Methods, apparatus, equipment and storage media for rainfall inundation analysis of the target area

Abstract

This application discloses a method, apparatus, device, and storage medium for analyzing rainfall-induced inundation in a target area. The method includes: obtaining an initialized water depth model for the target area based on a digital elevation model and cumulative rainfall information; updating the water depth of all grid cells in the initialized water depth model using a hydrodynamic model to obtain an updated water depth model; and obtaining a water depth map of the target area based on the updated water depth model. This solution enables the analysis of urban flooding caused by rainfall.

Description

Technical Field

[0001] This application relates to the field of geographic information technology, and in particular to a method, apparatus, equipment and storage medium for analyzing rainfall inundation in a target area. Background Technology

[0002] Urban flooding caused by short-duration heavy rainfall is a frequent natural disaster faced by many cities, posing a serious threat to people's lives and property. Inundation analysis technology can predict the area and depth of water accumulation during flooding, thus providing a basis for decision-making in municipal planning and construction, flood control material allocation, and personnel evacuation.

[0003] Existing inundation analyses can generally be divided into passive inundation analysis and active inundation analysis. Passive inundation analysis does not consider the source of the flood or the connectivity of the surface; it simply sets a flood head height. Areas within the target region where the ground elevation is below the flood head height are considered inundated, while areas where the ground elevation is above the flood head height are considered non-inundated. Active inundation analysis considers the source of the flood and the connectivity of the surface, and is applicable to situations where localized, sudden, point-like or linear flood sources spread and inundate the surrounding areas according to the terrain, such as the passage of flood peaks or dam breaches.

[0004] For urban flooding analysis caused by rainfall, the flood source is isomorphic, with rainwater converging towards low-lying areas after falling to the ground, representing a type of isomorphic water source inundation analysis. Existing urban flooding analysis combines Geographic Information System (GIS) and Stormwater Flood Management Modeling (SWMM) software. GIS provides detailed urban hydrological information to establish a high-precision urban hydrodynamic model. SWMM software then simulates the flow rates at pipes, rivers, and the surface, calculating overflow data at pipe points. This overflow is then used as the initial water depth, and the "window method" is used to simulate surface water accumulation, ultimately obtaining the water distribution and depth. However, establishing a city-level hydrological-hydrodynamic model requires a large amount of external data. Besides digital elevation models (DEMs), it also requires information on the underlying surface, pipe network parameters, hydrological data, and surrounding river network data. This modeling is difficult and costly, and the errors in various data points can accumulate, affecting the accuracy of the initial water accumulation calculation. Therefore, designing a rainfall flooding analysis method that does not rely on additional data beyond digital elevation models is crucial and of great significance. Summary of the Invention

[0005] The main technical problem addressed by this application is to provide a method, apparatus, equipment, and storage medium for analyzing rainfall inundation in a target area, which can realize urban rainfall inundation analysis based on a digital elevation model without relying on additional data outside of the digital elevation model.

[0006] To address the aforementioned issues, the first aspect of this application provides a method for analyzing rainfall inundation in a target area. The method includes: obtaining an initialized water depth model corresponding to the target area based on a digital elevation model and cumulative rainfall information; updating the water depth of all grids in the initialized water depth model using a hydrodynamic model to obtain an updated water depth model; and obtaining a water depth map of the target area based on the updated water depth model.

[0007] The step of obtaining an initial water depth model for the target area based on the digital elevation model and cumulative rainfall information of the target area includes: generating a water depth model for the target area using the digital elevation model and cumulative rainfall information of the target area; and initializing the water depth model using the cumulative rainfall distribution of the target area to obtain the initial water depth model for the target area.

[0008] The step of updating the water depth of all grids in the initialized water depth model using a hydrodynamic model to obtain an updated water depth model includes: establishing the hydrodynamic model within a preset range for each grid of the initialized water depth model; calculating the water depth update amount for each grid using the hydrodynamic model; and updating the water depth of each grid according to the water depth update amount to obtain the updated water depth model.

[0009] The preset range is either an eight-connected region or a four-connected region.

[0010] The step of calculating the water accumulation update amount of each grid cell using the hydrodynamic model includes: for the current grid cell, calculating the water flow rate between the current grid cell and surrounding grid cells within a preset range of the current grid cell using the hydrodynamic model; and obtaining the water accumulation update amount of the current grid cell based on the water flow rate between the current grid cell and surrounding grid cells within the preset range of the current grid cell.

[0011] Specifically, the step of calculating the water flow rate between the current grid and surrounding grids within a preset range of the current grid using the hydrodynamic model includes: calculating the water surface height of the current grid and surrounding grids within the preset range of the current grid for the current grid; calculating the water surface height difference between the current grid and surrounding grids based on the water surface height of the current grid and surrounding grids within the preset range of the current grid; and determining the water flow rate between the current grid and surrounding grids within the preset range of the current grid based on the water depth of the current grid and the water surface height difference between the current grid and surrounding grids.

[0012] The step of calculating the water surface height difference between the current grid and the surrounding grids based on the water surface height of the current grid and the surrounding grids within a preset range of the current grid includes: calculating the water surface height difference between the current grid and the surrounding grids using a preset number of convolutional kernels to obtain a water surface height difference map between the current grid and the surrounding grids; the preset number is the same as the number of surrounding grids within a preset range of the current grid, and the water surface height difference map includes water surface height differences corresponding to a preset number of channels, each channel corresponding to the direction between the current grid and a surrounding grid; the step of determining the water surface height difference between the current grid and the surrounding grids based on the water depth of the current grid and the water surface height difference between the current grid and the surrounding grids within a preset range of the current grid includes: calculating the water surface height difference between the current grid and the surrounding grids using a preset number of convolutional kernels to obtain a water surface height difference map between the current grid and the surrounding grids; the preset number is the same as the number of surrounding grids within a preset range of the current grid, and the water surface height difference map includes a preset number of channels corresponding to the water surface height difference, each channel corresponding to the direction between the current grid and a surrounding grid; the step of determining the water surface height difference between the current grid and the surrounding grids based on the water depth of the current grid and the water surface height difference between the current grid and the surrounding grids includes: calculating the water surface height difference between the current grid and the surrounding grids within a preset range of the current grid. The water flow rate between surrounding grids within a preset range of the front grid includes: obtaining a water flow rate map between the current grid and the surrounding grids based on the relationship between the water surface elevation difference corresponding to each channel in the water surface elevation difference map and the water depth of the current grid, and a preset water flow rate factor; the water flow rate map includes water flow rates corresponding to a preset number of channels, each channel corresponding to the direction between the current grid and a surrounding grid; obtaining the water depth update of the current grid based on the water flow rate between the current grid and the surrounding grids within a preset range of the current grid includes: stacking the preset number of convolutional kernels, and performing a convolution operation on the water flow rate map using the stacked convolutional kernels to obtain the water depth update of the current grid.

[0013] To address the aforementioned problems, a second aspect of this application provides a rainfall inundation analysis device for a target area, comprising: an initialization module, configured to obtain an initialized water depth model corresponding to the target area based on a digital elevation model and cumulative rainfall information corresponding to the target area; a processing module, configured to update the water depth of all grids in the initialized water depth model using a hydrodynamic model to obtain an updated water depth model; and an acquisition module, configured to obtain a water depth map of the target area based on the updated water depth model.

[0014] To address the aforementioned problems, a third aspect of this application provides an electronic device, wherein the sound source location positioning electronic device includes a processor and a memory interconnected; the memory is used to store program instructions, and the processor is used to execute the program instructions to implement the rainfall flooding analysis method for the target area described in the first aspect.

[0015] To address the aforementioned problems, a fourth aspect of this application provides a computer-readable storage medium storing program instructions thereon, which, when executed by a processor, implement the rainfall flooding analysis method for the target area described in the first aspect.

[0016] The beneficial effects of this invention are as follows: Unlike existing technologies, the rainfall inundation analysis method for the target area in this application obtains an initial water depth model for the target area based on the digital elevation model (DEM) and cumulative rainfall information. Then, it updates the water depth of all grids in the initial water depth model using a hydrodynamic model, resulting in an updated water depth model. Based on the updated water depth model, a water depth map of the target area can be obtained. By using a hydrodynamic model to simulate the flow and convergence process of areal rainwater on all grids of the DEM without relying on additional data beyond the DEM, this method is suitable for isal active inundation analysis and is more relevant to the problem scenario of urban flooding caused by rainfall. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating an embodiment of the rainfall inundation analysis method for the target area of ​​this application;

[0018] Figure 2 yes Figure 1 A flowchart illustrating an embodiment of step S11;

[0019] Figure 3 yes Figure 1 A flowchart illustrating an embodiment of step S12;

[0020] Figure 4 This is a schematic diagram of an embodiment of a hydrodynamic model in an application scenario of this application;

[0021] Figure 5 This is a schematic diagram of another embodiment of the hydrodynamic model in one application scenario of this application;

[0022] Figure 6 yes Figure 3 A flowchart illustrating an embodiment of step S122;

[0023] Figure 7 yes Figure 6 A flowchart illustrating an embodiment of step S1221;

[0024] Figure 8 This is a flowchart illustrating another embodiment of the rainfall inundation analysis method for the target area of ​​this application;

[0025] Figure 9 This is a schematic diagram of an embodiment of a convolution kernel in an application scenario of this application;

[0026] Figure 10 This is a schematic diagram of an embodiment of the water level difference between grids in an application scenario of this application;

[0027] Figure 11This is a schematic diagram of the structure of an embodiment of the rainfall inundation analysis device for the target area of ​​this application;

[0028] Figure 12 This is a schematic diagram of the structure of an embodiment of the electronic device of this application;

[0029] Figure 13 This is a schematic diagram of the structure of an embodiment of the computer-readable storage medium of this application. Detailed Implementation

[0030] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0031] In the following description, specific details such as particular system architectures, interfaces, and technologies are presented for illustrative purposes rather than for limiting purposes, in order to provide a thorough understanding of this application.

[0032] In this paper, the terms "system" and "network" are often used interchangeably. The term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship. Furthermore, "many" in this paper means two or more.

[0033] Please see Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the rainfall inundation analysis method for the target area of ​​this application. The rainfall inundation analysis method for the target area in this embodiment includes the following steps:

[0034] Step S11: Based on the digital elevation model and cumulative rainfall information corresponding to the target area, obtain the initialized water depth model corresponding to the target area.

[0035] The rainfall inundation analysis method for the target area in this application takes a digital elevation model (DEM) and cumulative rainfall as inputs and outputs a water depth model. Specifically, the DEM is a single-channel raster map, where each raster represents a sub-region of a specific shape within the target area, and the elevation value of the raster represents the ground height of that sub-region. The water depth model is also a single-channel raster map, where the geographical locations of the raster cells correspond one-to-one with those in the DEM, and the values ​​of the raster cells represent the water depth of the corresponding sub-region.

[0036] Please combine Figure 2 , Figure 2 yes Figure 1 A flowchart illustrating an embodiment of step S11. In one embodiment, the cumulative rainfall information includes cumulative rainfall and cumulative rainfall distribution; step S11 specifically includes:

[0037] Step S111: Using the digital elevation model corresponding to the target area and the cumulative rainfall corresponding to the target area, generate the water depth model corresponding to the target area.

[0038] Step S112: Initialize the water depth model using the cumulative rainfall distribution corresponding to the target area to obtain the initialized water depth model corresponding to the target area.

[0039] Understandably, based on the digital elevation model (DEM) corresponding to the target area, and combined with the cumulative rainfall in the target area, the water depth of each grid area corresponding to the DEM can be obtained, thus generating the water depth model for the target area. Then, the water depth model can be initialized according to the distribution of cumulative rainfall in the target area. The distribution of cumulative rainfall can be set to uniform or non-uniform according to the simulation requirements. For a uniform distribution, the cumulative rainfall across the entire target area is the same, and is R millimeters; in this case, each grid of the water depth model is initialized to R. For a non-uniform distribution, the rainfall R(i,j) within each grid is different; in this case, the corresponding grid of the water depth model is initialized to R(i,j).

[0040] Step S12: Update the water depth of all grids in the initialized water depth model using the hydrodynamic model to obtain the updated water depth model.

[0041] Step S13: Based on the updated water depth model, obtain the water depth map of the target area.

[0042] Understandably, since the water level of each grid cell is obtained by superimposing the ground height with the water depth, the water level of that grid cell can be calculated. When the water level of a grid cell is inconsistent with that of its neighboring grid cells, water will flow from the grid cells with higher water levels to the grid cells with lower water levels. Therefore, by establishing a hydrodynamic model to simulate the water flow between the grid cells of the water depth model, the water depth of all grid cells in the initialized water depth model can be updated based on the water flow, resulting in an updated water depth model. This allows for the generation of a water depth map of the target area, displaying the water depth of each sub-region within the target area, and enabling rainfall-induced flooding analysis of the target area.

[0043] The above scheme obtains an initial water depth model for the target area based on the digital elevation model (DEM) and cumulative rainfall information. Then, it updates the water depth of all grid cells in the initial water depth model using a hydrodynamic model, resulting in an updated water depth model. Based on this updated model, a water depth map of the target area can be obtained. By using a hydrodynamic model to simulate the flow and convergence of areal rainwater across all grid cells of the DEM without relying on additional data beyond the DEM, this approach is suitable for isal active inundation analysis and better addresses the problem of urban flooding caused by rainfall.

[0044] Please combine Figure 3 , Figure 3 yes Figure 1 A flowchart illustrating one embodiment of step S12. In one embodiment, step S12 specifically includes:

[0045] Step S121: For each grid cell of the initialized water depth model, establish the hydrodynamic model within its preset range.

[0046] For each grid cell, a simplified hydrodynamic model is built within a preset range with the grid cell as the center grid cell to simulate the water flow between the center grid cell and its surrounding grid cells. In order to reduce unnecessary redundant calculations, for the water flow calculation between a certain grid cell and its surrounding grid cells, only the flow between the center grid cell and the surrounding grid cells within the preset range is considered with the grid cell as the center grid cell.

[0047] In one embodiment, the preset range is an eight-connected region range. Please refer to... Figure 4 , Figure 4 This is a schematic diagram of an embodiment of a hydrodynamic model in an application scenario of this application. For each grid cell, a simplified hydrodynamic model is established within its eight-connected region to simulate the water flow between grid cells. The water level of each grid cell is obtained by superimposing the ground height and water depth on the ground height. When the water level of the central grid cell is inconsistent with that of the adjacent surrounding grid cells, water will flow from the grid cell with the higher water level to the grid cell with the lower water level. To reduce unnecessary redundant calculations, the hydrodynamic model can be restricted as follows: for the eight-connected region centered on grid cell A, only the flow between the central grid cell A and its surrounding grid cells a1 or a2 is considered, while the flow between surrounding grid cells a1 and a2 is not considered. The flow between a1 and a2 is only considered when a1 or a2 is the central grid cell. Considering the water flow between grid cells A and B, due to symmetry, outflow from A as the center viewpoint is equivalent to inflow from B as the center viewpoint, so only one of the two flow directions, outflow or inflow, is needed. In another embodiment, as... Figure 5 As shown, the preset range can also be a four-connected region range.

[0048] Step S122: Calculate the water update amount for each grid cell using the hydrodynamic model.

[0049] Please combine Figure 6 , Figure 6 yes Figure 3 A flowchart illustrating one embodiment of step S122. In one embodiment, step S122 specifically includes:

[0050] Step S1221: For the current grid, calculate the water flow between the current grid and surrounding grids within a preset range of the current grid using the hydrodynamic model.

[0051] Step S1222: Based on the water flow rate between the current grid and surrounding grids within a preset range of the current grid, obtain the water accumulation update amount of the current grid.

[0052] Understandably, after calculating the water flow for all grids, for each grid, the water flow out of that grid and the water flow into the surrounding grids within the preset range can be determined, thus obtaining the water accumulation update amount for each grid.

[0053] Step S123: Update the water depth of each grid cell according to the water depth update amount to obtain the updated water depth model.

[0054] After obtaining the water accumulation update amount for each grid cell, the water accumulation depth of each grid cell can be updated based on the water accumulation update amount. After the water accumulation depth is updated, the updated water accumulation depth model is obtained.

[0055] Please combine Figure 7 , Figure 7 yes Figure 6 A flowchart illustrating one embodiment of step S1221. In one embodiment, step S1221 specifically includes:

[0056] Step S12211: For the current grid, calculate the water surface height of the current grid and the surrounding grids within a preset range of the current grid.

[0057] Step S12212: Calculate the water level difference between the current grid and the surrounding grids based on the water level height of the current grid and the surrounding grids within a preset range of the current grid.

[0058] Step S12213: Determine the water flow rate between the current grid and the surrounding grids within a preset range of the current grid based on the water depth of the current grid and the water level difference between the current grid and the surrounding grids.

[0059] Specifically, the above scheme can be illustrated by selecting water flowing from the central grid to the surrounding grids. For example, taking the current grid as the central grid, when calculating the water flow between grids, the current water level of the central grid and the surrounding grids can be compared one by one to calculate the water level difference Δh between the central grid and the surrounding grids. If the water level of the central grid is low, since the water flow is calculated based on water flowing from the central grid to the surrounding grids, the water flow of the central grid is 0 (i.e., no outflow). If the water level of the central grid is high, the water flow of the central grid is s = min(Δh,d)*α, where Δh is the water level difference between the grids, d is the water depth of the central grid, and α is the flow factor, which can take values ​​between (0, 0.125). After calculating the outflow of water for all grids, the water depth of each grid can be updated. The change in grid water depth is equal to the water flow out of the grid minus the water flow into the grid.

[0060] Understandably, after the water depth of the grid is updated, the water level of the grid is also updated. As can be seen from the flow factor values, the water level difference between two grids cannot be leveled out with a single flow, thus requiring a subsequent iteration. This means multiple iterations are needed to gradually reduce the water level difference between the grids towards zero. Since only a portion of the water can be flowed in a single iteration, without requiring leveling the water level in a local area, flow calculations within a preset range around the centers of different grids can be performed in parallel.

[0061] Please see Figure 8 , Figure 8 This is a flowchart illustrating another embodiment of the rainfall inundation analysis method for the target area of ​​this application. The rainfall inundation analysis method for the target area in this embodiment includes the following steps:

[0062] Step S81: Based on the digital elevation model and cumulative rainfall information corresponding to the target area, obtain the initialized water depth model corresponding to the target area.

[0063] Step S81 in this embodiment is basically the same as step S11 in the above embodiment, and will not be described again here.

[0064] Step S82: For each grid cell of the initialized water depth model, establish the hydrodynamic model within its preset range.

[0065] Step S82 in this embodiment is basically the same as step S121 in the above embodiment, and will not be described again here.

[0066] Step S83: For the current grid, calculate the water surface height of the current grid and the surrounding grids within a preset range of the current grid.

[0067] Step S84: Calculate the water level difference between the current grid and the surrounding grids based on the water level heights of the current grid and the surrounding grids within a preset range of the current grid. Specifically, step S84 may include: calculating the water level difference between the current grid and the surrounding grids using a preset number of convolutional kernels to obtain a water level difference map between the current grid and the surrounding grids; the preset number is the same as the number of surrounding grids within a preset range of the current grid, and the water level difference map includes water level differences corresponding to a preset number of channels, each channel corresponding to the direction between the current grid and one surrounding grid.

[0068] like Figure 9 As shown, Figure 9 This is a schematic diagram of an embodiment of the convolution kernel in an application scenario of this application. Eight convolution kernels can be designed for an 8-connected region to calculate the water surface height difference between the central grid and surrounding grids. The water surface height map is a grid image of size 1*H*W, where 1 represents a single channel, H represents the image height, and W represents the image width. After convolution by eight kernels, a water surface height difference map of size 8*H*W is obtained, containing eight channels. Each channel represents the water surface height difference between the central grid and surrounding grids in one direction. Additionally, the ReLU activation function can be used to filter out values ​​less than 0 in the water surface height difference map.

[0069] Step S85: Determine the water flow rate between the current grid and surrounding grids within a preset range of the current grid based on the water depth of the current grid and the water level difference between the current grid and the surrounding grids. Specifically, step S85 may include: obtaining a water flow rate map between the current grid and the surrounding grids based on the relationship between the water level difference corresponding to each channel in the water level difference map and the water depth of the current grid, and a preset water flow rate factor; the water flow rate map includes the water flow rate corresponding to a preset number of channels, each channel corresponding to the direction between the current grid and one surrounding grid.

[0070] like Figure 10 As shown, Figure 10 This is a schematic diagram of an embodiment of the water surface difference between grids in an application scenario of this application. The water surface difference between grids obtained by convolution calculation may have two cases: one is that the water surface difference is entirely composed of accumulated water, and the other is that the water surface difference is composed of part of the ground height and accumulated water. Therefore, the smaller value between the water surface difference and the water depth of the central grid can represent the total amount of water that can flow through the central grid. Multiplying this by the flow factor, the actual water flow rate for each iteration can be calculated as s = min(Δh,d)*α. Thus, a water flow rate map of size 8*H*W can be obtained, where each channel of the water flow rate map represents the water flow rate from the central grid to the surrounding grids in one direction.

[0071] Step S86: Based on the water flow rate between the current grid and surrounding grids within a preset range of the current grid, obtain the water accumulation update amount of the current grid. Specifically, step S86 may include: stacking the preset number of convolutional kernels, and using the stacked convolutional kernels to perform convolution operations on the water flow map to obtain the water accumulation update amount of the current grid.

[0072] After obtaining the water flow map, convolution can be used to calculate the water depth update for each grid cell. For example, it can be... Figure 9 The eight convolutional kernels in the model are stacked in the order (w3, w4, w1, w2, w7, w8, w5, w6) to form a large convolutional kernel. After convolution of this stacked kernel, the water flow map yields a water depth update map of size 1*H*W, describing the water depth changes at each grid cell. Understandably, if a hydrodynamic model with four connected regions is used, only one kernel needs to be used when calculating the water surface elevation difference. Figure 9 The four convolutional kernels w1, w2, w3, and w4 in the model can be stacked into a large convolutional kernel in the order of (w3, w4, w1, w2) when calculating the water accumulation update. The other calculations are exactly the same as those in the hydrodynamic model scenario with eight connected regions.

[0073] Step S87: Update the water depth of each grid cell according to the water depth update amount to obtain the updated water depth model.

[0074] Step S88: Based on the updated water depth model, obtain the water depth map of the target area.

[0075] After obtaining the water accumulation update amount for each grid cell, the water accumulation depth of each grid cell can be updated based on the water accumulation update amount. The new water accumulation depth is obtained by subtracting the water accumulation update amount from the current water accumulation depth. After the water accumulation depth is updated, the updated water accumulation depth model is obtained.

[0076] Understandably, the above process of "water surface height calculation → water surface height difference calculation → water flow calculation → water accumulation update calculation → water depth update" can constitute an iteration. This iteration process is repeated multiple times until the termination condition is met. Two termination conditions can be used: one is that the number of iterations reaches the maximum number of iterations, and the other is that the maximum water accumulation update of the grid is less than the update threshold. When either of these two conditions is met, the calculation process ends, the final water depth model is obtained, and the final water depth map can be returned.

[0077] In one application scenario, the pseudocode for the rainfall inundation analysis method for the target area of ​​this application can be as follows:

[0078]

[0079]

[0080] This allows us to obtain the final water depth map of the target area, which displays the water depth of each sub-area within the target area, enabling us to perform rainfall-induced flooding analysis on the target area.

[0081] The rainfall inundation analysis method for the target area in this application embodiment simulates the flow and convergence process of areal rainwater on all grids of the digital elevation model without relying on additional data outside the digital elevation model. It takes into account the flood source and surface connectivity, and the results obtained are more accurate. It is suitable for isal active inundation analysis and is more in line with the problem scenario of urban flooding caused by rainfall. Furthermore, a simplified hydrodynamic model is proposed, in which the water volume is conserved within an eight- or four-connected range, and the water flows only between the central grid and the surrounding grids. Based on symmetry, only one flow direction needs to be calculated for outflow or inflow, so there is no need to calculate the diffusion source. The water in each grid flows automatically according to the simplified hydrodynamic model, and the calculation process is accelerated in parallel. In addition, a flow factor is introduced, and only a small part of the water is moved in each iteration, thereby decoupling the water flow of each central grid and enabling parallel calculation of all grids.

[0082] Please see Figure 11 , Figure 11 This is a schematic diagram of an embodiment of the rainfall inundation analysis device for the target area of ​​this application. The rainfall inundation analysis device 110 for the target area in this embodiment includes an initialization module 1100, a processing module 1102, and an acquisition module 1104 connected to each other. The initialization module 1100 is used to acquire an initialized water depth model corresponding to the target area based on the digital elevation model and cumulative rainfall information corresponding to the target area. The processing module 1102 is used to update the water depth of all grids in the initialized water depth model using a hydrodynamic model to obtain an updated water depth model. The acquisition module 1104 is used to obtain a water depth map of the target area based on the updated water depth model.

[0083] In one embodiment, the initialization module 1100 performs the step of obtaining an initialized water depth model corresponding to the target area based on the digital elevation model and cumulative rainfall information corresponding to the target area. Specifically, this includes: generating a water depth model corresponding to the target area using the digital elevation model and the cumulative rainfall information corresponding to the target area; and initializing the water depth model using the cumulative rainfall distribution information corresponding to the target area to obtain the initialized water depth model corresponding to the target area.

[0084] In one embodiment, the processing module 1102 performs the step of updating the water depth of all grids of the initialized water depth model using a hydrodynamic model to obtain an updated water depth model, including: for each grid of the initialized water depth model, establishing the hydrodynamic model within a preset range; calculating the water depth update amount for each grid using the hydrodynamic model; and updating the water depth of each grid according to the water depth update amount to obtain an updated water depth model.

[0085] In one embodiment, the preset range is an eight-connected region range or a four-connected region range.

[0086] In one embodiment, the processing module 1102 performs the step of calculating the water update amount of each grid using the hydrodynamic model, specifically including: for the current grid, calculating the water flow between the current grid and surrounding grids within a preset range of the current grid using the hydrodynamic model; and obtaining the water update amount of the current grid based on the water flow between the current grid and surrounding grids within the preset range of the current grid.

[0087] In one embodiment, the processing module 1102 performs the step of calculating the water flow rate between the current grid and surrounding grids within a preset range of the current grid using the hydrodynamic model for the current grid. Specifically, this includes: calculating the water surface height of the current grid and surrounding grids within a preset range of the current grid for the current grid; calculating the water surface height difference between the current grid and surrounding grids based on the water surface height of the current grid and surrounding grids within a preset range of the current grid; and determining the water flow rate between the current grid and surrounding grids within a preset range of the current grid based on the water depth of the current grid and the water surface height difference between the current grid and surrounding grids.

[0088] In one embodiment, the processing module 1102 performs a step of calculating the water surface height difference between the current grid and the surrounding grids based on the water surface height of the current grid and the surrounding grids within a preset range of the current grid. Specifically, this may include: calculating the water surface height difference between the current grid and the surrounding grids using a preset number of convolutional kernels to obtain a water surface height difference map between the current grid and the surrounding grids; the preset number is the same as the number of surrounding grids within a preset range of the current grid, and the water surface height difference map includes water surface height differences corresponding to a preset number of channels, with each channel corresponding to the direction between the current grid and one surrounding grid. At this time, the processing module 1102 performs the step of determining the water flow rate between the current grid and surrounding grids within a preset range of the current grid based on the water depth of the current grid and the water level difference between the current grid and the surrounding grids. Specifically, this may include: obtaining a water flow rate map between the current grid and the surrounding grids based on the relationship between the water level difference corresponding to each channel in the water level difference map and the water depth of the current grid, and a preset water flow rate factor; the water flow rate map includes the water flow rate corresponding to a preset number of channels, each channel corresponding to the direction between the current grid and a surrounding grid. Simultaneously, the processing module 1102 performs the step of obtaining the water update amount of the current grid based on the water flow rate between the current grid and surrounding grids within a preset range of the current grid. Specifically, this may include: stacking the preset number of convolutional kernels and performing a convolution operation on the water flow rate map using the stacked convolutional kernels to obtain the water update amount of the current grid.

[0089] Please see Figure 12 , Figure 12 This is a schematic diagram of the structure of an embodiment of the electronic device of this application. The electronic device 12 in this embodiment includes a processor 122 and a memory 121 connected to each other; the memory 121 is used to store program instructions, and the processor 122 is used to execute the program instructions stored in the memory 121 to implement the steps of the above-described embodiment of the rainfall inundation analysis method for any target area. In a specific implementation scenario, the electronic device 12 may include, but is not limited to, a microcomputer or a server.

[0090] Specifically, processor 122 controls itself and memory 121 to implement the steps of the rainfall flooding analysis method embodiment for any of the aforementioned target areas. Processor 122 may also be referred to as a CPU (Central Processing Unit). Processor 122 may be an integrated circuit chip with signal processing capabilities. Processor 122 may also be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. A general-purpose processor may be a microprocessor or any conventional processor. Furthermore, processor 122 may be implemented using integrated circuit chips.

[0091] Please see Figure 13 , Figure 13 This is a schematic diagram of a computer-readable storage medium according to an embodiment of the present application. The computer-readable storage medium 13 of the present application stores program instructions 130 thereon, which, when executed by a processor, implement the steps in the above-described embodiments of the rainfall flooding analysis method for any of the target areas.

[0092] The computer-readable storage medium 13 can be a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, or a medium that can store program instructions 130. Alternatively, it can be a server that stores the program instructions 130. The server can send the stored program instructions 130 to other devices for execution, or it can execute the stored program instructions 130 itself.

[0093] In the several embodiments provided in this application, it should be understood that the disclosed methods, devices, and apparatuses can be implemented in other ways. For example, the device and apparatus embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0094] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0095] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0096] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods of various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for analyzing rainfall inundation in a target area, characterized in that, The method includes: Based on the digital elevation model and cumulative rainfall information corresponding to the target area, an initial water depth model corresponding to the target area is obtained; wherein, the cumulative rainfall distribution of the initial water depth model includes whether the rainfall is uniformly distributed or non-uniformly distributed in each grid cell; For each grid cell of the initialized water depth model, a hydrodynamic model is established within its preset range. The hydrodynamic model simulates the flow of water between the grid cells of the water depth model. The water depth of all grid cells of the initialized water depth model is updated through the hydrodynamic model to obtain the updated water depth model. Based on the updated water depth model, a water depth map of the target area is obtained.

2. The method for analyzing rainfall inundation in a target area according to claim 1, characterized in that, The step of obtaining an initialized water depth model for the target area based on the digital elevation model and cumulative rainfall information corresponding to the target area includes: Using the digital elevation model corresponding to the target area and the cumulative rainfall corresponding to the target area, a water depth model corresponding to the target area is generated; The water depth model is initialized using the cumulative rainfall distribution data corresponding to the target area, resulting in an initialized water depth model for the target area.

3. The method for analyzing rainfall inundation in a target area according to claim 1, characterized in that, The step of updating the water depth model by using a hydrodynamic model to update the water depth of all grids in the initialized water depth model, resulting in an updated water depth model, includes: For each grid cell of the initialized water depth model, the hydrodynamic model is established within its preset range; The water accumulation update amount for each grid cell is calculated using the aforementioned hydrodynamic model; The water depth of each grid cell is updated based on the water depth update amount to obtain the updated water depth model.

4. The method for analyzing rainfall inundation in a target area according to claim 3, characterized in that, The preset range is either an eight-connected region or a four-connected region.

5. The method for analyzing rainfall inundation in a target area according to claim 3, characterized in that, The calculation of the water accumulation update amount for each grid cell using the hydrodynamic model includes: For the current grid cell, the water flow rate between the current grid cell and surrounding grid cells within a preset range of the current grid cell is calculated using the hydrodynamic model. The water replenishment amount of the current grid is obtained based on the water flow rate between the current grid and surrounding grids within a preset range of the current grid.

6. The method for analyzing rainfall inundation in a target area according to claim 5, characterized in that, For the current grid cell, the calculation of the water flow between the current grid cell and surrounding grid cells within a preset range of the current grid cell using the hydrodynamic model includes: For the current grid, calculate the water surface height of the current grid and the surrounding grids within a preset range of the current grid; Calculate the water level difference between the current grid and the surrounding grids within a preset range of the current grid. Based on the water depth of the current grid and the water level difference between the current grid and the surrounding grids, the water flow rate between the current grid and the surrounding grids within a preset range of the current grid is determined.

7. The method for analyzing rainfall inundation in a target area according to claim 6, characterized in that, The step of calculating the water level difference between the current grid and the surrounding grids based on the water level height of the current grid and the surrounding grids within a preset range of the current grid includes: The water level difference between the current grid and the surrounding grid is calculated using a preset number of convolution kernels to obtain a water level difference map between the current grid and the surrounding grid. The preset number is the same as the number of surrounding grids within a preset range of the current grid. The water level difference map includes water level differences corresponding to a preset number of channels, and each channel corresponds to the direction between the current grid and a surrounding grid. The step of determining the water flow rate between the current grid and surrounding grids within a preset range of the current grid, based on the water depth of the current grid and the water level difference between the current grid and the surrounding grids, includes: Based on the relationship between the water surface elevation difference corresponding to each channel in the water surface elevation difference map and the water depth of the current grid, and a preset water flow factor, a water flow map between the current grid and the surrounding grids is obtained; the water flow map includes the water flow corresponding to a preset number of channels, and each channel corresponds to the direction between the current grid and a surrounding grid. The step of obtaining the water accumulation update amount of the current grid cell based on the water flow rate between the current grid cell and surrounding grid cells within a preset range of the current grid cell includes: The preset number of convolution kernels are stacked, and the stacked convolution kernels are used to perform convolution operations on the water flow map to obtain the water accumulation update amount of the current grid.

8. A rainfall inundation analysis device for a target area, characterized in that, include: An initialization module is used to obtain an initialized water depth model corresponding to the target area based on the digital elevation model and cumulative rainfall information corresponding to the target area; wherein the cumulative rainfall distribution of the initialized water depth model can be uniform or non-uniform. The processing module is used to establish a hydrodynamic model within a preset range for each grid of the initialized water depth model. The hydrodynamic model simulates the flow of water between the grids of the water depth model. The water depth of all grids of the initialized water depth model is updated through the hydrodynamic model to obtain the updated water depth model. The acquisition module is used to obtain a water depth map of the target area based on the updated water depth model.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory interconnected with each other; The memory is used to store program instructions, and the processor is used to execute the program instructions to implement the rainfall flooding analysis method for the target area as described in any one of claims 1-7.

10. A computer-readable storage medium having program instructions stored thereon, characterized in that, When the program instructions are executed by the processor, they implement the rainfall flooding analysis method for the target area as described in any one of claims 1 to 7.

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