Flood inundation simulation methods, devices, electronic equipment and storage media

Abstract

This invention provides a flood inundation simulation method, apparatus, electronic device, and storage medium, relating to the field of hydraulics technology. The method includes: acquiring and preprocessing multi-source data; constructing a river channel buffer zone based on first DEM data; using the river channel buffer zone as a mask area, extracting DEM data within the mask area from the first DEM data, and filtering out DEM data outside the mask area from second DEM data to form nested DEM data; constructing a two-dimensional computational grid based on the nested DEM data; establishing a hydrodynamic model based on two-dimensional shallow water equations; and performing flood inundation simulation on the two-dimensional computational grid using the hydrodynamic model. This invention, by constructing multi-resolution nested DEMs and matching differentiated grid sizes, ensures the ability to represent topographic details and simulation accuracy in key areas while fully utilizing multi-scale topographic information, significantly reducing the overall computational scale and improving the efficiency of large-scale flood inundation simulation.

Description

Technical Field

[0001] This invention relates to the field of hydraulics technology, and in particular to a flood inundation simulation method, apparatus, electronic device, and storage medium. Background Technology

[0002] In recent years, influenced by global climate change and rapid urbanization, extreme rainfall events have become more frequent, leading to increasing economic losses and social impacts from floods. Flood inundation simulation is a crucial technical tool for flood disaster risk assessment, flood control planning, and emergency management. With the development of computer technology and geospatial data, hydrodynamic models based on two-dimensional shallow water equations have been widely applied to simulate flood evolution and predict inundation extent.

[0003] Digital elevation models (DEMs) are crucial foundational data for two-dimensional flood simulation. Currently, flood simulation research and engineering applications often use single-resolution DEMs to construct the computational domain. For watershed-scale or large-area flood simulations, a uniform high-resolution DEM or a uniform low-resolution DEM is typically used for modeling.

[0004] The above-mentioned schemes have the following main shortcomings: 1) It is difficult to balance simulation accuracy and computational efficiency: High-resolution DEMs have high accuracy but large computational load, while low-resolution DEMs have high efficiency but poor accuracy. The two cannot be balanced in the same model; 2) Insufficient ability to express terrain features: For areas along river channels, floodplain boundaries, and areas with large topographic relief, terrain details are easily smoothed when using a single low-resolution DEM, resulting in deviations in flood flow paths, water depth distribution, and inundation boundaries; 3) High consumption of computational resources: Using full-domain high-resolution DEM modeling to improve accuracy will result in a large waste of computational resources; 4) Low utilization rate of multi-scale terrain information: Insufficient collaborative utilization of multi-source, multi-scale DEM data makes it difficult to fully leverage the respective advantages of high-resolution and low-resolution DEMs. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a flood inundation simulation method, apparatus, electronic device and storage medium.

[0006] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: In a first aspect, the present invention provides a flood inundation simulation method, which adopts the following technical solution: A flood inundation simulation method includes: Acquire multi-source basic geographic and environmental data of the target area, and preprocess the multi-source basic geographic and environmental data to form a structured dataset; wherein, the target DEM terrain data in the structured dataset includes first DEM data at a first resolution and second DEM data at a second resolution, wherein the first resolution is greater than the second resolution; Construct a river buffer zone based on the first DEM data; Using the river buffer zone as a mask area, first simulated DEM data within the mask area is extracted from the first DEM data, and second simulated DEM data outside the mask area is filtered out from the second DEM data to form nested DEM data; A two-dimensional computational mesh is constructed based on the nested DEM data; wherein the mesh size within the mask region matches the first resolution, and the mesh size outside the mask region matches the second resolution; A hydrodynamic model is established based on the two-dimensional shallow water equation, and the model parameters and input data of the hydrodynamic model are obtained from the structured dataset. Flood inundation simulation is performed on the two-dimensional computational grid using the hydrodynamic model to obtain flood inundation simulation results.

[0007] The beneficial effects of this invention are as follows: by using the river buffer zone as a mask area, the terrain of key areas is extracted from the high-resolution DEM, and the terrain of the outer area is screened from the low-resolution DEM to construct a multi-resolution nested DEM. The key areas are matched with fine grids and the outer areas with sparse grids. While ensuring the ability to express the details of the river channel and floodplain terrain and the simulation accuracy, the invention makes full use of multi-scale terrain information, significantly reduces the overall number of computational grids, reduces the consumption of computational resources, and improves the efficiency of large-scale flood inundation simulation.

[0008] Based on the above technical solution, the present invention can be further improved as follows.

[0009] Further, the step of using the river buffer zone as a mask area, extracting the first simulated DEM data within the mask area from the first DEM data, and filtering out the second simulated DEM data outside the mask area from the second DEM data to form nested DEM data includes: Using the river buffer zone as the mask area, the grid cells within the mask area are cropped from the first DEM data to obtain the first simulated DEM data; Remove the grid cells within the mask area from the second DEM data, and retain the grid cells outside the mask area to obtain the second simulated DEM data; The first simulated DEM data and the second simulated DEM data are spatially superimposed to form the nested DEM data.

[0010] The beneficial effects of adopting the above-mentioned further scheme are: by extracting the terrain data of the key area and the outer area from the high-resolution DEM and the low-resolution DEM respectively through cropping and culling operations, and then forming a nested DEM through spatial overlay, the precise separation and efficient fusion of terrain data of different resolutions are achieved, ensuring the complete preservation of terrain details in the key area and the reasonable control of the calculation scale of the outer area.

[0011] Furthermore, the step of spatially overlaying the first simulated DEM data and the second simulated DEM data to form the nested DEM data includes: A transition region is provided at the boundary of the mask area; Within the transition area, the elevation values ​​of the first simulated DEM data and the second simulated DEM data are interpolated to obtain the elevation values ​​of the raster cells within the transition area. The first simulated DEM data, the second simulated DEM data, and the interpolated transition region are spatially superimposed to form the nested DEM data.

[0012] The beneficial effects of adopting the above-mentioned further scheme are: by setting a transition region at the boundary of the mask area and performing interpolation processing, the terrain abrupt change caused by the elevation difference between the high-resolution DEM and the low-resolution DEM at the boundary is avoided, ensuring the smooth transition of the nested DEM in the boundary area, and improving the continuity and accuracy of water flow when crossing different resolution areas during flood simulation.

[0013] Furthermore, the flood inundation simulation using the hydrodynamic model on the two-dimensional computational grid includes: On the grid within the mask area, flood evolution calculations are performed at a time step corresponding to the first resolution; On the grid outside the masked area, flood evolution calculations are performed at a time step corresponding to the second resolution.

[0014] The beneficial effects of adopting the above-mentioned further scheme are: to use a time step that matches the resolution region for flood evolution calculation, a smaller time step is used in the dense grid region to ensure calculation stability, and a larger time step is used in the sparse grid region to improve calculation speed, thereby further improving the overall calculation efficiency while ensuring simulation accuracy.

[0015] Furthermore, the multi-source basic geographic and environmental data includes raw DEM topographic data, raw rainfall data, raw hydrological data, raw land use data, and raw remote sensing imagery; The preprocessing of the multi-source basic geographic and environmental data includes: The original DEM terrain data is subjected to coordinate unification, depression filling and outlier processing to obtain the target DEM terrain data; Missing values ​​are imputed and outliers are removed from the original rainfall data and the original hydrological data to obtain the target rainfall data and the target hydrological data. The original land use data is reclassified and format converted to obtain the target land use data; Radiometric calibration, atmospheric correction, and geometric correction are performed on the original remote sensing image to obtain the target remote sensing image.

[0016] The beneficial effects of adopting the above-mentioned further scheme are: by performing targeted preprocessing on different types of raw data, problems such as inconsistent coordinates, outliers, and missing values ​​in the raw data are eliminated, improving the quality and consistency of the data, providing a reliable data foundation for subsequent parameter setting, boundary input, and model calibration of the hydrodynamic model, and ensuring the accuracy and reliability of the flood inundation simulation results.

[0017] Furthermore, the model parameters and input data of the hydrodynamic model are obtained from the structured dataset, including: Obtain the target rainfall data, the target hydrological data, the target land use data, and the target remote sensing image from the structured dataset; The target rainfall data is used as the boundary input condition for the hydrodynamic model; The target hydrological data is used as the calibration data for the hydrodynamic model; The target land use data is used as the basis for setting the roughness parameter of the hydrodynamic model; The remote sensing image of the target is used as verification data for the inundation range of the hydrodynamic model.

[0018] The beneficial effects of adopting the above-mentioned further scheme are: by using the preprocessed multi-source data for the boundary input, calibration, roughness parameter setting and inundation range verification of the hydrodynamic model, the different roles of various types of data in flood simulation are fully utilized, the accurate configuration of model input parameters and the effective verification of simulation results are achieved, and the accuracy and reliability of flood inundation simulation are further improved.

[0019] Furthermore, the construction of the river channel buffer based on the first DEM data includes: Based on the first DEM data, calculate the surface flow direction; Based on the first DEM data and the surface flow direction, calculate the cumulative runoff volume; Each grid cell whose cumulative runoff reaches a preset runoff threshold is identified as a river network; The river network is converted into vector line elements, and the river buffer zone is constructed at a preset distance using the vector line elements as the river centerline.

[0020] The beneficial effects of adopting the above-mentioned further scheme are: by performing flow direction calculation and confluence accumulation analysis based on high-resolution DEM, the location of the river channel and its spatial distribution can be accurately identified, and a river channel buffer zone can be constructed based on vector line elements to ensure that the key simulation area accurately covers the river channel and the adjacent floodplain, providing a reliable spatial range basis for subsequent multi-resolution DEM nesting.

[0021] Secondly, the present invention provides a flood inundation simulation device, which adopts the following technical solution: A flood inundation simulation device, comprising: The data acquisition module is used to acquire multi-source basic geographic and environmental data of the target area and preprocess the multi-source basic geographic and environmental data to form a structured dataset; wherein, the target terrain DEM data in the structured dataset includes first DEM data at a first resolution and second DEM data at a second resolution, wherein the first resolution is greater than the second resolution. A buffer construction module is used to construct a river channel buffer based on the first DEM data; The nested construction module is used to extract first simulated DEM data within the mask area from the first DEM data, and filter out second simulated DEM data outside the mask area from the second DEM data, thereby forming nested DEM data; A mesh construction module is used to construct a two-dimensional computational mesh based on the nested DEM data; wherein the mesh size within the mask region matches the first resolution, and the mesh size outside the mask region matches the second resolution; The model building module is used to establish a hydrodynamic model based on the two-dimensional shallow water equation and to obtain the model parameters and input data of the hydrodynamic model from the structured dataset. The simulation module is used to perform flood inundation simulation on the two-dimensional computing grid using the hydrodynamic model, and obtain flood inundation simulation results.

[0022] Thirdly, the present invention provides an electronic device that adopts the following technical solution: An electronic device includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor, when executing the computer program, implements the flood inundation simulation method as described in any of the first aspects.

[0023] Fourthly, the present invention provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the flood inundation simulation method as described in any of the first aspects.

[0024] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and will become apparent from the description or may be learned by practice of the invention. Attached Figure Description

[0025] Figure 1 A schematic flowchart of the flood inundation simulation method provided by the present invention; Figure 2 A schematic diagram of the construction of the river network buffer zone provided by the present invention; Figure 3 This is a schematic diagram of multi-resolution DEM nesting and fusion provided by the present invention; Figure 4 A schematic diagram of the flood inundation simulation device provided by the present invention; Figure 5 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0026] The principles and features of the present invention are described below. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0027] Please refer to Figure 1 , Figure 1 This is a schematic flowchart of the flood inundation simulation method provided by the present invention. Figure 1 As shown, the method may include the following steps S101-S106.

[0028] S101. Obtain multi-source basic geographic and environmental data of the target area, and preprocess the multi-source basic geographic and environmental data to form a structured dataset; wherein, the target DEM terrain data in the structured dataset includes first DEM data at a first resolution and second DEM data at a second resolution, wherein the first resolution is greater than the second resolution.

[0029] Specifically, multi-temporal and spatial resolution observational data and future projected data for more than ten indicators, including meteorology, hydrology, climate change, land use, soil, and administrative boundaries, were acquired within the target area to serve as multi-source basic geographic and environmental data. The specific types, indicators, sources, and uses of each data item are shown in Table 1.

[0030] Table 1. Multi-source basic geographic and environmental data The aforementioned multi-source basic geographic and environmental data are preprocessed to eliminate data quality issues and form a structured dataset. In one embodiment, the multi-source basic geographic and environmental data includes raw DEM data, raw rainfall data, raw hydrological data, raw land use data, and raw remote sensing imagery. The preprocessing of the multi-source basic geographic and environmental data includes: 1) performing coordinate unification, depression filling, and outlier processing on the raw DEM topographic data to eliminate coordinate inconsistencies, local depressions, and abnormal elevation values, obtaining target DEM topographic data for subsequent river network extraction and terrain modeling; 2) performing missing value imputation and outlier removal on the raw rainfall data and raw hydrological data to fill in missing values ​​caused by instrument malfunctions or communication interruptions. 1) Data gaps are filled, and outliers that deviate significantly from the normal range are removed to obtain target rainfall data and target hydrological data, which are used as boundary inputs and calibration verification for the hydrodynamic model; 2) The original land use data is reclassified and format converted, which can be merged according to the classification system required by the model and converted into a unified raster format to obtain target land use data, which is used to set the surface roughness parameter; 3) Radiometric calibration, atmospheric correction and geometric correction are performed on the original remote sensing images to eliminate sensor response differences, atmospheric scattering and absorption and geometric distortion caused by topography, to obtain target remote sensing images, which are used for subsequent inundation range inversion and verification.

[0031] After the above preprocessing, the target DEM terrain data in the obtained structured dataset contains DEM data at two resolutions: first-resolution first DEM data (such as 30-meter high-resolution DEM data) and second-resolution second DEM data (such as 90-meter low-resolution DEM data).

[0032] S102. Construct a river buffer zone based on the first DEM data.

[0033] In one embodiment, step S102 includes: calculating the surface flow direction based on the first DEM data; calculating the cumulative runoff based on the first DEM data and the surface flow direction; identifying each grid cell whose cumulative runoff reaches a preset runoff threshold as a river network; converting the river network into vector line features, and constructing a river buffer zone according to a preset distance using the vector line features as the river centerline.

[0034] Specifically, such as Figure 2As shown, firstly, depression filling is performed based on the first DEM data to eliminate local depressions and ensure the continuity of the water flow path. Then, the D8 single-direction algorithm is used to calculate the surface flow direction of each grid cell to determine the water flow direction. Next, based on the surface flow direction, the number of upstream confluence grid cells for each grid cell is counted to obtain the cumulative runoff. Grid cells whose cumulative runoff reaches a preset runoff threshold are identified as river grid cells, and all river grid cells are connected to form a river network. Subsequently, the grid-based river network is converted into vector line elements as the river centerline. Finally, based on this vector line element, the river buffer zone is constructed by expanding to both sides at preset distances (e.g., 30 meters). This river buffer zone covers the river channel and its adjacent floodplain, which is the key simulation area and the area most sensitive during flood propagation with the highest requirements for simulation accuracy.

[0035] S103. Using the river buffer zone as a mask area, extract the first simulated DEM data within the mask area from the first DEM data, and filter out the second simulated DEM data outside the mask area from the second DEM data to form nested DEM data.

[0036] In one embodiment, step S103 may include the following sub-steps S1031-S1033.

[0037] S1031. Using the river buffer zone as a mask area, the grid cells within the mask area are cut out from the first DEM data to obtain the first simulated DEM data.

[0038] Specifically, the river buffer zone is used as a mask area, which is then overlaid on the first DEM data (high-resolution DEM data). Spatial clipping is then used to extract the raster cells within the mask area, resulting in first simulated DEM data with effective elevation values ​​only within the river buffer zone. This first simulated DEM data fully preserves the river morphology, riverbank topography, and surrounding micro-topographic features, providing a detailed topographic foundation for subsequent simulations of flood evolution in key areas.

[0039] S1032. Remove the grid cells within the mask area from the second DEM data, and retain the grid cells outside the mask area to obtain the second simulated DEM data.

[0040] Specifically, using the river channel buffer zone as the removal area, raster cells within the masked area are removed from the second DEM data (low-resolution DEM data) covering the entire target area, retaining only the raster cells outside the masked area to obtain the second simulated DEM data. This second simulated DEM data is used to characterize the terrain contours of the surrounding ordinary areas to reduce the overall computational scale.

[0041] S1033. Spatially overlay the first simulated DEM data with the second simulated DEM data to form nested DEM data.

[0042] Specifically, the first simulated DEM data and the second simulated DEM data are spatially overlaid and fused. The fusion rule is as follows: when the raster is within the mask area, the elevation value of the first simulated DEM data is used; when the raster is outside the mask area, the elevation value of the second simulated DEM data is used. This results in nested DEM data where high resolution is used for key simulation areas and low resolution is used for peripheral ordinary areas, achieving a balance between detailed representation of key simulation areas and improved overall computational efficiency.

[0043] The above fusion rule can be expressed by expression (1): (1) in: This represents the elevation value of the first simulated DEM data. This represents the elevation value from the second simulated DEM data. This indicates the key simulation area corresponding to the river buffer zone. Indicates the outer ordinary area. This indicates the final nested DEM data.

[0044] Optionally, step S1033 includes: setting a transition region at the boundary of the mask region; interpolating the elevation values ​​of the first simulated DEM data and the second simulated DEM data within the transition region to obtain the elevation values ​​of the grid cells within the transition region; and spatially superimposing the first simulated DEM data, the second simulated DEM data, and the interpolated transition region to form nested DEM data.

[0045] By setting a transition region at the boundary and performing interpolation, the abrupt terrain changes caused by elevation differences between high-resolution and low-resolution DEMs at the boundary can be effectively avoided, ensuring a smooth transition of nested DEMs in the boundary region and improving the continuity and accuracy of water flow when crossing different resolution regions during flood simulation.

[0046] S104. Construct a two-dimensional computational grid based on nested DEM data; wherein the grid size within the mask region matches the first resolution, and the grid size outside the mask region matches the second resolution.

[0047] Specifically, a two-dimensional computational grid is constructed based on nested DEM data for subsequent numerical discretization and solution of the hydrodynamic model. The grid size is related to the DEM resolution of the corresponding region: within the masked area (i.e., the key simulation area), a smaller grid size is used due to the adoption of high-resolution first DEM data to fully preserve the micro-topographic features of the river channel and floodplain, ensuring the simulation accuracy of flood propagation paths and water depth distribution; outside the masked area (i.e., the surrounding general area), a larger grid size is used due to the adoption of low-resolution second DEM data to reduce the total number of computational grids and lower computational resource consumption. This results in a non-uniform grid system with a dense grid in the key area and a sparse grid in the surrounding area, significantly improving overall computational efficiency while ensuring the simulation accuracy of the key area.

[0048] The rules for setting the grid size mentioned above can be expressed by expression (2): (2) in, Indicates the grid size. This indicates the resolution of the DEM data.

[0049] S105. Establish a hydrodynamic model based on the two-dimensional shallow water equation, and obtain the model parameters and input data of the hydrodynamic model from the structured dataset.

[0050] Specifically, a two-dimensional shallow water equation (Saint-Venant equation) is used to describe flood movement, and a hydrodynamic model is established: 1) Continuity equation: (3) in, Indicates water depth. , Indicates flow rate, This indicates lateral inflow, and its physical meaning is conservation of mass; 2) Directional momentum equation: (4) in, Represents gravitational acceleration. express The terrain slope in the direction, express Friction gradient in the direction; 3) Momentum equation in the y-direction: (5) in, express The terrain slope in the direction, express Friction gradient in the direction.

[0051] After constructing the hydrodynamic model, it is necessary to configure the corresponding parameters and input data for it. In one embodiment, the model parameters and input data of the hydrodynamic model are obtained from a structured dataset, including: obtaining target rainfall data, target hydrological data, target land use data, and target remote sensing imagery from the structured dataset; using the target rainfall data as the boundary input conditions of the hydrodynamic model; using the target hydrological data as the calibration data of the hydrodynamic model; using the target land use data as the basis for setting the roughness parameter of the hydrodynamic model; and using the target remote sensing imagery as the verification data for the inundation range of the hydrodynamic model. At this point, all the parameters and input data required for the hydrodynamic model have been configured, and the model is ready for flood inundation simulation.

[0052] It should be noted that, regarding the roughness parameter, after reclassifying land use data according to land use type, the corresponding Manning roughness coefficient is assigned to each type of land use based on the Manning roughness empirical table. Manning's formula is expressed as: (6) in, Indicates flow rate, This represents the Manning roughness coefficient. Indicates the hydraulic radius. Indicates the slope. The larger the value, the lower the flow velocity and the greater the resistance.

[0053] S106. Flood inundation simulation is performed on a two-dimensional computational grid using a hydrodynamic model to obtain flood inundation simulation results.

[0054] Specifically, flood evolution calculations are performed using a hydrodynamic model on a two-dimensional computational grid. Since a finer grid is used within the masked area and a sparser grid is used outside the masked area, the stability requirements for the time step differ during numerical solution. Within the masked area, flood evolution calculations are performed using a time step corresponding to the first resolution; outside the masked area, calculations are performed using a time step corresponding to the second resolution. That is, within the masked area, a small time step corresponding to the first resolution is used to satisfy the CFL stability condition under a fine grid, ensuring the accuracy of the simulation in key areas; outside the masked area, a large time step corresponding to the second resolution is used to improve computational efficiency while maintaining stability. This differentiated time step strategy significantly improves overall computational efficiency while ensuring the simulation accuracy of key areas. After the simulation is completed, the flood inundation simulation results, including the maximum inundation depth, are output. Maximum flow rate and maximum flooding range Indicators characterizing flood inundation features, among others. Represents the area of ​​a unit.

[0055] The flood inundation simulation method provided by this invention extracts the topography of key areas from a high-resolution DEM using the river buffer zone as a mask area, filters the topography of the outer area from a low-resolution DEM, constructs a multi-resolution nested DEM, and uses a fine grid in the key area and a sparse grid in the outer area for matching. While ensuring the ability to express the details of the river channel and floodplain topography and the simulation accuracy, it makes full use of multi-scale topographic information, significantly reduces the overall number of computational grids, reduces the consumption of computational resources, and improves the efficiency of large-scale flood inundation simulation.

[0056] The following section uses the mountainous area of ​​the Hanjiang River basin, which covers the administrative boundary of Meizhou City and its upstream area, as an example to explain in detail the process of the flood inundation simulation method provided by this invention.

[0057] This embodiment takes the mountainous area of ​​the Hanjiang River basin, covering the administrative boundary of Meizhou City and its upstream region, as the research object, and constructs a two-dimensional flood inundation simulation model based on multi-resolution DEM scale nesting. The study area covers approximately 15,864 km², with terrain mainly consisting of mountains and hills and a well-developed river network. The main rivers include the Meijiang, Tingjiang, and Hanjiang Rivers. Due to the significant topographic relief within the study area, using a uniform high-resolution DEM for flood simulation would generate a large number of computational units, resulting in low computational efficiency. Therefore, the multi-resolution DEM scale nesting method proposed in this invention is used to establish the terrain model.

[0058] The specific implementation steps are as follows: 1) Use a 30m DEM to extract the river channel and the 500m buffer zone on both sides to determine the core range of the detailed simulation; 2) Construct the buffer zone and surrounding transition area using a 90m DEM to form a medium-resolution skeleton; 3) Establish a multi-resolution DEM nested model: merge the 30m DEM (core area) and the 90m DEM (outer area) according to spatial range to form a model like... Figure 3 The nested DEM structure Final_Merged_DEM shown in the figure; 4) Build a 2D model on the HEC-RAS 2D platform and load the Final_Merged_DEM as terrain input; 5) Input a 100-year design flood event and set boundary conditions; 6) Run flood evolution simulations and adopt a differentiated time step strategy (small step size within the mask area and large step size outside the mask area) to improve efficiency and accuracy; 7) Output the maximum flooding range and water depth results.

[0059] The results show that compared with the full-area 30m DEM simulation scheme, the calculation time of this method is reduced by about 60% to 80%, while the maximum water depth error in the key area (river buffer zone) is controlled within 5%, achieving a balance between calculation efficiency and simulation accuracy.

[0060] Please refer to Figure 4 , Figure 4 A schematic diagram of the flood inundation simulation device provided by the present invention. Figure 4 As shown, the device may include: The data acquisition module 401 is used to acquire multi-source basic geographic and environmental data of the target area and preprocess the multi-source basic geographic and environmental data to form a structured dataset; wherein, the target DEM terrain data in the structured dataset includes first DEM data at a first resolution and second DEM data at a second resolution, wherein the first resolution is greater than the second resolution. Buffer construction module 402 is used to construct a river channel buffer based on the first DEM data; Nested construction module 403 is used to extract first simulated DEM data within the mask area from first DEM data using the river buffer zone as the mask area, and filter out second simulated DEM data outside the mask area from second DEM data to form nested DEM data; Mesh building module 404 is used to build a two-dimensional computational mesh based on nested DEM data; wherein the mesh size within the mask region matches the first resolution, and the mesh size outside the mask region matches the second resolution; The model building module 405 is used to build a hydrodynamic model based on the two-dimensional shallow water equation and to obtain the model parameters and input data of the hydrodynamic model from the structured dataset. The simulation module 406 is used to perform flood inundation simulation on a two-dimensional computational grid using a hydrodynamic model, and obtain flood inundation simulation results.

[0061] In some embodiments, the flood inundation simulation device of the present invention can be implemented in a combination of hardware and software. As an example, the flood inundation simulation device of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the flood inundation simulation method of the present invention. For example, the processor in the form of a hardware decoding processor can be one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0062] The modules described in the embodiments of this invention can be implemented in software or hardware. The names of the modules are not, in some cases, limiting the scope of the module itself.

[0063] An electronic device according to an embodiment of the present invention includes 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 any of the above-described flood inundation simulation methods. That is, an electronic device according to an embodiment of the present invention may include, but is not limited to: a processor and a memory; the memory is used to store the computer program; the processor is used to execute the flood inundation simulation method shown in any embodiment of the present invention by calling the computer program.

[0064] In one alternative embodiment, an electronic device is provided, such as Figure 5 As shown, Figure 5 The illustrated electronic device 4000 includes a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, for example, via a bus 4002. Optionally, the electronic device 4000 may further include a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 4004 is not limited to one type, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0065] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this invention. Processor 4001 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0066] Bus 4002 may include a path for transmitting information between the aforementioned components. Bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 4002 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The bus 4002 is represented by only one thick line, but this does not mean that there is only one bus or one type of bus.

[0067] The memory 4003 may be ROM (Read Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0068] The memory 4003 stores application code (computer program) for executing the present invention, and its execution is controlled by the processor 4001. The processor 4001 executes the application code stored in the memory 4003 to implement the content shown in the foregoing method embodiments.

[0069] Among them, electronic devices can also be terminal devices, which can be any device that can install applications, including at least one of smartphones, tablets, laptops, desktop computers, smart speakers, smartwatches, smart TVs, and smart in-vehicle devices.

[0070] It should be noted that, Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0071] An embodiment of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements any of the above-described flood inundation simulation methods.

[0072] Alternatively, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, a floppy disk, and an optical data storage device, etc.

[0073] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform the flood simulation method described above.

[0074] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0075] It should be understood that the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0076] The computer-readable storage medium provided in this invention can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EEPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0077] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the method shown in the above embodiments.

[0078] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this invention is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-disclosed concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this invention.

[0079] It should be noted that the terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and represent a limitation on a specific order or sequence. Where appropriate, the order of use for similar objects can be interchanged so that the embodiments of this application described herein can be implemented in an order other than that shown or described.

[0080] Those skilled in the art will recognize that this invention can be implemented as a system, method, or computer program product. Therefore, this invention can be specifically implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, this invention can also be implemented as a computer program product contained in one or more computer-readable media, which includes computer-readable program code.

[0081] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for simulating flood inundation, characterized in that, include: Acquire multi-source basic geographic and environmental data of the target area, and preprocess the multi-source basic geographic and environmental data to form a structured dataset; wherein, the target DEM terrain data in the structured dataset includes first DEM data at a first resolution and second DEM data at a second resolution, wherein the first resolution is greater than the second resolution; Construct a river buffer zone based on the first DEM data; Using the river buffer zone as a mask area, first simulated DEM data within the mask area is extracted from the first DEM data, and second simulated DEM data outside the mask area is filtered out from the second DEM data to form nested DEM data; A two-dimensional computational mesh is constructed based on the nested DEM data; wherein the mesh size within the mask region matches the first resolution, and the mesh size outside the mask region matches the second resolution; A hydrodynamic model is established based on the two-dimensional shallow water equation, and the model parameters and input data of the hydrodynamic model are obtained from the structured dataset. Flood inundation simulation is performed on the two-dimensional computational grid using the hydrodynamic model to obtain flood inundation simulation results.

2. The flood inundation simulation method according to claim 1, characterized in that, The process involves using the riverbed buffer zone as a mask area, extracting first simulated DEM data within the mask area from the first DEM data, and filtering out second simulated DEM data outside the mask area from the second DEM data to form nested DEM data, including: Using the river buffer zone as the mask area, the grid cells within the mask area are cropped from the first DEM data to obtain the first simulated DEM data; Remove the grid cells within the mask area from the second DEM data, and retain the grid cells outside the mask area to obtain the second simulated DEM data; The first simulated DEM data and the second simulated DEM data are spatially superimposed to form the nested DEM data.

3. The flood inundation simulation method according to claim 2, characterized in that, The step of spatially overlaying the first simulated DEM data and the second simulated DEM data to form the nested DEM data includes: A transition region is provided at the boundary of the mask area; Within the transition area, the elevation values ​​of the first simulated DEM data and the second simulated DEM data are interpolated to obtain the elevation values ​​of the raster cells within the transition area. The first simulated DEM data, the second simulated DEM data, and the interpolated transition region are spatially superimposed to form the nested DEM data.

4. The flood inundation simulation method according to claim 1, characterized in that, The process of simulating flood inundation using the hydrodynamic model on the two-dimensional computational grid includes: On the grid within the mask area, flood evolution calculations are performed at a time step corresponding to the first resolution; On the grid outside the masked area, flood evolution calculations are performed at a time step corresponding to the second resolution.

5. The flood inundation simulation method according to claim 1, characterized in that, The multi-source basic geographic and environmental data includes raw DEM topographic data, raw rainfall data, raw hydrological data, raw land use data, and raw remote sensing imagery. The preprocessing of the multi-source basic geographic and environmental data includes: The original DEM terrain data is subjected to coordinate unification, depression filling and outlier processing to obtain the target terrain DEM data; Missing values ​​are imputed and outliers are removed from the original rainfall data and the original hydrological data to obtain the target rainfall data and the target hydrological data. The original land use data is reclassified and format converted to obtain the target land use data; Radiometric calibration, atmospheric correction, and geometric correction are performed on the original remote sensing image to obtain the target remote sensing image.

6. The flood inundation simulation method according to claim 5, characterized in that, The model parameters and input data of the hydrodynamic model are obtained from the structured dataset, including: Obtain the target rainfall data, the target hydrological data, the target land use data, and the target remote sensing image from the structured dataset; The target rainfall data is used as the boundary input condition for the hydrodynamic model; The target hydrological data is used as the calibration data for the hydrodynamic model; The target land use data is used as the basis for setting the roughness parameter of the hydrodynamic model; The remote sensing image of the target is used as verification data for the inundation range of the hydrodynamic model.

7. The flood inundation simulation method according to claim 1, characterized in that, The construction of the river buffer based on the first DEM data includes: Based on the first DEM data, calculate the surface flow direction; Based on the first DEM data and the surface flow direction, calculate the cumulative runoff volume; Each grid cell whose cumulative runoff reaches a preset runoff threshold is identified as a river network; The river network is converted into vector line elements, and the river buffer zone is constructed at a preset distance using the vector line elements as the river centerline.

8. A flood inundation simulation device, characterized in that, include: The data acquisition module is used to acquire multi-source basic geographic and environmental data of the target area and preprocess the multi-source basic geographic and environmental data to form a structured dataset; wherein, the target terrain DEM data in the structured dataset includes first DEM data at a first resolution and second DEM data at a second resolution, wherein the first resolution is greater than the second resolution. A buffer construction module is used to construct a river channel buffer based on the first DEM data; The nested construction module is used to extract first simulated DEM data within the mask area from the first DEM data, and filter out second simulated DEM data outside the mask area from the second DEM data, thereby forming nested DEM data; A mesh construction module is used to construct a two-dimensional computational mesh based on the nested DEM data; wherein the mesh size within the mask region matches the first resolution, and the mesh size outside the mask region matches the second resolution; The model building module is used to establish a hydrodynamic model based on the two-dimensional shallow water equation and to obtain the model parameters and input data of the hydrodynamic model from the structured dataset. The simulation module is used to perform flood inundation simulation on the two-dimensional computing grid using the hydrodynamic model, and obtain flood inundation simulation results.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the flood inundation simulation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the flood inundation simulation method as described in any one of claims 1 to 7.

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