A flooding data analysis method based on an efficient spatial search algorithm

Abstract

This invention relates to the field of flood inundation analysis technology, solving the problems of high technical requirements and low computational efficiency caused by the excessive computational power consumption of traditional techniques. Specifically, it relates to an inundation data analysis method based on an efficient spatial search algorithm. By acquiring topographic raster data corresponding to the target flood storage area and real-time water level data at the inlet, the raster cell corresponding to the inlet of the target flood storage area is used as the initial search node in a two-dimensional coordinate system composed of the topographic raster data. This invention employs a breadth-first spatial search algorithm, starting from the inlet gate, to search physically connected adjacent raster cells. This avoids the shortcomings of existing hydraulic models, such as high computational power consumption and long single-calculation time. By converting global calculation into local search, it not only shortens the calculation time but also enables rapid output of calculation results based on real-time measured water level data, fulfilling the need for high-frequency, real-time early warning simulations of flood storage areas.

Description

Technical Field

[0001] This invention relates to the field of flood inundation analysis technology, and in particular to a flood data analysis method based on an efficient spatial search algorithm. Background Technology

[0002] The delineation of flood inundation areas in flood storage and detention areas has long faced a difficult technical challenge in reconciling computational efficiency, physical simulation accuracy, and the degree of automation. Existing technologies typically employ hydraulic modeling software for delineation. This involves using software such as HEC-GeoRAS and MIKE to create hydrodynamic models with basic river information, including river networks, channels, distributaries, and river sections, within a GIS environment. Simultaneously, the calculation of the river water surface line generates DEM elevation model data of the inundation depth and a Shapefile file for the management boundary line, thereby forming the inundation area. Finally, the edge lines are extracted to form the inundation boundary line.

[0003] However, this method has technical drawbacks such as high professional modeling threshold and huge computing power consumption leading to low computational efficiency. It is difficult to meet the needs of the water conservancy system for high-frequency, real-time and rapid dynamic assessment of the flood storage area and property damage of residents based on real-time water level measurement. Its scalability and practicality are not strong. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a flooding data analysis method based on an efficient spatial search algorithm, which solves the problem that existing technologies have high professional requirements and consume a lot of computing power, resulting in low computational efficiency.

[0005] To address the aforementioned technical problems, this invention provides the following technical solution: a flooding data analysis method based on an efficient spatial search algorithm, comprising the following steps: Acquire topographic raster data corresponding to the target flood storage and detention area and real-time water level data at the inlet; In the two-dimensional coordinate system formed by the terrain raster data, the raster cell corresponding to the entrance of the target flood storage area is used as the initial search node, and the real-time water level data is used as the reference water level for the whole area to be flooded. Based on the breadth-first spatial search algorithm, the initial search node is used as the starting point to search for the surrounding neighboring grids, and the elevation values ​​of the neighboring grids are numerically compared with the benchmark water level of the entire flooded area. When the elevation value is less than the reference water level, it is confirmed that the adjacent grid meets the water connectivity condition. The adjacent grid is then included in the submerged grid set. At the same time, the adjacent grid is added as a new active search node to the waiting queue of the search queue, serving as the central node for subsequent searches. The search logic for adjacent grids and the judgment logic for water connectivity status are continuously looped until the number of active search nodes in the search queue is zero and becomes an empty set. At this point, a termination signal is triggered and the current search process ends. When the elevation value is greater than or equal to the reference water level, it is determined that the water body is blocked and the search in that direction is stopped. The corresponding adjacent grid is marked as a boundary grid. The search of adjacent grids and the water body connectivity judgment logic are continuously looped until all active search nodes in the search queue have been searched and the search queue becomes an empty set, at which time a global search termination command is triggered. Extract the flooded raster set and all boundary raster, use the Marching Squares algorithm to divide adjacent raster into local grid cells of a preset size, and perform state analysis on their vertices to generate flooded data analysis results.

[0006] Preferably, in a two-dimensional coordinate system composed of terrain raster data, the raster cell corresponding to the entrance of the target flood storage area is used as the initial search node, specifically including the following steps: A two-dimensional coordinate system is constructed based on terrain raster data, so that each raster cell in the terrain raster data is mapped to a discrete node in the two-dimensional coordinate system. Extract the geographic coordinates of the entrance to the target flood storage area, match and retrieve the specific raster cell corresponding to the geographic coordinates in the two-dimensional coordinate system, and mark the specific raster cell as the initial search node.

[0007] Preferably, the breadth-first spatial search algorithm searches for neighboring grid cells starting from the initial search node, specifically including the following steps: Construct a search queue to store the raster data to be processed, and add the initial search node as the first active search node to the search queue to initialize the breadth-first spatial search algorithm; Extract the active search node at the front of the search queue, use it as the current center node for spreading, and remove it from the waiting execution column of the search queue; In a two-dimensional coordinate system, a multi-directional neighborhood space traversal is initiated with the central node as the reference and in the orthogonal and diagonal directions to extract adjacent grid cells that are spatially connected to the central node.

[0008] Preferably, the inundation data analysis results include at least one of the following: the boundary line of the inundation area, the flood storage volume of the target flood detention area, and the results of residents' property losses. The specific steps for generating the boundary line of the inundation area include the following: Extract the flooded grid set and all boundary grids. Use the Marching Squares algorithm to divide adjacent grids in the two-dimensional coordinate system into local grid cells with a preset size, and map the four adjacent grids in each local grid cell to four geometric vertices respectively. Traverse each geometric vertex in the local grid cell and determine the discrete state of the geometric vertex according to the set properties of the corresponding grid. If the corresponding grid belongs to the submerged grid set, mark the state of its corresponding geometric vertex as the first state. If the corresponding grid belongs to the boundary grid, mark the state of its corresponding geometric vertex as the second state. Extract the spatial distribution combination of the first and second states of four geometric vertices within a single local mesh cell, and perform pattern matching with several preset standard boundary connectivity rules; Interpolation analysis is performed based on the successfully matched standard boundary connectivity rules to generate local contour segments that run through the current local grid cell. All local contour segments are then smoothly spliced ​​together sequentially according to the spatial adjacency relationship of adjacent local grid cells to generate a continuous flooding range boundary line.

[0009] Preferably, the specific steps for calculating the flood storage capacity based on the boundary line of the inundation area include the following: Based on the boundary line of the flooded area, all grid cells within the flooded area are divided into internal grids and boundary grids; Extract the complete surface area in the internal grid as the flooded area, and call the coordinates of the crossing point of the flooded range boundary line in the corresponding local topology grid cell to obtain the local flooded area of ​​the boundary grid on the water body connected side, thereby obtaining the effective flooded area of ​​each grid cell. The flood storage capacity of the target flood detention area is calculated by combining the elevation value of each grid cell and the total number of submerged grid cells. The calculation formula is as follows: In the above formula, This indicates the flood storage capacity of the target flood detention area; Indicates the index of the cumulative sequence variable for each raster cell; This represents the effective flooded area of ​​the i-th grid cell; The baseline water level indicating total submersion; This represents the elevation value corresponding to the i-th grid cell; This indicates the total number of submerged grid cells.

[0010] Preferably, the specific steps for generating the result of resident property loss include the following: A database of residents' property in the target flood storage and detention area is pre-constructed. The database includes the geographical coordinates of each resident's property within the target flood storage and detention area, as well as the benchmark information for calculating the economic value of the assets. Using the boundary line of the flooded area as the spatial query boundary, a flooded polygon search surface is constructed in the two-dimensional coordinate system of the Geographic Information System (GIS). This surface is then used as the spatial boundary to perform spatial intersection search and comparison operations with the residential property database. Extract all target residents' property affected by the disaster within the flooded polygon enclosed by the boundary line of the flooded area, based on the geographic coordinate information, and summarize them based on the asset economic value accounting benchmark information to generate the result of residents' property loss in the target flood storage area at the current specific water level.

[0011] A flooding data analysis system based on an efficient spatial search algorithm includes a processor and a memory. The memory stores a computer program, which is executed by the processor to implement the flooding data analysis method.

[0012] By employing the above technical solution, the present invention provides a flooding data analysis method based on an efficient spatial search algorithm, which has at least the following beneficial effects: 1. This invention employs a breadth-first spatial search algorithm, starting from the inlet gate to search for physically connected adjacent grids. This avoids the drawbacks of existing hydraulic models, such as high computational cost and long single calculation time. By converting global calculation into local search, it not only shortens the calculation time but also enables rapid output of calculation results based on real-time measured water level data. This fulfills the need for high-frequency, real-time early warning simulation of flood storage and detention areas under the existing water conservancy system.

[0013] 2. This invention uses the Marching Squares algorithm to calculate the inundation range line at a specific water level, which can handle the jagged edges of discrete grids and accurately reconstruct continuous and smooth inundation range lines. This greatly improves the extraction accuracy of the inundation range line, reduces the area calculation error caused by coarse grids, and improves the efficiency of analyzing inundation data in flood storage and detention areas.

[0014] 3. By collecting topographic raster data and real-time water level data of the target area, this invention solves the problem that existing technologies require the manual establishment of complex basic information such as river networks, channels, and tributaries. This reduces the threshold for the research, development, deployment, and operation and maintenance of the entire system, enabling it to be used in flood storage and detention areas of different watersheds and terrains at extremely low cost, and enhancing the engineering promotion and universal applicability of the system.

[0015] 4. This invention transforms the boundary line of the flooded area into a polygonal spatial retrieval surface and calls the Geographic Information System (GIS) engine to calculate the results of residents' property losses, avoiding the intermediate link of manual intervention. This enables flood control command departments to combine real-time water levels to not only quickly assess current property losses, but also to quickly compare different flood storage and detention areas, providing rapid and accurate decision support for flood control scheduling when flood storage and detention areas are activated. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart of the flooding analysis method in this invention; Figure 2 This is a logic diagram of the spatial search algorithm in this invention; Figure 3 This is a schematic diagram of the spatial search algorithm in this invention; Figure 4 This is a diagram showing the results of the spatial search algorithm in this invention; Figure 5 The flooding range line generated by this invention. Detailed Implementation

[0017] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. This will allow for a full understanding of how the present application uses technical means to solve technical problems and achieve technical effects, and to facilitate its implementation.

[0018] Existing technologies use hydraulic modeling software to delineate the flood inundation range of flood storage and detention areas, requiring a high level of expertise and mastery of the hydrodynamic modeling process. However, their practical applicability and generalizability are limited. To avoid the drawbacks of existing hydraulic models, such as excessive computational consumption and long calculation times per run, and to meet the need for high-frequency, real-time early warning simulations of flood storage and detention areas within the existing water conservancy system, this invention proposes an inundation data analysis method based on an efficient spatial search algorithm, such as... Figure 1 As shown, the method includes the following steps: By acquiring topographic raster data corresponding to the target flood storage and detention area, as well as real-time water level data at the inlet of the flow field in the target flood storage and detention area, the topographic raster data can be digital elevation model raster data or elevation grayscale map, etc. This reduces the modeling threshold and data acquisition cost of water conservancy systems when analyzing flood inundation ranges, and enhances the engineering promotion and universal applicability of the system.

[0019] Digital Elevation Model (DEM) raster data is a type of isometric spatial data composed of continuous rasters. It cuts the real, continuous undulating terrain into regular square grids, directly using them as a two-dimensional coordinate system for analysis. In this two-dimensional coordinate system, each raster (grid cell) records the terrain elevation value corresponding to that geographical location. Each pixel in the elevation grayscale map is equivalent to a discrete grid cell in this two-dimensional coordinate system. The absolute or relative column and row number of this pixel in the coordinate matrix constitutes its two-dimensional coordinate position.

[0020] Based on a two-dimensional coordinate system established from digital elevation model raster data or elevation grayscale maps, each raster cell in the terrain raster data is mapped to a discrete node in the two-dimensional coordinate system. The geographic coordinates of the inlet of the target flood storage area are extracted, and specific raster cells corresponding to these geographic coordinates are matched and retrieved in the two-dimensional coordinate system. These specific raster cells are then marked as the initial search node. Simultaneously, the real-time water level data at the inlet of the target flood storage area's flow field is used as the benchmark water level for total flooding.

[0021] By determining the initial search nodes and the baseline water level for total flooding, the flood control boundary conditions are established, ensuring the spatial accuracy of the water spread simulation. This allows for the automatic and precise identification of the water-blocking boundaries of the real water flow, thus improving the spatial accuracy of the model simulation.

[0022] Existing technologies (such as those using software like MIKE and HEC-GeoRAS) require solving extremely complex fluid dynamics equations when building hydrodynamic models, resulting in enormous computational costs and extremely long processing times, which cannot meet the needs of dynamic assessment of flood storage and detention areas. This paper proposes a breadth-first spatial search algorithm that uses an initial search node as a starting point to perform a diffuse topological search to its surrounding connected neighboring grids, and compares the elevation values ​​of the searched neighboring grids with the baseline water level for total flooding. This enables the entire system to effectively meet the requirements of real-time computation, thereby supporting dynamic disaster simulation based on real-time water level measurements.

[0023] Specifically, such as Figure 2 As shown, in this embodiment, the coordinates of the entrance gate of the flood storage area are set as (0,0), the water level at point (0,0) is h, and the white line is the entrance gate restriction line. The grid elevation at the restriction line can be forced to infinity or any value higher than h. A topology search is performed starting from the starting point (0,0), and the search directions include the +x direction, -x direction, +y direction, -y direction, and the four diagonal directions.

[0024] In this embodiment, as a preferred implementation method, the implementation steps are as follows: A search queue is constructed to store the raster data to be processed, and the initial search node is added to the search queue as the first active search node to initialize the preset breadth-first spatial search algorithm. This extracts the active search nodes at the front of the search queue, such as... Figure 3 As shown, the central node is selected as the current spreading center node and removed from the search queue. In a two-dimensional coordinate system, a multi-directional neighborhood space traversal is initiated from the central node in its orthogonal and diagonal directions, specifically an eight-directional neighborhood space, to extract adjacent grids that are spatially connected to the central node. Then, the elevation values ​​of the adjacent grids are numerically compared with the reference water level to determine whether the adjacent grids meet the water connectivity condition.

[0025] When the elevation value of an adjacent grid is less than the reference water level, it is confirmed that the adjacent grid meets the water connectivity condition. The adjacent grid is then included in the submerged grid set and added as a new active search node to the waiting queue of the search queue, serving as the central node for subsequent searches. The search logic for adjacent grids and the judgment logic for water connectivity status are continuously looped until the number of active search nodes in the search queue becomes zero and becomes an empty set. At this point, a termination signal is triggered, and the current search process ends.

[0026] When the elevation value of an adjacent grid is greater than or equal to the reference water level, the search in that direction is stopped because the water spread is blocked. The corresponding adjacent grid is marked as a boundary grid. The search for adjacent grids and the water connectivity judgment logic are continuously looped until all active search nodes in the search queue have been searched and the search queue becomes an empty set, at which point a global search termination command is triggered.

[0027] In response to the global search termination command, all adjacent grids that have been included in the flooded grid set and all marked boundary grids are extracted and summarized. Based on the coordinate position of each grid in the two-dimensional coordinate system, spatial mapping and combination are performed to determine the spatial flood inundation range of the target flood storage area at a specific water level.

[0028] The searched set of inundated grid cells and all marked boundary grid cells are extracted. Based on a preset Marching Squares algorithm, adjacent grid cells are divided into local grid cells of a preset size, and state analysis is performed on their vertices to generate inundation data analysis results. These results include at least one of the following: the boundary line of the inundated area, the flood storage capacity of the target flood detention area, and the property damage results.

[0029] Specifically, the Marching Squares algorithm maps four adjacent grid cells to a 2x2 array as a data unit for analysis, with each grid cell serving as a vertex in the 2x2 array. Each grid cell has two states: one is below the baseline water level (the first state), represented by a white dot in this embodiment (corresponding to...). Figure 4 The calculation result (×) is another one, which is the second state, where the water level is higher than the benchmark level. We represent this with black dots (corresponding to...). Figure 4 The calculation results (circles) can yield 16 different cases, i.e., 16 standard boundary connectivity rules, based on different vertex states. Using these connectivity rules, connectivity interpolation analysis is performed on the grids marked with "×" in all calculation results to obtain the optimized flood inundation range line, such as... Figure 5 The blue string in the middle.

[0030] To address the issue that traditional hydraulic models require significant computational resources for boundary line extraction and cannot provide real-time output, this embodiment, as a preferred implementation, includes the following specific steps for generating the inundation range boundary line: Extract the flooded grid set and all boundary grids. Use the Marching Squares algorithm to divide adjacent grids in the two-dimensional coordinate system into local grid cells with a preset size, and map the four adjacent grids in each local grid cell to four geometric vertices respectively.

[0031] Traverse each geometric vertex in the local grid cell and determine the discrete state of the geometric vertex according to the set attribute of the corresponding grid. If the corresponding grid belongs to the submerged grid set, mark the state of its corresponding geometric vertex as the first state. If the corresponding grid belongs to the boundary grid, mark the state of its corresponding geometric vertex as the second state. Extract the spatial distribution combination of the first state and the second state of the four geometric vertices in a single local grid cell and perform pattern matching with several preset standard boundary connectivity rules, specifically 16 standard boundary connectivity rules.

[0032] Interpolation analysis is performed based on the successfully matched standard boundary connectivity rules to generate local contour segments that run through the current local grid cell. All local contour segments are then smoothly spliced ​​together sequentially according to the spatial adjacency relationship of adjacent local grid cells to generate a continuous flooding range boundary line.

[0033] To overcome the drawback of difficulty in quickly and accurately quantifying water volume in complex terrain, this embodiment, as a preferred implementation, includes the following specific steps for calculating flood storage capacity based on the inundation boundary line: Based on the boundary line of the inundation range, all grid cells within the inundation range are divided into internal grids and boundary grids. Internal grids are completely located inside the boundary line, while boundary grids are cut through by the boundary line. The complete surface area of ​​the internal grid is extracted as the inundated area, and the coordinates of the crossing point of the boundary line of the inundation range in the corresponding local topological grid cell are called. Based on the principle of polygon area calculation, the local inundated area of ​​the boundary grid on the water body connected side is accurately calculated, thereby obtaining the effective inundated area of ​​each grid cell.

[0034] The flood storage capacity of the target flood detention area is calculated based on the effective flood-affected area of ​​each grid cell, combined with the elevation value of each grid cell and the total number of flooded grid cells. The calculation formula is as follows: In the above formula, This indicates the flood storage capacity of the target flood detention area; Indicates the index of the cumulative sequence variable for each grid cell, ensuring that the global spatial integration is traversed without omission; This represents the effective flooded area of ​​the i-th grid cell; The baseline water level indicating total submersion; This represents the elevation value corresponding to the i-th grid cell; This indicates the total number of flooded raster cells (including fully flooded inner rasters and partially flooded boundary rasters).

[0035] To address the problem of severely delayed and time-consuming disaster loss statistics caused by relying on manual secondary comparisons, this method not only enables rapid assessment of current property losses but also allows for rapid comparison of different flood storage and detention area plans. In this embodiment, as a preferred implementation, the specific steps for generating residents' property loss results include the following: By pre-constructing a database of residents' property in the target flood storage and detention area, the database includes the geographical coordinates of each resident's property within the target flood storage and detention area, as well as the benchmark information for calculating the economic value of the linked assets.

[0036] Using the boundary line of the inundation area as the spatial query boundary, a submerged polygon search surface is constructed in the two-dimensional coordinate system of the Geographic Information System (GIS). This surface is used as the spatial boundary to perform spatial intersection search and comparison operations with the residential property database. All target residents' disaster-affected property objects whose geographic coordinate information falls within the submerged polygon enclosed by the boundary line of the inundation area are extracted. Based on the asset economic value accounting benchmark information, the results of residents' property loss in the target flood storage area at the current specific water level are summarized to generate the results of residents' property loss in the target flood storage area.

[0037] This analysis method acquires topographic raster data corresponding to the target flood storage area and real-time water level data at the inlet. A two-dimensional coordinate system is constructed from the topographic raster data. The raster cell corresponding to the inlet of the target flood storage area is used as the initial search node, and the real-time water level data is used as the reference water level for the entire flood area. Based on the breadth-first spatial search algorithm, the method searches for neighboring raster cells starting from the initial search node. The elevation values ​​of neighboring raster cells are compared with the reference water level. If the elevation value of a neighboring raster cell is less than the reference water level, the corresponding neighboring raster cell is added to the flooded raster set and added as an active search node to the search queue to continue searching until the search is complete. If the elevation value of a neighboring raster cell is greater than or equal to the reference water level, the corresponding neighboring raster cell is marked as a boundary raster cell and the search stops. Then, the flooded raster set and all boundary raster cells are extracted. The Marching Squares algorithm is used to divide the neighboring raster cells into local grid cells of a preset size, and the state analysis of their vertices is performed to obtain the flood data analysis results.

[0038] The present invention also provides a flooding data analysis system based on an efficient spatial search algorithm, including a processor and a memory. The memory is used to store a computer program, and when the computer program is executed by the processor, it implements the flooding data analysis method.

[0039] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0040] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. Since the above embodiments are substantially similar to the method embodiments, their descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0041] The above embodiments provide a detailed description of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A flooding data analysis method based on an efficient spatial search algorithm, characterized in that, The method includes the following steps: Acquire topographic raster data corresponding to the target flood storage and detention area and real-time water level data at the inlet; In the two-dimensional coordinate system formed by the terrain raster data, the raster cell corresponding to the entrance of the target flood storage area is used as the initial search node, and the real-time water level data is used as the reference water level for the whole area to be flooded. The breadth-first spatial search algorithm searches for neighboring grids starting from the initial search node and determines whether the elevation value of the neighboring grids is less than the reference water level. If so, add the corresponding adjacent grid cells to the flooded grid cell set and add them as active search nodes to the search queue to continue searching until the set is empty; If not, mark the corresponding adjacent grid as a boundary grid and stop the search; Extract the flooded raster set and all boundary raster, use the Marching Squares algorithm to divide adjacent raster into local grid cells of a preset size, and perform state analysis on their vertices to generate flooded data analysis results.

2. The flooding analysis method according to claim 1, characterized in that, In the two-dimensional coordinate system formed by the terrain raster data, the raster cell corresponding to the entrance of the target flood storage and detention area is used as the initial search node, which specifically includes the following steps: A two-dimensional coordinate system is constructed based on terrain raster data, so that each raster cell in the terrain raster data is mapped to a discrete node in the two-dimensional coordinate system. Extract the geographic coordinates of the entrance to the target flood storage area, match and retrieve the specific raster cell corresponding to the geographic coordinates in the two-dimensional coordinate system, and mark the specific raster cell as the initial search node.

3. The flooding analysis method according to claim 1, characterized in that, The breadth-first spatial search algorithm searches for neighboring grid cells starting from the initial search node, specifically including the following steps: Construct a search queue to store the raster data to be processed, and add the initial search node as the first active search node to the search queue to initialize the breadth-first spatial search algorithm; Extract the active search node at the front of the search queue, use it as the current center node for spreading, and remove it from the waiting execution column of the search queue; In a two-dimensional coordinate system, a multi-directional neighborhood space traversal is initiated with the central node as the reference and in the orthogonal and diagonal directions to extract adjacent grid cells that are spatially connected to the central node.

4. The flooding analysis method according to claim 1, characterized in that, The inundation data analysis results include at least one of the following: the boundary line of the inundation area, the flood storage volume of the target flood detention area, and the property loss results of residents. The specific steps for generating the boundary line of the inundation area include the following: Extract the flooded grid set and all boundary grids. Use the Marching Squares algorithm to divide adjacent grids in the two-dimensional coordinate system into local grid cells with a preset size, and map the four adjacent grids in each local grid cell to four geometric vertices respectively. Traverse each geometric vertex in the local grid cell and determine the discrete state of the geometric vertex according to the set properties of the corresponding grid. If the corresponding grid belongs to the submerged grid set, mark the state of its corresponding geometric vertex as the first state. If the corresponding grid belongs to the boundary grid, mark the state of its corresponding geometric vertex as the second state. Extract the spatial distribution combination of the first and second states of four geometric vertices within a single local mesh cell, and perform pattern matching with several preset standard boundary connectivity rules; Interpolation analysis is performed based on the successfully matched standard boundary connectivity rules to generate local contour segments that run through the current local grid cell. All local contour segments are then smoothly spliced ​​together sequentially according to the spatial adjacency relationship of adjacent local grid cells to generate a continuous flooding range boundary line.

5. The flooding analysis method according to claim 4, characterized in that, The specific steps for calculating the flood storage capacity based on the boundary line of the inundation area include the following: Based on the boundary line of the flooded area, all grid cells within the flooded area are divided into internal grids and boundary grids; Extract the complete surface area in the internal grid as the flooded area, and call the coordinates of the crossing point of the flooded range boundary line in the corresponding local topology grid cell to obtain the local flooded area of ​​the boundary grid on the water body connected side, thereby obtaining the effective flooded area of ​​each grid cell. The flood storage capacity of the target flood detention area is calculated by combining the elevation value of each grid cell and the total number of submerged grid cells.

6. The flooding analysis method according to claim 5, characterized in that, The formula for calculating the flood storage capacity is as follows: In the above formula, This indicates the flood storage capacity of the target flood detention area; Indicates the index of the cumulative sequence variable for each raster cell; This represents the effective flooded area of ​​the i-th grid cell; The baseline water level indicating total submersion; This represents the elevation value corresponding to the i-th grid cell; This indicates the total number of submerged grid cells.

7. The flooding analysis method according to claim 4, characterized in that, The specific steps for generating the results of residents' property loss include the following: A database of residents' property in the target flood storage and detention area is pre-constructed. The database includes the geographical coordinates of each resident's property object in the target flood storage and detention area and the benchmark information for calculating the economic value of the assets. Using the boundary line of the flooded area as the spatial query boundary, a flooded polygon retrieval surface is constructed in the two-dimensional coordinate system of the geographic information system. This surface is then used as the spatial boundary to perform spatial intersection retrieval and comparison operations with the residents' property database. Extract all target residents' property affected by the disaster within the flooded polygon enclosed by the boundary line of the flooded area, based on the geographic coordinate information, and summarize them based on the asset economic value accounting benchmark information to generate the result of residents' property loss in the target flood storage area at the current specific water level.

8. The flooding analysis method according to claim 1, characterized in that, The specific steps for adding the corresponding adjacent grid cells to the submerged grid cell set when the elevation value of an adjacent grid cell is less than the reference water level, and adding them as active search nodes to the search queue to continue searching until the set is empty, include the following: When the elevation value is less than the reference water level, it is confirmed that the adjacent grid meets the water body connectivity condition, the adjacent grid is included in the submerged grid set, and the adjacent grid is added as a new active search node to the waiting queue of the search queue, so as to serve as the central node for subsequent searches. The search logic for adjacent grids and the determination of water connectivity status are continuously looped until the number of active search nodes in the search queue becomes zero and becomes an empty set. At this point, a termination signal is triggered and the current search process ends.

9. The flooding analysis method according to claim 1, characterized in that, The specific steps for marking the corresponding adjacent grid as a boundary grid and stopping the search when the elevation value of an adjacent grid is greater than or equal to the reference water level include the following: When the elevation value is greater than or equal to the reference water level, it is determined that the water spread is blocked and the search in that direction is stopped, and the corresponding adjacent grid is marked as a boundary grid. The search logic continuously loops between adjacent grids and determines the connectivity status of water bodies until all active search nodes in the search queue have been searched and the search queue becomes empty, at which point a global search termination command is triggered.

10. A system for implementing the flooding data analysis method according to any one of claims 1-9, characterized in that, It includes a processor and a memory, the memory being used to store a computer program that, when executed by the processor, implements the flooding data analysis method as described in any one of claims 1-9.

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