Flood dynamic display method and device, equipment, medium and product

Abstract

The invention discloses a flood dynamic display method and device, equipment, a medium and a product. The method comprises the steps of performing grid reconstruction on irregular quadrilateral grid data at a plurality of moments based on a triangulated irregular network algorithm, and generating first triangular grid data at the plurality of moments; extracting a target quadrilateral grid from the irregular quadrilateral grid data at multiple moments; determining second triangular mesh data at multiple moments corresponding to the target quadrilateral mesh in the first triangular mesh data at multiple moments; constructing an index structure of the second triangular mesh data based on the index identifier, the first mapping relationship and the second mapping relationship; based on the second triangular mesh data and the index structure, generating a to-be-rendered dynamic water surface data set; and based on a time sequence and a multi-normal superposition rendering technology based on a graphic interface, generating visual data representing dynamic changes of the water surface. In this way, the visualization effect and performance of flood routing simulation are improved.

Description

Technical Field

[0001] The present application relates to the field of water conservancy engineering informatization, and in particular to a method, device, equipment, medium and product for dynamic display of floods. Background Art

[0002] In the field of hydrodynamic simulation and visualization today, with the continuous progress of scientific research and technological application, two-dimensional hydrodynamic models have been widely used in various scenarios such as flood simulation, water resources management, and disaster warning. The model simulates the flow of water in a large area of ​​water and provides a basis for relevant decision-making. However, since the result data generated by the two-dimensional hydrodynamic model is presented as a huge quadrilateral grid at multiple times, this brings a series of technical difficulties in the subsequent three-dimensional rendering.

[0003] First, direct rendering of raw data often leads to the problem of uneven water surface. When simulating scenes such as floods, the water surface should appear as a smooth, natural surface to accurately reproduce the dynamics of the water flow. However, since the result data of the two-dimensional hydrodynamic model presents a complex quadrilateral mesh, the direct rendering of these meshes will cause unnecessary ups and downs and depressions on the water surface, seriously affecting the authenticity of the rendering effect. The uneven water surface phenomenon not only hinders the accurate restoration of the flood evolution scene, but also makes it difficult for users to visually perceive the natural dynamics of the water flow, thereby reducing the credibility and usability of the simulation results.

[0004] Secondly, the rendering performance problem is particularly prominent. The output data of the two-dimensional hydrodynamic model usually includes huge quadrilateral mesh data that is calculated and stored at multiple time nodes. The loading, rendering and storage of this data consumes a huge amount of computing resources. Especially on low-configuration devices, the system often loads slowly, freezes or even crashes when processing these massive amounts of data, which greatly affects the real-time performance of the simulation and the user experience. For real-time flood dynamic simulations that require fast and efficient rendering, data processing and rendering efficiency have become a key issue that needs to be solved urgently.

[0005] Furthermore, the problem of uneven switching of temporal data also seriously affects the fluency of the simulation. In the simulation of flood evolution, the switching of data between different time nodes should present a smooth transition to ensure the continuity of the entire simulation process. However, the original data lacks a smooth transition effect during the temporal switching process, resulting in obvious stuttering and jumping at the moment of data switching, as if the continuity of time was artificially interrupted. This sense of discontinuity not only destroys the realism of the simulation scene, but also makes it impossible for users to accurately capture subtle changes when observing the evolution of the flood, which seriously affects the intuitiveness and accuracy of the simulation results. Summary of the invention

[0006] In view of this, the embodiments of the present application provide a method, device, equipment, medium and product for dynamic display of floods, aiming to solve the technical problems of low accuracy, poor rendering performance and fluency in flood evolution simulation.

[0007] The technical solution of the embodiment of the present application is implemented as follows:

[0008] In a first aspect, an embodiment of the present application provides a method for displaying flood dynamics, the method comprising:

[0009] Acquire water surface temporal result data for a target area generated by a two-dimensional hydrodynamic model, wherein the water surface temporal result data includes irregular quadrilateral grid data at multiple time points;

[0010] Reconstructing the irregular quadrilateral mesh data at the multiple moments based on an irregular triangulated network algorithm to generate first triangular mesh data at the multiple moments, wherein the irregular triangulated network algorithm is used to reconstruct the vertices of the irregular quadrilateral mesh data into a shared vertex triangular mesh;

[0011] Extracting a target quadrilateral grid from the irregular quadrilateral grid data at the plurality of moments, wherein the target quadrilateral grid is an irregular quadrilateral grid containing water depth data at each moment;

[0012] Determine second triangular mesh data at multiple moments corresponding to the target quadrilateral mesh among the first triangular mesh data at the multiple moments;

[0013] Re-indexing the second triangular mesh data at the multiple moments to generate index identifiers of the second triangular mesh data; constructing an index structure of the second triangular mesh data based on the index identifier, the first mapping relationship, and the second mapping relationship, wherein the index structure is used to associate the index identifiers of the vertices of the triangular meshes in the second triangular mesh data with the water surface temporal data; and generating a dynamic water surface data set to be rendered based on the second triangular mesh data and the index structure;

[0014] The first mapping relationship includes the correspondence between the irregular quadrilateral mesh at the multiple moments and the vertices of the second triangular mesh at the multiple moments, the second mapping relationship includes the correspondence between the irregular quadrilateral mesh at the multiple moments and the water surface temporal data, and the water surface temporal data includes the water depth data and water flow data of the target area;

[0015] Based on the time series and the multiple normal overlay rendering technology based on the graphic interface, the dynamic water surface data set to be rendered is rendered to generate visualization data representing the dynamic changes of the water surface.

[0016] In some embodiments, the method further comprises:

[0017] The visualization data is sent to the browser device based on real-time communication of the web page.

[0018] In some embodiments, the method further comprises:

[0019] storing the second triangular mesh data at the plurality of time instants based on a set storage format, wherein the set storage format includes a binary format;

[0020] The second triangular mesh data at the multiple time instants are compressed based on a lossless data compression algorithm.

[0021] In some embodiments, the method further comprises:

[0022] Acquire terrain information of the target area, river section data of the target area, hydrological data of the target area, and elevation information of the target area;

[0023] Meshing the target area based on the two-dimensional hydrodynamic model to generate a plurality of irregular quadrilateral meshes;

[0024] Based on the multiple irregular quadrilateral grids, the terrain information, the river section data, the hydrological data, the elevation information and the two-dimensional hydrodynamic model, the water surface temporal result data is generated, and the water surface temporal result data includes the irregular quadrilateral grid data at the multiple time moments.

[0025] In some embodiments, the irregular triangulated network algorithm is a Delaunay triangulation algorithm, and the irregular quadrilateral mesh data at the multiple moments are reconstructed based on the irregular triangulated network algorithm to generate first triangular mesh data at the multiple moments, including:

[0026] The irregular quadrilateral mesh data at the multiple moments are reconstructed based on the Delaunay triangulation algorithm to generate the first triangular mesh data.

[0027] In some embodiments, reconstructing the irregular quadrilateral mesh data at the plurality of time instants based on the Delaunay triangulation algorithm to generate the first triangular mesh data includes:

[0028] Construct the Veronese diagram corresponding to the Delaunay triangulation;

[0029] Based on the dual relationship between the Veronese diagram and the Delaunay triangulation, the first triangular mesh data is generated; wherein the circumscribed circle of each triangular mesh does not contain other points.

[0030] In some embodiments, the method further comprises:

[0031] Obtaining a water level difference value of each triangular mesh in the second triangular mesh data, wherein the water level difference is a difference between a water level height and a base elevation value;

[0032] The dynamic water surface data set to be rendered is generated based on the water level difference value, the second triangular mesh data and the index structure.

[0033] In some embodiments, the method further comprises:

[0034] Acquire the base elevation value of the target area, the water level value of each triangular mesh in the second triangular mesh data at the current moment, and the water level value of each second triangular mesh at the previous moment;

[0035] The water level difference value is generated based on the basic elevation value, the water level value at the current moment, the water level at the previous moment and a time interpolation coefficient.

[0036] In a second aspect, an embodiment of the present application provides a flood dynamic display device, the device comprising:

[0037] An acquisition module is used to acquire water surface temporal result data for a target area generated by a two-dimensional hydrodynamic model, wherein the water surface temporal result data includes irregular quadrilateral grid data at multiple time points;

[0038] A mesh reconstruction module, used for reconstructing the irregular quadrilateral mesh data at the plurality of moments based on an irregular triangulated network algorithm to generate first triangular mesh data at the plurality of moments, wherein the irregular triangulated network algorithm is used for reconstructing the vertices of the irregular quadrilateral mesh data into a shared vertex triangular mesh;

[0039] An extraction module is used to extract a target quadrilateral grid from the irregular quadrilateral grid data at the multiple moments, wherein the target quadrilateral grid is an irregular quadrilateral grid containing water depth data at each moment;

[0040] A determination module, determining second triangular mesh data at multiple moments corresponding to the target quadrilateral mesh among the first triangular mesh data at multiple moments;

[0041] A generation module, used for re-indexing the second triangular mesh data at the plurality of time instants to generate an index identifier of the second triangular mesh data; constructing an index structure of the second triangular mesh data based on the index identifier, the first mapping relationship and the second mapping relationship, wherein the index structure is used to associate the index identifiers of the vertices of the triangular meshes in the second triangular mesh data with the water surface temporal data; and generating a dynamic water surface data set to be rendered based on the second triangular mesh data and the index structure;

[0042] The first mapping relationship includes the correspondence between the irregular quadrilateral mesh at the multiple moments and the vertices of the second triangular mesh at the multiple moments, the second mapping relationship includes the correspondence between the irregular quadrilateral mesh at the multiple moments and the water surface temporal data, and the water surface temporal data includes the water depth data and water flow data of the target area;

[0043] The rendering module is used to render the dynamic water surface data set to be rendered based on time series and multiple normal overlay rendering technology based on a graphical interface, and generate visualization data representing the dynamic changes of the water surface.

[0044] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor and a memory for storing a computer program that can be run on the processor, wherein when the processor is used to run the computer program, it executes the steps of the method described in the first aspect of the embodiment of the present application.

[0045] In a fourth aspect, an embodiment of the present application provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0046] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0047] The technical solution provided by the embodiment of the present application is a method for dynamic display of floods, the method comprising: obtaining water surface temporal result data for a target area generated by a two-dimensional hydrodynamic model, the water surface temporal result data comprising irregular quadrilateral mesh data at multiple moments; reconstructing the irregular quadrilateral mesh data at multiple moments based on an irregular triangulated network algorithm to generate first triangular mesh data at multiple moments, the irregular triangulated network algorithm being used to reconstruct the vertices of the irregular quadrilateral mesh data into shared vertex triangular meshes; extracting a target quadrilateral mesh from the irregular quadrilateral mesh data at multiple moments, the target quadrilateral mesh being an irregular quadrilateral mesh containing water depth data at each moment; determining second triangular mesh data at multiple moments corresponding to the target quadrilateral mesh in the first triangular mesh data at multiple moments; reconstructing the second triangular mesh data at multiple moments Index, generate an index identifier of the second triangular mesh data; based on the index identifier, the first mapping relationship and the second mapping relationship, construct an index structure of the second triangular mesh data, the index structure is used to associate the index identifier of the vertices of the triangular mesh in the second triangular mesh data with the water surface temporal data; and based on the second triangular mesh data and the index structure, generate a dynamic water surface data set to be rendered; wherein the first mapping relationship includes a correspondence between an irregular quadrilateral mesh at multiple moments and the vertices of the second triangular mesh at multiple moments, the second mapping relationship includes a correspondence between the irregular quadrilateral mesh at multiple moments and the water surface temporal data, the water surface temporal data includes water depth data and water flow data of the target area; based on time series and multi-normal overlay rendering technology based on a graphical interface, render the dynamic water surface data set to be rendered, and generate visualization data representing the dynamic changes of the water surface.

[0048] In this way, the embodiment of the present application greatly reduces resource usage by optimizing data structure and algorithm, especially when processing massive watershed data, avoiding the problem of excessive memory and computing resource consumption common in traditional methods, and significantly improving performance and visualization effects. Specifically, (1) This solution converts the complex mesh structure in the water surface temporal result data into a triangular mesh that is more suitable for dynamic rendering through triangulation of irregular quadrilateral meshes. In particular, the triangulated mesh is reconstructed using an irregular triangulated network algorithm (TIN), which can reconstruct the vertices of the original data into a shared vertex triangular mesh, thereby effectively reducing the computational complexity and improving performance. (2) In the generated second triangular mesh data, the vertex index of the triangular mesh is associated with the water surface temporal data (such as water depth and water flow data) by establishing an efficient data structure based on index identifiers. This index structure not only improves the speed of data access and update, but also ensures the temporal consistency of the water surface data, further enhancing the real-time performance and accuracy in dynamic rendering. (3) In terms of data visualization, a rendering method based on time series and multiple normal overlay rendering technology is used to transform the processed triangulated data into accurate visualization graphics. This rendering method greatly improves the expressiveness of the dynamic changes of the water surface and can truly show the process of flood inundation. In particular, the dynamic changes of flood evolution and the expansion of the flooded area are extremely realistic, which can help users intuitively understand the changes in water flow and the impact of disasters. (4) It provides a very realistic flood control drill environment for flood control management agencies. In this virtual environment, managers can simulate various flood scenarios, formulate corresponding flood control strategies, and exercise and evaluate these strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic diagram of a flood dynamic display method provided in an embodiment of the present application;

[0050] Figure 2 A flow chart of a method for rendering temporal data of water surface in a large river basin provided for an application example of the present application;

[0051] Figure 3 A schematic diagram of the structure of a flood dynamic display device provided in an embodiment of the present application;

[0052] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0055] Before further describing the embodiments of the present application in detail, the nouns and terms involved in the embodiments of the present application are explained. The nouns and terms involved in the embodiments of the present application are subject to the following interpretations:

[0056] Two-dimensional hydrodynamic model: Unlike the one-dimensional hydrodynamic model, the two-dimensional hydrodynamic model not only considers the flow of water in a certain direction (such as the direction of the river), but also considers the movement of water in the horizontal plane (water surface). In other words, the two-dimensional model can simulate the wide distribution of water flow, including the speed and direction of the water flow.

[0057] The generation of temporal data of two-dimensional hydrodynamic models is a complex and rigorous process. It is calculated based on high-precision regional terrain data, detailed river section data and rich hydrological data. In this process, the two-dimensional hydrodynamic model plays a key role. When the two-dimensional model analyzes and calculates the data, the entire study area is usually finely divided into a large number of unit grids. Then, a specific elevation value is assigned to each unit grid. In the process of terrain characterization or elevation assignment, there are two different unit modes, namely the slope bottom mode and the flat bottom mode.

[0058] The oblique bottom mode has a unique feature, which is to define the elevation at the nodes that make up the grid unit. In this mode, the terrain generalization accuracy is high and can reach second-order accuracy. In practical applications, unstructured triangular meshes generally adopt this mode. Due to the flexibility and complexity of unstructured triangular meshes, the oblique bottom mode can better adapt to its needs and more accurately describe the changes in terrain.

[0059] The flat bottom mode defines the elevation at the center of the grid cell. In this mode, the grid cell is assumed to be flat. This method makes the terrain generalization only have first-order accuracy. Relatively speaking, its description of the terrain is not as detailed as the sloping bottom mode, but it is also applicable in some scenarios where the accuracy requirements are not extremely high.

[0060] Triangulated Irregular Network (TIN) algorithm: It is a form of vector-based digital geographic data, which is constructed by forming a series of vertex points into triangles. This construction method gives it a unique advantage in expressing geographic information. TIN has a wide range of applications in the two broad fields of Geographic Information Systems (GIS) and computer graphics. It only uses necessary sampling points to represent the terrain, just like using the least number of chess pieces to lay out the pattern that best reflects the situation on the chessboard. Moreover, its data structure can share vertices, which cleverly avoids data redundancy and greatly improves storage efficiency. When TIN data is combined with DirectX vertex rendering technology, it can create amazing realistic water effects.

[0061] DirectX technology: As a powerful graphics interface collection for drawing, it occupies an important position in the field of graphics processing. It mainly includes graphics libraries such as Direct3D and Direct2D, which can draw exquisite two-dimensional and three-dimensional graphics. DirectX has a series of significant advantages, such as high performance, hardware acceleration and real-time rendering capabilities. In the 3D rendering process, water surface graphics and material information are two crucial elements. The water surface graphics determine its placement and shape in the virtual space, just like the skeleton of a building, which determines the basic outline of the object; while the material gives the water surface graphics rich characteristics, such as brilliant colors, light and dark changes, and delicate ripple textures, making the water surface look more real and vivid.

[0062] WebRTC (Web Real-Time Communications) technology: is an innovative real-time communication technology that allows web applications or sites to easily establish peer-to-peer connections between browsers without the help of an intermediary. Through this connection, seamless transmission of video streams, audio streams or any other data can be achieved. With the help of WebRTC technology, the transmission of video streams, audio streams and data streams between the application and browser can be perfectly realized, thereby achieving the purpose of cloud rendering. This means that users can easily view and operate 3D scenes on the Web, as if a complex 3D world is installed in a small window of the browser. Through the cloud rendering architecture, the platform-independent characteristics of the engine can also be realized, and it can run smoothly regardless of the operating system or device; at the same time, the security of core data is guaranteed, so that users do not need to worry about the risk of data leakage; and the terminal hardware is lightweight, so that even low-configuration devices can enjoy a high-quality 3D experience.

[0063] The present application embodiment provides a flood dynamic display method, such as Figure 1 As shown, the method comprises the following steps:

[0064] Step 110: Acquire water surface temporal result data for the target area generated by the two-dimensional hydrodynamic model, where the water surface temporal result data includes irregular quadrilateral grid data at multiple time instants.

[0065] Here, the two-dimensional hydrodynamic model will generate water surface temporal result data for the target area. The water surface temporal result data presents a unique form, that is, it contains a large number of irregular quadrilateral grid data at multiple times. It can be understood that irregular quadrilateral grid data is equivalent to a piece of "puzzle" in the process of flood evolution, which together depicts the complex movement state and evolution trend of water bodies in the basin.

[0066] Step 120: Reconstruct the irregular quadrilateral mesh data at multiple times based on an irregular triangulated network algorithm to generate first triangular mesh data at multiple times. The irregular triangulated network algorithm is used to reconstruct the vertices of the irregular quadrilateral mesh data into a shared vertex triangular mesh.

[0067] Here, in the initial stage of data processing, this application focuses on irregular quadrilateral mesh data. These data are large in volume and complex in structure, and will face many problems if used directly for subsequent processing. Therefore, this application uses the advanced irregular triangulated network algorithm TIN to reconstruct and process irregular quadrilateral meshes at multiple times. The TIN algorithm has excellent performance in the field of geographic information and graphics processing. It can cleverly convert quadrilateral mesh data into shared vertex data, thereby generating the first triangular mesh data.

[0068] It should be noted that in this reconstruction process, the irregular quadrilateral mesh and the vertices of the triangulated mesh form a one-to-two correspondence. This correspondence is not accidental, but is carefully designed to optimize the data structure and reduce data redundancy while ensuring the integrity of data information, laying a solid data foundation for the subsequent rendering process, just like building a solid and reasonable structure for a building.

[0069] Furthermore, when the basic quadrilateral mesh is reconstructed into triangulated network data with shared vertices according to the TIN algorithm, this one-to-two correspondence between the quadrilateral mesh and the vertices of the triangulated network has profound significance. It is not just a simple change in data structure, but is to better adapt to the processing and calling of data in the subsequent rendering process. This correspondence can ensure that the information of the original data is retained to the maximum extent during the data conversion process, while making the newly generated first triangulated network data more compact and orderly in structure, providing a strong guarantee for the efficient operation of the entire rendering process.

[0070] Step 130: extracting a target quadrilateral mesh from the irregular quadrilateral mesh data at multiple moments, where the target quadrilateral mesh is an irregular quadrilateral mesh containing water depth data at each moment.

[0071] It is understandable that in this step, the present application needs to strictly screen the grid data based on the water depth data at all moments in the irregular quadrilateral grid data. That is, for those quadrilateral grid data that have never appeared in the entire temporal result data, they are removed to extract the target quadrilateral grid, which is the irregular quadrilateral grid containing water depth data at each moment.

[0072] It should be noted that this operation is crucial, because these grids without water depth information do not contribute substantially to the rendering of the flood evolution process, but will increase the amount of data and affect the rendering efficiency. By removing these unnecessary data, the amount of data required for rendering can be significantly reduced, just like removing useless debris from a pile of materials to make the useful parts more prominent, thereby improving the performance of the entire rendering process.

[0073] It is understandable that the operation of removing the quadrilateral mesh data that has never appeared in the water depth according to the temporal result data in step 130 is based on a comprehensive consideration of the amount of rendering data and the rendering effect. During the entire flood evolution simulation process, a large amount of data needs to be processed, but those quadrilateral mesh data that have never had water depth information are like "noise", which will interfere with the rendering process and occupy valuable system resources. By accurately removing this data, the rendering system can focus on truly valuable data and reduce unnecessary computing and storage overhead, thereby significantly improving rendering efficiency while ensuring rendering quality, making the entire flood evolution simulation smoother and more accurate.

[0074] For example, in this key step, the grids with water depth at all times involved can be numbered. This numbering process is like attaching a unique "identity tag" to each grid with water depth information. Subsequently, these numbers are deduplicated, and after this delicate operation, all grid numbers with water depth can be obtained.

[0075] This step is of vital importance, and its core purpose is to reduce the amount of mesh data. This application example can be understood in this way: if a mesh does not contain the key information of water depth at all times, then in the subsequent rendering process, rendering such a mesh will not only consume unnecessary computing resources and storage resources, but also have no substantial help for the entire rendering effect. Through this data elimination method, the data can be made more refined, preparing for more efficient subsequent processing and rendering.

[0076] Step 140: Determine second triangular mesh data at multiple times corresponding to the target quadrilateral mesh in the first triangular mesh data at multiple times.

[0077] It is understandable that, for the irregular quadrilateral mesh data with water depth remaining after screening, that is, the target quadrilateral mesh, the corresponding triangular mesh data, that is, the second triangular mesh data at multiple moments can be screened out according to the quadrilateral meshes with water depth at multiple moments. These second triangular mesh data are the key elements for subsequent rendering.

[0078] Step 150: Re-index the second triangular mesh data at multiple moments to generate an index identifier for the second triangular mesh data; construct an index structure for the second triangular mesh data based on the index identifier, the first mapping relationship, and the second mapping relationship, wherein the index structure is used to associate the index identifiers of the vertices of the triangular mesh in the second triangular mesh data with the water surface temporal data; and generate a dynamic water surface data set to be rendered based on the second triangular mesh data and the index structure; wherein the first mapping relationship includes a correspondence between an irregular quadrilateral mesh at multiple moments and the vertices of the second triangular mesh at multiple moments, and the second mapping relationship includes a correspondence between the irregular quadrilateral mesh at multiple moments and the water surface temporal data, and the water surface temporal data includes water depth data and water flow data of the target area.

[0079] In this step, the embodiment of the present application operates with the second triangulated mesh data at multiple times as the core. First, the second triangulated mesh data at each time is re-indexed, that is, a unique "index identifier" is re-assigned to each triangulated mesh vertex. This re-indexing method can make data management more efficient and facilitate the rapid location and reference of related data in subsequent processing.

[0080] Next, an index structure is constructed based on the first mapping relationship and the second mapping relationship. The first mapping relationship refers to the vertex correspondence between the irregular quadrilateral mesh and the second triangular mesh, while the second mapping relationship associates the irregular quadrilateral mesh with the temporal data of the water surface (including water depth, flow velocity, flow direction, etc.). Through these mapping relationships, each vertex of the triangular mesh can be bound to the corresponding hydrodynamic data (such as water depth and water flow data), making each vertex an "information node" containing rich hydrodynamic information.

[0081] Specifically, the first step is to re-index each data point and generate a unique index identifier for each vertex, which makes subsequent data management and calling more efficient. The second step is to clarify the correspondence between the irregular quadrilateral mesh and the triangular mesh vertices through the first mapping relationship to ensure the correct matching of data. The third step is to use the second mapping relationship to correspond the irregular quadrilateral mesh to the temporal data of the water surface (such as water depth, flow velocity, etc.), so that each triangular mesh vertex carries rich hydrodynamic information.

[0082] Finally, based on the constructed index structure and the second triangular mesh data, a dynamic water surface dataset to be rendered is generated. This dataset provides comprehensive and accurate data support for water surface rendering, so that the generated dynamic water surface can truly reflect the hydrodynamic evolution of the target area, ensuring that the final rendering effect is realistic and fits the actual hydrodynamic scene, especially in application scenarios such as simulating flood evolution.

[0083] Step 160: Based on the time series and the multiple normal overlay rendering technology based on the graphic interface, the dynamic water surface data set to be rendered is rendered to generate visualization data representing the dynamic changes of the water surface.

[0084] Here, the multiple normal overlay rendering technology based on the graphics interface may be the multiple normal overlay rendering technology of DirectX.

[0085] This rendering technology can achieve a smooth transition of the height of the water surface vertices, which is a very critical feature. In real flood scenes, the height of the water surface changes continuously and naturally. Through this smooth transition effect, the simulated flood evolution picture is more realistic. Whether the water level rises slowly or overflows quickly, it can be presented with an extremely realistic visual effect, as if letting users feel the dynamic change process of the flood as if they were there.

[0086] In this step, the data optimized in the previous step, i.e., the dynamic water surface dataset with rendering, is subjected to flood evolution simulation in a time series to generate visualization data representing the dynamic changes of the water surface.

[0087] In this way, the embodiment of the present application greatly reduces resource usage by optimizing data structure and algorithm, especially when processing massive watershed data, avoiding the problem of excessive memory and computing resource consumption common in traditional methods, and significantly improving performance and visualization effects. Specifically, (1) This solution converts the complex mesh structure in the water surface temporal result data into a triangular mesh that is more suitable for dynamic rendering through triangulation of irregular quadrilateral meshes. In particular, the triangulated mesh is reconstructed using an irregular triangulated network algorithm (TIN), which can reconstruct the vertices of the original data into a shared vertex triangular mesh, thereby effectively reducing the computational complexity and improving performance. (2) In the generated second triangular mesh data, the vertex index of the triangular mesh is associated with the water surface temporal data (such as water depth and water flow data) by establishing an efficient data structure based on index identifiers. This index structure not only improves the speed of data access and update, but also ensures the temporal consistency of the water surface data, further enhancing the real-time performance and accuracy in dynamic rendering. (3) In terms of data visualization, a rendering method based on time series and multiple normal overlay rendering technology is used to transform the processed triangulated data into accurate visualization graphics. This rendering method greatly improves the expressiveness of the dynamic changes of the water surface and can truly show the process of flood inundation. In particular, the dynamic changes of flood evolution and the expansion of the flooded area are extremely realistic, which can help users intuitively understand the changes in water flow and the impact of disasters. (4) It provides a very realistic flood control drill environment for flood control management agencies. In this virtual environment, managers can simulate various flood scenarios, formulate corresponding flood control strategies, and exercise and evaluate these strategies.

[0088] In some embodiments, the method further comprises:

[0089] Send visualization data to browser devices based on real-time communication on web pages.

[0090] Here, the embodiment of the present application uses WebRTC (Web Real-Time Communication) technology to send the visualization data to the browser device.

[0091] It is understandable that the embodiment of the present application utilizes WebRTC (Web Real-Time Communications) to push the carefully rendered flood evolution effect to a web page. WebRTC technology can establish a stable and efficient point-to-point connection between browsers without the aid of an intermediary. Through this connection, high-quality flood evolution video streams and related data can be accurately transmitted to the web page. In this way, users do not need to install complex professional software, but can easily watch the simulation effect of flood evolution in a common browser, which greatly improves the accessibility and ease of use of the simulation results.

[0092] In some embodiments, the method further comprises:

[0093] storing the second triangular mesh data at multiple times based on a set storage format, wherein the set storage format includes a binary format;

[0094] The second triangular mesh data at multiple time points is compressed based on a lossless data compression algorithm.

[0095] Here, after obtaining the second triangular mesh data at multiple time points corresponding to the target quadrilateral mesh in the first triangular mesh data at multiple time points, the data may be compressed and stored in a specific data format.

[0096] When storing these data, they can be stored as binary data (latitude and longitude Double, height Float, triangulation relationship Int). This storage method is carefully designed, and it can effectively save storage space while ensuring data accuracy.

[0097] In addition, considering the diversity of flood storage and detention areas, data of corresponding ranges are stored separately according to the range of the flood storage and detention areas. This is like classifying and storing items in different areas to facilitate subsequent management and use.

[0098] Here, in order to further optimize storage efficiency, the lossless data compression algorithm needs to use Gzip compression technology. Gzip compression is like putting a compact "coat" on the data. It can significantly reduce the data volume without losing important information, thereby reducing the burden of data storage and transmission, and ensuring the efficiency and smoothness of the entire data processing process.

[0099] This compressed storage method has been carefully optimized. It can not only effectively save storage space, but also greatly improve the speed of data request. When the rendering process needs to call data, it can be obtained quickly and accurately, just like being able to quickly find the required books in an organized library, ensuring the efficiency of rendering work.

[0100] In some embodiments, the method further comprises:

[0101] Obtaining topographic information of the target area, river section data of the target area, hydrological data of the target area, and elevation information of the target area;

[0102] The target area is meshed based on the two-dimensional hydrodynamic model to generate multiple irregular quadrilateral meshes;

[0103] Based on multiple irregular quadrilateral grids, terrain information, river section data, hydrological data, elevation information and a two-dimensional hydrodynamic model, water surface temporal result data is generated, and the water surface temporal result data includes irregular quadrilateral grid data.

[0104] In some embodiments, the irregular triangulated network algorithm is a Delaunay triangulation algorithm, and the irregular quadrilateral mesh data at multiple times are reconstructed based on the irregular triangulated network algorithm to generate first triangular mesh data at multiple times, including:

[0105] The irregular quadrilateral mesh data at multiple time points are reconstructed based on the Delaunay triangulation algorithm to generate the first triangular mesh data.

[0106] Here, the mesh reconstruction in the embodiment of the present application uses the Delaunay triangulation algorithm, which has unique principles and advantages. When a set of points on a plane is given, Delaunay triangulation will carefully construct a set of triangles.

[0107] In this construction process, there is a key rule, that is, the circumcircle of any triangle does not contain any other points. This feature makes the generated triangulated network have good geometric properties, such as more uniform distribution of angles between triangles, and can avoid the appearance of overly narrow and long triangles. The first triangulated mesh data generated by this uniform triangulated network structure is of great significance for subsequent calculations and rendering processes. It can more accurately describe the geometric shapes of objects such as terrain or water surfaces, reduce errors caused by unreasonable data structures, and lay a solid data foundation for the entire 3D rendering process.

[0108] In some embodiments, reconstructing the irregular quadrilateral mesh data at multiple times based on the Delaunay triangulation algorithm to generate first triangular mesh data includes:

[0109] Construct the Veronese diagram corresponding to the Delaunay triangulation;

[0110] Based on the dual relationship between the Veronese diagram and the Delaunay triangulation, the first triangular mesh data is generated; wherein the circumscribed circle of each triangular mesh does not contain other points.

[0111] Here, a scheme of how to reconstruct the irregular quadrilateral mesh data at multiple time points based on the Delaunay triangulation algorithm to generate the first triangular mesh data is described.

[0112] First, construct the Veronese diagram corresponding to the Delaunay triangulation:

[0113] It can be understood that the Voronoi diagram is the dual diagram of the Delaunay triangulation. Each Voronoi region represents the "influence range" of a point, that is, the distance from any point in the region to the center point is less than the distance to other points. Each region in the Voronoi diagram Corresponding to one , any point in the region satisfies The distance to is smaller than the distance to other points.

[0114] Based on the input irregular quadrilateral grid data points, the corresponding Voronoi diagram is constructed. Each Voronoi region represents the "influence range" of a point, that is, the distance from any point in the region to the center point is smaller than the distance to other points. It is defined as:

[0115]

[0116] in, Indicates q to The Euclidean distance of represents the i-th data point, q represents an arbitrary point on the two-dimensional plane, which belongs to a Veronix region , Refers to the two-dimensional Euclidean space. N represents the total number of input points, that is, the number of data points used to construct the Veronese diagram, which means that when comparing the distance between point q and all input points, the points itself.

[0117] Secondly, based on the dual relationship between the Veronese diagram and the Delaunay triangulation, generate the first triangulation data: using the dual relationship between the Veronese diagram and the Delaunay triangulation, generate the Delaunay triangulation. The specific steps are as follows:

[0118] (1) Initialize the baseline: randomly select a point from all the data points, find the point closest to it, and connect them to form a baseline.

[0119] (2) Construct the initial triangle: Find the third point on the right side of the baseline according to the Delaunay rule so that the resulting triangle satisfies the Delaunay condition, that is, the circumcircle of the triangle does not contain any other points.

[0120] (3) Iteratively construct a new triangle: Use each side of the newly formed triangle as a new baseline and continue to search for the third point that meets the Delaunay condition to form a new triangle.

[0121] (4) Repeat the above steps until all data points are contained in one or more triangles and the reconstruction of the entire mesh is completed.

[0122] Through the above process, the first triangular mesh data finally generated ensures that the circumscribed circle of each triangle does not contain other points, thereby achieving high-quality mesh reconstruction.

[0123] In some embodiments, the method further comprises:

[0124] Obtain the water level difference of each triangular mesh in the second triangular mesh data, where the water level difference is the difference between the water level height and the base elevation value;

[0125] Based on the water level difference, the second triangular mesh data and the index structure, a dynamic water surface data set to be rendered is generated.

[0126] It is understandable that in order to ensure that the dynamic water surface data set can achieve smooth transition, it is necessary to first obtain the water level difference of each triangular mesh in the second triangular mesh data. The water level difference refers to the difference between the water level height and the base elevation value, which is used to represent the height change of the water surface at different time points.

[0127] On this basis, it is also necessary to generate a dynamic water surface dataset to be rendered based on the third triangle mesh data and index structure, combined with the water level difference. This dataset provides accurate water surface height information for the rendering process, ensuring that the height change of the water surface when switching between moments has a smooth transition effect.

[0128] For example, since the grid numbers without water depth are removed, the index relationship needs to be re-established. At the same time, the water level difference value of each triangular grid is calculated to ensure a smooth transition of the water surface height during rendering. This process can effectively avoid sudden changes in the water surface at different time points, thereby generating a smoother and more realistic dynamic water surface effect.

[0129] In some embodiments, the method further comprises:

[0130] Obtaining the base elevation value of the target area, the water level value of each triangular mesh in the second triangular mesh data at the current moment, and the water level value of each second triangular mesh at the previous moment;

[0131] The water level difference is generated based on the base elevation value, the water level value at the current moment, the water level at the previous moment and the time interpolation coefficient.

[0132] Exemplarily, the water level difference value may be generated based on the following formula:

[0133]

[0134] Among them, h is the basic elevation value, h1 is the water level difference at the current moment, and h2 is the water level difference at the previous moment. The range is [0, ].

[0135] Below, this application is described in detail with reference to an application example.

[0136] This application example proposes an innovative process and method for rendering temporal data of water surface in a large river basin. In this process, the temporal data of water surface generated by the two-dimensional hydrodynamic algorithm is first constructed. This data carries rich information, including key elements such as water depth, flow direction, and flow velocity. In order to present this data in a vivid and intuitive way, this application example uses advanced DirectX and WebRTC technologies for rendering. By creating a dynamic water surface, the content contained in the hydrodynamic result data is fully simulated and presented, thereby accurately expressing the entire flooding process of the Haihe River Basin.

[0137] Specifically, the flood inundation simulation method involved in this application example has a unique processing method. It mainly triangulates a large amount of irregular quadrilateral mesh data in the hydrodynamic results. On the basis of triangulation, the triangulated network is reconstructed using the TIN algorithm, and the triangulated network data is processed through a series of carefully designed data optimization methods. For example, the precision of the data is adjusted, redundant information is removed, etc., to ensure the efficiency and accuracy of the data in the subsequent processing process.

[0138] In terms of data visualization, DirectX vertex rendering technology is used. This technology can accurately convert processed triangulated data into visual graphics, vividly showing the flooding scene. At the same time, WebRTC technology is used to realize the function of viewing visualization effects on Web pages, so that users can easily view the results of flood simulation through common web browsers without installing additional software.

[0139] This application example has significant advantages and can successfully solve the problem of large resource usage that was previously faced when processing massive amounts of watershed data. Traditional methods often consume a lot of memory and computing resources when processing large amounts of data, causing the system to run slowly or even crash. This application example greatly reduces resource usage by optimizing data structures and algorithms. In addition, previous flooding evolution effects were often not realistic enough and could not truly reflect the actual situation of flood disasters. The flooding evolution effect presented by the present invention is extremely realistic, and both the dynamic changes in the water flow and the expansion process of the flooded area are highly consistent with the actual situation.

[0140] This application example provides a very realistic flood control drill environment for flood control management agencies. In this virtual environment, managers can simulate various flood scenarios, develop corresponding flood control strategies, and exercise and evaluate these strategies. For researchers and emergency management departments, it helps them better understand the dynamic process and potential impact of flood disasters. Researchers can analyze the simulation results to conduct in-depth research on the formation mechanism and propagation law of floods; emergency management departments can formulate more scientific and reasonable emergency response plans based on the simulation results. This will effectively improve the efficiency and response capabilities of flood control and disaster relief, and provide a solid scientific basis and reliable technical support for future flood control and disaster reduction strategies.

[0141] As shown in Figure 2, this application example proposes a flow chart of a method based on three-dimensional rendering of temporal data of water surface in a large watershed. This innovative method mainly includes the following steps:

[0142] Step 210: Start.

[0143] Step 220: Calling the hydrodynamic model algorithm to generate temporal data.

[0144] Step 230: Processing of hydrodynamic model result data.

[0145] The data processing of the hydrodynamic model results includes five steps, as follows:

[0146] (1) Data TIN (triangulated irregular network) triangulation.

[0147] In this step, the focus is on processing the two-dimensional hydrodynamic foundation irregular quadrilateral mesh. That is, the irregular quadrilateral mesh output by the two-dimensional hydrodynamic model at multiple times is processed and reconstructed and processed using TIN (irregular triangulated network). The irregular quadrilateral mesh data at the multiple times is reconstructed based on the Delaunay triangulation algorithm to generate the first triangular mesh data at multiple times.

[0148] This application example uses TIN (irregular triangulated network) to reconstruct and process it, and the Delaunay triangulation algorithm is used for mesh reconstruction. This algorithm has unique principles and advantages. When a set of points on a plane is given, Delaunay triangulation will carefully construct a set of triangles. In this construction process, there is a key rule, that is, the circumcircle of any triangle does not contain any other points. This feature makes the generated triangulated network have good geometric properties, such as a more uniform distribution of angles between triangles, which can avoid the appearance of overly narrow and long triangles. This uniform triangulated network structure is of great significance for subsequent calculations and rendering processes. It can more accurately describe the geometric shapes of objects such as terrain or water surfaces, reduce errors caused by unreasonable data structures, and lay a solid data foundation for the entire 3D rendering process, just like when building a high-rise building, you must first ensure that the foundation is stable and flat.

[0149] The Voronoi diagram is the dual diagram of the Delaunay triangulation. Each Voronoi region represents the "influence range" of a point, that is, the distance from any point in the region to the center point is less than the distance to other points. It is defined as: each region in the Voronoi diagram corresponds to one, and any point in the region satisfies that the distance to the center point is less than the distance to other points, that is:

[0150]

[0151] where q represents the Euclidean distance to .

[0152] (1) Pick any point 1 from all the data, find the point 2 closest to this point, and connect the baseline;

[0153] (2) Find the third point on the right side of the baseline according to the Delaunay law to form a triangle;

[0154] (3) Use the new edge as the new baseline to find a new triangle;

[0155] (4) Repeat the above steps until all data processing is completed.

[0156] (2) Eliminate redundant data.

[0157] In this key step, the grids with water depth at all times involved in the algorithm results are numbered. This numbering process is like attaching a unique "identity tag" to each grid with water depth information. Subsequently, these numbers are deduplicated, and after this delicate operation, all grid numbers with water depth can be obtained. This is the aforementioned extraction of the target quadrilateral grid from the irregular quadrilateral grid data at the multiple times.

[0158] This step is of vital importance, and its core purpose is to reduce the amount of mesh data. If a mesh does not contain the key information of water depth at all times, then in the subsequent rendering process, rendering such a mesh will not only consume unnecessary computing resources and storage resources, but also have no substantial help for the entire rendering effect, just like when building a beautiful puzzle, those pieces that are not related to the target pattern are not needed, so there is no need to render them. By eliminating data in this way, the data can be refined and prepared for more efficient processing and rendering in the future.

[0159] (3) Data re-indexing (data construction).

[0160] There is a close one-to-one correspondence between the grid numbers obtained above and the basic grid data. Based on this correspondence, the embodiment of the present application needs to accurately extract the corresponding grid coordinate data in the basic data grid. This process requires a high degree of accuracy, just like accurately finding specific information in a complex database. That is, the second triangular mesh data at multiple moments corresponding to the target quadrilateral mesh in the first triangular mesh data at the aforementioned multiple moments is determined.

[0161] (4) Data sharding.

[0162] Since the grid numbers without water depth are eliminated, the grid data at the moment needs to be re-indexed according to the data in step (3) and the water level difference of the triangulated network is calculated. The water level difference is the difference between the water level and the base elevation value, which is used to smoothly transition the water surface height when switching at the moment. The water level difference formula is as follows:

[0163]

[0164] h is the base elevation value, h1 is the water level difference at the current moment, and h2 is the water level difference at the previous moment. The range is [0, ].

[0165] (5) Data compression

[0166] Next, based on the reconstructed triangulated network generated by (1) (i.e., the aforementioned first triangulated mesh data), all triangulated network data corresponding to the algorithm result are extracted from it. When storing these data, a specific method is adopted, that is, storing them in binary data (latitude and longitude Double, height Float, triangulated network relationship Int). This storage method is carefully designed, and it can effectively save storage space while ensuring data accuracy. Moreover, considering the diversity of the scope of the flood storage area, the data of the corresponding range will be stored separately according to the scope of the flood storage area, which is like classifying and storing items in different areas to facilitate subsequent management and use. In order to further optimize storage efficiency, Gzip compression technology is also used. Gzip compression is like putting a compact "coat" on the data. It can greatly reduce the data volume without losing important information of the data, thereby reducing the burden of data storage and transmission, and ensuring the efficiency and smoothness of the entire data processing process.

[0167] Step 240: Rendering water surface data (time, coordinates, flow rate, direction, water depth)

[0168] In the key step of rendering, this application example combines a variety of geographic data with advanced rendering technology to present a realistic water surface effect. First of all, this application example will integrate rich geographic data such as oblique photography data and terrain data. These data are like the cornerstones of building a virtual world, providing a solid geographical environment foundation for the entire rendering scene. The data obtained by oblique photography technology can accurately reflect the three-dimensional information of surface objects, and the terrain data describes the ups and downs of the earth in detail. The combination of the two makes the virtual scene closer to the real world.

[0169] Next, the reconstructed water surface is processed using the powerful DirectX rendering technology. This process is carefully executed in a time sequence, just like a skilled director who presents each frame in an orderly manner according to a pre-set time rhythm. This application example builds a delicate water surface model and uses DirectX rendering technology to give it a vivid water flow effect, making the water flow look lifelike, as if it has real vitality.

[0170] On this basis, the water flow model is rendered based on the multi-normal map hybrid mapping technology. Normal map plays a vital role in this process. It is mainly used to simulate small ripples and water surface details. Prepare a normal map that specifically depicts the details of the water surface. This map is like a magical brush that adds delicate texture to the water surface. At the same time, combined with the flow direction and flow rate information contained in the data, the water flow can achieve a natural flow effect. In addition, through the normal vector superposition algorithm, this information is integrated to form a realistic water surface ripple movement effect. This movement effect is not a simple mechanical movement, but a comprehensive consideration of the physical characteristics of the water flow and environmental factors, so that the propagation and change of the ripples are more in line with the real situation, just like the water surface fluctuations observed in a real river.

[0171] Step 250: Build WebRTC (Web Real-time Communication) to connect and push images (image streaming)

[0172] The streaming process involves a complex and orderly interaction between the client and the rendering server. First, the client and the rendering server need to establish a WebRTC connection. The process of establishing this connection is like building an invisible bridge that allows both parties to communicate smoothly. Specifically, the signaling service is used to exchange their respective SessionDescription data. This data is like the "language rules" for communication between the two parties, which specifies the format and parameters of communication.

[0173] At the same time, both parties need to obtain their own ICE Candidates (Interactive Connection Establishment Candidates) from the STUN server. These candidate information contains possible network connection paths. After obtaining, they are exchanged through signaling services. This series of operations is like finding the most suitable communication path for both parties. When these preparations are completed, the call link is successfully established.

[0174] After the connection is successfully established, the next step is data transmission and processing. The two connected parties send data directly to the target IP port according to the content agreed in SessionDescription. For the rendered screen, each frame of the rendered screen will generate an image frame. This process is like breaking down a continuous animation into separate pictures. Then, these image frames are compressed by an efficient video encoder and transcoded into a video stream. This process is like carefully organizing and packaging a series of beautiful paintings for easy transmission. After that, the video stream is transmitted to the client using the WebRTC protocol.

[0175] After receiving the video stream, the client will perform a decoding operation. This process is like opening a package and re-displaying the scroll inside. Finally, the image is rendered on the screen so that the user can see the wonderful picture. In addition, the client's interactive input (such as mouse, keyboard, touch, etc.) can be transmitted back to the server through WebRTC. The server updates the scene based on these interactive contents, forming a closed loop of real-time interaction. This closed loop is like a complete ecosystem. The user's operation can be fed back to the server in a timely manner. The server adjusts the scene based on the feedback, bringing a more immersive experience to the user, making the user feel as if they are in a virtual scene and interacting with the elements in the scene in real time.

[0176] Step 260: End

[0177] Thus, the embodiment of the present application can significantly improve the performance and visualization effect through the above data processing flow and in combination with the powerful DirectX vertex rendering technology.

[0178] In order to implement the method of the embodiment of the present application, the embodiment of the present application also provides a flood dynamic display device, which corresponds to the above-mentioned flood dynamic display method, and each step in the above-mentioned flood dynamic display method embodiment is also fully applicable to the present flood dynamic display device embodiment.

[0179] like Figure 3As shown, the flood dynamic display device 300 includes: an acquisition module 301, a mesh reconstruction module 302, an extraction module 303, a determination module 304, a generation module 305 and a rendering module 306. The acquisition module 301 is used to obtain the water surface temporal result data for the target area generated by the two-dimensional hydrodynamic model, and the water surface temporal result data includes irregular quadrilateral mesh data at multiple moments; the mesh reconstruction module 302 is used to reconstruct the irregular quadrilateral mesh data at multiple moments based on the irregular triangulated network algorithm to generate the first triangular mesh data at multiple moments, and the irregular triangulated network algorithm is used to reconstruct the vertices of the irregular quadrilateral mesh data into a shared vertex triangular mesh; the extraction module 303 is used to extract the target quadrilateral mesh from the irregular quadrilateral mesh data at multiple moments, and the target quadrilateral mesh contains the water depth at each moment. The irregular quadrilateral mesh of the data; the determination module 304 is used to determine the second triangular mesh data at multiple moments corresponding to the target quadrilateral mesh in the first triangular mesh data at multiple moments; the generation module 305 is used to re-index the second triangular mesh data at multiple moments to generate an index identifier of the second triangular mesh data; based on the index identifier, the first mapping relationship and the second mapping relationship, an index structure of the second triangular mesh data is constructed, and the index structure is used to associate the index identifier of the vertex of the triangular mesh in the second triangular mesh data with the water surface temporal data; and based on the second triangular mesh data and the index structure, a dynamic water surface data set to be rendered is generated;

[0180] Among them, the first mapping relationship includes the correspondence between the irregular quadrilateral mesh at multiple moments and the vertices of the second triangular mesh at multiple moments, and the second mapping relationship includes the correspondence between the irregular quadrilateral mesh at multiple moments and the temporal data of the water surface, and the temporal data of the water surface includes the water depth data and water flow data of the target area; the rendering module 306 is used to render the dynamic water surface data set to be rendered based on time series and multiple normal overlay rendering technology based on a graphical interface, and generate visualization data representing the dynamic changes of the water surface.

[0181] In some embodiments, the flood dynamic display device further includes a sending module 307 for sending visualization data to a browser device based on real-time communication of a web page.

[0182] In some embodiments, the flood dynamic display device also includes a storage compression module 308, which is used to store the second triangular mesh data at multiple times based on a set storage format, and the set storage format includes a binary format; and compress the second triangular mesh data at multiple times based on a lossless data compression algorithm.

[0183] In some embodiments, the acquisition module 301 is also used to acquire terrain information of the target area, river section data of the target area, hydrological data of the target area and elevation information of the target area; the generation module 305 is also used to grid the target area based on the two-dimensional hydrodynamic model to generate multiple irregular quadrilateral grids; based on multiple irregular quadrilateral grids, terrain information, river section data, hydrological data, elevation information and a two-dimensional hydrodynamic model, water surface temporal result data is generated, and the water surface temporal result data includes irregular quadrilateral grid data at multiple time moments.

[0184] In some embodiments, the irregular triangulated network algorithm is a Delaunay triangulation algorithm, and the mesh reconstruction 302 is used to reconstruct the irregular quadrilateral mesh data at multiple time points based on the Delaunay triangulation algorithm to generate first triangular mesh data.

[0185] In some embodiments, the mesh reconstruction module 302 is also used to construct a Veronese diagram corresponding to the Delaunay triangulation network; based on the dual relationship between the Veronese diagram and the Delaunay triangulation network, generate first triangular mesh data; wherein the circumscribed circle of each triangular mesh does not contain other points.

[0186] In some embodiments, the acquisition module 301 is also used to obtain the water level difference of each triangular mesh in the second triangular mesh data, where the water level difference is the difference between the water level height and the base elevation value; the generation module 305 is also used to generate a dynamic water surface data set to be rendered based on the water level difference, the second triangular mesh data and the index structure.

[0187] In some embodiments, the acquisition module 301 is also used to obtain the basic elevation value of the target area, the water level value of each triangular mesh in the second triangular mesh data at the current moment, and the water level value of each second triangular mesh at the previous moment; the generation module 305 is also used to generate a water level difference value based on the basic elevation value, the water level value at the current moment, the water level at the previous moment, and the time interpolation coefficient.

[0188] In practical applications, the acquisition module 301, the grid reconstruction module 302, the extraction module 303, the determination module 304, the generation module 305, the rendering module 306, the sending module 307 and the storage compression module 308 can be implemented by a processor in the flood dynamic display device. Of course, the processor needs to run the computer program in the memory to realize its function.

[0189] It should be noted that: the flood dynamic display device provided in the above embodiment only uses the division of the above program modules as an example when performing flood dynamic display. In actual applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device is divided into different program modules to complete all or part of the processing described above. In addition, the flood dynamic display device and the flood dynamic display method embodiment provided in the above embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0190] Based on the hardware implementation of the above program modules and in order to implement the method of the embodiment of the present application, the embodiment of the present application also provides an electronic device. Figure 4 Only an exemplary structure of the electronic device is shown, not the entire structure. Part or all of the structures shown in FIG. 4 may be implemented as needed. As shown in FIG. 4 , the electronic device 400 provided in the embodiment of the present application includes: at least one processor 401, a memory 402, a user interface 403, and at least one network interface 404. The various components in the electronic device 400 are coupled together via a bus system 405. It can be understood that the bus system 405 is used to achieve connection and communication between these components. In addition to the data bus, the bus system 405 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, various buses are labeled as bus systems 405 in FIG. 4 .

[0191] The user interface 403 may include a display, a keyboard, a mouse, a trackball, a click wheel, keys, buttons, a touch pad or a touch screen.

[0192] The memory 402 in the embodiment of the present application is used to store various types of data to support the operation of the electronic device. Examples of such data include: any computer program used to operate on the electronic device.

[0193] The method for dynamic display of flood in electronic device disclosed in the embodiment of the present application can be applied to processor 401, or implemented by processor 401. Processor 401 may be an integrated circuit chip with signal processing capability. In the implementation process, each step of the method for dynamic display of flood in electronic device can be completed by hardware integrated logic circuit or software instruction in processor 401. The above-mentioned processor 401 can be a general processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 401 can implement or execute the methods, steps and logic block diagrams disclosed in the embodiment of the present application. The general processor can be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present application, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in memory 402. The processor 401 reads the information in memory 402 and completes the steps of the method for dynamic display of flood in electronic device provided in the embodiment of the present application in combination with its hardware.

[0194] In an exemplary embodiment, the electronic device may be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD), field programmable gate array (FPGA), general processor, controller, microcontroller (MCU), microprocessor, or other electronic components to execute the aforementioned method.

[0195] It can be understood that the memory 402 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), and direct RAM bus random access memory (DRRAM, Direct Rambus Random Access Memory).The memories described in the embodiments of the present application are intended to include, but are not limited to, these and any other suitable types of memories.

[0196] In an exemplary embodiment, the present application also provides a computer storage medium, which can be a computer-readable storage medium, on which a computer program is stored, and the computer program can be executed by a processor to complete the steps of the method of the present application. The computer-readable storage medium can be a memory such as ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface storage, optical disk, or CD-ROM.

[0197] In an exemplary embodiment, the embodiment of the present application further provides a computer program product, including a computer program, and the above-mentioned computer program can be executed by the processor 401 of the electronic device to complete the steps of the method of the embodiment of the present application.

[0198] It should be noted that: "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0199] In addition, the technical solutions described in the embodiments of the present application can be combined arbitrarily without conflict.

[0200] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A flood dynamic display method, characterized in that: include: Acquire water surface temporal result data for a target area generated by a two-dimensional hydrodynamic model, wherein the water surface temporal result data includes irregular quadrilateral grid data at multiple time points; Reconstructing the irregular quadrilateral mesh data at the multiple moments based on an irregular triangulated network algorithm to generate first triangular mesh data at the multiple moments, wherein the irregular triangulated network algorithm is used to reconstruct the vertices of the irregular quadrilateral mesh data into a shared vertex triangular mesh; Extracting a target quadrilateral grid from the irregular quadrilateral grid data at the plurality of moments, wherein the target quadrilateral grid is an irregular quadrilateral grid containing water depth data at each moment; Determine second triangular mesh data at multiple moments corresponding to the target quadrilateral mesh among the first triangular mesh data at the multiple moments; Re-indexing the second triangular mesh data at the multiple moments to generate index identifiers of the second triangular mesh data; Based on the index identifier, the first mapping relationship and the second mapping relationship, an index structure of the second triangular mesh data is constructed, wherein the index structure is used to associate the index identifiers of the vertices of the triangular mesh in the second triangular mesh data with the water surface temporal data; and based on the second triangular mesh data and the index structure, a dynamic water surface data set to be rendered is generated; The first mapping relationship includes the correspondence between the irregular quadrilateral mesh at the multiple moments and the vertices of the second triangular mesh at the multiple moments, the second mapping relationship includes the correspondence between the irregular quadrilateral mesh at the multiple moments and the water surface temporal data, and the water surface temporal data includes the water depth data and water flow data of the target area; Based on the time series and the multiple normal overlay rendering technology based on the graphic interface, the dynamic water surface data set to be rendered is rendered to generate visualization data representing the dynamic changes of the water surface.

2. The method according to claim 1, characterized in that The method further comprises: The visualization data is sent to the browser device based on real-time communication of the web page.

3. The method according to claim 1, characterized in that The method further comprises: storing the second triangular mesh data at the plurality of time instants based on a set storage format, wherein the set storage format includes a binary format; The second triangular mesh data at the multiple time instants are compressed based on a lossless data compression algorithm.

4. The method according to claim 1, characterized in that: The method further comprises: Acquire terrain information of the target area, river section data of the target area, hydrological data of the target area, and elevation information of the target area; Meshing the target area based on the two-dimensional hydrodynamic model to generate a plurality of irregular quadrilateral meshes; Based on the multiple irregular quadrilateral grids, the terrain information, the river section data, the hydrological data, the elevation information and the two-dimensional hydrodynamic model, the water surface temporal result data is generated, and the water surface temporal result data includes the irregular quadrilateral grid data at the multiple time moments.

5. The method according to claim 1, characterized in that The irregular triangulated network algorithm is a Delaunay triangulation algorithm, and the irregular quadrilateral mesh data at the plurality of moments are reconstructed based on the irregular triangulated network algorithm to generate first triangular mesh data at the plurality of moments, including: The irregular quadrilateral mesh data at the multiple moments are reconstructed based on the Delaunay triangulation algorithm to generate the first triangular mesh data.

6. The method according to claim 5, characterized in that The step of reconstructing the irregular quadrilateral mesh data at the plurality of time instants based on the Delaunay triangulation algorithm to generate the first triangular mesh data includes: Construct the Veronese diagram corresponding to the Delaunay triangulation; Based on the dual relationship between the Veronese diagram and the Delaunay triangulation, the first triangular mesh data is generated; wherein the circumscribed circle of each triangular mesh does not contain other points.

7. The method according to claim 1, characterized in that The method further comprises: Obtaining a water level difference value of each triangular mesh in the second triangular mesh data, wherein the water level difference is a difference between a water level height and a base elevation value; The dynamic water surface data set to be rendered is generated based on the water level difference value, the second triangular mesh data and the index structure.

8. The method according to claim 7, characterized in that The method further comprises: Acquire the base elevation value of the target area, the water level value of each triangular mesh in the second triangular mesh data at the current moment, and the water level value of each second triangular mesh at the previous moment; The water level difference value is generated based on the basic elevation value, the water level value at the current moment, the water level at the previous moment and a time interpolation coefficient.

9. A flood dynamic display device, characterized in that: The device comprises: An acquisition module is used to acquire water surface temporal result data for a target area generated by a two-dimensional hydrodynamic model, wherein the water surface temporal result data includes irregular quadrilateral grid data at multiple time points; A mesh reconstruction module, used for reconstructing the irregular quadrilateral mesh data at the plurality of moments based on an irregular triangulated network algorithm to generate first triangular mesh data at the plurality of moments, wherein the irregular triangulated network algorithm is used for reconstructing the vertices of the irregular quadrilateral mesh data into a shared vertex triangular mesh; An extraction module is used to extract a target quadrilateral grid from the irregular quadrilateral grid data at the multiple moments, wherein the target quadrilateral grid is an irregular quadrilateral grid containing water depth data at each moment; A determination module, configured to determine second triangular mesh data at multiple moments corresponding to the target quadrilateral mesh among the first triangular mesh data at multiple moments; A generation module, used for re-indexing the second triangular mesh data at the plurality of time instants to generate an index identifier of the second triangular mesh data; constructing an index structure of the second triangular mesh data based on the index identifier, the first mapping relationship and the second mapping relationship, wherein the index structure is used to associate the index identifiers of the vertices of the triangular meshes in the second triangular mesh data with the water surface temporal data; and generating a dynamic water surface data set to be rendered based on the second triangular mesh data and the index structure; The first mapping relationship includes the correspondence between the irregular quadrilateral mesh at the multiple moments and the vertices of the second triangular mesh at the multiple moments, the second mapping relationship includes the correspondence between the irregular quadrilateral mesh at the multiple moments and the water surface temporal data, and the water surface temporal data includes the water depth data and water flow data of the target area; The rendering module is used to render the dynamic water surface data set to be rendered based on time series and multiple normal overlay rendering technology based on a graphical interface, and generate visualization data representing the dynamic changes of the water surface.

10. An electronic device, characterized in that: include: A processor and a memory for storing a computer program that can be executed on the processor, wherein: The processor is used to execute the steps of the method according to any one of claims 1 to 8 when running a computer program.

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