Prediction method, system and equipment for water level change rate in butt joint process of ship reception chambers of final-stage ship lift and medium

Abstract

The invention belongs to the technical field of navigation building water level prediction, and discloses a water level change rate prediction method, system, equipment and medium in the docking process of ship reception chambers of a last-stage ship lift, and the method comprises the following steps: obtaining basic data of a research water area, and constructing a model boundary condition based on the basic data; on the basis of the constructed model boundary conditions, a one-dimensional Saint-Venant equation and a two-dimensional shallow water motion equation are combined to construct a multi-dimensional coupling hydrodynamic model; and performing discrete solution on the multi-dimensional coupling hydrodynamic model based on a finite volume method to obtain water level variation rate data of different minute levels at the joint position of the ship reception chamber of the final-stage ship lift and the downstream approach channel under the conditions of given flow and water level boundary. The method can accurately and quickly simulate and predict the water level change rate in the docking process of the ship reception chamber of the last-stage ship lift, so that a scientific basis is provided for accurately determining the navigation stopping time period of the ship lift, and the loss caused by long-time navigation stopping of the ship lift is reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of water level prediction of navigation buildings, and in particular relates to a method, system, equipment and medium for predicting water level variation rate during docking of a last-stage ship lift carrier. Background Art

[0002] Affected by the tailwater of the hydropower hub power generation regulation and the non-constant water discharge of the hub dispatch, the ship lift compartment (only the last-stage ship lift is connected to the multi-stage ship lift) that is frequently connected to the lower pilot channel will face the risk of uncontrolled collision and bottoming out due to the short-term fluctuation of the water level in the pilot channel, which will threaten the operation of the ship lift and the safety of ship navigation. At present, in the actual operation of the ship lift, the management arranges irregular suspension of navigation according to the power generation dispatch of the power plant or the hub water discharge plan received in advance, and the decision on the suspension period is mainly determined by the management personnel based on experience and lacks scientific basis. Irregular suspension of navigation will affect the efficiency of the ship lift and is not conducive to the improvement of the hub's throughput capacity. In particular, with the increase in the traffic flow of ships passing through the lift, the problem of the docking of the water level of the last-stage ship lift compartment affecting the efficiency of ship passing will become more and more prominent, and may even become a bottleneck restricting the hub's throughput capacity. Therefore, in order to solve the problem of rapid water level changes and the need for accurate prediction when the last-stage ship lift docks due to dynamic flow regulation during flood control and power generation in cascade reservoirs, it is urgent to develop more advanced and accurate technical means to achieve real-time monitoring and accurate prediction of water level fluctuations. Summary of the invention

[0003] The purpose of the present invention is to provide a method, system, equipment and medium for predicting the water level variation rate during the docking process of the last-stage ship lift cabin, so as to solve the problems existing in the above-mentioned prior art.

[0004] To achieve the above object, the present invention provides a method for predicting the water level variation rate during the docking process of the last-stage ship lift carrier, comprising:

[0005] Obtain basic data of the research waters, including upstream hub power generation regulation or flood control dispatch data, river topography data, downstream reservoir operation data and hydrological observation data;

[0006] Building model boundary conditions based on the basic data;

[0007] Based on the constructed model boundary conditions, a multi-dimensional coupled hydrodynamic model is constructed by combining the one-dimensional Saint-Venant equation and the two-dimensional shallow water motion equation;

[0008] The multi-dimensional coupled hydrodynamic model is discretely solved based on the finite volume method to obtain the water level variation data of different minute levels at the intersection of the last-stage ship lift compartment and the downstream pilot channel under given flow and water level boundary conditions.

[0009] Optionally, the downstream reservoir operation data includes data such as reservoir type, dam height, reservoir operation characteristic water level and corresponding storage capacity.

[0010] Optionally, before constructing the model boundary conditions based on the basic data, the basic data is further processed to remove outliers and interpolate missing values ​​to obtain preprocessed basic data, and the model boundary conditions are constructed based on the preprocessed basic data.

[0011] Optionally, the process of constructing the model boundary conditions specifically includes:

[0012] The upstream hub power generation regulation or flood control dispatch discharge data is used as the inflow boundary;

[0013] Based on the downstream reservoir operation data, the reservoir capacity under different characteristic water levels is calculated according to the cross-section method, the calculated data is curve-fitted to obtain a reservoir capacity curve, and the reservoir capacity curve is used as the outflow boundary;

[0014] The inflow boundary and the outflow boundary are used as boundary conditions of the model.

[0015] Optionally, based on the constructed model boundary conditions, a multi-dimensional coupled hydrodynamic model is constructed by combining the one-dimensional Saint-Venant equation and the two-dimensional shallow water motion equation, including:

[0016] A one-dimensional hydrodynamic model for describing the water flow movement in the long river section below the hub dam is constructed based on the one-dimensional Saint-Venant equation;

[0017] Based on the two-dimensional shallow water motion equation, a two-dimensional hydrodynamic model is constructed to describe the water flow motion under the complex structures and terrain in the hub dam area;

[0018] The one-dimensional hydrodynamic model and the two-dimensional hydrodynamic model are coupled, and the multi-dimensional coupled hydrodynamic model is obtained by setting the model boundary conditions.

[0019] A prediction system for water level variation rate during docking of a last-stage ship lift carrier, comprising:

[0020] A data acquisition module is used to obtain basic data of the research waters, including upstream hub power generation regulation or flood control dispatch data, river topography data, downstream reservoir operation data and hydrological observation data;

[0021] A model building module is used to build model boundary conditions according to the basic data; based on the built model boundary conditions, a multi-dimensional coupled hydrodynamic model is built in combination with the one-dimensional Saint-Venant equation and the two-dimensional shallow water motion equation;

[0022] The model solving module is used to discretely solve the multi-dimensional coupled hydrodynamic model according to the finite volume method to obtain the water level variation data of different minute levels at the intersection of the last-stage ship lift cabin and the downstream pilot channel under given flow and water level boundary conditions.

[0023] An electronic device comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program so that the electronic device executes a method for predicting water level variation rate during docking of a last-stage ship lift cabin.

[0024] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements a method for predicting the water level variation rate during docking of a last-stage ship lift ship compartment.

[0025] The technical effects of the present invention are:

[0026] The present invention obtains the discharge data of hydropower station power generation regulation or flood control scheduling and reservoir operation related data, and uses a one- and two-dimensional coupled hydrodynamic model to achieve real-time and quantitative simulation and prediction of the water level variation rate in the downstream navigation channel of the ship lift, providing scientific decision-making support for the safe and efficient operation of ships entering and exiting the ship lift at the cascade hub. The method can accurately and quickly simulate and predict the water level variation rate during the docking process of the last-stage ship lift, thereby providing a scientific basis for accurately determining the suspension period and minimizing the loss of the ship lift caused by the long-term suspension of the ship lift. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0029] Figure 1 Schematic diagram of a water level-storage capacity curve in an embodiment of the present invention;

[0030] Figure 2 This is a schematic diagram of a typical day's downstream flow regulation process of the Wujiang Silin Power Station in an embodiment of the present invention;

[0031] Figure 3 It is a schematic diagram of the 10-minute water level variation process at the intersection of the ship lift cabin and the downstream pilot channel under the influence of the regulation of the Wujiang Silin Power Station in an embodiment of the present invention;

[0032] Figure 4 It is a schematic diagram of discretizing a river network in a watershed in an embodiment of the present invention;

[0033] Figure 5 This is a prediction flow chart in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as limiting the present invention, but should be understood as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0035] It should be understood that the terms described in the present invention are only for describing special embodiments and are not intended to limit the present invention. In addition, for the numerical range in the present invention, it should be understood that each intermediate value between the upper and lower limits of the scope is also specifically disclosed. Each smaller range between the intermediate value in any stated value or stated range and any other stated value or intermediate value in the described range is also included in the present invention. The upper and lower limits of these smaller ranges can be independently included or excluded in the scope.

[0036] Unless otherwise indicated, all technical and scientific terms used herein have the same meanings as those of ordinary skill in the art generally understood by the present invention. Although the present invention describes only preferred methods, any method similar or equivalent to that described herein may also be used in the implementation or testing of the present invention. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods related to the documents. In the event of a conflict with any incorporated document, the content of this specification shall prevail.

[0037] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments of the present invention description without departing from the scope or spirit of the present invention. Other embodiments derived from the present invention description will be apparent to those skilled in the art. The present application description and examples are exemplary only.

[0038] The words “include,” “including,” “have,” “contain,” etc. used in this article are open-ended terms, meaning including but not limited to.

[0039] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0040] Embodiment 1

[0041] like Figure 1 - Figure 5As shown, in this embodiment, a method for predicting the water level variation rate during the docking process of the last-stage ship lift carriage is provided, comprising: obtaining basic data of the study water area, the basic data including upstream hub power generation regulation or flood control scheduling data, river topography data, downstream reservoir operation data and hydrological observation data; constructing model boundary conditions based on the basic data; based on the constructed model boundary conditions, a multidimensional coupled hydrodynamic model is constructed in combination with the one-dimensional Saint-Venant equation and the two-dimensional shallow water motion equation; based on the finite volume method, the multidimensional coupled hydrodynamic model is discretely solved to obtain water level variation rate data at different minute levels at the intersection of the last-stage ship lift carriage and the downstream pilot channel under given flow and water level boundary conditions.

[0042] This embodiment is based on the discharge flow process of the upstream cascade hydropower station and the water level operation process on the downstream cascade reservoir dam under different hydropower station generator unit output plans and flood control scheduling operation modes. It uses a one- and two-dimensional coupled hydrodynamic model to achieve real-time and quantitative simulation and prediction of the water level variability in the downstream navigation channel of the ship lift, providing scientific decision-making support for the safe and efficient operation of ships entering and exiting the ship lift at the cascade hub. This method can accurately and quickly simulate and predict the water level variability during the docking process of the last-stage ship lift, thereby providing a scientific basis for accurately determining the suspension period and minimizing the loss of the ship lift caused by the long-term suspension of the ship lift. The specific steps of this embodiment include:

[0043] (1) Obtain the downstream reservoir operation data including reservoir type, dam height, reservoir operation characteristic water level and corresponding storage capacity, calculate the reservoir storage capacity under the characteristic water level using the cross-section method, select the exponential function model to fit the reservoir storage capacity curve through different characteristic water levels and their storage capacity data samples, and determine the storage capacity curve of the downstream reservoir;

[0044] (2) Based on the one-dimensional Saint-Venant equation and the two-dimensional shallow water motion equation, a one- and two-dimensional coupled hydrodynamic mathematical model is established. The non-constant water discharge process of power generation regulation or hub dispatching known in advance from the power generation enterprise is used as the inflow boundary, and the water level-discharge relationship of the downstream hydrological section or the reservoir storage capacity curve is used as the outflow boundary. The water level fluctuation in the approach channel caused by the non-constant inflow and the downstream water level support is simulated and predicted.

[0045] (3) Theoretically, the mathematical model can output the water level change rate of each calculation step, and the calculation step length of the mathematical model is usually in the second level. The model can output water level change rate results at different minute levels, which can meet the water level change rate requirements of ships entering and leaving the docking compartment during different ship lift water level docking processes;

[0046] (4) The mathematical model adopts a one-two-dimensional coupled mathematical model that combines a local two-dimensional plane model with a one-dimensional model of a long river section. The model is simple and complex enough to ensure that the solution is real-time and efficient.

[0047] For the river hydrodynamic model, the reservoir can be generalized as a node or unit. The changes in the inflow, outflow and water level of the reservoir satisfy the water balance equation, that is, the law of conservation of mass.

[0048]

[0049] Where V r (z),q i (t),q o (z) are the reservoir capacity, the time course of the inflow, and the reservoir discharge, respectively.

[0050] The storage capacity satisfies the water level-storage capacity curve, such as Figure 1 As shown in Figure 1, the discharge flow is generally determined by the reservoir water level-discharge flow curve based on the discharge structure and the gate opening. When the reservoir problem is considered alone, equation (1) is the reservoir flood control equation. When the reservoir is an upstream node of the river network in the basin, the time course of the inflow needs to be given based on the hydrological model or measured data. When the reservoir is a midstream or downstream node of the river network in the basin, the inflow needs to be coupled with the river network model for calculation.

[0051] Flow control equations: The control equations describing fluid motion are the Navier-Stokes equations (NS equations), which are established based on the laws of conservation of mass and momentum in physics. The corresponding flow control equations are called the mass conservation equation (continuity equation) and the momentum conservation equation. To simplify the scale of the problem, the NS equations can be averaged in the cross section along the flow direction and in the depth direction, and the one-dimensional Saint-Venante equations and the two-dimensional shallow water equations can be obtained respectively.

[0052] Among them, the one-dimensional basic equation describing the movement of river water is the Saint-Venant equation, which includes:

[0053] Mass equation:

[0054] Equations of motion:

[0055] In the above formula, A is the cross-sectional area of ​​the river, Q is the cross-sectional flow volume, q is the uniform side inflow, Qc is the concentrated side inflow, δ is Diracδ, z is the water level, K is the flow modulus, and it is calculated by Xie Cai's formula.

[0056] For the movement of water bodies in open waters where the horizontal scale is much larger than the vertical scale, the two-dimensional shallow water equation can be used to describe it, specifically:

[0057] Continuity equation:

[0058]

[0059] Equations of motion:

[0060]

[0061] In the above equation, H is the water depth, u and v are the vertical average flow velocities, x, y and t are the plane coordinates and time. C and ν are the Scheherazade coefficient and the eddy viscosity coefficient; f is the Coriolis force coefficient. Water level function It can be determined by the water depth H(x, y, t) and the riverbed elevation h(x, y).

[0062] Model discretization and solution: In order to facilitate the processing of complex river network problems, the finite element method is used to discretize the river network in the basin. The basin is divided into river section units, reservoir units, sluice weir units and river branch units. The intersection of units is the node, and the variables such as water level and flow to be solved are defined on the node.

[0063] Discrete solution of one-dimensional Saint-Venant equation: Taking the river channel as an example, Figure 4 As shown in the figure, the solution domain is divided into several finite elements for the continuity equation. Suppose two adjacent river channel elements E i 、E j , E i The two nodes are N m 、N k , E j The two nodes are N k 、N n , N k A shared node.

[0064] The continuity equation is in N k The unit interpolation function is obtained by discretizing the finite volume at N j , then the water head H and saturation c of the unit node piezometer can be expressed as:

[0065]

[0066] Where Δt is the time step, Δs i ,Δs i For river section E i , E j The length, Q i ,Q j To pass through river section E i , E j The flow rate can be calculated by using some interpolation format from the node flow Q k ,Q n If the central interpolation method is used, then

[0067] Q i =0.5(Q m +Qk ),Q j =0.5(Q k +Q n )(9)

[0068] The equation of motion is expressed in N k Discretize it by finite volume, and we get:

[0069]

[0070] Where u is the average velocity, fz is the driving force for calculating the average gradient of the upstream and downstream, and α is the friction coefficient after linearization. Momentum flux (uQ) i ,(uQ) j Multiple interpolation formats can be used for calculation, such as central interpolation, upwind format, Quick format, Smart format, etc. When the upwind format is used,

[0071]

[0072] make

[0073] Q=(1-θ)Q n +θQ n+1 (13)

[0074] z n+1 =(z n+1 )'+δη(14)

[0075] A n+1 =(A n+1 )'+δA=(A n+1 )'+Bδη(15)

[0076] Where θ is the time weight coefficient, 0≤θ≤1, (z n+1 )',δη are the iterative water level and water level correction respectively, (A n +1 )', B are the iteration area and river width respectively, after simplification, we get:

[0077] aδη m +bδη k +cδη n =d(16)

[0078]

[0079] b=B k -(a+c)

[0080]

[0081] In this way, a tridiagonal coefficient matrix for solving δη is constructed at the river node, because Therefore, |b|>|a|+|c|, which can ensure diagonal dominance, and the Gauss-Seidel iteration or pursuit method can be used to solve δη.

[0082] Discrete solution of two-dimensional shallow water equations: The finite volume method (FVM) is a type of numerical method that directly discretizes the integral conservation form of the control equation on the control volume selected in the physical space. The selection of the control volume is relatively flexible, and there are two main methods. This paper adopts the CC finite volume method, where the variables are defined at the centroid of the control volume, and the control volume is taken as a triangular unit. The integral equations on the triangular control volume are:

[0083]

[0084] In the formula, A i is the area of ​​the triangular control volume.

[0085] Applying Green's formula to convert the area integral in the equation into a line integral, we can get:

[0086]

[0087] In the formula, Γ i is the boundary of the ith control volume; n is the unit external normal vector of the boundary.

[0088] The discretization of equation (18) is:

[0089]

[0090] In the formula, i represents the i-th unit; ij represents the j-th edge of the i-th unit; n ij is the unit external normal vector of the jth edge; ΔΓ ij is the length of the jth edge; U i , S i is the mean of the variable defined at the center of the unit; E * is the numerical flux of the control volume interface.

[0091] In order to construct a format with second-order spatial accuracy and prevent the generation of non-physical oscillations, the linear reconstruction and multidimensional limiter methods are used. The time term discretization uses the third-order Runge-Kutta method to obtain high-order time accuracy, and the friction source term is fully implicitly discretized to increase the stability of the format. The limited water depth method is used to deal with the moving boundary problem. The model has a good ability to capture discontinuities with high accuracy and can effectively simulate the moving boundary problem under the premise of ensuring mass conservation.

[0092] Model verification: Model verification includes three aspects: water volume verification, water level verification and flow rate verification. Among them, model water volume verification mainly counts the inflow and outflow of water in the model, and verifies the conservation of the model simulation of the main and branch river network by checking the balance of the model water volume. Model water level verification adjusts the resistance of the model through the measured water level data along the way, and on the other hand, verifies the simulation capacity of the model after the resistance adjustment to ensure the model's ability and accuracy in simulating different non-constant flow processes. Although the prediction model mainly predicts the real-time changes in the water level docking point of the pilot channel ship compartment, the model flow rate verification is also of great reference value for verifying the model simulation capability and simulation accuracy.

[0093] Result output: After the model predicts the water level in real time, it is necessary to output the predicted data. In theory, the mathematical model can output the water level change rate of each calculation step, and the calculation step length of this mathematical model is usually in seconds. The model can output water level change rate results at different minute levels, which can meet the water level change rate requirements of ships entering and leaving the docking compartment during different ship lift water level docking processes;

[0094] ① Output the curve diagram of given calculated flow boundary conditions (flow process of upstream hub discharge, flow process of power generation dispatch);

[0095] ② Output given calculated water level boundary conditions (water level fluctuation process of downstream river / reservoir, water level-flow process line or reservoir capacity curve of lower boundary);

[0096] ③ Output the water level variation rate at different minute levels (time series on the horizontal axis, water level variation rate at different minute levels on the vertical axis).

[0097] Through the above steps, the water level variation rate during the docking process of the last-stage ship lift can be accurately and quickly simulated and predicted, providing a scientific basis for determining the suspension period and reducing the loss of the ship lift caused by long-term suspension of the ship lift.

[0098] A prediction system for water level variation rate during docking of a last-stage ship lift carrier, comprising:

[0099] A data acquisition module is used to obtain basic data of the research waters, including upstream hub power generation regulation or flood control dispatch data, river topography data, downstream reservoir operation data and hydrological observation data;

[0100] A model building module is used to build model boundary conditions according to the basic data; based on the built model boundary conditions, a multi-dimensional coupled hydrodynamic model is built in combination with the one-dimensional Saint-Venant equation and the two-dimensional shallow water motion equation;

[0101] The model solving module is used to discretely solve the multi-dimensional coupled hydrodynamic model according to the finite volume method to obtain the water level variation data of different minute levels at the intersection of the last-stage ship lift cabin and the downstream pilot channel under given flow and water level boundary conditions.

[0102] An electronic device comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program so that the electronic device executes a method for predicting water level variation rate during docking of a last-stage ship lift cabin.

[0103] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements a method for predicting the water level variation rate during docking of a last-stage ship lift ship compartment.

[0104] The above is only a preferred specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for predicting the water level variation rate during the docking process of the last-stage ship lift, characterized in that: include: Obtain basic data of the research waters, including upstream hub power generation regulation or flood control dispatch data, river topography data, downstream reservoir operation data and hydrological observation data; Building model boundary conditions based on the basic data; Based on the constructed model boundary conditions, a multi-dimensional coupled hydrodynamic model is constructed by combining the one-dimensional Saint-Venant equation and the two-dimensional shallow water motion equation; The multi-dimensional coupled hydrodynamic model is discretely solved based on the finite volume method to obtain the water level variation data of different minute levels at the intersection of the last-stage ship lift compartment and the downstream pilot channel under given flow and water level boundary conditions.

2. The method for predicting the water level variation rate during the docking process of the last-stage ship lift cabin according to claim 1 is characterized in that: The downstream reservoir operation data include reservoir type, dam height, reservoir operation characteristic water level and corresponding storage capacity.

3. The method for predicting water level variation rate during docking of the last-stage ship lift cabin according to claim 1, characterized in that: Before constructing the model boundary conditions based on the basic data, the basic data is further processed to remove outliers and interpolate missing values ​​to obtain preprocessed basic data, and the model boundary conditions are constructed based on the preprocessed basic data.

4. The method for predicting the water level variation rate during the docking process of the last-stage ship lift cabin according to claim 1 is characterized in that: The process of constructing the model boundary conditions specifically includes: The upstream hub power generation regulation or flood control dispatch discharge data is used as the inflow boundary; Based on the downstream reservoir operation data, the reservoir capacity under different characteristic water levels is calculated according to the cross-section method, the calculated data is curve-fitted to obtain a reservoir capacity curve, and the reservoir capacity curve is used as the outflow boundary; The inflow boundary and the outflow boundary are used as boundary conditions of the model.

5. The method for predicting water level variation rate during docking of the last-stage ship lift cabin according to claim 1, characterized in that: Based on the constructed model boundary conditions, a multidimensional coupled hydrodynamic model is constructed by combining the one-dimensional Saint-Venant equation and the two-dimensional shallow water motion equation, including: A one-dimensional hydrodynamic model for describing the water flow movement in the long river section below the hub dam is constructed based on the one-dimensional Saint-Venant equation; Based on the two-dimensional shallow water motion equation, a two-dimensional hydrodynamic model is constructed to describe the water flow motion under the complex structures and terrain in the hub dam area; The one-dimensional hydrodynamic model and the two-dimensional hydrodynamic model are coupled, and the multi-dimensional coupled hydrodynamic model is obtained by setting the model boundary conditions.

6. A prediction system for water level variation during docking of the last-stage ship lift, characterized in that: include: A data acquisition module is used to obtain basic data of the research waters, including upstream hub power generation regulation or flood control dispatch data, river topography data, downstream reservoir operation data and hydrological observation data; A model building module is used to build model boundary conditions according to the basic data; based on the built model boundary conditions, a multi-dimensional coupled hydrodynamic model is built in combination with the one-dimensional Saint-Venant equation and the two-dimensional shallow water motion equation; The model solving module is used to discretely solve the multi-dimensional coupled hydrodynamic model according to the finite volume method to obtain the water level variation data of different minute levels at the intersection of the last-stage ship lift cabin and the downstream pilot channel under given flow and water level boundary conditions.

7. An electronic device, characterized in that: It comprises a memory and a processor, the memory is used to store a computer program, the processor runs the computer program so that the electronic device executes a method for predicting water level variation during docking of a last-stage ship lift compartment according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that: It stores a computer program, which, when executed by a processor, implements a method for predicting water level variation during docking of a last-stage ship lift compartment as described in any one of claims 1-5.

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