Digital twinborn basin construction method, device and equipment and storage medium

Abstract

The embodiment of the invention provides a digital twin basin construction method, device and equipment and a storage medium, and the method comprises the steps that a basin center server divides a target physical basin based on basin basic information and a basin geographic image, obtains a plurality of basin grids, determines subtasks of the basin grids, and carries out the subtasks of the basin grids for each basin grid; and issuing the subtasks of the drainage basin grid and the grid space data of the drainage basin grid to a grid edge server deployed by the drainage basin grid, and performing edge calculation and edge simulation by the grid edge server to obtain a grid calculation result and a grid simulation result. The drainage basin center server can determine a digital twinborn simulation result of an interaction area among a plurality of drainage basin grids based on each grid calculation result, drainage basin basic information and a drainage basin geographic image, and integrates each grid simulation result and the digital twinborn simulation result to obtain a digital twinborn drainage basin; the calculation pressure of the drainage basin central server is reduced; and the data transmission time delay is reduced.

Description

Technical Field

[0001] The present application belongs to the field of digital twin technology, and in particular relates to a digital twin watershed construction method, apparatus, equipment and storage medium. Background Art

[0002] To improve water resource management efficiency and enhance water security risk prevention and control capabilities, digital twin river basin technology has emerged. This technology applies digital twin technology to the water conservancy sector, constructing a digital river basin identical to the physical one. This allows for digital mapping, intelligent simulation, and proactive rehearsal of the physical river basin.

[0003] Currently, digital twins of all river basin elements, including upper reaches, main streams, tributaries, and water conservancy projects, are typically constructed at once according to unified standards for the basin. This creates a holistic digital twin basin, facilitating subsequent unified water resource scheduling and flood control operations. However, if digital twins of all elements are constructed at once according to unified standards, it is difficult to coordinate the development levels of each element, and the cost and difficulty of constructing the entire basin at once are high. Summary of the Invention

[0004] The embodiments of the present application provide a digital twin watershed construction method, apparatus, equipment, and computer storage medium, which can realize the digital twin watershed construction of the target physical watershed through gridding and edge computing with high efficiency.

[0005] In a first aspect, an embodiment of the present application provides a method for constructing a digital twin watershed, which is applied to a watershed center server. The method includes:

[0006] Obtain basic watershed information and geographical images of the target physical watershed;

[0007] Dividing the target physical watershed according to the watershed basic information and the watershed geographic image to obtain a plurality of watershed grids, and determining grid spatial data of each watershed grid;

[0008] Determining subtasks of each watershed grid according to the target scheduling task of the target physical watershed;

[0009] For each watershed grid, the subtasks of the watershed grid and the grid spatial data of the watershed grid are sent to the grid edge server deployed on the watershed grid;

[0010] Receive grid computing results and grid simulation results returned by each grid edge server after executing a subtask based on grid spatial data, wherein the grid computing results are quantitative data of the watershed grid state after executing the subtask, and the grid simulation results are the results obtained by dynamic simulation based on the grid computing results;

[0011] Determine the digital twin simulation results of the interaction areas between the multiple watershed grids based on the calculation results of each grid, the basic information of the watershed, and the geographical image of the watershed;

[0012] According to the simulation results of each grid and the digital twin simulation results, a digital twin watershed of the target physical watershed is obtained.

[0013] In one feasible implementation, the target physical watershed is divided according to the watershed basic information and the watershed geographic image to obtain a plurality of watershed grids, specifically including:

[0014] Divide the target physical watershed according to the basic watershed information and the watershed geographic image to obtain a plurality of initial grids;

[0015] Based on the administrative area data of the target physical watershed, the initial grids are combined to obtain a plurality of watershed grids.

[0016] In one feasible implementation, the initial grids are combined based on the administrative area data of the target physical watershed to obtain multiple watershed grids, specifically including:

[0017] Based on the administrative area data of the target physical watershed, the initial grids in each administrative area are combined according to the water flow exchange situation and the grid area to obtain a plurality of watershed grids.

[0018] In one feasible implementation, based on the calculation results of each grid, the basic information of the watershed, and the geographical image of the watershed, a digital twin simulation result of the interaction area between the multiple watershed grids is determined, specifically including:

[0019] Determine the digital twin calculation results of the interaction areas between the multiple watershed grids based on the calculation results of each grid;

[0020] Superimposing the basic information of the watershed and the geographical image of the watershed to obtain the watershed spatial data of the target physical watershed;

[0021] The digital twin calculation results are dynamically simulated on the watershed spatial data to determine the digital twin simulation results.

[0022] In one feasible implementation, according to the target scheduling task of the target physical watershed, the subtasks corresponding to each watershed grid are determined, specifically including:

[0023] Determining a target scheduling task for the target physical watershed based on a user's simulation instruction;

[0024] The task type of the target scheduling task is used as the target type, wherein the task type includes at least one of water resource scheduling, flood calculation, and water environment analysis;

[0025] Determining the geographical coverage of the target scheduling task according to the target type;

[0026] According to the target scheduling task, subtasks of each watershed grid within the geographical coverage are determined.

[0027] In a second aspect, an embodiment of the present application provides a method for constructing a digital twin watershed, which is applied to a grid edge server, including:

[0028] Receive subtasks and grid space data sent by the basin center server;

[0029] Acquire multi-source perception data of the watershed grid to which the grid edge server belongs, and execute the issued subtasks according to the multi-source perception data to obtain grid computing results;

[0030] Dynamically simulate the grid calculation results on the grid space data to obtain grid simulation results;

[0031] The grid calculation results and the grid simulation results are returned to the basin center server.

[0032] In one feasible implementation, the grid calculation result is dynamically simulated on the grid spatial data to obtain a grid simulation result, specifically including:

[0033] The grid calculation results are dynamically simulated on the grid space data according to a preset simulation time range and simulation time step to obtain grid simulation results.

[0034] In one feasible implementation, executing the issued subtasks based on the multi-source perception data to obtain grid computing results specifically includes:

[0035] In the case where the issued subtask is water resource scheduling, the multi-source sensing data is input into a preset water resource scheduling model, and the water resource scheduling process is simulated by the water resource scheduling model to obtain a grid calculation result;

[0036] In the case where the issued subtask is flood calculation, the multi-source sensing data is input into a preset flood control scheduling model, and the flood control scheduling process is simulated by the flood control scheduling model to obtain a grid calculation result;

[0037] When the subtask issued is water environment analysis, the multi-source perception data is input into a preset water environment analysis model, and the water environment analysis model is used to simulate the impact of water resource scheduling or flood control scheduling on the water environment to obtain grid calculation results.

[0038] In a third aspect, an embodiment of the present application provides a digital twin watershed construction device, comprising:

[0039] The acquisition module is used to obtain the basic information of the target physical watershed and the geographical image of the watershed;

[0040] A grid division module is used to divide the target physical watershed according to the watershed basic information and the watershed geographic image to obtain multiple watershed grids and determine the grid spatial data of each watershed grid;

[0041] A subtask determination module, configured to determine the subtasks of each watershed grid according to the target scheduling task of the target physical watershed;

[0042] The subtask distribution module is used to send the subtasks of each watershed grid and the grid spatial data of the watershed grid to the grid edge server deployed on the watershed grid;

[0043] A first receiving module is configured to receive grid computing results and grid simulation results returned by each grid edge server after executing a subtask based on grid spatial data. The grid computing results are quantitative data on the watershed grid state after executing the subtask, and the grid simulation results are results obtained by dynamic simulation based on the grid computing results.

[0044] A calculation summary module is used to determine the digital twin simulation results of the interaction area between the multiple watershed grids based on the calculation results of each grid, the basic information of the watershed and the geographical image of the watershed;

[0045] The digital twin watershed module is used to obtain the digital twin watershed of the target physical watershed based on the simulation results of each grid and the digital twin simulation results.

[0046] In a fourth aspect, an embodiment of the present application provides a digital twin watershed construction device, comprising:

[0047] The second receiving module is used to receive subtasks and grid space data sent by the basin center server;

[0048] The grid computing module is used to obtain multi-source perception data of the watershed grid and execute the issued subtasks according to the multi-source perception data to obtain grid computing results;

[0049] A grid simulation module, configured to dynamically simulate the grid calculation results on the grid spatial data to obtain grid simulation results;

[0050] The result feedback module is used to return the grid calculation results and the grid simulation results to the watershed central server.

[0051] In the fifth aspect, an embodiment of the present application provides a digital twin watershed construction device, which includes: a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement any one of the above-mentioned digital twin watershed construction methods.

[0052] In a sixth aspect, an embodiment of the present application provides a computer storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, any one of the above-mentioned digital twin watershed construction methods is implemented.

[0053] In the seventh aspect, an embodiment of the present application provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes any one of the above-mentioned digital twin watershed construction methods.

[0054] A digital twin watershed construction method, apparatus, equipment, and computer storage medium of an embodiment of the present application can divide the target physical watershed based on the basic watershed information and geographical image of the target physical watershed to obtain multiple watershed grids, and then obtain a digital twin watershed of the target physical watershed through integration and summary by performing edge computing and edge simulation within each watershed grid. According to the target scheduling tasks of the target physical watershed, the subtasks of each watershed grid are determined. Then, for each watershed grid, the subtasks of the watershed grid and the grid spatial data of the watershed grid are sent to the grid edge server deployed by the watershed grid. The grid edge server executes the sent subtasks based on the grid spatial data to obtain grid calculation results and grid simulation results. The watershed center server can determine the digital twin simulation results of the interaction areas between multiple watershed grids based on the calculation results of each grid, the basic information of the watershed and the geographic image of the watershed, integrate and summarize the simulation results of each grid and the digital twin simulation results to obtain the digital twin watershed of the target physical watershed, that is, to disperse the digital twin watershed construction tasks of the target physical watershed to the grid edge servers of each watershed grid and the watershed center server. While realizing the construction of the digital twin watershed of the target physical watershed, the computing pressure of the watershed center server and the data transmission delay are reduced.

[0055] Furthermore, the target physical watershed can be divided based on its basic basin information and geographic imagery to generate multiple initial grids. These initial grids can then be combined based on the administrative region data of the target physical watershed, resulting in multiple watershed grids. This division and combination approach better aligns with the actual management system and can meet the construction requirements of different regions and tasks. Furthermore, by combining grids based on water flow exchange and grid area, small and scattered initial grids can be merged nearby, reducing computing resource consumption and simplifying the complexity of building a digital twin of the target physical watershed. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0057] Figure 1 This is a flow chart of a method for constructing a digital twin watershed provided in an embodiment of the present application;

[0058] Figure 2 This is a schematic diagram of a digital twin watershed construction system provided in an embodiment of the present application;

[0059] Figure 3 This is a schematic diagram of data exchange between various units in a digital twin watershed construction system provided in an embodiment of the present application;

[0060] Figure 4 Schematic diagram of the structure of a digital twin watershed construction device provided in an embodiment of the present application;

[0061] Figure 5 Schematic diagram of the structure of a digital twin watershed construction device provided in an embodiment of the present application;

[0062] Figure 6 It is a structural schematic diagram of a digital twin watershed construction device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0063] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present application by illustrating the examples of the present application.

[0064] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, the elements defined by the phrase "comprising..." do not exclude the presence of other identical elements in the process, method, article, or device comprising the elements.

[0065] To improve water resource management efficiency and enhance water security risk prevention and control capabilities, digital twin river basin technology has emerged. This technology applies digital twin technology to the water conservancy sector, constructing a digital river basin identical to the physical one. This allows for digital mapping, intelligent simulation, and proactive rehearsal of the physical river basin.

[0066] Currently, digital twins of all river basin elements, including river sections, main streams, tributaries, and water conservancy projects, are generally constructed at once according to unified standards for the river basin. This forms a holistic digital twin of the river basin, facilitating subsequent unified water resources scheduling and flood control operations. However, if digital twins of all elements are constructed at once according to unified standards, the construction levels and construction cycles of each element will be inconsistent, making it difficult to complete them in a coordinated manner. Furthermore, the cost and difficulty of constructing the entire river basin at once will be high, and the construction cycle will be long.

[0067] In order to solve the problems of the prior art, the embodiments of the present application provide a method, device, equipment and computer storage medium for constructing a digital twin watershed.

[0068] The following first describes a method for constructing a digital twin watershed provided in an embodiment of the present application.

[0069] Figure 1 A flow chart of a method for constructing a digital twin watershed provided in one embodiment of the present application is shown.

[0070] like Figure 1 As shown, the method includes the following steps:

[0071] S100: The watershed center server obtains basic watershed information and watershed geographic images of the target physical watershed.

[0072] In one or more embodiments of the present application, in order for the watershed center server to divide the target physical watershed in subsequent steps, in this step, the watershed center server needs to obtain basic watershed information and watershed geographic images of the target physical watershed.

[0073] Specifically, the watershed center server can obtain the basic watershed information and watershed geographic images of the target physical watershed.

[0074] It should be noted that the basic information of the watershed characterizes the basic characteristics of the natural geography and engineering facilities of the target physical watershed, and the geographical image of the watershed characterizes the geographical characteristics of the surface morphology and spatial distribution of the target physical watershed. For example, the basic information of the watershed includes the basic characteristics of the natural geography such as the watershed area, river section, main stream, main tributaries, as well as the basic characteristics of the engineering facilities such as the deployment points, reservoir capacity, and water storage capacity of the water conservancy projects. The geographical image of the watershed includes the oblique photography data of the river section, main stream, and main tributaries of the watershed and basic geographical spatial data such as topographic maps and land use maps, which provide rich topography and landforms. In this application, there is no restriction on the method of obtaining basic information of the watershed and geographical image of the watershed. For example, the basic information of the watershed can be obtained from the Geographic Information System (GIS) database, hydrological and meteorological observation stations, etc., and the geographical image of the watershed can be obtained through drones or satellite remote sensing platforms. In addition, after obtaining the basic information of the watershed and the geographical image of the watershed, the central server of the watershed can perform data pre-processing operations such as format conversion and data cleaning on the obtained data to improve the data quality.

[0075] S101: The watershed center server divides the target physical watershed according to the watershed basic information and the watershed geographic image to obtain multiple watershed grids, and determines the grid spatial data of each watershed grid.

[0076] In one or more embodiments of the present application, in order to realize grid edge computing and grid edge simulation in subsequent steps, in this step, the watershed center server can divide the target physical watershed according to the watershed basic information and watershed geographic image obtained in step S100, obtain multiple watershed grids, and determine the grid spatial data of each watershed grid.

[0077] Specifically, the watershed center server can divide the target physical watershed according to the basic watershed information and the watershed geographic image of the target physical watershed, thereby obtaining multiple watershed grids after division, and for each watershed grid, superimpose the basic watershed information belonging to the watershed grid and the watershed geographic image belonging to the watershed grid to obtain the grid spatial data of the watershed grid.

[0078] It should be noted that the specific method of dividing the target physical watershed is not limited in this application. For example, terrain analysis can be performed through geographic information system technology to achieve the division of the target physical watershed, or it can be divided according to elements, that is, each element is gridded and customized. Elements refer to the geographic spatial features such as river sections, main streams, tributaries, and engineering facilities such as reservoirs and dams within the target physical watershed. Grid spatial data characterizes the geographic spatial features and spatial distribution of engineering facilities within the watershed grid. This application does not limit the method of determining grid spatial data. For example, geographic information system technology can be used to achieve spatial superposition of basic watershed information and watershed geographic images, thereby obtaining richer grid spatial data.

[0079] Since different administrative regions may have different management standards, the watershed grids may be divided with reference to the administrative region data of the target physical watershed. In one or more embodiments of the present application, first, the watershed center server may divide the target physical watershed according to the basic watershed information and the geographical image of the watershed to obtain multiple initial grids. Secondly, the watershed center server may combine the initial grids based on the administrative region data of the target physical watershed to obtain multiple watershed grids, wherein the administrative region data represents the management boundary and responsibility division of the target physical watershed.

[0080] In addition, the size of the watershed grid is not limited in this application and can be set according to actual needs. Of course, the method of customizing the combination of initial grids based on administrative area data is not limited in this application and can be set according to actual needs, such as combining based on water flow direction and catchment area. In one or more embodiments of the present application, the watershed center server can combine the initial grids in each administrative area based on the administrative area data of the target physical watershed, according to the water flow exchange situation and the grid area, to obtain multiple watershed grids, wherein the water flow exchange situation characterizes the degree of dynamic interaction of water flow between the initial grids. By merging initial grids with smaller areas and higher degrees of dynamic interaction nearby, the use of computing resources is reduced and the complexity of constructing the digital twin watershed corresponding to the target physical watershed is simplified.

[0081] S102: The watershed central server determines the subtasks of each watershed grid according to the target scheduling task of the target physical watershed.

[0082] In one or more embodiments of the present application, in order to realize grid edge computing and grid edge simulation of each watershed grid in subsequent steps, in this step, the watershed center server needs to determine the subtasks of each watershed grid based on the target scheduling tasks of the target physical watershed.

[0083] Specifically, the basin center server may determine the subtasks of each basin grid according to the target scheduling tasks of the target physical basin.

[0084] It should be noted that target scheduling tasks refer to comprehensive tasks such as water resource management, flood control, power generation, and ecological protection for the target physical basin, while subtasks refer to the specific tasks within the basin grid that are broken down from the target scheduling task. For example, if the target scheduling task is flood control, subtasks may include water resource scheduling, flood calculation, and reservoir discharge control. Target scheduling tasks can be set by the user or determined based on historical scheduling data for the target physical basin. Target scheduling tasks include water resource scheduling during droughts, flood calculation during flood seasons, and water environment analysis.

[0085] In addition, the basin center server can determine the geographical coverage affected by the target scheduling task based on the task type of the target scheduling task, and thereby determine the subtasks of each basin grid within the geographical coverage based on the target scheduling task. In one or more embodiments of the present application, first, the basin grid center server can determine the target scheduling task of the target physical basin based on the user's simulation instructions. Secondly, the basin grid center server can use the task type of the target scheduling task as the target type, and the task type includes at least one of water resources scheduling, flood calculation, and water environment analysis. Finally, the basin grid center server can determine the geographical coverage of the target scheduling task based on the target type, and thereby determine the subtasks of each basin grid within the geographical coverage based on the target scheduling task. The specific method of determining the geographical coverage of the target scheduling task based on the target type is not limited in this application and can be set according to actual needs. For example, the geographical coverage involved in the historical scheduling task of the target type in the historical event can be determined by analyzing historical scheduling data, or the geographical coverage of the target scheduling task of the task type can be determined by analyzing the topography and spatial distribution of the target physical basin.

[0086] S103: The watershed center server sends the subtasks of each watershed grid and the grid spatial data of the watershed grid to the grid edge server deployed on the watershed grid.

[0087] Specifically, the watershed center server may send the grid spatial data of the watershed grid determined in step 101 and the subtask of the watershed grid determined in step S102 to the grid edge server deployed on each watershed grid.

[0088] S104: The grid edge server receives the subtasks and grid space data sent by the basin center server.

[0089] S105: The grid edge server obtains multi-source perception data of the watershed grid to which it belongs, and executes the issued subtasks according to the multi-source perception data to obtain grid calculation results.

[0090] In one or more embodiments of the present application, in order to determine the grid simulation results of the watershed grid in subsequent steps, in this step, the grid edge server can obtain multi-source perception data within the watershed grid to which it belongs, and then execute the issued subtasks based on the multi-source perception data to obtain the grid calculation results of the watershed grid to which it belongs.

[0091] Specifically, the grid edge server can obtain multi-source perception data of the watershed grid to which it belongs, and execute the issued subtasks based on the multi-source perception data to obtain the grid calculation results of the watershed grid to which it belongs. The grid calculation results are quantitative data of the watershed grid status after executing the subtasks.

[0092] It should be noted that multi-source perception data characterizes the state of the environment within the watershed grid. The multi-source perception data may include meteorological perception, hydrological perception, and video perception. Meteorological perception includes at least precipitation, temperature, wind speed, wind direction, and moderation, reflecting the real-time meteorological conditions within the watershed grid. Hydrological perception includes at least water level, flow, water quality, and water temperature, reflecting the real-time state of the water body within the watershed grid. Video perception includes mainstream video, flood risk point video, engineering facility video, etc. Since multi-source perception data may have problems such as noise and inconsistent format, the grid edge server can perform data preprocessing on the acquired multi-source perception data to obtain high-quality and consistent-format multi-source perception data. Of course, the specific content of data preprocessing, such as data detection and data cleaning, structuring, vectorization, etc., is not limited in this application. In one or more embodiments of the present application, when the subtask issued is water resource scheduling, the grid edge server may input the multi-source perception data into a preset water resource scheduling model, simulate the water resource scheduling process through the water resource scheduling model, and obtain the grid calculation result of the watershed grid to which the grid edge server belongs; when the subtask issued is flood calculation, the grid edge server may input the multi-source perception data into a preset flood control scheduling model, simulate the flood control scheduling process through the flood control scheduling model, and obtain the grid calculation result of the watershed grid to which the grid edge server belongs; when the subtask issued is water environment analysis, the grid edge server may input the multi-source perception data into a preset water environment analysis model, simulate the impact of water resource scheduling or flood control scheduling on the water environment through the water environment analysis model, and obtain the grid calculation result of the watershed grid to which the grid edge server belongs.

[0093] Of course, the specific types of water resource scheduling models, flood control scheduling models, and water environment analysis models are not limited in this application and can be set according to actual needs. For example, the water resource scheduling model can be a deterministic model, a Monte Carlo simulation model, a Markov decision model, a system dynamics model, a SWAT model, a HEC-HMS model, a genetic algorithm model, a particle swarm optimization model, etc. The flood control scheduling model can be a particle swarm optimization algorithm, a dynamic programming algorithm, a segmented trial algorithm, a list trial algorithm, a MOLA-based reservoir group real-time flood control multi-objective optimization scheduling algorithm, etc. The water environment analysis model can be SWMM, a one-dimensional-two-dimensional coupled water environment model, a 4P model algorithm, a single-objective and multi-objective decision analysis algorithm, a water environment mathematical model algorithm, etc. The impact of water resource scheduling or flood control scheduling on the water environment refers to the impact on agriculture, aquatic organisms, water area coastline, etc. in the discharge area, or the impact on agriculture, aquatic organisms, water area coastline, etc. in the flooded area.

[0094] S106: The grid edge server performs dynamic simulation on the grid calculation result on the grid spatial data to obtain a grid simulation result.

[0095] In one or more embodiments of the present application, in order to integrate and summarize the digital twin of the target physical watershed in subsequent steps, in this step, the grid edge server may obtain a grid simulation result through dynamic simulation based on the grid calculation result determined in step S105.

[0096] Specifically, the grid edge server may perform dynamic simulation on the grid space data of the watershed grid to which the grid calculation result determined in step S105 belongs, to obtain a grid simulation result.

[0097] It should be noted that the specific method of dynamic simulation is not limited in this application and can be set according to actual needs, such as using two-dimensional images for dynamic simulation or using three-dimensional images for dynamic simulation. In order to integrate the simulation results into a digital twin watershed in subsequent steps, in one or more embodiments of this application, the grid edge server can dynamically simulate the grid calculation results on the grid space data according to the preset simulation time range and simulation time step to obtain a grid simulation result with unified accuracy.

[0098] In addition, each watershed grid may or may not adopt a unified edge computing model and edge simulation model. This is not restricted in this application, but the use of a unified edge computing model and edge simulation model facilitates subsequent unified upgrades according to unified standards.

[0099] S107: The grid edge server returns the grid calculation result and the grid simulation result to the watershed center server.

[0100] S108: The watershed center server receives the grid calculation results and grid simulation results returned by each grid edge server after executing the subtask based on the grid spatial data. The grid calculation results are quantitative data of the watershed grid status after executing the subtask, and the grid simulation results are the results obtained by dynamic simulation based on the grid calculation results.

[0101] S109: The watershed center server determines the digital twin simulation results of the interaction areas between the multiple watershed grids based on the calculation results of each grid, the basic information of the watershed, and the geographical image of the watershed.

[0102] In one or more embodiments of the present application, in order to obtain a digital twin basin of the target physical basin in subsequent steps, in this step, the basin center server needs to determine the digital twin simulation results of the interaction areas between multiple basin grids based on the calculation results of each grid, the basic information of the basin obtained in step S100, and the basin geographic image.

[0103] Specifically, the basin center server can determine the digital twin simulation results of the interaction areas between multiple basin grids based on the calculation results of each grid, basic information of the basin, and geographic images of the basin.

[0104] It's important to note that the interaction areas between multiple watershed grids refer to areas where water flow exchange, water quality imaging, or other interactions occur between the grids. This means that when constructing a digital twin of a target physical watershed, not only the independent states of each grid must be considered, but also the interactions between them. For example, the Chongqing section of the Yangtze River is the target physical watershed, with two grids: the Jialing River and the Fu River. Suppose rainfall falls on the Jialing River between 9:00 and 10:00 AM, adding 100 million cubic meters of precipitation. Flood inundation will be calculated for the Jialing River grid and simulated for that grid. If rainfall falls on the Fu River between 10:00 and 11:00 AM, adding 50 million cubic meters of precipitation, flood inundation will also be calculated for the Fu River grid and simulated for that grid. Suppose the Jialing River grid calculates the 100 million cubic meters of precipitation, minus the water storage in the reservoirs within that grid, to obtain a grid calculation result of 50 million cubic meters of water flowing into the Yangtze River. Assume that the Fu River basin grid subtracts the water storage in the reservoirs within the grid from the additional 50 million cubic meters of precipitation, resulting in a grid calculation result of 25 million cubic meters of water flowing into the Yangtze River. By aggregating the grid calculation results for each basin grid, it is determined that after the Fu River joins the Chongqing section of the Yangtze River, the Yangtze River will experience an additional 75 million cubic meters of water. This flood control model then calculates the inundation situation after the Fu River joins the Chongqing section of the Yangtze River, generating digital twin calculation results for the interaction areas between multiple basin grids. Based on this digital twin calculation result, this section of the basin is simulated to produce a digital twin simulation result.

[0105] Of course, the specific method of determining the digital twin simulation results is not limited in this application. For example, the calculation results of each grid can be matched with the basic information of the watershed and the geographical image of the watershed, and the digital twin simulation results of the interaction area between multiple watershed grids can be obtained through a preset simulation model. In one or more embodiments of the present application, first, the watershed center server can determine the digital twin calculation results of the interaction area between multiple watershed grids based on the calculation results of each grid. Secondly, the watershed center server can superimpose the basic information of the watershed and the geographical image of the watershed obtained in step S100 to obtain the watershed spatial data of the target physical watershed. Finally, the watershed center server can dynamically simulate the digital twin calculation results on the watershed spatial data to determine the digital twin simulation results.

[0106] S110: The watershed center server obtains the digital twin watershed of the target physical watershed based on the simulation results of each grid and the digital twin simulation results.

[0107] Specifically, the basin center server can aggregate and integrate the simulation results of each grid and the digital twin simulation results determined in step S109 to form a digital twin of the target physical basin. Using the above example, the grid simulation results of the Jialing River basin grid, the grid simulation results of the Fu River basin grid, and the digital twin simulation results of the confluence of the Fu River in the Chongqing section of the Yangtze River are aggregated to form a digital twin of the target physical basin.

[0108] In the above method, the basin center server can divide the target physical basin into multiple basin grids based on the basic basin information and basin geographic imagery of the target physical basin. Edge computing and edge simulation are then performed within each basin grid. The digital twin of the target physical basin is then obtained by integrating and summarizing the grid simulation results and digital twin simulation results of each basin grid. Based on the target scheduling task of the target physical basin, subtasks for each basin grid are determined. Then, for each basin grid, the subtasks and grid spatial data of the basin grid are distributed to the grid edge server deployed in that basin grid. Each grid edge server can then obtain multi-source perception data and, based on this multi-source perception data and grid spatial data, execute subtasks to obtain grid computing results and grid simulation results. The basin center server receives the grid calculation results and grid simulation results returned by each grid edge server after executing subtasks based on grid spatial data. Based on the calculation results of each grid, the basic information of the basin and the geographic image of the basin, it determines the digital twin simulation results of the interaction area between multiple basin grids, integrates and summarizes the simulation results of each grid and the digital twin simulation results, and obtains the digital twin basin of the target physical basin, that is, the digital twin basin construction task of the target physical basin is dispersed to the grid edge servers of each basin grid and the basin center server. Finally, through integration and summary, the construction of the digital twin basin of the target physical basin is realized. At the same time, the computing pressure of the basin center server is reduced and the data transmission delay is reduced.

[0109] It should be noted that in addition to independent simulation of each basin grid and digital twin simulation of the interaction area between multiple basin grids, and obtaining a digital twin basin through integration and summary, after obtaining the grid calculation results of each basin grid, centralized simulation of the target physical basin can be performed based on the calculation results of each grid, which is highly flexible.

[0110] Based on the above-mentioned digital twin watershed construction method, the present application embodiment provides a digital twin watershed construction system. Figure 2 , which is a schematic diagram of the principles of a digital twin watershed construction system provided in an embodiment of the present application, includes a basic information management unit 200, a watershed gridding unit 201, a multi-source sensing access unit 202, a unified task scheduling unit 203, an edge computing unit 204, an edge simulation unit 205, a watershed computing unit 206, and a watershed simulation unit 207. The basic information management unit, watershed gridding unit, unified task scheduling unit, watershed computing unit, and watershed simulation unit are deployed on the watershed central server, and the multi-source sensing access unit, edge computing unit, and edge simulation unit are deployed on the grid edge server of each watershed grid.

[0111] like Figure 3As shown, it is a schematic diagram of data exchange between various units in a digital twin watershed construction system provided in an embodiment of the present application. The process of data exchange between various units in the digital twin watershed construction system includes steps S300 to S311.

[0112] The basic information management unit 200 is configured to execute step S300:

[0113] S300: Acquire basic watershed information and a watershed geographic image of the target physical watershed; and send the basic watershed information and the watershed geographic image to the watershed gridding unit.

[0114] In some embodiments, the basic information management unit is further used to obtain administrative area data of the target physical watershed and send the administrative area data to the watershed gridding unit.

[0115] The watershed gridding unit 201 is used to execute steps S301 to S302:

[0116] S301: Divide the target physical watershed according to the basic watershed information and the watershed geographic image to obtain multiple watershed grids, and determine the grid spatial data of each watershed grid.

[0117] S302: For each watershed grid, the grid spatial data of the watershed grid is sent to an edge simulation unit on a grid edge server where the watershed grid is deployed.

[0118] In some embodiments, the watershed gridding unit is also used to divide the target physical watershed according to the basic information of the watershed and the geographical image of the watershed to obtain multiple initial grids; based on the administrative area data of the target physical watershed, the initial grids are combined to obtain multiple watershed grids.

[0119] In some embodiments, the watershed gridding unit is further used to combine the initial grids in each administrative area according to the water flow exchange conditions and grid areas based on the administrative area data of the target physical watershed to obtain multiple watershed grids.

[0120] The multi-source sensing access unit 202 is configured to execute step S303:

[0121] S303: Acquire multi-source perception data of the watershed grid to which the grid edge server belongs; and send the multi-source perception data to the edge computing unit.

[0122] The unified task scheduling unit 203 is configured to execute step S304:

[0123] S304: Determine the subtasks of each watershed grid according to the target scheduling task of the target physical watershed; for each watershed grid, send the subtask of the watershed grid to the edge computing unit on the grid edge server deployed by the watershed grid.

[0124] In some embodiments, the unified task scheduling unit is also used to determine the target scheduling task of the target physical watershed based on the user's simulation instructions; use the task type of the target scheduling task as the target type, and the task type includes at least one of water resources scheduling, flood calculation, and water environment analysis; determine the geographical coverage of the target scheduling task according to the target type; and determine the subtasks of each watershed grid within the geographical coverage according to the target scheduling task.

[0125] The edge computing unit 204 is configured to execute steps S305 to S306:

[0126] S305: Execute the issued subtasks according to the multi-source perception data to obtain the grid computing results.

[0127] S306: Send the grid calculation result to the edge simulation unit and the watershed calculation unit.

[0128] In some embodiments, the edge computing unit is also used to input the multi-source perception data into a preset water resource scheduling model when the subtask issued is water resource scheduling, simulate the water resource scheduling process through the water resource scheduling model, and obtain the grid computing result; when the subtask issued is flood calculation, input the multi-source perception data into a preset flood control scheduling model, simulate the flood control scheduling process through the flood control scheduling model, and obtain the grid computing result; when the subtask issued is water environment analysis, input the multi-source perception data into a preset water environment analysis model, simulate the impact of water resource scheduling or flood control scheduling on the water environment through the water environment analysis model, and obtain the grid computing result.

[0129] The edge simulation unit 205 is configured to execute steps S307 to S308:

[0130] S307: Dynamically simulate the grid calculation results on the grid space data to obtain grid simulation results.

[0131] S308: Send the grid simulation result to the watershed simulation unit.

[0132] In some embodiments, the edge simulation unit is further used to dynamically simulate the grid calculation results on the grid space data according to a preset simulation time range and simulation time step to obtain a grid simulation result.

[0133] The watershed calculation unit 206 is configured to execute step S309:

[0134] S309: Based on the calculation results of each grid, determine the digital twin calculation results of the interaction area between multiple watershed grids.

[0135] S310: Send the digital twin calculation results to the watershed simulation unit.

[0136] The watershed simulation unit 207 is configured to execute step S311:

[0137] S311: Determine the digital twin simulation results of the interaction areas between multiple watershed grids based on the digital twin calculation results; obtain the digital twin watershed of the target physical watershed based on the simulation results of each grid and the digital twin simulation results.

[0138] In some embodiments, the watershed simulation unit is also used to superimpose the basic information of the watershed and the geographical image of the watershed to obtain the watershed spatial data of the target physical watershed; dynamically simulate the digital twin calculation results on the watershed spatial data to determine the digital twin simulation results.

[0139] Figure 4 This is a schematic diagram of the structure of a digital twin watershed construction device provided in an embodiment of the present application. Figure 4 As shown, the device may include an acquisition module 401, a grid division module 402, a subtask determination module 403, a subtask distribution module 404, a first receiving module 405, a calculation summary module 406 and a digital twin watershed module 407.

[0140] An acquisition module 401 is used to acquire basic watershed information and a watershed geographic image of a target physical watershed;

[0141] A grid division module 402 is configured to divide the target physical watershed according to the watershed basic information and the watershed geographic image, obtain a plurality of watershed grids, and determine grid spatial data of each watershed grid;

[0142] The subtask determination module 403 is used to determine the subtasks of each watershed grid according to the target scheduling task of the target physical watershed;

[0143] The subtask distribution module 404 is used to distribute the subtasks and grid spatial data of each watershed grid to the grid edge server deployed on the watershed grid.

[0144] A first receiving module 405 is configured to receive grid computing results and grid simulation results returned by each grid edge server after executing a subtask based on grid spatial data. The grid computing results are quantitative data on the watershed grid state after executing the subtask, and the grid simulation results are results obtained by dynamic simulation based on the grid computing results.

[0145] A calculation summary module 406 is used to determine the digital twin simulation results of the interactive areas between the multiple watershed grids based on the calculation results of each grid, the basic information of the watershed, and the geographical image of the watershed;

[0146] The digital twin watershed module 407 is used to obtain the digital twin watershed of the target physical watershed based on the simulation results of each grid and the digital twin simulation results.

[0147] In one feasible implementation, the grid division module 402 is specifically used to divide the target physical watershed according to the basic information of the watershed and the geographical image of the watershed to obtain multiple initial grids; and based on the administrative area data of the target physical watershed, the initial grids are combined to obtain multiple watershed grids.

[0148] In one feasible implementation, the grid division module 402 can also be used to combine the initial grids in each administrative area according to the water flow exchange conditions and grid area based on the administrative area data of the target physical watershed to obtain multiple watershed grids.

[0149] In one feasible implementation, the subtask determination module 403 is specifically used to determine the target scheduling task of the target physical watershed based on the user's simulation instructions; take the task type of the target scheduling task as the target type, and the task type includes at least one of water resources scheduling, flood calculation and water environment analysis; determine the geographical coverage of the target scheduling task according to the target type; and determine the subtasks of each watershed grid within the geographical coverage according to the target scheduling task.

[0150] In one feasible implementation, the calculation summary module 406 is specifically used to determine the digital twin calculation results of the interaction area between the multiple watershed grids based on the calculation results of each grid; superimpose the basic information of the watershed and the geographic image of the watershed to obtain the watershed spatial data of the target physical watershed; and dynamically simulate the digital twin calculation results on the watershed spatial data to determine the digital twin simulation results.

[0151] Figure 5 This is a schematic diagram of the structure of a digital twin watershed construction device provided in an embodiment of the present application. Figure 5 As shown, the apparatus may include a second receiving module 501 , a grid computing module 502 , a grid simulation module 503 and a result feedback module 504 .

[0152] The second receiving module 501 is used to receive subtasks and grid space data sent by the basin center server;

[0153] The grid computing module 502 is used to obtain multi-source sensing data of the watershed grid and execute the issued subtasks according to the multi-source sensing data to obtain grid computing results.

[0154] A grid simulation module 503 is used to dynamically simulate the grid calculation result on the grid space data to obtain a grid simulation result;

[0155] The result feedback module 504 is used to return the grid calculation result and the grid simulation result to the watershed central server.

[0156] In one achievable implementation, the grid calculation module 502 is specifically configured to dynamically simulate the grid calculation result on the grid space data according to a preset simulation time range and simulation time step to obtain a grid simulation result.

[0157] In one feasible implementation, the grid simulation module 503 is specifically used to, when the subtask issued is water resource scheduling, input the multi-source perception data into a preset water resource scheduling model, simulate the water resource scheduling process through the water resource scheduling model, and obtain a grid calculation result; when the subtask issued is flood calculation, input the multi-source perception data into a preset flood control scheduling model, simulate the flood control scheduling process through the flood control scheduling model, and obtain a grid calculation result; when the subtask issued is water environment analysis, input the multi-source perception data into a preset water environment analysis model, simulate the impact of water resource scheduling or flood control scheduling on the water environment through the water environment analysis model, and obtain a grid calculation result.

[0158] Figure 6 A hardware structure diagram of a digital twin watershed construction device provided in an embodiment of the present application is shown.

[0159] A digital twin watershed construction device may include a processor 601 and a memory 602 storing computer program instructions.

[0160] Specifically, the processor 601 may include a central processing unit (CPU) or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0161] The memory 602 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 602 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. In one example, the memory 602 may include a removable or non-removable (or fixed) medium, or the memory 602 may be a non-volatile solid-state memory. The memory 602 may be inside or outside the integrated gateway disaster recovery device.

[0162] In one example, the memory 602 may be a read-only memory (ROM). In one example, the ROM may be a mask-programmable ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or a flash memory, or a combination of two or more of these.

[0163] The memory 602 may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical / tangible memory storage devices. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present application.

[0164] The processor 601 reads and executes the computer program instructions stored in the memory 602 to implement Figure 1 A method for constructing a digital twin watershed in the illustrated embodiment.

[0165] In one example, a digital twin watershed construction device may further include a communication interface 603 and a bus 604. Figure 6 As shown, the processor 601 , the memory 602 , and the communication interface 603 are connected via a bus 604 and communicate with each other.

[0166] The communication interface 603 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0167] Bus 604 includes hardware, software or both, and couples the components of online data flow metering equipment to each other. For example, and not limitation, bus may include Accelerated Graphics Port (AGP) or other graphics bus, Enhanced Industry Standard Architecture (EISA) bus, Front Side Bus (FSB), Hyper Transport (HT) interconnection, Industry Standard Architecture (ISA) bus, InfiniBand interconnection, Low Pin Count (LPC) bus, memory bus, Micro Channel Architecture (MCA) bus, Peripheral Component Interconnect (PCI) bus, PCI-Express (PCI-X) bus, Serial Advanced Technology Attachment (SATA) bus, Video Electronics Standards Association Local (VLB) bus or other suitable bus or a combination of two or more of these. Where appropriate, bus 604 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0168] In addition, in conjunction with a method for constructing a digital twin watershed in the above embodiment, an embodiment of the present application may provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any of the methods for constructing a digital twin watershed in the above embodiment is implemented.

[0169] An embodiment of the present application also provides a computer program product, including a computer program, which, when processed and executed, implements any one of the digital twin watershed construction methods in the above embodiments.

[0170] It should be understood that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated. Those skilled in the art can make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present application.

[0171] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of the present application are programs or code segments used to perform the required tasks. The programs or code segments can be stored in a machine-readable medium, or transmitted on a transmission medium or communication link via a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memories (ROMs), flash memories, erasable read-only memories (EROMs), floppy disks, compact disc read-only memories (CD-ROMs), optical discs, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segments can be downloaded via computer networks such as the Internet and intranets.

[0172] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0173] Aspects of the present application have been described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed via the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. This processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It is also understood that each box in the block diagram and / or the flowchart and the combination of the boxes in the block diagram and / or the flowchart can also be implemented by the dedicated hardware that performs the specified function or action, or can be implemented by the combination of dedicated hardware and computer instructions.

[0174] The above description is only a specific embodiment of the present application. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.

Claims

1. A digital twin watershed construction method, characterized in that: Applied to the basin center server, including: Obtain basic watershed information and geographical images of the target physical watershed; Dividing the target physical watershed according to the watershed basic information and the watershed geographic image to obtain a plurality of watershed grids, and determining grid spatial data of each watershed grid; Determining subtasks of each watershed grid according to the target scheduling task of the target physical watershed; For each watershed grid, the subtasks of the watershed grid and the grid spatial data of the watershed grid are sent to the grid edge server deployed on the watershed grid; Receive grid computing results and grid simulation results returned by each grid edge server after executing a subtask based on grid spatial data, wherein the grid computing results are quantitative data of the watershed grid state after executing the subtask, and the grid simulation results are the results obtained by dynamic simulation based on the grid computing results; Determine the digital twin simulation results of the interaction areas between the multiple watershed grids based on the calculation results of each grid, the basic information of the watershed, and the geographical image of the watershed; According to the simulation results of each grid and the digital twin simulation results, a digital twin watershed of the target physical watershed is obtained.

2. The method according to claim 1, characterized in that Divide the target physical watershed according to the basic watershed information and the watershed geographic image to obtain multiple watershed grids, specifically including: Dividing the target physical watershed according to the basic watershed information and the watershed geographic image to obtain a plurality of initial grids; Based on the administrative area data of the target physical watershed, the initial grids are combined to obtain a plurality of watershed grids.

3. The method according to claim 2, characterized in that Based on the administrative area data of the target physical watershed, the initial grids are combined to obtain multiple watershed grids, specifically including: Based on the administrative area data of the target physical watershed, the initial grids in each administrative area are combined according to the water flow exchange situation and the grid area to obtain a plurality of watershed grids.

4. The method according to claim 1, wherein Determine the digital twin simulation results of the interaction areas between the multiple watershed grids based on the calculation results of each grid, the basic information of the watershed, and the geographical image of the watershed, specifically including: Determine the digital twin calculation results of the interaction areas between the multiple watershed grids based on the calculation results of each grid; Superimposing the basic information of the watershed and the geographical image of the watershed to obtain the watershed spatial data of the target physical watershed; The digital twin calculation results are dynamically simulated on the watershed spatial data to determine the digital twin simulation results.

5. The method according to claim 1, wherein According to the target scheduling task of the target physical watershed, the subtasks corresponding to each watershed grid are determined, specifically including: Determining a target scheduling task for the target physical watershed based on a user's simulation instruction; The task type of the target scheduling task is used as the target type, wherein the task type includes at least one of water resource scheduling, flood calculation, and water environment analysis; Determining the geographical coverage of the target scheduling task according to the target type; According to the target scheduling task, subtasks of each watershed grid within the geographical coverage are determined.

6. A digital twin watershed construction method, characterized in that: Applicable to grid edge servers, including: Receive subtasks and grid space data sent by the basin center server; Acquire multi-source perception data of the watershed grid to which the grid edge server belongs, and execute the issued subtasks according to the multi-source perception data to obtain grid computing results; Dynamically simulate the grid calculation results on the grid space data to obtain grid simulation results; The grid calculation results and the grid simulation results are returned to the basin center server.

7. The method according to claim 6, characterized in that The grid calculation result is dynamically simulated on the grid space data to obtain a grid simulation result, specifically including: The grid calculation results are dynamically simulated on the grid space data according to a preset simulation time range and simulation time step to obtain grid simulation results.

8. The method according to claim 6, characterized in that Based on the multi-source perception data, the issued subtasks are executed to obtain grid computing results, specifically including: In the case where the issued subtask is water resource scheduling, the multi-source sensing data is input into a preset water resource scheduling model, and the water resource scheduling process is simulated by the water resource scheduling model to obtain a grid calculation result; In the case where the issued subtask is flood calculation, the multi-source sensing data is input into a preset flood control scheduling model, and the flood control scheduling process is simulated by the flood control scheduling model to obtain a grid calculation result; When the subtask issued is water environment analysis, the multi-source perception data is input into a preset water environment analysis model, and the water environment analysis model is used to simulate the impact of water resource scheduling or flood control scheduling on the water environment to obtain grid calculation results.

9. A digital twin watershed construction device, characterized in that: The device comprises: The acquisition module is used to obtain the basic information of the target physical watershed and the geographical image of the watershed; A grid division module is used to divide the target physical watershed according to the watershed basic information and the watershed geographic image to obtain multiple watershed grids and determine the grid spatial data of each watershed grid; A subtask determination module, configured to determine the subtasks of each watershed grid according to the target scheduling task of the target physical watershed; The subtask distribution module is used to send the subtasks of each watershed grid and the grid spatial data of the watershed grid to the grid edge server deployed on the watershed grid; A first receiving module is configured to receive grid computing results and grid simulation results returned by each grid edge server after executing a subtask based on grid spatial data. The grid computing results are quantitative data on the watershed grid state after executing the subtask, and the grid simulation results are results obtained by dynamic simulation based on the grid computing results. A calculation summary module is used to determine the digital twin simulation results of the interaction area between the multiple watershed grids based on the calculation results of each grid, the basic information of the watershed and the geographical image of the watershed; The digital twin watershed module is used to obtain the digital twin watershed of the target physical watershed based on the simulation results of each grid and the digital twin simulation results.

10. A digital twin watershed construction device, characterized in that: The device comprises: The second receiving module is used to receive subtasks and grid space data sent by the basin center server; The grid computing module is used to obtain multi-source perception data of the watershed grid and execute the issued subtasks according to the multi-source perception data to obtain grid computing results; A grid simulation module, configured to dynamically simulate the grid calculation results on the grid spatial data to obtain grid simulation results; The result feedback module is used to return the grid calculation results and the grid simulation results to the watershed central server.

11. A digital twin watershed construction device, characterized in that: The device includes: a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the digital twin watershed construction method according to any one of claims 1 to 8.

12. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the digital twin watershed construction method according to any one of claims 1 to 8.

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