Urban inland inundation rapid simulation method coupling SWMM and earth surface two-dimensional hydrodynamic model

Abstract

The invention discloses an urban inland inundation rapid simulation method coupling an SWMM and an earth surface two-dimensional hydrodynamic model, and relates to the technical field of urban rainfall inland inundation numerical simulation. The method comprises the following steps: acquiring basic data, and constructing an SWMM model; simulating rainfall confluence and pipe network hydrodynamic process of a target area by using an SWMM model, and calculating overflow data of each pipe network node; constructing an earth surface two-dimensional hydrodynamic model; the pipe network node overflow data are corrected and input into the earth surface two-dimensional hydrodynamic model, and a simulation effect is obtained; verifying the simulation effect by using historical submerging data; and under the condition that the verification is passed, simulating and analyzing urban rainfall inland inundation results under different design rainfall conditions based on the SWMM model and the earth surface two-dimensional hydrodynamic model. The simulation precision and the simulation efficiency can be considered, and the method has the advantages of being simple, clear in logic, high in operability and high in simulation result precision.

Description

Technical Field

[0001] The present application relates to the technical field of numerical simulation of urban waterlogging caused by rainfall, and in particular to a method for rapid simulation of urban waterlogging by coupling SWMM and a two-dimensional surface hydrodynamic model. Background Art

[0002] Urban waterlogging simulation can not only identify potential risk areas of urban waterlogging, but also help determine the effectiveness of different drainage measures under complex conditions. It is an important means to accurately estimate urban waterlogging risks and scientifically formulate urban waterlogging disaster prevention and mitigation measures. SWMM is a commonly used one-dimensional urban waterlogging simulation model, which is free and open source and has stable operation. Its advantage is that it can better simulate the hydrodynamic process of the pipe network, but it cannot present the results of surface overland flow simulation, and it is difficult to give the results of urban waterlogging such as flooded area, flooded depth and flooded duration, which is not conducive to the correct assessment of urban waterlogging risks.

[0003] There are currently two types of technical means that attempt to solve the surface overflow simulation problem of SWMM. The first is to combine SWMM with geographic information system (GIS) technology, with SWMM calculating the overflow of the pipe network, and GIS estimating the flooded area and flooded depth based on the overflow. The first method can achieve better results in areas with simple terrain, but when the terrain is complex, it is easy to cause deviations in the flooded range due to the lack of surface overflow process calculation. The second method couples SWMM with two-dimensional models such as MIKE, LISFLOOD-FP, and FVCOM, and the two-dimensional model is responsible for the surface overflow process calculation, which has achieved certain results, but the current coupling models mostly use a tight coupling method, which not only makes the data interaction logic between models complex, but also further reduces the model calculation efficiency. Therefore, in view of the shortcomings of the prior art methods, the present invention proposes a rapid simulation method for urban waterlogging that couples SWMM and a surface two-dimensional hydrodynamic model, which can take into account both the simulation accuracy of urban waterlogging and the calculation efficiency of the model. Summary of the invention

[0004] This application proposes a method for rapid simulation of urban waterlogging by coupling SWMM and a two-dimensional surface hydrodynamic model. By decoupling the pipe network hydrodynamic calculation from the surface hydrodynamic calculation, it can not only accurately simulate the pipe network hydrodynamic and surface hydrodynamic processes, but also simplify the data interaction logic of the coupling model and improve the model calculation efficiency.

[0005] In order to achieve the above purpose, the technical solution adopted in this application is:

[0006] The present invention provides a method for rapid simulation of urban waterlogging by coupling SWMM and a two-dimensional surface hydrodynamic model, comprising:

[0007] Acquire basic data, resample and interpolate the basic data, and regularize data with inconsistent time scales or spatial scales to obtain a data set; the data set includes measured rainfall data, terrain data, land use, soil type, surface building vectors, pipe network data, pump station data, and historical inundation data;

[0008] Based on the data set, construct a SWMM model;

[0009] The SWMM model is used to simulate the rainfall runoff and pipe network hydrodynamic process in the target area, and the overflow data of each pipe network node is calculated;

[0010] Construct a two-dimensional surface hydrodynamic model based on terrain data, surface building vectors, land use and soil type data;

[0011] The overflow data of the pipe network nodes are corrected and input into the two-dimensional surface hydrodynamic model to simulate the rainfall waterlogging process and obtain the simulation effect;

[0012] Verifying the simulation effect using the historical flooding data;

[0013] When the simulation effect is verified, the results of urban waterlogging under different design rainfall conditions are simulated and analyzed based on the SWMM model and the two-dimensional surface hydrodynamic model.

[0014] Furthermore, based on the data set, a SWMM model is constructed, including:

[0015] Divide the target area into different sub-catchments based on topographic data;

[0016] Determine the spatial layout of the pipeline network according to the pipeline network data, wherein the spatial layout of the pipeline network includes the starting point and end point, length, diameter, and slope of the pipeline;

[0017] Determine the node locations of the pipeline network, the connection relationships between sub-catchments and pipeline networks;

[0018] Digitize pipeline length, diameter, slope, and buried depth;

[0019] According to the material and shape of the pipe network, set the roughness of the pipe network and determine whether the pipe is a pressurized pipe.

[0020] Furthermore, the SWMM model is used to simulate the runoff generation and convergence of rainfall in the target area and the hydrodynamic process of the pipe network, and the overflow data of each pipe network node is calculated, including:

[0021] The measured rainfall data was input into the SWMM model to calculate the flow generation and confluence time of the target area, and the network flow, flow velocity and network node overflow data were calculated using the dynamic wave algorithm; the total overflow calculation formula is as follows:

[0022]

[0023] Where: O t is the total overflow of the coupled model at time t; it is the overflow volume of the ith pipe network node at time t; n is the number of pipe network nodes where overflow occurs at time t.

[0024] Furthermore, a two-dimensional surface hydrodynamic model is constructed based on terrain data, surface building vectors, land use and soil type data, including:

[0025] The surface of the target area is divided using triangular or quadrilateral meshes, and the surface building vectors are considered during the division. The area where the surface buildings are located is set as a non-floodable area, and the impact of surface buildings on surface waterlogging is clarified;

[0026] Interpolate terrain elevation data into the divided surface grid to form digital elevation terrain;

[0027] According to the land use and soil data, the initial roughness of the surface two-dimensional hydrodynamic model is set;

[0028] According to the coordinates of the pipe network nodes in the SWMM model, corresponding water source nodes are set and numbered in the surface two-dimensional hydrodynamic model, which are used to exchange simulation data between the SWMM model and the surface two-dimensional hydrodynamic model. The interactive data types include the overflow of the pipe network nodes and the surface water depth. The pipe network nodes of the SWMM model are mapped to the surface two-dimensional hydrodynamic model by the following formula (2):

[0029]

[0030] Where: X, Y are the horizontal and vertical coordinates of the pipe network node in the two-dimensional hydrodynamic model on the surface, D X and D Y is the translation of the network node in the x and y directions during coordinate transformation; m is the scaling factor; θ is the rotation angle, and x0, y0 are the horizontal and vertical coordinates of the network node in the SWMM model.

[0031] Furthermore, the overflow data of the pipe network nodes are corrected and input into the two-dimensional surface hydrodynamic model to simulate the rainfall waterlogging process and obtain the simulation results, including:

[0032] According to the overflow status of the pipeline network nodes, the pipeline network nodes are divided into three categories, as shown in equations (3) to (6):

[0033] n=A+B+C (3)

[0034] A={x A |o x≥0} (4)

[0035] B={x B |o x <0,Depth x ≥TH} (5)

[0036] C={x C |o x <0,Depth x <TH} (6)

[0037] Where n is the total number of nodes in the coupled model network; TH is the water depth threshold; set A represents the overflow volume of the network node o x Node numbers greater than or equal to 0; set B represents the node overflow o x Less than 0 and the water depth at the x node is Depth x The node numbers that meet the water depth threshold requirements; Set C represents the node overflow less than 0, and the water depth Depth at the x node x The node number that does not meet the water depth threshold requirement.

[0038] At this time, the total overflow of the coupling model is shown in formula (7):

[0039] O n =O A +O B +O C (7)

[0040] Where: O n is the total overflow volume of the network node at time t, m 3 ;O A , O B and O C are the overflow volumes of the corresponding pipe network nodes of sets A, B, and C, m 3 .

[0041] For the pipe network node x belonging to set A A , the overflow volume is not corrected; for the pipe network node x belonging to set B B , the overflow O' at node x of the two-dimensional hydrodynamic model on the surface x The overflow volume O of the corresponding node in the SWMM model can be x Correction is obtained, as shown in equations (8) to (9); for the pipe network node x belonging to set C C , and its overflow is set to 0 in the surface two-dimensional hydrodynamic model.

[0042]

[0043] Where: k is the overflow correction coefficient.

[0044] The total surface water pumping capacity of the coupled model is calculated by the following formula:

[0045]

[0046] Where: D t is the total surface water pumping capacity of the coupled model at time t, m 3 ; α is the adjustment coefficient, which is calibrated using historical flooding data; m is the number of pumping stations; pump jt is the pumping capacity of the jth pumping station at time t. When the accumulated water is pumped out, the overflow is set to a negative number, which represents the receding of the accumulated water.

[0047] The corrected pipe network node overflow time series is input into the surface water dynamic model to simulate the accumulation and receding process of urban waterlogging. The simulation process is shown in equations (11) to (13):

[0048]

[0049] Where: x, y are Cartesian coordinates, m; t is time, s; h is water depth, m, u, v are flow velocities in x and y directions, m / s; z is water level, m; g is gravitational acceleration, m / s 2 ;v t is the turbulent viscosity coefficient, N·s / m 2 ; n is the Manning roughness coefficient, m / s^(1 / 3).

[0050] Further, the simulation effect is verified using the historical flooding data, including:

[0051] The maximum flooding range, maximum flooding depth, and waterlogging process data of the coupled simulation are compared with the historical flooding data. The Nash efficiency coefficient, root mean square error, and determination coefficient are used to evaluate the coupling simulation effect to verify whether the model accuracy meets the requirements. If the accuracy requirements are not met, the improved particle swarm optimization algorithm is used to iterate and adjust the coupling model parameters to rebuild the SWMM model. The coupling model parameters include runoff coefficient, infiltration rate, surface roughness, pipeline roughness, and pipe network outflow adjustment coefficient. The iterative process of the improved particle swarm optimization algorithm is as follows:

[0052]

[0053] Where: is the position of the i-th particle in the k-th iteration, representing the value of the model parameter; is the velocity of the ith particle in the kth iteration, representing the adjustment of the model parameters; P best (i) is the current optimal value of particle i; G bestis the global optimal value; c1 and c2 are non-negative learning factors; r1 and r2 are uniform random numbers generated in the range of [0, 1], ω max and ω min are the maximum and minimum values ​​of the inertia weight respectively; k is the current number of iterations; T is the maximum number of iterations; is the velocity of the ith particle in the k+1th iteration, is the position of the i-th particle in the k+1-th iteration;

[0054] The reconstructed SWMM model is used to simulate the rainfall runoff and pipe network hydrodynamic process in the target area, and the overflow data of each pipe network node is recalculated. The recalculated pipe network node overflow data is corrected and input into the surface two-dimensional hydrodynamic model to simulate the rainfall waterlogging process, obtain new simulation results, and verify the new simulation results.

[0055] Furthermore, based on the SWMM model and the two-dimensional surface hydrodynamic model, the results of urban waterlogging under different designed rainfall conditions are simulated and analyzed, including:

[0056] The designed rainfall processes with different return periods are input into the SWMM model, and the output of the SWMM model is input into the two-dimensional hydrodynamic model to simulate and analyze the urban rainfall waterlogging process under different designed rainfall scenarios, and finally output the pipe network overflow, maximum flooding range and depth, flooding duration at different locations and flooding process data.

[0057] The benefits of this application are:

[0058] This application integrates the advantages of a one-dimensional pipe network model and a two-dimensional ground hydrodynamic model, simplifies the complex data interaction logic during the coupled simulation of one-dimensional and two-dimensional models, and can improve simulation accuracy and efficiency. It has the advantages of simple methods, clear logic, strong operability, and high accuracy of simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0060] Figure 1 A flowchart of a method for rapid simulation of urban waterlogging by coupling SWMM and a two-dimensional surface hydrodynamic model provided in an embodiment of the present application;

[0061] Figure 2 The coupling construction result of SWMM and the surface two-dimensional hydrodynamic model provided in the embodiment of the present application, wherein (a) is a SWMM model; (b) is a surface two-dimensional hydrodynamic model;

[0062] Figure 3A comparison diagram of the historical flooding process and the simulated flooding process provided in the embodiment of the present application;

[0063] Figure 4 This is a diagram of the simulation results of the depth of waterlogging caused by rainfall in the target area provided in an embodiment of the present application.

[0064] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0065] The following examples are only for better explanation of the present invention, but the content of the present invention is not limited to the application in the examples. Therefore, those skilled in the art can make non-essential improvements and adjustments to the implementation scheme according to the above content of the invention and apply them to other examples, which are still within the protection scope of the present invention.

[0066] The present invention will now be further described with reference to the accompanying drawings.

[0067] The present application embodiment provides a method for rapid simulation of urban waterlogging by coupling SWMM and a two-dimensional surface hydrodynamic model. Figure 1 This is a flowchart of a method for rapid simulation of urban flooding by coupling SWMM and a two-dimensional surface hydrodynamic model provided in an embodiment of the present application. Figure 1 As shown, the method includes the following steps 1 to 7.

[0068] Step 1: Obtain basic data, resample and interpolate the basic data, and regularize data with inconsistent time or spatial scales to obtain a data set; the data set includes measured rainfall data, terrain data, land use, soil type, surface building vectors, pipe network data, pump station data, and historical inundation data.

[0069] In this embodiment, the data source can be the basic data required to be collected from the National Meteorological Science Data Center, the Resource and Environmental Science and Data Center of the Chinese Academy of Sciences, the Municipal Water Resources Bureau and the Housing and Construction Bureau, including hourly measured rainfall data, modeling area terrain, land use and soil type data, surface building vector data, underground pipe network length, diameter and flow direction data, pump station distribution and installed capacity, and historical flooding data. The basic data is resampled, interpolated, and other processing is performed to regularize data with inconsistent time or spatial scales.

[0070] Step 2: Build a SWMM model based on the data set.

[0071] In this embodiment, GIS is used to extract the elevation, slope, flow direction, etc. of the target area, and the target area is divided into different sub-catchments. Based on the municipal pipe network data, the spatial layout of the pipeline network is determined, including the starting and ending points of the pipeline, length, diameter, slope and other attributes. Determine the node positions of the pipeline network, and the connection relationship between the sub-catchments and the pipeline network. According to land use, soil type, etc., preliminarily set the sub-catchment runoff coefficient, infiltration rate, etc.; digitize the pipeline length, diameter, slope, burial depth and other information and input it into the model; according to the material and shape of the pipeline network, set the pipeline network roughness and whether it is a pressurized pipeline. In summary, the construction of the SWMM model can be completed. The results of the SWMM model construction in this embodiment are as follows. Figure 2 As shown in (a).

[0072] Step 3: Use the SWMM model to simulate the rainfall runoff and pipe network hydrodynamic process in the target area and calculate the overflow data of each pipe network node.

[0073] In this embodiment, the measured rainfall data is input into the constructed SWMM model to calculate the flow rate and confluence time of the target area, and the dynamic wave algorithm is used to calculate the pipe network flow rate, flow velocity and overflow data of the pipe network nodes for the calculation of the two-dimensional hydrodynamic process on the surface. The overflow time series calculation method is as shown in formula (1):

[0074]

[0075] Where: O t is the total overflow of the coupled model at time t, m 3 ;o it is the overflow volume of the ith pipe network node at time t, m 3 ; n is the number of pipe network nodes where overflow occurs at time t.

[0076] Step 4: Construct a two-dimensional surface hydrodynamic model based on terrain data, surface building vectors, land use and soil type data.

[0077] In this embodiment, a triangular grid or a quadrilateral grid is used to divide the surface of the target area. The surface building vector is taken into account during the division, and the area where the surface buildings are located is set as a non-floodable area to clarify the impact of the surface buildings on the surface water. The terrain elevation data is interpolated into the divided surface grid to form a digital elevation terrain of the target area. According to the land use and soil data, the initial roughness of the surface two-dimensional hydrodynamic model is set. Because the regional runoff calculation has been completed by the SWMM model, no repeated calculation is performed when the two-dimensional hydrodynamic model is constructed. According to the (x0, y0) coordinates of the pipe network nodes in the SWMM model, the corresponding water source nodes are set and numbered in the surface two-dimensional hydrodynamic model for the interaction of the SWMM model and the simulation data of the surface two-dimensional hydrodynamic model. The interactive data types include the overflow of the pipe network nodes and the depth of surface water. The pipe network node mapping method is shown in formula (2):

[0078]

[0079] Where: X, Y are the coordinates of the network nodes in the two-dimensional hydrodynamic model on the surface, D X and D Y is the translation amount of the network node in the x and y directions during coordinate transformation, m; m is the scaling factor; θ is the rotation angle.

[0080] like Figure 2 (b) is a schematic diagram of the two-dimensional surface hydrodynamic model.

[0081] Step 5, correct the overflow data of the pipe network nodes and input them into the two-dimensional surface hydrodynamic model to simulate the rainfall waterlogging process and obtain the simulation effect.

[0082] In this embodiment, when the SWMM model is calculated, it is assumed that the network overflow always exists at the overflow node and will not flow with the terrain, which is inconsistent with the actual situation, so it is necessary to correct the network node overflow time series. If the network node overflow is positive, it means that the flow overflows from the network node. At this time, the overflow data will be transmitted to the corresponding node position in the surface two-dimensional hydrodynamic model, and the surface hydrodynamic process will be simulated as a free fluid, thereby reflecting the overflow state on the surface and accumulating in low-lying areas. When the rainfall decreases, the network drainage capacity will be greater than the drainage volume. At this time, the surface water will re-enter the network and be discharged, and the network node overflow is negative. Since the SWMM overflow generation and water discharge occur at the same node position, and the water is free to flow in the surface two-dimensional hydrodynamic model, if the SWMM overflow data is mapped in situ to the node of the surface hydrodynamic model, it will cause some high-lying network nodes to be unable to correctly simulate the process of waterlogging and waterlogging, and corrections are required.

[0083] First, according to the overflow status of the pipeline network nodes, the pipeline network nodes are divided into three categories, as shown in equations (3) to (6):

[0084] n=A+B+C (3)

[0085] A={x A |o x ≥0} (4)

[0086] B={x B |o x <0,Depth x ≥TH} (5)

[0087] C={x C |o x <0,Depth x <TH} (6)

[0088] Where n is the total number of nodes in the coupled model network; TH is the water depth threshold, cm; Set A represents the node numbers of the network nodes whose overflow is greater than or equal to 0; Set B represents the node overflow is less than 0, but the water depth at the x node is Depth x The node number that meets the water depth threshold requirement; the node overflow in set C is less than 0, and the water depth at node x is Depth x The node number that does not meet the water depth threshold requirement.

[0089] At this time, the total overflow of the coupling model is shown in formula (7):

[0090] O n =O A +O B +O C (7)

[0091] Where: O n is the total overflow volume of the network node at time t, m 3 ;O A , O B and O C are the overflow volumes of the corresponding pipe network nodes of sets A, B, and C, m 3 .

[0092] For the pipe network node x belonging to set A A , the overflow volume is not corrected; for the pipe network node x belonging to set B B , the overflow O' at node x of the two-dimensional hydrodynamic model on the surface x The overflow volume O of the corresponding node in the SWMM model can be x Correction is obtained, as shown in equations (8) to (9); for the pipe network node x belonging to set C C , and its overflow is set to 0 in the surface two-dimensional hydrodynamic model.

[0093]

[0094]

[0095] Where: k is the overflow correction coefficient.

[0096] The total surface water pumping capacity of the coupled model is calculated by the following formula:

[0097]

[0098] Where: D t is the total surface water pumping capacity of the coupled model at time t, m 3 ; α is the adjustment coefficient, which is mainly related to factors such as the flooding depth of the pipe network node and whether the rainwater grate is covered by garbage. It needs to be calibrated with historical flooding data; m is the number of pumping stations. In municipal management, for areas with deep water accumulation, pumping stations need to be called to speed up the removal of water accumulation. Its value is obtained from survey data; pump jt is the pumping capacity of the jth pumping station at time t, m 3 When the accumulated water is pumped out, the overflow is set to a negative number, which means that the accumulated water has receded.

[0099] The corrected network node overflow time series is input into the surface water dynamic model to simulate the accumulation and receding process of urban waterlogging. The calculation method is shown in equations (11) to (13):

[0100]

[0101] Where: x, y are Cartesian coordinates, m; t is time, s; h is water depth, m, u, v are flow velocities in x and y directions, m / s; z is water level, m; g is gravitational acceleration, m / s 2 ;v t is the turbulent viscosity coefficient, N·s / m 2 ; n is the Manning roughness coefficient, m / s^(1 / 3).

[0102] Step 6: Use historical flooding data to verify the simulation results.

[0103] In this embodiment, the maximum flooding range, maximum flooding depth, water accumulation process and other data of the coupled simulation are compared with the historical flooding data, and the Nash-Sutcliffe efficiency coefficient (NSE), root mean square error (RMSE), coefficient of determination (R 2) to evaluate the coupling simulation effect and check whether the model accuracy meets the requirements. If the accuracy requirements are not met, return to step 2 and use the improved particle swarm optimization algorithm to iterate and adjust the coupling model parameters such as runoff coefficient, infiltration rate, surface roughness, pipeline roughness, and pipe network outflow adjustment coefficient. The principle of the improved particle swarm optimization algorithm is as shown in equations (14) to (16):

[0104]

[0105]

[0106] Where: is the position of the i-th particle in the k-th iteration, which can represent the value of the model parameters; is the velocity of the ith particle in the kth iteration, which can represent the adjustment amount of the model parameters; P best (i) is the optimal value of particle i so far; G best is the global optimal value; c1 and c2 are non-negative learning factors; r1 and r2 are uniform random numbers generated in the range of [0, 1]. max and ω min are the maximum and minimum values ​​of the inertia weight respectively; k is the current number of iterations; T is the maximum number of iterations.

[0107] Repeat steps 3 to 5 until the simulation accuracy meets the requirements. Figure 3 shown.

[0108] Step 7: When the simulation effect is verified, the results of urban waterlogging under different design rainfall conditions are simulated and analyzed based on the SWMM model and the two-dimensional surface hydrodynamic model.

[0109] In this embodiment, a 24-hour design rainfall process under a once-in-50-year condition is calculated. The once-in-50-year design rainfall process is input into the model, and the urban rainfall waterlogging process under the design rainfall scenario is simulated and analyzed. Data such as pipe network overflow, maximum flooding range and depth, flooding duration and flooding process at different locations are output, providing method tools and data support for urban drainage network resilience assessment, waterlogging risk assessment, and emergency management decision-making. The simulation results of waterlogging depth in the target area are shown in the figure. Figure 4 shown.

[0110] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may still be modified, or some or all of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for rapid simulation of urban flooding by coupling SWMM and a two-dimensional surface hydrodynamic model, characterized in that: include: Acquire basic data, resample and interpolate the basic data, and regularize data with inconsistent time scales or spatial scales to obtain a data set; the data set includes measured rainfall data, terrain data, land use, soil type, surface building vectors, pipe network data, pump station data, and historical inundation data; Based on the data set, construct a SWMM model; The SWMM model is used to simulate the rainfall runoff and pipe network hydrodynamic process in the target area, and the overflow data of each pipe network node is calculated; Construct a two-dimensional surface hydrodynamic model based on terrain data, surface building vectors, land use and soil type data; The overflow data of the pipe network nodes are corrected and input into the two-dimensional surface hydrodynamic model to simulate the rainfall waterlogging process and obtain the simulation effect; Verifying the simulation effect using the historical flooding data; When the simulation effect is verified, the urban rainfall waterlogging results under different design rainfall conditions are simulated and analyzed based on the SWMM model and the two-dimensional surface hydrodynamic model.

2. The method according to claim 1, characterized in that Based on the data set, a SWMM model is constructed, including: Divide the target area into different sub-catchments based on topographic data; Determine the spatial layout of the pipeline network according to the pipeline network data, wherein the spatial layout of the pipeline network includes the starting point and end point, length, diameter, and slope of the pipeline; Determine the node locations of the pipeline network, the connection relationships between sub-catchments and pipeline networks; Digitize pipeline length, diameter, slope, and buried depth; According to the material and shape of the pipe network, set the roughness of the pipe network and determine whether the pipe is a pressurized pipe.

3. The method according to claim 1, characterized in that The SWMM model is used to simulate the rainfall runoff and pipe network hydrodynamic process in the target area, and the overflow data of each pipe network node are calculated, including: The measured rainfall data was input into the SWMM model to calculate the flow generation and confluence time of the target area, and the network flow, flow velocity and network node overflow data were calculated using the dynamic wave algorithm; the total overflow calculation formula is as follows: Where: O t is the total overflow of the coupled model at time t; it is the overflow volume of the ith pipe network node at time t; n is the number of pipe network nodes where overflow occurs at time t.

4. The method according to claim 3, characterized in that Based on terrain data, surface building vectors, land use and soil type data, a two-dimensional surface hydrodynamic model is constructed, including: The surface of the target area is divided using triangular or quadrilateral meshes, and the surface building vectors are considered during the division. The area where the surface buildings are located is set as a non-floodable area, and the impact of surface buildings on surface waterlogging is clarified; Interpolate terrain elevation data into the divided surface grid to form digital elevation terrain; According to the land use and soil data, the initial roughness of the surface two-dimensional hydrodynamic model is set; According to the coordinates of the pipe network nodes in the SWMM model, corresponding water source nodes are set and numbered in the surface two-dimensional hydrodynamic model, which are used to exchange simulation data between the SWMM model and the surface two-dimensional hydrodynamic model. The interactive data types include the overflow of the pipe network nodes and the surface water depth. The pipe network nodes of the SWMM model are mapped to the surface two-dimensional hydrodynamic model by the following formula (2): Where: X, Y are the horizontal and vertical coordinates of the pipe network node in the two-dimensional hydrodynamic model on the surface, D X and D Y is the translation of the network node in the x and y directions during coordinate transformation; m is the scaling factor; θ is the rotation angle, and x0, y0 are the horizontal and vertical coordinates of the network node in the SWMM model.

5. The method according to claim 4, characterized in that The overflow data of the pipe network nodes are corrected and input into the two-dimensional surface hydrodynamic model to simulate the rainfall waterlogging process and obtain the simulation results, including: According to the overflow status of the pipeline network nodes, the pipeline network nodes are divided into three categories, as shown in equations (3) to (6): n=A+B+C (3) A={x A |o x ≥0} (4) B={x B |o x <0,Depth x ≥TH} (5) C={x C |o x <0,Depth x <TH} (6) Where n is the total number of nodes in the coupled model network; TH is the water depth threshold; set A represents the overflow volume of the network node o x Node numbers greater than or equal to 0; set B represents the node overflow o x Less than 0 and the water depth at the x node is Depth x The node numbers that meet the water depth threshold requirements; Set C represents the node overflow less than 0, and the water depth Depth at the x node x The node number that does not meet the water depth threshold requirement; The total overflow of the coupling model is shown in formula (7): The n =O A +O B +O C (7) Where: O n is the total overflow of the pipe network node at time t; A , O B and O C are the overflow volumes of the corresponding pipe network nodes of sets A, B, and C respectively; For the pipe network node x belonging to set A A , the overflow volume is not corrected; for the pipe network node x belonging to set B B , the overflow O' at node x of the two-dimensional hydrodynamic model on the surface x The overflow volume O of the corresponding node in the SWMM model x Correction is obtained, as shown in equations (8) to (9); for the pipe network node x belonging to set C C , whose overflow is set to 0 in the surface two-dimensional hydrodynamic model; Where: k is the overflow correction coefficient; The total surface water pumping capacity of the coupled model is calculated by the following formula: Where: D t is the total surface water pumping capacity of the coupled model at time t, α is the adjustment coefficient, which is calibrated using historical flooding data; m is the number of pumping stations; pump jt is the pumping capacity of the jth pumping station at time t. When the accumulated water is pumped out, the overflow is set to a negative number, which means that the accumulated water in the water has receded; The corrected pipe network node overflow time series is input into the surface water dynamic model to simulate the accumulation and receding process of urban waterlogging. The simulation process is shown in equations (11) to (13): Where: x, y are Cartesian coordinates; t is time; h is water depth; u, v are flow velocities in the x and y directions, respectively; z is water level; g is gravitational acceleration; v t is the turbulent viscosity coefficient; n is the Manning roughness coefficient.

6. The method according to claim 5, characterized in that Verifying the simulation effect using the historical flooding data, including: The maximum flooding range, maximum flooding depth, and waterlogging process data of the coupled simulation are compared with the historical flooding data. The Nash efficiency coefficient, root mean square error, and determination coefficient are used to evaluate the coupling simulation effect to verify whether the model accuracy meets the requirements. If the accuracy requirements are not met, the improved particle swarm optimization algorithm is used to iterate and adjust the coupling model parameters to rebuild the SWMM model. The coupling model parameters include runoff coefficient, infiltration rate, surface roughness, pipeline roughness, and pipe network outflow adjustment coefficient. The iterative process of the improved particle swarm optimization algorithm is as follows: Where: is the position of the i-th particle in the k-th iteration, representing the value of the model parameter; is the velocity of the ith particle in the kth iteration, representing the adjustment of the model parameters; P best (i) is the current optimal value of particle i; G best is the global optimal value; c1 and c2 are non-negative learning factors; r1 and r2 are uniform random numbers generated in the range of [0, 1], ω max and ω min are the maximum and minimum values ​​of the inertia weight respectively; k is the current number of iterations; T is the maximum number of iterations; is the velocity of the ith particle in the k+1th iteration, is the position of the i-th particle in the k+1-th iteration; The reconstructed SWMM model is used to simulate the rainfall runoff and pipe network hydrodynamic process in the target area, and the overflow data of each pipe network node is recalculated. The recalculated pipe network node overflow data is corrected and input into the surface two-dimensional hydrodynamic model to simulate the rainfall waterlogging process, obtain new simulation results, and verify the new simulation results.

7. The method according to claim 5, characterized in that Based on the SWMM model and the two-dimensional surface hydrodynamic model, the results of urban flooding under different design rainfall conditions are simulated and analyzed, including: The designed rainfall processes with different return periods are input into the SWMM model, and the output of the SWMM model is input into the surface two-dimensional hydrodynamic model to simulate and analyze the urban rainfall waterlogging process under different designed rainfall scenarios, and finally output the pipe network overflow, maximum flooding range and depth, flooding duration at different locations and flooding process data.

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