coefficient of the water-sand interface by combining online monitoring and automatic data analysis.

Description

Technical Field

[0001] This invention relates to the determination of the effective diffusion coefficient at the water-sand interface, and more specifically to a system and method for determining the effective diffusion coefficient at the water-sand interface. Background Technology

[0002] The water-sediment interface is the transition zone between surface water and bottom sediment, controlling the bidirectional migration and exchange of nutrients, heavy metals, organic pollutants, and other substances. Effective diffusion coefficient. The effective diffusion coefficient is a crucial parameter describing the migration rate of interfacial materials and plays a fundamental role in aquatic environment simulation, water quality prediction, pollutant fate analysis, and river ecological restoration design. Existing methods for determining the effective diffusion coefficient at the water-sediment interface mainly include still-water experiments and in-situ probe methods. Still-water experiments typically use transparent cylinders or reactors, calculating the diffusion coefficient under static conditions through tracer experiments and offline sampling analysis. This method is simple in setup but cannot reflect the influence of hydrodynamic shear on interfacial material migration under flowing water conditions, and the sampling and analysis process is prone to human error. In-situ probe methods can directly obtain the concentration gradient of pore water in sediments in actual water bodies, thereby calculating the effective diffusion coefficient. However, these methods involve expensive equipment, complex operation, limited measurement points, difficulty in generating continuous dynamic data, and insufficient stability under flowing water conditions.

[0003] In recent years, some studies have used open channels or circulating water tanks to simulate dynamic water conditions. However, such devices generally require the installation of return water and energy dissipation facilities, making the systems complex and prone to backflow hydraulic interference. At the same time, existing experiments often rely on manual sampling, lack real-time monitoring methods, and are difficult to synchronize with flow field parameters; in terms of data processing, empirical formulas are mostly used, failing to achieve coupled analysis of hydrodynamic and mass transport processes.

[0004] Therefore, existing technologies have the following shortcomings in determining the effective diffusion coefficient at the water-sand interface:

[0005] (1) There is a lack of controllable experimental platforms that can simulate the real hydrodynamic characteristics under dynamic water conditions;

[0006] (2) The measurement method relies on offline sampling, which has low spatiotemporal resolution and is prone to large errors;

[0007] (3) The data analysis methods are not perfect and it is difficult to fully reveal the influence of factors such as flow rate, porosity and particle size on the effective diffusion coefficient.

[0008] In summary, there is an urgent need for an experimental system and method that can simulate the hydraulic environment of a river under dynamic water conditions, and combine online monitoring and automated data analysis to achieve continuous, dynamic and accurate determination of the effective diffusion coefficient of the water-sediment interface. Summary of the Invention

[0009] Purpose of the invention: One objective of this invention is to provide a system and method for determining the effective diffusion coefficient of the water-sediment interface, which can simulate the hydraulic environment of a river under dynamic water conditions and combine online monitoring and automated data analysis to achieve continuous, dynamic and accurate determination of the effective diffusion coefficient of the water-sediment interface.

[0010] Technical Solution: The present invention provides a system for determining the effective diffusion coefficient of the water-sand interface, comprising a transparent annular water tank, with a liftable rotating power control device disposed in the center of the annular water tank; a plurality of connecting parts are evenly arranged around the outer periphery of the rotating power control device, each connecting part having a shear plate installed at its end, the shear plates being vertically inserted into the annular water tank along the radial direction, and the shear plates being evenly distributed along the circumference of the annular water tank; the rotating power control device is connected to a computer via a data acquisition system; a PIV particle image velocimeter is disposed outside the annular water tank, the PIV particle image velocimeter being directly facing the overlying water layer inside the annular water tank, used to acquire the velocity vector information of the overlying water layer flow field; a sensor connection device is disposed on the annular water tank, a concentration sensor is disposed on the sensor connection device, and the concentration sensor is connected to the computer.

[0011] Furthermore, when the bottom surface of the shear plates is below the liquid level in the annular water tank, after the rotary power control device is activated, the rotary power control device drives the shear plates to rotate synchronously in the annular water tank, so that the water in the annular water tank generates a stable flow in the circumferential direction, thereby simulating the flow conditions of an infinitely long straight tank.

[0012] Furthermore, a sedimentation tank is placed at the bottom of the annular water tank, and the sedimentation tank is filled with bottom mud. The thickness of the bottom mud layer can be controlled by replacing the sedimentation tank.

[0013] Furthermore, the flow rate of water in the annular water tank is controlled by controlling the lifting height and rotation speed of the rotary power control device.

[0014] Furthermore, the rotary power control device is driven by a variable frequency motor and regulated by a computer-controlled closed-loop speed regulation system to drive several shear plates to rotate synchronously at a constant angular velocity, thereby creating a water flow environment with constant shear stress within the annular water tank.

[0015] Furthermore, the PIV particle image velocimeter includes an emitting sheet light source and a high-speed camera. The PIV particle image velocimeter projects planar laser light into an annular water tank and continuously images the tracer particles to obtain the near-bottom flow velocity distribution and flow velocity profile.

[0016] Furthermore, the concentration sensor continuously monitors the solute concentration of the overlying water in the annular water tank in real time.

[0017] Based on the same inventive concept, the present invention provides a method for determining the effective diffusion coefficient of a water-sediment interface, applied to the aforementioned system for determining the effective diffusion coefficient of a water-sediment interface, the method comprising:

[0018] Substrate preparation: Fill the bottom of the annular water tank with the required thickness of substrate and remove air bubbles from the substrate; determine the volume of overlying water. water-sand interface area Prepare an inert tracer solution and record its molecular diffusion coefficient. ;

[0019] Hydrodynamic setting and flow velocity measurement: Activate the rotary dynamic control device and adjust it to achieve the set flow velocity for the annular water flow, maintaining a stable flow velocity; activate the PIV particle image velocimeter and measure the instantaneous flow velocity at a height z above the water-sand interface. The average velocity of the overlying water was obtained by averaging over time. Calculate the frictional velocity With shear stress ;

[0020] Tracer dosing and online data collection: In The prepared inert tracer solution is continuously and evenly added to the overlying water to bring the solute concentration in the overlying water to the preset initial solute concentration. Two-point or multi-point calibration is performed via sensor connection device to collect real-time solute concentration in the overlying water after the addition of inert tracer solution. And synchronized with the flow field data measured by the PIV particle image velocimeter;

[0021] Data processing and effective diffusion coefficient inversion: Computer above water cover volume water-sand interface area For geometric parameters, the average flow velocity of the overlying water is... Frictional flow velocity and shear stress As hydrodynamic input, the initial concentration of solutes in the overlying water and real-time concentration of overlying water solutes To obtain the observation data, a comprehensive analysis of the above parameters was performed. Based on the water mass conservation equation and the one-dimensional sediment diffusion model, and combined with Fick's law and interfacial mass transfer boundary conditions, the solute concentration-time curve was fitted to obtain the effective diffusion coefficient of the water-sediment interface in real time. .

[0022] Furthermore, the volume of water covering the computer. water-sand interface area For geometric parameters, the average flow velocity of the overlying water is... Frictional flow velocity and shear stress As hydrodynamic input, the initial concentration of solutes in the overlying water and real-time concentration of overlying water solutes To obtain the observation data, a comprehensive analysis of the above parameters was performed. Based on the water mass conservation equation and the one-dimensional sediment diffusion model, and combined with Fick's law and interfacial mass transfer boundary conditions, the solute concentration-time curve was fitted to obtain the effective diffusion coefficient of the water-sediment interface in real time. ,include:

[0023] Real-time concentration of solutes in overlying water Preliminary corrections and noise filtering were performed to remove outliers, resulting in a solute concentration-time series of the overlying water, forming a joint dataset for different time periods. ;

[0024] Calculate the cumulative mass of solute entering the sediment:

[0025] ;

[0026] in, This represents the cumulative mass of solute entering the sediment. Mass transferred per unit area; The volume of the overlying water; The water-sand interface area;

[0027] When the semi-infinite sediment approximation is satisfied in the early stage of diffusion, the following is adopted: Analytical method for estimating the effective diffusion coefficient at the water-sediment interface :

[0028] ;

[0029] Depend on The effective diffusion coefficient in the initial stage of diffusion was obtained by linear fitting. , and used as initial values ​​for subsequent numerical inversion;

[0030] Establish a one-dimensional diffusion control equation:

[0031]

[0032] in, The porosity of the sediment; This refers to the solute concentration in the sediment. This refers to the depth of the bottom sediment.

[0033] Establish the overlying water balance equation:

[0034] ;

[0035] in, This refers to the concentration of solutes in the overlying water. The volume of the overlying water; The water-sand interface area; For interface flux;

[0036] Computational Interface Flux :

[0037] ;

[0038] in, The effective diffusion coefficient after flow velocity correction; and These are the real-time solute concentrations in the overlying water and the sediment; To match the frictional flow velocity u * The relevant mass transfer coefficient can be calculated using the following formula:

[0039]

[0040] in, The molecular diffusion coefficient; The characteristic length; This refers to the concentration of solutes in the overlying water. Kinematic viscosity; and These are all empirical parameters;

[0041] Establish empirical power-law relationships:

[0042]

[0043] in, The equivalent diffusion coefficient for still water; The parameters to be calibrated are then used; finally, numerical solutions and parameter inversion are performed.

[0044] Furthermore, the specific process of numerical solution and parameter inversion is as follows:

[0045] The coupled equations are discretized using the finite difference / finite volume method, with each time period as input. The simulated curve is obtained by solving. ;

[0046] Combined with simulation curves The effective diffusion coefficient of the water-sediment interface was obtained by inversion using the least squares method. The objective function is established as follows:

[0047] ;

[0048] in, To measure the solute concentration in the overlying water; This is a simulated concentration value;

[0049] Through the minimum objective function To obtain the optimal effective diffusion coefficient that minimizes the deviation between the simulation results and the measured data. ;

[0050] The computer system automatically outputs the fitting residuals and correlation coefficients during the inversion process. The root mean square error is used to evaluate the model fit quality and is calculated through covariance analysis. The confidence interval;

[0051] Finally, the effective diffusion coefficient at the water-sand interface is output. The time series and average values ​​are obtained, and a results report is generated, including numerical corrections, fitting residuals, and confidence intervals.

[0052] Beneficial effects: Compared with the prior art, the significant technical effects of the present invention are as follows:

[0053] (1) More realistic experimental conditions: By establishing a continuous and stable flow through an annular water tank, the boundary effects generated by the static water experiment and the straight tube tank are avoided, which is closer to the natural river conditions.

[0054] (2) More advanced measurement method: It adopts online sensors and flow field measurement, which can collect data on solute concentration and flow velocity of the overlying water in real time, eliminating the need for frequent manual sampling and reducing human error;

[0055] (3) The calculation method is more accurate: the inversion algorithm is used to process the data of the whole time period, which is more comprehensive and reliable than the traditional empirical formula. It can not only obtain a fixed optimal effective diffusion coefficient, but also reveal the variation law of diffusion coefficient under different flow velocities and different sediment conditions.

[0056] (4) Wide range of applications: It can be used for research on pollutant migration in rivers, lakes and other water bodies, environmental risk assessment and water conservancy engineering design, and has good prospects for promotion. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the structure of a system for measuring the effective diffusion coefficient of the water-sand interface according to the present invention;

[0058] Figure 2 This is a top view of the annular water tank in this invention;

[0059] Figure 3 This is a schematic diagram of the flow at the water-sand interface in this invention. Detailed Implementation

[0060] The technical solution of the present invention will now be described in detail with reference to specific embodiments and accompanying drawings.

[0061] Example 1

[0062] like Figures 1-3 As shown, a system for determining the effective diffusion coefficient of the water-sand interface according to the present invention includes a transparent annular water tank. The annular water tank is composed of an inner cylinder 1 and an outer cylinder 2 arranged concentrically, and a bottom plate 10 connecting the inner cylinder 1 and the outer cylinder 2, thereby forming a closed annular channel. In this embodiment, the inner radius of the annular channel is 0.8 m, the width of the channel is 0.3 m, and the effective water depth is 0.5 m. Both the inner cylinder 1 and the outer cylinder 2 are made of plexiglass. The inner and outer walls of the annular water tank are transparent to facilitate PIV imaging. A sediment tank is placed at the bottom of the annular water tank, and the sediment tank is filled with bottom sediment. The thickness of the bottom sediment layer is controlled by changing the sediment tank, and the thickness range of the bottom sediment layer is [missing information]. A height-adjustable rotary power control device 5 is installed in the center of the annular water tank. In this embodiment, an automatic lifting rod 4 is installed on the bottom surface of the rotary power control device 5 to adjust its height. The rotary power control device 5 is used for closed-loop setting and stabilizing the average flow velocity in the water tank. The data acquisition system 8 includes a multi-channel acquisition card, a signal processing module, and a communication interface, used to convert the control signals issued by the computer into frequency signals and feed them back to the rotary power control device 5 to achieve closed-loop speed regulation. The rotary power control device 5 is connected to the computer 9 through the data acquisition system 8 to achieve speed setting. A PIV particle image velocimeter 6 is installed outside the annular water tank, facing the overlying water layer in the annular water tank, to acquire the velocity vector information of the overlying water layer flow field. A sensor connection device 7 is installed on the annular water tank. The sensor connection device 7 includes a base, a sealed connecting pipe, and a waterproof cable connector, on which a concentration sensor is installed and fixed. The sensor connection device 7 is connected to the computer 9 to achieve continuous real-time monitoring of the solute concentration in the overlying water in the annular water tank, with a sampling frequency of not less than 1 Hz. In this embodiment, the PIV particle image velocimeter 6 includes an emission sheet light source and a high-speed camera. The PIV particle image velocimeter 6 projects planar laser light into the annular water tank and continuously images the tracer particles, resolving the near-bottom velocity distribution and velocity profile to provide a basis for interfacial shear flow field analysis. The sensor connection device 7 is used to install and fix the concentration sensor, enabling continuous real-time monitoring of the solute concentration in the overlying water within the annular water tank, with a sampling frequency... This reflects the dynamic characteristics of solute concentration changes over time near the water-sediment interface. The data acquisition and analysis unit includes a data acquisition system 8 and a computer 9. The data acquisition system 8 performs multi-channel synchronous acquisition, signal conditioning, and preprocessing. The computer 9 is used for experimental parameter inversion and result uncertainty assessment, and has built-in control software and algorithm modules to achieve comprehensive control and data analysis of the entire experimental system.

[0063] like Figure 1 and Figure 2As shown, a plurality of connecting members are evenly arranged around the outer periphery of the rotary power control device 5. A shearing plate 3 is installed at the end of each connecting member. The plurality of shearing plates 3 are vertically placed into the annular water tank along the radial direction, and are evenly distributed along the circumference of the annular water tank. In this embodiment, there are 8 shearing plates 3, evenly distributed along the circumference of the annular water tank.

[0064] When the bottom surfaces of several shear plates 3 are below the liquid surface in the annular water tank, the rotary power control device 5 is activated. The device drives the shear plates 3 to rotate synchronously within the annular water tank, causing a stable flow of water along the circumference. This simulates the flow conditions of an infinitely long straight tank, establishing a stable velocity field without the need for backflow or energy dissipation. Precise control of the flow velocity within the annular water tank can be achieved by adjusting the lifting height and rotation speed of the rotary power control device 5. The rotary power control device 5 is driven by a variable frequency motor and regulated by a computer-controlled closed-loop speed regulation system to drive the shear plates 3 to rotate synchronously at a constant angular velocity, thereby creating a constant shear stress water flow environment within the annular water tank.

[0065] This invention overcomes the problems of cumbersome sampling processes, large measurement errors, and inability to achieve real-time continuous monitoring in existing technologies. This system can efficiently and accurately obtain the effective diffusion coefficient of the water-sediment interface under controllable hydrodynamic conditions, making it suitable for fields such as pollutant migration research and environmental risk assessment, and has broad application prospects.

[0066] Example 2

[0067] The present invention provides a method for determining the effective diffusion coefficient of the water-sediment interface, applied to the system for determining the effective diffusion coefficient of the water-sediment interface described in Example 1. The method includes the following steps:

[0068] S1. Sediment Preparation: First, fill the sediment tank at the bottom of the annular flume to the required thickness. The sediment was collected and saturated with pore water by agitation or vacuuming to remove air bubbles; then, the volume of overlying water was determined. water-sand interface area Finally, prepare an inert tracer solution (such as NaCl or Rhodamine WT) and record the molecular diffusion coefficient of the inert tracer solution. .

[0069] S2. Hydrodynamic Setting and Flow Velocity Measurement: First, start the rotary power control device 5 and adjust the speed of the variable frequency motor in the rotary power control device 5 so that the annular water flow can reach the set flow velocity, maintain stable shear flow, and keep the flow velocity stable; then start the PIV particle image velocimeter 6, at a height of [missing information - likely a distance in meters] above the water-sand interface. Instantaneous flow velocity measured at the location (Agreement) (For the interface, upward is positive), and the average velocity of the overlying water is obtained by averaging over time. Determine the frictional velocity from the bottom profile. With shear stress :

[0070]

[0071] in, Density of water; This refers to kinematic viscosity.

[0072] S3. Tracer Dosing and Online Data Acquisition: First, in The prepared inert tracer solution is continuously and evenly added to the overlying water to bring the solute concentration in the overlying water to the preset initial solute concentration. Then, two-point or multi-point calibration is performed via sensor connection device 7 to collect real-time solute concentration in the overlying water after the addition of inert tracer solution. The flow velocity data was synchronized with that measured by the PIV particle image velocimeter 6; finally, a constant flow velocity was maintained or a flow velocity variation process was set according to experimental requirements to study the effect of flow velocity variation on the flow field. Dynamic response.

[0073] S4. Data Processing and Effective Diffusion Coefficient Inversion: Computer 9 uses the overlying water volume determined in step S1. water-sand interface area The geometric parameters are the average velocity of the overlying water measured in step S2. Frictional flow velocity and shear stress As the hydrodynamic input, the initial concentration of solutes in the overlying water is collected in real time in step S3. and real-time concentration of overlying water solutes To obtain the observation data, a comprehensive analysis of the above parameters was performed. Based on the water mass conservation equation and the one-dimensional sediment diffusion model, and combined with Fick's law and interfacial mass transfer boundary conditions, the solute concentration-time curve was fitted to obtain the effective diffusion coefficient of the water-sediment interface in real time. .

[0074] The specific implementation process of step S4 is as follows:

[0075] S4.1, Real-time concentration of solutes in overlying water Preliminary corrections and noise filtering were performed to remove outliers, resulting in a solute concentration-time series of the overlying water, forming a joint dataset for different time periods. ;

[0076] S4.2 Calculate the cumulative mass of solute entering the sediment:

[0077] ;

[0078] in, This represents the cumulative mass of solute entering the sediment. Mass transferred per unit area; The volume of the overlying water; The water-sand interface area;

[0079] S4.3, Early Analytical Solution Verification:

[0080] When the semi-infinite sediment approximation is satisfied in the early stage of diffusion, the following is adopted: Analytical method for estimating the effective diffusion coefficient at the water-sediment interface :

[0081] ;

[0082] Depend on The effective diffusion coefficient in the initial stage of diffusion was obtained by linear fitting. , and used as initial values ​​for subsequent numerical inversion;

[0083] S4.4 Establish the one-dimensional diffusion control equation:

[0084] Sediment side:

[0085]

[0086] in, The porosity of the sediment; This refers to the solute concentration in the sediment. This refers to the depth of the bottom sediment.

[0087] Establish the overlying water balance equation:

[0088] ;

[0089] in, This refers to the concentration of solutes in the overlying water. The volume of the overlying water; The water-sand interface area; For interface throughput.

[0090] Computational Interface Flux :

[0091]

[0092] in, The effective diffusion coefficient after flow velocity correction; and These are the real-time solute concentrations in the overlying water and the sediment; To match the frictional flow velocity The relevant mass transfer coefficient can be calculated using the following formula:

[0093]

[0094] in, is the molecular diffusion coefficient, which is recorded in step S1; The characteristic length; This refers to the concentration of solutes in the overlying water. Kinematic viscosity; and These are all empirical parameters, and in this example, we take... and .

[0095] Establish empirical power-law relationships:

[0096]

[0097] in, The effective diffusion coefficient for still water is generally taken as... ; These are the parameters to be calibrated.

[0098] S4.5 Numerical Solution and Parameter Inversion: The coupled equations above are discretized using the finite difference / finite volume method, and the input for each time period is... The simulated curve is obtained by solving. .

[0099] Combined with simulation curves The effective diffusion coefficient of the water-sediment interface was obtained by inversion using the least squares method. The objective function is established as follows:

[0100]

[0101] in, To measure the solute concentration in the overlying water; These are simulated concentration values.

[0102] Through the minimum objective function To obtain the optimal effective diffusion coefficient that minimizes the deviation between the simulation results and the measured data. .

[0103] The computer system automatically outputs the fitting residuals and correlation coefficients during the inversion process. Statistical indicators such as root mean square error (RMSE) are used to evaluate the model fit quality, and covariance analysis is used to calculate... The confidence interval.

[0104] Finally, the effective diffusion coefficient at the water-sand interface is output. The time series and average values ​​are obtained, and a results report is generated, including numerical corrections, fitting residuals, and confidence intervals.

[0105] Using the aforementioned system and method, concentration and flow field information can be acquired in real time under dynamic water conditions, and the effective diffusion coefficient can be retrieved using a mechanistic model. This scheme overcomes the problems of static water experiments failing to reflect shear effects, large offline sampling errors, and significant device boundary effects, resulting in a higher effective diffusion coefficient. It has high accuracy and good repeatability, and is suitable for river pollutant migration research, environmental risk assessment and engineering design parameter calibration.

[0106] This invention enables the control of water under dynamic conditions. This system enables continuous, dynamic, and high-precision measurements, avoiding the time lag and errors associated with traditional static water sampling and offline analysis. It boasts advantages such as modular structure, controllable parameters, and repeatable results, and can reveal the effects of factors like flow velocity, porosity, and particle size on... The mechanism of action is applicable to studies on river pollutant migration, environmental risk assessment, and calibration of engineering design parameters.

Claims

1. A method for determining the effective diffusion coefficient at the water-sand interface, characterized in that, This method is applied to a system for determining the effective diffusion coefficient of the water-sand interface, the system comprising a transparent annular water tank, wherein a liftable rotary power control device (5) is provided in the center of the annular water tank. The rotational power control device (5) has several connectors evenly arranged on its outer periphery. Each connector has a shearing plate (3) installed at its end. The shearing plates (3) are vertically placed into the annular water tank along the radial direction of the annular water tank. The shearing plates (3) are evenly distributed along the circumference of the annular water tank. The rotary power control device (5) is connected to the computer (9) through the data acquisition system (8); A PIV particle image velocimeter (6) is installed outside the annular water tank. The PIV particle image velocimeter (6) is facing the overlying water layer inside the annular water tank and is used to obtain the velocity vector information of the flow field of the overlying water layer. A sensor connection device (7) is installed on the annular water tank, and a concentration sensor is installed on the sensor connection device (7). The concentration sensor is connected to a computer (9). The method includes: Substrate preparation: Fill the bottom of the annular water tank with the required thickness of substrate and remove air bubbles from the substrate; determine the volume of overlying water. water-sand interface area Prepare an inert tracer solution and record its molecular diffusion coefficient. ; Hydrodynamic setting and flow velocity measurement: Start the rotary power control device (5) and adjust the rotary power control device (5) to make the annular water flow reach the set flow velocity and keep the flow velocity stable; start the PIV particle image velocimeter (6) and measure the flow velocity at a height of [missing information] above the water-sand interface. Instantaneous flow velocity measured at the location The average velocity of the overlying water was obtained by averaging over time. Calculate the frictional velocity With shear stress ; Tracer dosing and online data collection: In The prepared inert tracer solution is continuously and evenly added to the overlying water to bring the solute concentration in the overlying water to the preset initial solute concentration. ; Two-point or multi-point calibration is performed through the sensor connection device (7), and the real-time concentration of solute in the overlying water after the addition of inert tracer solution is collected. And synchronized with the flow field data measured by the PIV particle image velocimeter (6); Data processing and effective diffusion coefficient inversion: Computer (9) above water cover volume water-sand interface area For geometric parameters, the average flow velocity of the overlying water is... Frictional flow velocity and shear stress As hydrodynamic input, the initial concentration of solutes in the overlying water and real-time concentration of overlying water solutes To obtain the observation data, a comprehensive analysis of the above parameters was performed. Based on the water mass conservation equation and the one-dimensional sediment diffusion model, and combined with Fick's law and interfacial mass transfer boundary conditions, the solute concentration-time curve was fitted to obtain the effective diffusion coefficient of the water-sediment interface in real time. ,include: Real-time concentration of solutes in overlying water Preliminary corrections and noise filtering were performed to remove outliers, resulting in a solute concentration-time series of the overlying water, forming a joint dataset for different time periods. ; Calculate the cumulative mass of solute entering the sediment: ； in, This represents the cumulative mass of solute entering the sediment. Mass transferred per unit area; This refers to the volume of the overlying water. The water-sand interface area; When the semi-infinite sediment approximation is satisfied in the early stage of diffusion, the following is adopted: Analytical method for estimating the effective diffusion coefficient at the water-sediment interface : ； Depend on The effective diffusion coefficient in the initial stage of diffusion was obtained by linear fitting. , and used as initial values ​​for subsequent numerical inversion; Establish a one-dimensional diffusion control equation: ； in, The porosity of the sediment; This refers to the solute concentration in the sediment. This refers to the depth of the bottom sediment. Establish the overlying water balance equation: ； in, This refers to the concentration of solutes in the overlying water. This refers to the volume of the overlying water. The water-sand interface area; For interface flux; Computational Interface Flux : ； in, The effective diffusion coefficient after flow velocity correction; and These are the real-time solute concentrations in the overlying water and the sediment; To match the frictional flow velocity The relevant mass transfer coefficient can be calculated using the following formula: ； in, The molecular diffusion coefficient; The characteristic length; This refers to the concentration of solutes in the overlying water. Kinematic viscosity; and These are all empirical parameters; Establish empirical power-law relationships: ； in, The equivalent diffusion coefficient for still water; The parameters to be calibrated are then used; finally, numerical solutions and parameter inversion are performed.

2. The method for determining the effective diffusion coefficient at the water-sand interface according to claim 1, characterized in that: When the bottom surface of the shear plates (3) is below the liquid surface in the annular water tank, the rotary power control device (5) is started. The rotary power control device (5) drives the shear plates (3) to rotate synchronously in the annular water tank, so that the water in the annular water tank generates a stable flow in the circumferential direction, thereby simulating the flow conditions of an infinitely long straight channel.

3. The method for determining the effective diffusion coefficient at the water-sand interface according to claim 1, characterized in that: A sedimentation tank is placed at the bottom of the annular water tank, and the sedimentation tank is filled with bottom mud. The thickness of the bottom mud layer is controlled by replacing the sedimentation tank.

4. The method for determining the effective diffusion coefficient at the water-sand interface according to claim 1, characterized in that: The flow rate of water in the annular water tank is controlled by controlling the lifting height and rotation speed of the rotary power control device (5).

5. The method for determining the effective diffusion coefficient at the water-sand interface according to claim 1, characterized in that: The rotary power control device (5) is driven by a variable frequency motor and regulated by a closed-loop speed regulation system controlled by a computer (9) to drive several shear plates (3) to rotate synchronously at a constant angular velocity, thereby creating a water flow environment with constant shear stress in the annular water tank.

6. The method for determining the effective diffusion coefficient at the water-sand interface according to claim 1, characterized in that: The PIV particle image velocimeter (6) includes an emission sheet light source and a high-speed camera. The PIV particle image velocimeter (6) projects planar laser sheet light into an annular water tank and performs continuous imaging of tracer particles to obtain the near-bottom flow velocity distribution and flow velocity profile.

7. The method for determining the effective diffusion coefficient at the water-sand interface according to claim 1, characterized in that: The concentration sensor continuously monitors the solute concentration of the overlying water in the annular water tank in real time.

8. The method for determining the effective diffusion coefficient at the water-sand interface according to claim 1, characterized in that, The specific process of numerical solution and parameter inversion is as follows: The coupled equations are discretized using the finite difference / finite volume method, with each time period as input. The simulated curve is obtained by solving. ; Combined with simulation curves The effective diffusion coefficient of the water-sediment interface was obtained by inversion using the least squares method. The objective function is established as follows: ； in, To measure the solute concentration in the overlying water; This is a simulated concentration value; Through the minimum objective function To obtain the optimal effective diffusion coefficient that minimizes the deviation between the simulation results and the measured data. ; The computer (9) automatically outputs the fitting residuals and correlation coefficients during the inversion process. The root mean square error is used to evaluate the model fit quality and is calculated through covariance analysis. The confidence interval; Finally, the effective diffusion coefficient at the water-sand interface is output. The time series and average values ​​are obtained, and a results report is generated, including numerical corrections, fitting residuals, and confidence intervals.

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