A method for simulating the planar flow field of a braided river channel

Abstract

The application discloses a method for simulating the planar flow field of a braided river channel, comprising the following steps: preparing a two-dimensional calculation grid of the river channel; interpolating the terrain of the grid points to complete fine modeling of the planar area riverbed topography of the braided river channel; numerically discretizing two-dimensional hydrodynamic control equations on the two-dimensional calculation grid to construct a basic two-dimensional hydrodynamic solver; establishing a dry-wet dynamic boundary processing module in a memory and compensation mode, making it work in coordination with the hydrodynamic solver, and jointly forming a complete two-dimensional hydrodynamic model; setting the import and export flow, water level open boundary conditions for the target river section of the braided river channel, simulating the planar flow field of the braided river channel, saving the water level distribution and flow field results calculated by the model on a hard disk, and displaying on a computer screen to feedback to the user. The application solves the problems of too large error, poor effect or weak method universality of the braided river channel planar flow field simulation method in the river simulation technical field.

Description

Technical Field

[0001] The present application relates to the field of hydraulic simulation, and specifically to a method for simulating the planar flow field of braided river channels. Background Art

[0002] Common river channel types in nature include straight, curved, bifurcated, and braided. Braided rivers are widely distributed in the middle and lower reaches of river basins, deltas, and other areas. They are the most complex type of river channel, with wide, shallow, and multi-branched (interwoven like braids) riverbed characteristics and staggered and scattered water flow patterns. The difficulty of numerical simulation of the plane flow field of braided rivers is also the greatest among all types of rivers. At the same time, simulating and studying the plane flow field of braided river channels is also the basis for carrying out braided river channel regulation and river flow control, regional flood prevention, and other work, and has important practical value in water conservancy engineering practice. The simulation of the plane flow field of river channels generally uses a planar two-dimensional hydrodynamic model (referred to as a two-dimensional model). The difficulties of using it to simulate the water flow movement in braided rivers are analyzed as follows.

[0003] First, braided river channels are often over 2–3 km wide, and many of their gullies are only 50 m wide or even smaller. This wide channel width necessitates a large simulation area and a large number of 2D grid cells. At the same time, accurately depicting the distribution of shoals and narrow gullies requires a fine-scale grid. Balancing the coverage of wide channel areas with accurate depiction of river regimes presents significant challenges in 2D meshing of braided channels (the first step in 2D modeling). Furthermore, conventional measured topographic maps of wide channels (1:5000–1:10000) typically have elevation measurement points spaced over 50–100 m. This means that many gullies in braided channels often have only a single or no topographic measurement point across their lateral direction. Consequently, the spatial resolution of conventional measured topography for braided channels is insufficient to accurately interpolate the 2D grid topography of the channel (the second step in 2D modeling). These two factors make detailed 2D modeling of braided channels extremely challenging. Second, braided channels experience frequent transitions between wet and dry states, a complex flow path and variable flow regimes. This places stringent demands on the ability of 2D models to simulate both wet and dry dynamic boundaries. Third, the minimum cell size of the computational grid used to describe complex braided channels is typically very small. In this context, the alternating slow and rapid currents and scattered flow patterns of braided channels increase the risk of computational instability in 2D models, placing high demands on the model's numerical solution.

[0004] Hydrodynamic models are categorized into explicit and implicit types. Implicit hydrodynamic models, while more complex in structure, offer excellent numerical stability. With the rapid development of computational mathematics and computational fluid dynamics in this century, semi-implicit hydrodynamic models based on the Euler-Lagrange method have become suitable for simulating a variety of slow, rapid, and complex flow regimes, and can utilize large time steps. These models have effectively addressed the instability issues associated with two-dimensional hydrodynamic calculations in braided channels. However, challenges remain regarding the detailed modeling of two-dimensional braided channel models and the treatment of complex and frequently moving dry and wet boundaries. In particular, there is a lack of a highly stable moving dry and wet boundary treatment method suitable for complex two-dimensional channel models that ensures mass conservation.

[0005] The water area and its boundaries in a river channel frequently change as floods propagate, a phenomenon known as the wet-dry dynamic boundary problem. During the calculation of a two-dimensional hydrodynamic model, these changes in the water area can cause some cells in the grid to become submerged during flooding and dry out during falling water. The computational process used to implement mesh wet-dry transitions to characterize the changes in the water area and its boundaries is called wet-dry dynamic boundary simulation. The critical water depth method is the most commonly used approach for simulating wet-dry dynamic boundaries. It defines a critical water depth h0 (e.g., 0.001 m) to define the wet-dry state of a grid element. When the water depth is less than h0, the grid element is dry; otherwise, it is wet. Furthermore, a wet-dry flag is assigned to each grid element (one-to-one with the grid element) to record its current wet-dry state. By updating the wet-dry state of the grid elements in real time based on the latest flow information, the dynamics of the water area and its boundaries can be described. In the traditional critical water depth method, when the water depth of a wet cell is less than h0, it is immediately "dried out" and exits the model calculation. When a dry cell meets the conditions for resuming flow, it is wetted and reentered into the model calculation at the next time step. The restoration flow conditions for the dry→wet transition of a dry cell are as follows: ① The water level at the center of the dry cell is interpolated using the information of adjacent wet cells and the water depth is calculated. The water depth should be greater than h0; ② There should be an inflowing water flux on the side of the dry cell, or a large water level gradient exists between the dry cell and its adjacent wet cells.

[0006] Traditional critical depth methods, unable to promptly address potential negative depth issues in hydrodynamic calculations, can easily lead to water volume violations and distorted results in complex channel conditions. This problem is particularly prominent when using implicit models with large time steps. The advantage of implicit hydrodynamic models is that they allow for large time steps in river flow calculations. However, they generally do not update the grid's wet / dry state in real time during the iterative solution of a single time step. These characteristics make it very easy for implicit models based on the traditional critical depth method to generate local negative depth cells in areas with complex terrain and large water level gradients when using large time steps. This can lead to water volume violations and distorted results. This creates a conflict between the need for large time steps in hydrodynamic calculations and the requirement for small time steps to simulate rapidly changing water boundary dynamics. This problem remains unresolved and can lead to significant errors in braided river flow simulations. Summary of the Invention

[0007] The purpose of the embodiments of the present application is to provide a method for simulating the plane flow field of braided river flow, so as to solve the problems of excessive error, poor effect, and low versatility of the plane flow field simulation method of braided river flow in the current field of water conservancy simulation (river simulation) technology.

[0008] To achieve the above objectives, this application provides the following technical solutions:

[0009] The present invention provides a method for simulating a planar flow field of a braided river, comprising the following steps:

[0010] Step 1: Create a two-dimensional computational grid for the river channel, including classifying and marking the planar areas of the braided river channel, drawing the boundary lines between the inside and outside of the river channel, and generating the computational grid by zoning.

[0011] Step 2: Interpolate the terrain of the grid points, including classifying and identifying the scattered points and grid points of the braided river channel terrain, pairing the grid points with the scattered points, and interpolating the terrain of the grid points, thereby completing the detailed modeling of the riverbed topography and landforms in the planar area of ​​the braided river channel;

[0012] Step 3: Numerically discretize the 2D hydrodynamic control equations on a 2D computational grid and construct a basic 2D hydrodynamic solver.

[0013] Step 4: Establish a dry-wet dynamic boundary processing module with memory and compensation methods, coordinate and synchronize it with the hydrodynamic solver, and together form a complete two-dimensional hydrodynamic model. This model has the ability to handle the dynamic changes of water areas in the propagation of floods in braided complex rivers in real time;

[0014] Step 5: For the target braided river section, set its inlet and outlet flow rates and water level open boundary conditions, carry out simulation of the plane flow field of the braided river, save the water level distribution and flow field results calculated by the model to the hard disk, and display them on the computer screen to provide feedback to the user.

[0015] In step 1, the two-dimensional computational grid of the river is prepared as follows:

[0016] Step 11: Divide the river channel into three areas, referring to the waterside and beach edge lines in the measured topographic map of the braided river channel. The first area is the in-channel beach, which is the area between the beach edge lines of the left and right inner beaches and the outer boundary of the river channel, and is marked with -1. The second area is the sandbars within the river channel, which are only submerged when the flow is high. The sandbars within the river channel are marked with non-repeating positive integers such as 1, 2, 3, ..., N, where N is the total number of sandbars. The third area is the channel between the beach and the sandbar, and is marked with 0.

[0017] Step 12: Draw the dike line according to the selected spatial step size, and use the area within the dike as the calculation area; draw the beach-channel boundary line along the beach edge line or waterside line in the river channel according to the selected spatial step size;

[0018] Step 13: Generate the surface areas of the side beach, groove flow channel, and center beach respectively, and obtain the computational grids of each partition of the three types of areas by generating each surface area separately.

[0019] In step 2, the terrain of the interpolation grid point is specifically:

[0020] Step 21: Corresponding to the classification of the calculation area in step 11, the measured topographic scattered points located in the beach, trough, and sandbar divisions are marked with -1, 0, and positive integers respectively;

[0021] Step 22: Pair the grid points with the terrain scattered points through identification to form a "grid point-terrain scattered point" grouping;

[0022] Step 23: Within each group, the terrain of the grid points is interpolated based on the elevation data of the scattered terrain points.

[0023] The method of two-dimensional computational grid division of the braided river channel in step 1 and grouped terrain interpolation of the grid of the braided river channel in step 2 is referred to as the "zoning division and grouping interpolation" fine modeling method. Its advantage is that the river channel and riverbed topography established based on this method can smoothly fit the flow path boundary, and the topographic measurement points above and below the water will not interfere with each other when interpolating the grid point terrain, thereby achieving a two-dimensional river channel modeling effect with smooth and simple groove boundaries, clear and accurate flow paths and river flows, and accurate depiction of the braided river channel morphology, effectively avoiding the occurrence of groove boundary fragmentation, flow path blockage and other phenomena.

[0024] In step 3, the basic two-dimensional hydrodynamic solver is constructed as follows:

[0025] Step 31: Use the depth-averaged two-dimensional shallow water equation as the control equation;

[0026] Step 32: Use the θ semi-implicit method to discretize the water level gradient term in the control equation to eliminate the limitation on the solver calculation stability caused by the rapid surface gravity wave;

[0027] Step 33: Use the Euler-Lagrange method to solve the convection term in the governing equations so that the solver calculation time step is not limited by the stability conditions related to the grid size;

[0028] Step 34: Use the finite volume method to discretize the governing equations to ensure water conservation in the hydrodynamic calculations;

[0029] Step 35: By constructing a set of algebraic equations based on velocity-pressure coupling and solving them iteratively, coupled calculations of water level gradient and flow field in the river area are achieved.

[0030] The hydrodynamic solver belongs to the type and category of implicit two-dimensional hydrodynamic model. This type of solver is applicable to solving various slow, rapid and complex water flows and has the advantages of being able to use large time steps and high efficiency. It can solve the problem of easy instability in two-dimensional hydrodynamic calculation of braided rivers. The main calculation parameters of the hydrodynamic solver include river roughness (n m The operation mode of the hydrodynamic solver is: select a time step Δt and deduce the evolution process of the water flow step by step.

[0031] In step 4, a dry-wet dynamic boundary processing module with memory and compensation mode is established to coordinate and synchronize with the hydrodynamic solver to form a complete two-dimensional hydrodynamic model. Specifically:

[0032] Step 41: Detect the "wet→dry" state transition event of the unit and the negative water depth unit, and update the wet / dry flag of the unit. Traverse all the units in the computational grid that are wet at the beginning of this time step in the order of unit numbers from small to large. According to the latest unit water level solved by the hydrodynamic solver at this time step, calculate the center water depth of the unit, represented by h. If h ≥ h0, the unit continues to remain in the wet state; if h <h0,则表明单元在本时步发生了“湿→干”的状态转变,将其标识为干,对于所有在本时步发生“湿→干”转换的单元,根据单元水深进行进一步判断:若h> 0, the cell is an ordinary dry cell, and the process goes directly to step 43; if h<0, the cell is identified as a negative water depth cell, and the adjacent wet cells are identified as affected cells, and step 42 is executed;

[0033] Step 42: Calculate the water debit and return of the newly generated negative water depth dry cells, traverse all the newly generated negative water depth dry cells according to the cell number, and execute steps 421-423;

[0034] Step 421: For a newly generated negative water depth dry cell, calculate the water debit Ah of the cell at the current time step using its plan area A and water depth h;

[0035] Step 422: Sort and specify the priority of the affected cells around the negative water depth dry cell; at the same time, calculate and record the water return amount M of each affected cell according to its water volume weight;

[0036] Step 423: Specify the water return amount ETAC of the affected cells at each time step, divide M by ETAC to obtain the water return frequency CI of each affected cell;

[0037] Step 43: The affected cells give water according to the specified time step amount ETAC, for an affected cell, its water level decreases by ETAC at each time step; while performing water level correction, CI decreases by 1, once CI is found to have decreased to 0, immediately eliminate the "affected cell" identity of the cell, traverse all the affected cells according to the cell number, and perform the above cell water level correction operation;

[0038] Step 44: Detect the "dry→wet" conversion event and update the cell identification, traverse all the dry cells according to the cell number order, judge whether they will be wet due to the hydraulic conditions of the adjacent cells, for ordinary dry cells, when the cell restores over-flowing condition is met, set its dry-wet flag to wet and water depth to h0, and let it participate in the next time step model calculation, for negative water depth dry cells, when the cell restores over-flowing condition is met, add a water level increment Δh to the memory variable η of the cell, when it is found that the updated η is higher than the bed surface by h0, immediately eliminate its "negative water depth cell" identity, and set its dry-wet flag to wet, after this detection and update, all the remaining dry cells do not participate in the next time step model calculation;

[0039] Step 45: Based on the latest cell dry-wet information obtained in steps 41-44, update the dry-wet state of other grid elements such as nodes and edges in the calculation grid.

[0040] The wet-dry dynamic boundary processing module of the memory and compensation method needs to define the following variables before application. A wet-dry identifier (variable DW) is defined for each cell of the grid to distinguish between wet cells and dry cells; at the same time, a negative water depth identifier (variable NEG) is defined for each cell to distinguish between negative water depth dry cells and ordinary dry cells. The wet cells around the negative water depth cell are defined as "affected cells". According to the flow direction on each side of the negative water depth cell (refer to the state of the cell before it is converted from a wet cell to a negative water depth cell), the affected cells are divided into two categories: if the flow direction deviates from the negative water depth cell, it is called a water receiving cell, otherwise it is called an ordinary neighboring cell. It is stipulated that the priority of the water return volume of the water receiving cell is higher than that of the ordinary neighboring cell. For the negative water depth cell, its instantaneous water level (η) is used as a memory variable (Note: the negative water depth cell η is lower than the riverbed).

[0041] The amount of water returned by the affected unit at each time step is ETAC, which specifically refers to the height by which the water level of the water column in the two-dimensional unit is lowered due to the water expenditure correction at each time step.

[0042] The memory and compensation method for handling wet and dry dynamic boundaries, compared to the traditional critical water depth method, adds a mechanism for handling negative water depth units: the neighboring units of the negative water depth unit gradually return the overdrawn water volume of the negative water depth unit through a step-by-step local correction method, maintaining the conservation of water volume calculated in complex water flow models while ensuring stability. The new wet and dry dynamic boundary processing method solves the contradiction between the large time step hydrodynamic calculation and the requirement of using a small time step to simulate the rapidly changing wet and dry boundary dynamics. The execution of the new wet and dry dynamic boundary processing method is independent of the hydrodynamic calculation and will not adversely affect the hydrodynamic calculation. In addition, this method is not only applicable to braided rivers (the most complex), but also to other types of rivers (such as straight, curved, and bifurcated rivers), and is a universal simulation method.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] The detailed modeling of zoning and group interpolation lays the foundation for accurately simulating the complex planar flow field of braided rivers. By using a memory and compensation method for wet-dry dynamic boundary processing, the conservation of hydrodynamic calculations is ensured without compromising the stability, time step, execution flow, and efficiency of the hydrodynamic calculations. Ultimately, this method addresses the problems of excessive error, poor results, and limited versatility in braided river planar flow field simulation methods in river simulation technology. The method also offers the advantages of high reliability, high computational efficiency, and strong versatility. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the process of implementing the method of the present invention.

[0046] Figure 2It is a schematic diagram of the execution flow of the dry-wet dynamic boundary processing method implementing the memory and compensation mode of the present invention.

[0047] Figure 3 It is a schematic diagram of the classification and identification of planar areas of braided river channels according to the present invention.

[0048] Figure 4 It is a schematic diagram of the partitioning and subdivision of the two-dimensional computational grid of a braided river channel according to the present invention.

[0049] Figure 5 It is a schematic diagram of the result of terrain interpolation of braided river channel calculation grid grouping according to the present invention.

[0050] Figure 6 It is a schematic diagram of the water boundary and flow field of the Niyang River in accordance with the present invention. DETAILED DESCRIPTION

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0052] As attached Figure 1 As shown, a method for simulating the plane flow field of braided river flow includes the following steps:

[0053] Step 1: Create a two-dimensional computational grid for the river channel, including classifying and marking the planar areas of the braided river channel, drawing the boundary lines between the inside and outside of the river channel, and generating the computational grid by zoning.

[0054] Step 2: Interpolate the terrain of the grid points, including classifying and identifying the scattered points and grid points of the braided river channel terrain, pairing the grid points with the scattered points, and interpolating the terrain of the grid points, thereby completing the detailed modeling of the riverbed topography and landforms in the planar area of ​​the braided river channel;

[0055] Step 3: Numerically discretize the 2D hydrodynamic control equations on a 2D computational grid and construct a basic 2D hydrodynamic solver.

[0056] Step 4: Establish a dry-wet dynamic boundary processing module with memory and compensation methods, coordinate and synchronize it with the hydrodynamic solver, and together form a complete two-dimensional hydrodynamic model. This model has the ability to handle the dynamic changes of water areas in the propagation of floods in braided complex rivers in real time;

[0057] Step 5: For the target braided river section, set its inlet and outlet flow and water level open boundary conditions, carry out simulation of the plane flow field of the braided river, save the water level distribution and flow field results calculated by the model to the hard disk, and display them on the computer screen to provide feedback to the user.

[0058] Figure 2 It is a schematic diagram of the execution flow of the memory and compensation method for processing dry-wet dynamic boundaries of the present invention. Figure 2 middle,

[0059] Step 41: Detect the "wet→dry" state transition event of the unit and the negative water depth unit, and update the wet / dry flag (variable) of the unit. Traverse all the units in the computational grid that are wet at the beginning of this time step in the order of unit numbers from small to large. Based on the latest unit water level solved by the hydrodynamic solver at this time step, calculate the center water depth of the unit (represented by h). If h ≥ h0, the unit continues to remain in the wet state; if h <h0,则表明单元在本时步发生了“湿→干”的状态转变,将其标识为干。对于所有在本时步发生“湿→干”转换的单元,根据单元水深进行进一步判断:若h> If h < 0, the cell is an ordinary dry cell, and the process goes directly to step 43. If h < 0, the cell is identified as a negative water depth cell, and the adjacent wet cells are identified as affected cells, and step 42 is executed.

[0060] Step 42: Calculate the water overdraft and water return of the newly generated negative water depth dry unit. All newly generated negative water depth dry units can be traversed according to the unit number, and the following steps are performed: ① For a newly generated negative water depth dry unit, use its plane area A and water depth h to calculate the water overdraft Ah in this time step; ② Sort out and specify the priority of the affected units around the negative water depth dry unit, and calculate and record the water return M required by each of them according to the water volume weight of the affected units; ③ Specify the water return (ETAC) required by the affected units in each time step, and divide M by ETAC to obtain the water return times (CI) of each affected unit.

[0061] Step 43: The affected units provide water according to the specified time-step quota (ETAC). For example, for an affected unit, its water level drops by ETAC at each time step; while performing water level correction, its CI decreases by 1. Once the CI reaches 0, the unit is immediately removed from the "affected unit" status. All affected units can be traversed by unit number, performing the above unit water level correction operation.

[0062] Step 44: Detect the unit "dry→wet" conversion event and update the unit identification. Traverse all dry units in the order of unit numbers to determine whether they will become wet due to the hydraulic conditions of the neighboring units. For ordinary dry units, when the unit recovery flow condition is met, its dry-wet flag is set to wet and the water depth is set to h0, and it is allowed to participate in the model calculation of the next time step. For negative water depth dry units, when the unit recovery flow condition is met, add a water level increment Δh to the memory variable (η) of the unit. When it is found that the updated η is higher than the bed surface by h0, its "negative water depth unit" identity is immediately eliminated and its dry-wet flag is set to wet. After this detection and update, all remaining dry units do not participate in the model calculation of the next time step.

[0063] Step 45: Based on the latest unit wetness information obtained in steps 41 to 44, the wetness status of other grid elements such as nodes and edges in the computational grid is updated.

[0064] Figure 3 The present invention is a schematic diagram of the classification and identification of planar areas of braided rivers (taking the estuary section of the Niyang River, a first-level tributary of the Yarlung Zangbo River, as an example). Figure 3 middle,

[0065] Based on the waterside and beach edge lines on the measured topographic map (1:10,000), the target river section was divided into three areas: ① Beaches, the areas between the beach edge lines on the left and right inner sides of the river channel and the outer boundary of the river channel (including beach and highlands). These areas have high elevations and do not flow under low or medium flows, and are labeled with -1; ② Sandbars within the river channel, which are only flooded under high flows, are labeled with unique numbers such as 1, 2, 3, ..., N (N is the total number of sandbars); ③ Channels between beach and sandbars are labeled with 0. Correspondingly, measured topographic points within the beach, channel, and sandbar zones are labeled with -1, 0, and positive integers, respectively. Based on these labels, grid points are paired with topographic points to form several "grid point-topographic point" groups.

[0066] Figure 4 It is a schematic diagram of the two-dimensional computational grid partitioning of a braided river channel according to the present invention (taking the estuary section of the Niyang River, a first-level tributary of the Yarlung Zangbo River, as an example). Figure 4 middle,

[0067] According to the set grid size (50m in this example), Figure 3 The three regions in the model were meshed separately, with appropriate densification within the trenches. The resulting triangular unstructured mesh contained 91,396 cells and 46,433 nodes. Cell centers were then selected as the "control terrain" grid points, and cell centers within each partition were identified with the corresponding partition markers to prepare for grouped terrain interpolation.

[0068] Figure 5 It is a schematic diagram of the results of the grid grouping terrain interpolation for calculating braided river channels according to the present invention (taking the estuary section of the Niyang River, a first-level tributary of the Yarlung Zangbo River, as an example). Figure 5 middle,

[0069] As can be seen from the figure, when using the conventional gridding and terrain interpolation method (using a uniform grid and a mixture of surface and underwater terrain scatter points for grid point terrain interpolation), the resulting trench water boundary is very fragmented, making it difficult to clearly reflect the braided river channel flow path due to the inability of the two-dimensional grid to smoothly fit the flow path boundary, and the interference between the surface and underwater terrain measurement points when interpolating the grid point terrain. When using the partitioning and grouping interpolation method (interpolating the grid point terrain based on the elevation data of the terrain scatter points within each "grid point-topography scatter point" group), the resulting trench boundary is smooth and simple, can clearly depict the braided river channel flow path and river flow, and the modeling effect is consistent with the actual river channel morphology.

[0070] Figure 6 The figure is a schematic diagram of the water boundary and flow field of the Niyang River calculated by implementing the method of the present invention (taking the estuary section of the Niyang River, a first-level tributary of the Yarlung Zangbo River, as an example). Figure 6 middle,

[0071] Comparison shows that the dry season flow path ( Figure 6 b) Compared with the measured dry season flow path ( Figure 3 ) are in good agreement, while the range of water areas calculated by the two-dimensional model using the traditional critical water depth method is much larger than the measured dry season water areas (i.e., the calculated planar flow field is severely distorted). In the upper reaches of the Niyang River in the calculation area, the water areas and flow fields simulated by the two methods are relatively close. However, the flow field calculated by the two-dimensional model using the traditional critical water depth method shows a significant enhancement after the water flows through the area with complex river flow units. When this flow enhancement phenomenon develops to the downstream estuary area, many grooves that are not actually through flow also become flow channels. These scenarios are significantly different from the measured flow paths.

[0072] The water conservation error calculated by the two-dimensional hydrodynamic model shows that the flow rate at the outlet of the study area calculated by the model using the traditional critical water depth method is almost doubled relative to the total inflow flow, and the water conservation error is 94.31%. In contrast, the water conservation error of the model using the method of the present invention is less than 1.0% when simulating braided rivers, ensuring the accuracy of the two-dimensional hydrodynamic calculation results.

[0073] The above embodiments are merely illustrative of the technical solutions of the present invention. The inversion model construction method involved in the present invention is not limited to the content described in the above embodiments, but is subject to the scope defined by the claims. Any modifications, supplements, or equivalent substitutions made by those skilled in the art based on the present invention are within the scope of protection claimed by the present invention.

Claims

1. A method for simulating the plane flow field of braided river flow, characterized in that: The steps include: Step 1: Create a two-dimensional computational grid for the river channel, including classifying and marking the planar areas of the braided river channel, drawing the boundary lines between the inside and outside of the river channel, and generating the computational grid by zoning. Step 2: Interpolate the terrain of the grid points, including classifying and identifying the scattered points and grid points of the braided river channel terrain, pairing the grid points with the scattered points, and interpolating the terrain of the grid points, thereby completing the detailed modeling of the riverbed topography and landforms in the planar area of ​​the braided river channel; Step 3: Numerically discretize the 2D hydrodynamic control equations on a 2D computational grid and construct a basic 2D hydrodynamic solver. Step 4: Establish a dry-wet dynamic boundary processing module with memory and compensation methods, coordinate and synchronize it with the hydrodynamic solver, and together form a complete two-dimensional hydrodynamic model. This model has the ability to handle the dynamic changes of water areas in the propagation of floods in braided complex rivers in real time; Step 5: For the target braided river section, set its inlet and outlet flow and water level open boundary conditions, carry out simulation of the plane flow field of the braided river, save the water level distribution and flow field results calculated by the model to the hard disk, and display them on the computer screen to provide feedback to the user.

2. A method for simulating the planar flow field of braided river flow according to claim 1, characterized in that: In step 1, the two-dimensional computational grid of the river is prepared as follows: Step 11: Divide the river channel into three areas, referring to the waterside lines and beach edge lines in the measured topographic map of the braided river channel. The first area is the in-channel beach, which is the area between the beach edge lines of the left and right inner beaches and the outer boundary of the river channel, and is marked with -1. The second area is the sandbars in the river channel, which are marked with non-repeating positive integers such as 1, 2, 3, ..., N, where N is the total number of sandbars. The third area is the channel between the beach and the sandbar, and is marked with 0. Step 12: Draw the dike line according to the selected spatial step size, and use the area within the dike as the calculation area; draw the beach-channel boundary line along the beach edge line or waterside line in the river channel according to the selected spatial step size; Step 13: Generate the surface areas of the side beach, groove flow channel, and center beach respectively, and obtain the computational grids of each partition of the three types of areas by generating each surface area separately.

3. A method for simulating the planar flow field of braided river flow according to claim 2, characterized in that: In step 2, the terrain of the interpolation grid point is specifically: Step 21: Corresponding to the classification of the calculation area in step 11, the measured topographic scattered points located in the beach, trough, and sandbar divisions are marked with -1, 0, and positive integers respectively; Step 22: Pair the grid points with the terrain scattered points through identification to form a "grid point-terrain scattered point" grouping; Step 23: Within each group, the terrain of the grid points is interpolated based on the elevation data of the scattered terrain points.

4. A method for simulating the planar flow field of braided river flow according to claim 1, characterized in that: In step 3, the basic two-dimensional hydrodynamic solver is constructed as follows: Step 31: Use the depth-averaged two-dimensional shallow water equation as the control equation; Step 32: Use the θ semi-implicit method to discretize the water level gradient term in the control equation to eliminate the limitation on the solver calculation stability caused by the rapid surface gravity wave; Step 33: Use the Euler-Lagrange method to solve the convection term in the governing equations so that the solver calculation time step is not limited by the stability conditions related to the grid size; Step 34: Use the finite volume method to discretize the governing equations to ensure water conservation in the hydrodynamic calculations; Step 35: Implement the coupled calculation of water level gradient and flow field in the river channel area by constructing and iteratively solving an algebraic equation system based on flow velocity-pressure coupling.

5. The method for simulating the planar flow field of braided river flow according to claim 1, characterized in that: In step 4, a dry-wet moving boundary processing module with memory and compensation methods is established to work coordinately and synchronously with the hydrodynamic solver, and they are jointly formed into a complete two-dimensional hydrodynamic model. Specifically: Step 41: Detect the "wet → dry" state conversion event and negative water depth cells of the unit, and update the dry-wet identification of the unit. Traverse all the cells that are wet at the beginning of this time step in the computational grid in ascending order of cell number. Calculate the water depth at the center of the cell using the latest cell water level solved by the hydrodynamic solver in this time step, denoted as h. If h ≥ h0, the cell remains wet; if h < h0, it indicates that the cell has undergone a "wet → dry" state transition in this time step, and mark it as dry. For all cells that have undergone a "wet → dry" transition in this time step, further judgment is made based on the cell water depth: if h > 0, the cell is an ordinary dry cell, and directly jump to step 43; if h < 0, mark the cell as a negative water depth cell, and mark the adjacent wet cells as affected cells, and execute step 42. Step 4: Carry out the calculation of water volume overdraw and returned water volume of the newly generated negative water depth dry cells. Traverse all the newly generated negative water depth dry cells in ascending order of cell number, and execute steps 421 to 423. Step 421: For a newly generated negative water depth dry cell, use its planar area A and water depth h to calculate the overdrawn water volume Ah in this time step. Step 422: Sort out and define the priorities of the affected cells around the negative water depth dry cells; at the same time, calculate and record the water volume M that each of them needs to return according to the water volume weight of the affected cells. Step 423: Define the water volume ETAC that the affected cells need to return in each time step, and divide M by ETAC to obtain the water volume return times CI of each affected cell. Step 43: The affected cells give out water according to the specified time step quota ETAC. For a certain affected cell, its water level drops by ETAC in each time step; while performing the water level correction, its CI decreases by 1. Once it is found that CI has decreased to 0, immediately eliminate the "affected cell" status of the cell. Traverse all the affected cells in ascending order of cell number and perform the above cell water level correction operation. Step 44: Detect the "dry → wet" conversion event of the unit and update the unit identification. Traverse all the dry cells in ascending order of cell number and judge whether they will become wet due to the hydraulic conditions of adjacent cells. For ordinary dry cells, when the cell restoration over-flow condition is met, set its dry-wet flag to wet and the water depth to h0, and let it participate in the model calculation of the next time step. For negative water depth dry cells, when the cell restoration over-flow condition is met, add a water level increment Δh to the memory variable η of the cell. When it is found that the updated η is higher than the bed surface by h0, immediately eliminate its "negative water depth cell" status and set its dry-wet flag to wet. After this detection and update, all the remaining dry cells do not participate in the model calculation of the next time step. Step 45: Based on the latest unit wetness information obtained in steps 41 to 44, the wetness status of nodes, edges, and other grid elements in the computational grid is updated.

Images