Urban flood simulation method based on virtual pool network and SWMM coupling

Abstract

The invention discloses an urban flood simulation method based on virtual pool network and SWMM coupling, and the method comprises the steps: taking each sub catchment region of a research region as an independent water storage unit, and constructing a corresponding virtual pool; adjacent pools are connected through triangular weirs to form a virtual pool network reflecting the evolution of surface accumulated water; for a sub catchment area containing an inspection well, bidirectional water exchange between a virtual pool and a pipe network is established by using a transverse weir, so that overflow of the pipe network can be supplemented to the earth surface, and accumulated water on the earth surface can also be discharged into the pipe network. The surface runoff firstly enters the corresponding virtual pools and then is exchanged between the virtual pools or between the virtual pools and the pipe network through the weir structure, so that the whole process simulation of rainfall runoff-surface ponding-pipe network drainage is realized. According to the method, the precision, the efficiency and the realizability are coordinated and unified, the bottleneck that high precision and high efficiency are difficult to consider in an existing urban flood simulation technology is broken through, and the method has remarkable engineering practical value and wide popularization prospects.

Description

Technical Field

[0001] This invention relates to an urban flood simulation method based on the coupling of a virtual pool network and a SWMM, belonging to the field of urban flood simulation and control technology. Background Technology

[0002] With the acceleration of urbanization, the increase in impermeable surfaces has led to reduced rainwater infiltration and a significant increase in surface runoff, resulting in frequent urban flooding disasters and causing severe economic losses and social impacts. Urban flood simulation is a core component of flood control and drainage systems, and its accuracy and efficiency directly determine the scientific nature of risk assessment, drainage facility design, and emergency dispatch decisions.

[0003] Currently, there are three main types of methods for simulating urban flooding: (1) Physical mechanism model based on two-dimensional shallow water equations (2D Hydrodynamic Model, 2DHM). This type of model accurately simulates the evolution of surface water flow by solving the two-dimensional Saint-Venant equation (shallow water equation), and can reflect the water accumulation range and velocity distribution under complex terrain. Representative models include GAST, MIKE FLOOD, and InfoWorks ICM. However, since the two-dimensional equation system needs to be solved explicitly or implicitly at high spatial resolution, its computational load is extremely large and it is highly dependent on computing resources. In large-scale urban areas or high-frequency real-time forecast scenarios, it is often difficult to meet the "rapid response" requirement. In addition, this type of model requires high-precision terrain and drainage system data. Actual urban pipe network data is often outdated or missing, which further limits its application. (2) One-dimensional pipe network model based on SWMM. SWMM is short for Storm Water Management Model. It was developed and open-sourced by the U.S. Environmental Protection Agency and is currently the most widely used urban stormwater analysis model. It uses one-dimensional dynamic wave equations to simulate the unsteady flow process of pipes, and is computationally efficient and stable. However, the traditional SWMM surface runoff generation module uses a distributed generalized hydrological model, which lacks characterization of the spatial distribution of surface water accumulation and surface water flow. Although nodes in SWMM can be set as overflow nodes to represent water accumulation phenomena, they cannot realistically reproduce the diffusion, confluence and interconnection of water accumulation areas, resulting in insufficient simulation accuracy of flood spatial distribution. (3) Coupled Hydrodynamic and Hydraulic Model (CHHM). To make up for the shortcomings of SWMM, some researchers have proposed to couple one-dimensional pipe networks with two-dimensional surface models by “node overflow triggering two-dimensional shallow water equations” to achieve flood simulation of two-way exchange between surface and subsurface. This method improves the representation of dynamic changes in water accumulation to some extent, but still has significant problems, including: ① When overflow does not occur, the surface water level fails to dynamically respond to rainfall and runoff processes, making it difficult to characterize the early stage of water accumulation formation; ② The coupling interface is complex, and the stability of the interaction between the surface and the pipe network depends on the time step and the matching of boundary conditions; ③ The two-dimensional calculation part still requires high computing power, making it difficult to use in large-scale or real-time predictions.

[0004] In summary, existing urban flood simulation methods still face a difficult trade-off between computational accuracy, computational efficiency, and model universality. Two-dimensional physical models offer high accuracy but come with enormous computational costs; one-dimensional SWMM models are efficient but fail to adequately depict surface processes; and hydro-hydraulic coupled models offer a compromise to some extent, but are still limited by complex data requirements and computational burdens.

[0005] Therefore, there is still an urgent need for a lightweight modeling method that can realize the diffusion of surface water and bidirectional exchange between the surface and the pipe network, which can maintain high simulation accuracy and have extremely high computational efficiency, making it easy to embed into real-time early warning and urban drainage scheduling systems. Summary of the Invention

[0006] The technical problem to be solved by this invention is to provide an urban flood simulation method based on the coupling of virtual pool network and SWMM. Without changing the core structure of the commonly used open source SWMM, a virtual pool network is introduced, and the water exchange process between the surface space and the surface-pipe network is simulated through the weir structure. This realizes the simulation of the whole process of urban flood within SWMM, overcoming the bottleneck of existing models that are difficult to balance accuracy and efficiency.

[0007] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A method for simulating urban flooding based on the coupling of a virtual pool network and a Swimming Scale (SWMM) includes the following steps: Step 1: Obtain land use data, digital elevation model and underground pipe network topology data of the area to be studied. Use the method of combining hydrological analysis and Thiessen polygons to divide the area to be studied into several sub-catchment areas. Build the surface hydrological model and the underground one-dimensional pipe network model of the area to be studied on the SWMM platform. Step 2: Establish a virtual pool corresponding to the terrain for each sub-catchment area. Each sub-catchment area is connected to the corresponding virtual pool. The flow calculated from the production and drainage of each sub-catchment area is fed into the corresponding virtual pool to describe the surface water storage process of each sub-catchment area. Step 3: Use triangular weirs to connect adjacent sub-catchments to form a virtual pool network, which is used to describe the water flow process between the various sub-catchments on the surface. Step 4: For sub-catchment areas containing manhole nodes, a cross weir is used to establish a two-way water exchange between the virtual pool corresponding to the sub-catchment area containing manhole nodes and the corresponding manhole nodes of the underground pipe network, so that the overflow of the underground pipe network can replenish the surface, and the surface water can be discharged into the underground pipe network. Step 5: Calculate surface runoff and runoff, and calculate underground pipe network runoff, and output the water level of the virtual pool and underground pipe network inspection well nodes in real time; Step 6: Based on the real-time water level of the virtual pool, reconstruct the surface water depth space and output the water level and water accumulation area information of the virtual pool.

[0008] As a preferred embodiment of the present invention, in step 1, the land use data includes the underlying surface type, surface roughness, impermeability, and infiltration parameters; the underground pipe network topology data includes manhole nodes, pipes, and outlets, and the manholes are located in the same topographic spatial position as the area to be studied.

[0009] As a preferred embodiment of the present invention, in step 1, the area to be studied is divided into several sub-catchment areas using a combination of hydrological analysis and Thiessen polygons, as detailed below: Based on the topographic features and drainage pipeline distribution of the area to be studied, the area to be studied is preliminarily divided into several sub-basins using hydrological analysis tools; Within each sub-basin, based on the spatial distribution of manhole nodes, the Thiessen polygon method is used to further subdivide each sub-basin, so that each manhole node corresponds to a sub-catchment area, thereby obtaining the sub-catchment area boundary that conforms to the characteristics of the actual drainage system.

[0010] As a preferred embodiment of the present invention, the specific process of step 2 is as follows: A virtual pool corresponding to the terrain is created for each sub-catchment area. The virtual pool is represented by the Storage Units component in SWMM. From the digital elevation model of the area to be studied, the elevation of the lowest point of each sub-catchment is extracted as the virtual pool bottom height corresponding to each sub-catchment; The water level is gradually increased by a preset step size, and the effective submerged area at the corresponding water level is calculated to form a depth-area curve. The depth-area curve is then input into the corresponding virtual pool attributes to enable the virtual pool to store water. Each sub-catchment is connected to a corresponding virtual pool, and the flow calculated from the production and drainage of each sub-catchment is channeled into the corresponding virtual pool, realizing the process from rainfall to water storage.

[0011] As a preferred embodiment of the present invention, the specific process of step 3 is as follows: Construct an equivalent triangular weir to connect adjacent sub-catchments, forming a virtual pool network to describe the water flow confluence process between various sub-catchments on the surface; The equivalent triangular weir is represented by the V-notch Weirs component in SWMM. The lowest elevation, maximum elevation difference, and horizontal width of the interface profile of adjacent sub-catchments are extracted and used as the bottom elevation, height, and crest width of the equivalent triangular weir connecting the two adjacent sub-catchments, respectively.

[0012] As a preferred embodiment of the present invention, the specific process of step 4 is as follows: For a sub-catchment containing a manhole node, a cross weir is set between the virtual pool corresponding to the sub-catchment containing the manhole node and the corresponding pipe network manhole node; the bottom height of the cross weir is set to the ground elevation of the manhole, and the width of the weir crest is taken as the circumference of the manhole opening. When the water level of the virtual pool corresponding to the sub-catchment area containing the inspection well node is higher than the bottom height of the cross weir, the surface water flows into the pipe network; when the water level of the underground pipe network inspection well node is higher than the bottom height of the cross weir, it flows back to the surface; thus realizing bidirectional dynamic exchange between the surface and underground pipe networks without the need for external models or additional interfaces.

[0013] In a preferred embodiment of the present invention, in step 6, the surface water depth space is reconstructed based on the real-time water level of the virtual pool, as follows: For each sub-catchment, the water depth at each grid point is calculated using the elevation difference between the grid point elevation in the digital elevation model and the bottom elevation of the virtual pool: , in, For grid points The water depth, This represents the virtual water level in the pool. The difference in elevation between the grid points and the bottom of the virtual pool is used to estimate the water depth distribution and inundation range at any location on the Earth's surface.

[0014] A computer device includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to implement the steps of the urban flood simulation method based on virtual pool network coupled with SWMM.

[0015] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the urban flood simulation method based on the coupling of a virtual pool network and SWMM.

[0016] Compared with the prior art, the present invention, employing the above technical solution, has the following technical effects: 1. This invention requires no external two-dimensional hydrodynamic module; it can simulate the entire process of urban flooding solely based on the native SWMM computational framework. Its model structure and parameter setting methods are compatible with existing drainage system models and can be directly integrated into urban drainage simulation systems of different regions and scales, exhibiting excellent portability and scalability.

[0017] 2. This invention replaces the two-dimensional hydrodynamic equations with a "virtual pool" and uses weir components to represent the surface water flow and surface-to-pipeline exchange process, which effectively reduces the number of calculation equations and time step iterations, enabling the model to complete large-area flood calculations in a very short time and meet the application requirements of real-time early warning and rapid dispatch.

[0018] 3. This invention uses triangular weir and cross weir structure to realize the hydraulic connection between virtual water pools and between water pools and pipe networks, which can continuously and dynamically describe the entire process of surface water formation, diffusion and receding under rainfall conditions, overcoming the defect of traditional SWMM model that cannot simulate the evolution process of surface water.

[0019] 4. This invention calculates the surface water depth distribution by comparing the water level in a virtual pool with the elevation difference in a digital elevation model. It can quickly restore the water accumulation range and depth without introducing a two-dimensional shallow water equation, achieving a refined expression of the spatial pattern of floods and balancing spatial accuracy and computational efficiency.

[0020] 5. The method proposed in this invention is applicable to both offline scenarios such as urban drainage planning and pipeline renovation, and online scenarios such as real-time forecasting and emergency dispatching. Its flexible structure and lightweight features allow it to be embedded in various types of systems, including smart water management, flood warning, and dispatch optimization.

[0021] 6. The parameters of the virtual pool and weir structure proposed in this invention can be automatically extracted or calibrated using DEM and conventional drainage system data, avoiding complex two-dimensional mesh division and boundary setting, and simplifying the model building and application process. Attached Figure Description

[0022] Figure 1 This is a flowchart of the urban flood simulation method based on the coupling of virtual pool network and SWMM proposed in this invention; Figure 2 This is a modeling process for urban flooding, where (a) is a diagram of a real urban flooding process, (b) is a simplified diagram of the SWMM model principle, and (c) is a simplified diagram of the StoSWMM model principle. Figure 3 This is an overview of the study area in this embodiment of the invention, wherein (a) is the drainage network of the study area, (b) is the land use, and (c) is the high-precision digital elevation model (DEM). Figure 4 This is the process of establishing the StoSWMM model, where (a) is the traditional SWMM model, (b) is the virtual pool, and (c) is the StoSWMM model. Figure 5 This is a comparison of the maximum flooding distribution results of three models under a 50-year return period rainfall scenario; Figure 6 This is a comparison of water accumulation processes at different locations under a 50-year return period rainfall scenario. Among them, (a) is the point with the largest water accumulation, (b) is a relatively large water accumulation point, and (c) is a water accumulation point in a low-lying area without pipe network. Detailed Implementation

[0023] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0024] like Figure 1 As shown, this invention proposes an urban flood simulation method based on the coupling of a virtual water pool network and a surface water model (SWMM) (StoSWMM). This method introduces a virtual water pool network into the SWMM framework, and by explicitly characterizing the accumulation and exchange process of surface water, it bridges the gap between the simulation method and the actual flood process. Figure 2 As shown in (a)-(c) of the diagram. Compared with the traditional "nodal overflow" model of SWMM, StoSWMM more closely reflects the coupling characteristics of complex urban surfaces and pipe networks, providing a new approach for the efficient characterization of the spatial distribution and temporal evolution of floods. The specific steps are as follows: Step 1: Data Preparation and Construction of Traditional SWMM Model 1. Obtain land use data (underlying surface type, surface roughness, impermeability, infiltration parameters, etc.) and a high-precision digital elevation model (DEM) for the study area; 2. Obtain pipeline topology data (inspection wells, pipes, outlets, etc.) and ensure that the nodes are consistent with the spatial location of the terrain; 3. Based on surface and underground pipe network data, a traditional SWMM model is constructed. The specific process is similar to that of technicians in the same field and will not be elaborated further. When dividing sub-catchments, each sub-catchment should ideally contain only one depression to avoid deviations in the virtual water storage and drainage simulation caused by multiple depressions. Therefore, a combination of hydrological analysis and Thiessen polygons is preferred: first, combining the topographic features of the study area and the distribution of drainage pipes, hydrological analysis tools are used to initially delineate larger sub-basins; then, within each sub-basin, based on the spatial distribution of manhole nodes, the Thiessen polygon method is used for further subdivision, so that each manhole node corresponds to a sub-catchment, thereby obtaining sub-catchment boundaries that better reflect the characteristics of the actual drainage system.

[0025] Step 2: Create a virtual pool unit 1. A virtual water reservoir corresponding to the terrain is established for each sub-catchment to describe the surface water storage process in that area. The virtual water reservoir is represented by the "Storage Units" component in SWMM; 2. Extract the elevation of the lowest point of the sub-catchment area from the DEM as the virtual pool bottom elevation; 3. Gradually increase the water level with a fixed step size (preferably 0.01~0.05 m), calculate the effective submerged area at the corresponding water level, and form a depth-area curve; 4. Input the depth-area curve into the corresponding virtual pool attributes to enable the virtual pool to store water. 5. Each sub-catchment area is connected to the corresponding virtual pool, indicating that the flow obtained from its production and catchment calculations flows into the virtual pool, realizing the process from rainfall to water storage.

[0026] Step 3: Build a virtual pool network 1. Construct an equivalent triangular weir to connect adjacent pools, and extract the lowest elevation, maximum elevation difference, and horizontal width of the junction profile, which are used as the weir bottom elevation, weir height, and weir crest width, respectively. 2. The above weir structure is represented by the "V-notchWeirs" component of SWMM. Adjacent virtual pools are connected to form a complete virtual pool network, which is used to describe the water flow process between various water catchment areas on the surface.

[0027] Step 4: Two-way water exchange between the surface and the pipe network 1. For sub-catchment areas that include inspection wells, a transverse weir is set between the virtual water tank and the corresponding pipe network node. 2. The bottom height of the cross weir is set as the elevation of the manhole ground, the width of the weir crest is taken as the circumference of the manhole opening, and the flow coefficient is set based on experience. 3. The cross weir allows bidirectional flow: when the water level in the virtual pool is higher than the weir bottom, it flows into the pipe network; when the water level at the pipe network node is higher than the weir bottom, it flows back to the surface. This setting can achieve bidirectional dynamic exchange between the surface and the pipe network within the SWMM framework, without the need for external models or additional interfaces.

[0028] Step 5: Calculation of surface runoff and pipeline runoff 1. The surface runoff generation and confluence process adopts the existing rainfall-runoff generation and confluence module of SWMM; 2. The pipeline flow calculation adopts the dynamic wave algorithm built into SWMM, which is a non-steady flow simulation method based on the Saint-Venant equation; 3. During the simulation, the water levels of the virtual pool and the pipe network nodes are updated simultaneously at each time step to achieve joint evolution of the surface and underground.

[0029] Step 6: Surface water depth spatial reconstruction 1. Simulate and output the real-time water level of each virtual pool, representing the submerged water depth at the lowest point of the corresponding sub-catchment area; 2. For each sub-catchment area, calculate the water depth at that point using the elevation difference between each grid point in the DEM and the bottom elevation of the virtual pool: , in, For grid points i The water depth, This represents the virtual water level in the pool. For grid points The difference in elevation between the water level and the bottom of the virtual pool allows for rapid estimation of water depth distribution and inundation range at any location on the Earth's surface without solving the two-dimensional shallow water equation, achieving an approximate two-dimensional spatial distribution effect.

[0030] Step 7: Output and Analysis 1. Output information such as the water level and water area of ​​the virtual pool; 2. Generate water depth distribution maps, water accumulation process curves, and overflow statistics as needed.

[0031] Through the above steps, this invention significantly reduces computational complexity while maintaining high physical consistency, achieving unified simulation of the entire urban flooding process (rainfall - surface runoff - surface water accumulation - groundwater drainage). This method combines the accuracy of a physical model with the efficiency of a simplified model, and can be widely applied to real-time simulation, early warning scheduling, and drainage system optimization design in large-scale urban areas.

[0032] The method of the present invention will be described below with reference to a specific embodiment.

[0033] I. Implementation Area and Data Source A typical university campus area was selected as a demonstration research area (e.g.) Figure 3 (As shown in (a)-(c)). The terrain in this area is relatively flat, with a higher elevation in the west and a lower elevation in the east. The drainage network layout is clear, exhibiting representative urban drainage structure characteristics. The study area covers approximately 0.7 km², containing over 160 inspection wells, over 160 pipes, and 3 outlets. Topographic data was generated using a 1m resolution digital elevation model (DEM) from RTK measurements; land use data was derived from remote sensing image classification results; and pipe network topology data was obtained from drainage system design drawings and field surveys. Rainfall events were designed based on the Chicago rainfall pattern (50-year return period, peak rainfall coefficient of 0.4, time interval of 1 minute, total rainfall duration of 120 minutes) to examine the model's performance under extreme short-duration rainfall scenarios.

[0034] II. Model building and parameterization, such as Figure 4 As shown in (a)-(c) 1. Construction of Traditional SWMM Model A one-dimensional pipe network model of the study area was established on the SWMM platform, defining sub-catchments, manholes, pipes, and outlet nodes. The Manning roughness of the impermeable and permeable zones were set to 0.018 and 0.20, respectively. The area, impermeability, and average slope of each sub-catchment were obtained through GIS statistics, and infiltration parameters were assigned values ​​based on the land surface type.

[0035] 2. Construction of Virtual Water Pool Units For each sub-catchment, the DEM data is cropped, and the lowest point elevation is extracted as the bottom height of the virtual pool. The water level is gradually increased in steps of 0.02m, and the submerged area at each water level is calculated to obtain the depth-area curve. This depth-area curve is then input into the Storage Units module of SWMM, giving the virtual pool variable water storage capacity.

[0036] 3. Construction of Virtual Pool Network The interface profiles of adjacent sub-catchments are extracted from the DEM. Each pair of sub-catchments that meet the elevation connectivity conditions is connected by an equivalent triangular weir. The weir base height is taken as the elevation of the lowest point in the profile, the weir height is taken as the maximum elevation difference, the weir crest width is determined by the width of the interface profile, and the flow rate system is set to a large value to ensure unimpeded water exchange between surface pools (here uniformly set to 5). The triangular weir is added to SWMM in the form of a V-notch Weir component to realize the surface overflow connection between adjacent pools, forming a virtual pool network covering the entire area.

[0037] 4. Two-way water exchange between the virtual water tank and the pipe network In sub-catchments containing manholes, a transverse weir is installed between the virtual water tank and the corresponding pipe network node. The weir base height is taken from the ground elevation, the weir crest width is taken from the manhole perimeter, and the flow coefficient is empirically set to 1.0. The transverse weir allows bidirectional flow: when the surface water level is higher than the ground threshold, water flows into the pipe network; when the water level at the pipe network node is higher than the ground, overflow occurs and flows back to the surface. This setup can achieve dynamic coupling between the surface and the pipe network within the SWMM framework, without the need for an external two-dimensional model.

[0038] 5. Solving and Time Step Setting StoSWMM employs the Horton infiltration model and nonlinear reservoir model, commonly used in the SWMM architecture, for surface runoff generation and runoff calculations. The hydraulic calculations for the pipe network utilize the dynamic wave method based on the one-dimensional Saint-Venant equations. Virtual pool units and pipe network nodes are coupled and updated within the same time step, achieving synchronous balance between surface and groundwater volumes.

[0039] III. Simulation Process and Results 1. The process of water accumulation The simulation of the rainfall process using this method shows that in the early stage of rainfall, the runoff from each sub-catchment area rapidly flows into the corresponding virtual pool, and water accumulation first appears in local depressions; as the rainfall intensifies, water exchange occurs between the virtual pools through weir structures, and the water accumulation area expands over time.

[0040] When the local water level exceeds the wellhead elevation, the cross weir channel activates drainage, allowing rainwater to flow into the pipe network. During extreme rainfall, if the water level at some nodes exceeds the limit, reverse overflow occurs, further expanding the waterlogged area. After the rainfall stops, the surface water gradually recedes over time, forming a complete dynamic process of "accumulation-overflow-receding".

[0041] 2. Characteristics of surface water depth distribution, such as Figure 5 As shown By utilizing the difference between the water level in a virtual pool and the elevation of a DEM (Digital Elevation Model), the surface water depth distribution at various times can be rapidly reconstructed. Results show that the water depth is highly consistent with topographic changes, with significant water accumulation in low-lying areas and rapid receding water in areas with topographic slopes. This method can obtain an approximate two-dimensional spatial water distribution without requiring calculations using two-dimensional shallow water equations, exhibiting good spatial continuity.

[0042] IV. Performance Comparison and Application Results To highlight the performance advantages of the StoSWMM method proposed in this invention, two representative commonly used methods are selected as comparison objects: two-dimensional surface hydrodynamic models (2DHM) and coupled hydrodynamic models based on manhole overflow (CHHM). The 2DHM method can accurately depict the flood evolution process under complex underlying surface conditions, and is therefore considered a benchmark model for comparing high-precision simulation results of urban flooding. The CHHM method, by reducing the use of the two-dimensional model in the non-overflow stage of nodes, significantly reduces the computational burden and has high efficiency over large-scale areas, thus gaining widespread application in engineering. However, its drawback lies in the fact that the water accumulation evolution before overflow depends on a simplified model, making it difficult to accurately depict the spatial distribution and dynamic changes of surface water storage, thereby limiting its application in localized refined flood risk analysis.

[0043] 1. Comparison of surface inundation results Surface inundation is a key focus in urban flood simulation. For ease of direct comparison, the StoSWMM model uses the same surface grid as 2DHM and CHHM for surface inundation calculations. Figure 5 The maximum flooding distribution results obtained from three models are presented. Overall, based on the 2DHM simulation results, both the StoSWMM and CHHM models can reproduce the flooding pattern of the study area well, especially in the most severely flooded areas. However, differences exist among the three models in areas with missing pipe networks, with CHHM performing the worst. This is because it can only reflect the water accumulation evolution near manholes. Conversely, StoSWMM, relying on a virtual pool network, can capture the water accumulation evolution across the entire area, and its simulation results in areas with missing pipe networks are still close to those of 2DHM. In summary, StoSWMM is closer to 2DHM in terms of accuracy in simulating water accumulation across the entire area, while CHHM has limited applicability in areas with missing pipe networks and far from manholes.

[0044] In addition, the water accumulation process was compared at different locations (the point of maximum water depth, the point of greater water depth, and local depressions), and the results are as follows: Figure 6As shown in (a)-(c), the simulation results of StoSWMM at all three locations fit well with 2DHM (NSE between 0.96 and 0.98), accurately reproducing the dynamic changes of the water accumulation process; while the simulation effect of CHHM is relatively poor, and it cannot reproduce the water accumulation process at depressions where the pipe network is missing, such as... Figure 6 As shown in (c) above. It is worth noting that while CHHM's estimation of peak water accumulation at the maximum and deeper water points is relatively accurate, its water accumulation initiation time lags significantly behind StoSWMM and 2DHM. This discrepancy stems from CHHM's use of nodal overflow as the trigger for surface inundation, which differs from the actual runoff generation and confluence mechanism, leading to insufficient early warning. In contrast, StoSWMM, relying on a virtual pool network structure, can simulate the evolution of water accumulation in low-lying areas earlier after runoff formation, better reflecting real urban flooding processes.

[0045] 2. Comparison of model computational efficiency Numerical simulations were performed on a computer equipped with a Core™ i9-12900KF (3.20 GHz) CPU and 32.0 GB of memory. During the same 300-minute simulation duration, 2DHM took 647 seconds, CHHM took 125 seconds, while StoSWMM took only 2 seconds. CHHM's computation time was more than 40 times that of StoSWMM, while 2DHM's was more than 300 times longer, demonstrating a significant difference in computational efficiency. Therefore, StoSWMM maintains high simulation accuracy while offering extremely high timeliness, making it particularly suitable for applications such as rapid urban flood simulation, real-time early warning, and drainage scheme optimization.

[0046] The application of this invention in typical urban areas demonstrates that the model can accurately depict the entire process of surface water formation and receding, and the generated water distribution pattern is basically consistent with actual observations. This method significantly improves computational efficiency while maintaining high spatial accuracy, enabling rapid flood simulation of rainfall scenarios on ordinary computers. The model structure is fully compatible with existing SWMM input files, facilitating direct integration with existing drainage models, and can serve as a foundational model for urban flood risk analysis, drainage system optimization, and intelligent scheduling.

[0047] Based on the same inventive concept, this application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the aforementioned urban flood simulation method based on the coupling of virtual pool network and SWMM.

[0048] Based on the same inventive concept, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the aforementioned urban flood simulation method based on virtual pool network coupled with SWMM.

[0049] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0050] This invention is described with reference to flowchart illustrations of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each step in the flowchart, and combinations of steps in the flowchart, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing device, generate instructions for implementing the steps in the flowchart. Figure 1 A device for a function specified in one or more processes.

[0051] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 The function specified in one or more processes.

[0052] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 Steps of a specified function in one or more processes.

[0053] The above embodiments are merely illustrative of the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solutions based on the technical concept proposed in this invention shall fall within the scope of protection of this invention.

Claims

1. A city flood simulation method based on virtual pool net coupling with SWMM, characterized in that, The method comprises the following steps: Step 1, obtaining land use data, digital elevation model and underground pipe network topology data of a region to be studied, dividing the region to be studied into a plurality of sub-catchment areas by using a hydrological analysis-Tesler polygon combination method, and establishing a surface hydrological model and a one-dimensional underground pipe network model of the region to be studied on a SWMM platform; Step 2, establishing a virtual pool corresponding to the terrain for each sub-catchment area, connecting each sub-catchment area with the corresponding virtual pool, and flowing the flow calculated by the sub-catchment area into the corresponding virtual pool to describe the surface water storage process of each sub-catchment area; Step 3, connecting adjacent sub-catchment areas by using a triangular weir to form a virtual pool network for describing the water flow process between the surface sub-catchment areas; Step 4, for the sub-catchment area containing a manhole node, establishing a two-way water exchange between the virtual pool corresponding to the sub-catchment area containing the manhole node and the corresponding manhole node of the underground pipe network by using a cross-section weir, so that the underground pipe network overflow can be replenished to the surface, and the surface accumulated water can be discharged into the underground pipe network; Step 5, calculating the surface runoff and flow concentration, and calculating the underground pipe network flow concentration, and outputting the water level of the virtual pool and the manhole node of the underground pipe network in real time; Step 6, according to the real-time water level of the virtual pool, reconstructing the surface water depth space, and outputting the water level and accumulated water area information of the surface virtual pool.

2. The urban flood simulation method based on virtual pool net and SWMM coupling according to claim 1, characterized in that, In the step 1, the land use data includes underlying surface types, surface roughness, impermeable rate and infiltration parameters; the underground pipe network topology data includes manhole nodes, pipes and water outlets, and the manhole nodes are consistent with the spatial positions of the terrain of the region to be studied.

3. The urban flood simulation method based on virtual pool mesh and SWMM coupling according to claim 1, characterized in that, In the step 1, the region to be studied is divided into a plurality of sub-catchment areas by using a hydrological analysis-Tesler polygon combination method, and the specific process is as follows: According to the terrain characteristics and the distribution of the drainage pipe of the region to be studied, the region to be studied is preliminarily divided into a plurality of sub-basins by using a hydrological analysis tool; In each sub-basin, according to the spatial distribution of the manhole nodes, each sub-basin is further subdivided by using a Tesler polygon method, so that each manhole node corresponds to a sub-catchment area, thereby obtaining a sub-catchment area boundary conforming to the characteristics of the actual drainage system.

4. The urban flood simulation method based on virtual pool net and SWMM coupling according to claim 1, characterized in that, The specific process of the step 2 is as follows: A virtual pool corresponding to the terrain is established for each sub-catchment area, and the virtual pool is represented by using a StorageUnits component in SWMM; The lowest point elevation of each sub-catchment area is extracted from the digital elevation model of the region to be studied as the bottom height of the virtual pool corresponding to the sub-catchment area; The water level is gradually increased at a preset step length, the effective flooded area at the corresponding water level is calculated, a depth-area curve is formed, and the depth-area curve is input into the corresponding virtual pool attribute, so that the virtual pool has water storage capacity; Each sub-catchment area is connected with the corresponding virtual pool, and the flow calculated by the sub-catchment area is flowed into the corresponding virtual pool, so as to realize the process from rainfall to water storage.

5. The urban flood simulation method based on virtual pool net and SWMM coupling according to claim 1, characterized in that, The specific process of the step 3 is as follows: Equivalent triangular weirs are constructed to connect adjacent sub-catchment areas to form a virtual pool network for describing the water flow process between the surface sub-catchment areas; The equivalent triangular weir is represented by the V-notch Weirs component in SWMM. The lowest elevation, the maximum height difference and the horizontal width of the intersection profile of adjacent subcatchments are extracted as the weir bottom elevation, weir height and weir top width of the equivalent triangular weir connecting the adjacent two subcatchments.

6. The urban flood simulation method based on virtual pool mesh coupling with SWMM according to claim 1, characterized in that, The specific process of step 4 is as follows: For the subcatchment containing the inspection well node, a cross weir is set between the virtual pool corresponding to the subcatchment containing the inspection well node and the corresponding pipe network inspection well node; the bottom height of the cross weir is set as the ground elevation of the inspection well, and the weir top width is taken as the circumference of the well mouth; When the water level of the virtual pool corresponding to the subcatchment containing the inspection well node is higher than the bottom height of the cross weir, the surface accumulated water flows into the pipe network; when the water level of the underground pipe network inspection well node is higher than the bottom height of the cross weir, it flows back to the surface; thereby realizing the bidirectional dynamic exchange between the surface and the underground pipe network, without the need for external models or additional interfaces.

7. The urban flood simulation method based on virtual pool net and SWMM coupling according to claim 1, characterized in that, In step 6, according to the real-time water level of the virtual pool, the surface water depth space is reconstructed, which is as follows: For each subcatchment, the water depth of each grid point is calculated by using the height difference between the elevation of each grid point in the digital elevation model and the bottom height of the virtual pool: ， wherein, is the water depth at the grid point is the water depth at the grid point is the virtual water pool water level, is the water depth at the grid point is the height difference between the grid point and the virtual water pool bottom height; thereby estimating the water depth distribution and the inundation area at any location on the ground surface.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, The processor executes the computer program to realize the steps of the urban flood simulation method based on the coupling of the virtual pool network and SWMM according to any one of claims 1 to 7.

9. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 8. The computer program is executed by the processor to realize the steps of the urban flood simulation method based on the coupling of the virtual pool network and SWMM according to any one of claims 1 to 7.

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