A digital twin scene construction method and system for flood control of a river basin and a medium

Abstract

The present application relates to the technical field of digital twin modeling, and more particularly to a digital twin scene construction method and system for flood control in a river basin, and a medium. The method comprises the following steps: collecting terrain data, hydrological data and flood control engineering data of the river basin, and generating a river basin flood control basic data set through correlation verification and standardized integration; extracting terrain correlation parameters and engineering layout information in the river basin flood control basic data set, and dividing a flood control simulation unit to construct a river basin digital twin model; determining corresponding flood levels and engineering dispatch scenarios according to engineering design parameters and hydrological measured data in the river basin flood control basic data set; and performing flood evolution coupling operation on the flood control simulation unit of the river basin digital twin model based on the flood levels and the engineering dispatch scenarios. The present application integrates multi-source river basin data and divides the flood control simulation unit, realizes accurate restoration of flood evolution, and thus improves the accuracy of river basin flood control and the efficiency of emergency response.

Description

Technical Field

[0001] This invention relates to the field of digital twin modeling technology, and in particular to a method, system and medium for constructing a digital twin scenario for watershed flood control. Background Technology

[0002] Digital twin technology for watershed flood control has become an important support for flood management. By integrating topographic, hydrological, and engineering data to construct simulated scenarios, and combining flood evolution simulation with engineering scheduling logic, it enables dynamic analysis and presentation of watershed floods. However, existing technologies still have key shortcomings: First, the data collection and integration process lacks standardization, resulting in inconsistent formats and accuracies among different data types and insufficient spatial matching, leading to discrepancies between the simulated scenarios and the actual watershed environment. Second, flood simulations do not fully incorporate seasonal characteristics, dynamic engineering scheduling parameters, and inter-unit flood exchange patterns, limiting the accuracy of capturing the actual flood movement process. Third, the linkage mechanism between real-time monitoring data and simulated scenarios is imperfect, and the visualization of risks is not intuitive enough, making it difficult to quickly and accurately reflect the impact and risk level of floods, thus affecting the timeliness and effectiveness of flood control responses. Summary of the Invention

[0003] Therefore, it is necessary to provide a method, system, and medium for constructing a digital twin scenario for watershed flood control in order to solve at least one of the aforementioned technical problems.

[0004] To achieve the above objectives, a method for constructing a digital twin scenario for watershed flood control is provided, the method comprising the following steps: Step S1: Collect watershed topographic data, hydrological data, and flood control engineering data, and generate a basic dataset for watershed flood control through correlation verification and standardization integration; Step S2: Extract topographic correlation parameters and engineering layout information from the basic flood control dataset of the watershed, divide the flood control simulation units, and construct a digital twin model of the watershed; Step S3: Based on the engineering design parameters and hydrological measurement data in the basin flood control basic dataset, determine the corresponding flood magnitude and engineering scheduling scenario; perform flood evolution coupling calculation on the flood control simulation unit of the basin digital twin model based on the flood magnitude and engineering scheduling scenario; Step S4: Collect watershed rainfall monitoring data and flood control project monitoring data in real time, and dynamically adjust the flood evolution calculation parameters of each flood control simulation unit based on the watershed rainfall monitoring data and flood control project monitoring data; perform scene rendering processing on the watershed digital twin model after parameter adjustment, and output dynamic twin scene analysis results.

[0005] Preferably, the present invention also provides a digital twin scenario construction system for watershed flood control, used to execute the above-described digital twin scenario construction method for watershed flood control, the digital twin scenario construction system for watershed flood control comprising: The data acquisition module is used to collect watershed topographic data, hydrological data, and flood control engineering data. After correlation verification and standardization integration, it generates a basic dataset for watershed flood control. The digital twin modeling module is used to extract topographic correlation parameters and engineering layout information from the basic flood control dataset of the watershed, divide the flood control simulation units, and construct a digital twin model of the watershed. The flood scenario matching module is used to determine the corresponding flood magnitude and engineering scheduling scenario based on the engineering design parameters and hydrological measurement data in the basin flood control basic dataset; and to perform flood evolution coupling calculations on the flood control simulation units of the basin digital twin model based on the flood magnitude and engineering scheduling scenario. The watershed flood control adjustment module is used to collect watershed rainfall monitoring data and flood control project monitoring data in real time, dynamically adjust the flood evolution calculation parameters of each flood control simulation unit based on the watershed rainfall monitoring data and flood control project monitoring data, perform scene rendering processing on the watershed digital twin model after parameter adjustment, and output dynamic twin scene analysis results.

[0006] Preferably, a computer-readable storage medium stores a computer program thereon, which, when executed, implements the above-described method for constructing a digital twin scenario for watershed flood control.

[0007] The beneficial effects of this invention are as follows: First, by collecting topographic data segment by segment, hydrological data quarterly, and flood control engineering data precisely, spatial matching and verification are performed based on the latitude and longitude coordinates of the topographic data. Data that exceeds the range is eliminated and the format and precision units are unified to form a standardized basic dataset covering multiple dimensions of topography, hydrology, and engineering. This ensures a high degree of fit between the digital twin scenario and the actual environment of the watershed and eliminates the problem of scenario distortion caused by data fragmentation.

[0008] Second, based on engineering design parameters and hydrological measurement data, multiple flood levels are divided according to season. Dynamic parameters such as dam opening degree and reservoir discharge volume are set in combination with engineering scheduling scenarios. The step-by-step calculation method of first low-lying areas and then high-lying areas is adopted to simulate the flood filling process. The flood exchange law is defined according to the topographic elevation difference between units. The total flood volume and inflow / outflow deviation within the unit are calibrated in real time, so that the flood evolution simulation accurately restores the actual flood overflow, engineering interception and inter-unit transmission process.

[0009] Third, real-time monitoring and visualization output improve risk response efficiency: Distributed sensors collect data such as rainfall intensity, river water level, and engineering operation status in real time, dynamically adjust calculation parameters such as runoff coefficient and water blocking coefficient according to preset rules, combine 3D visualization technology to render the scene according to water depth gradient, overlay engineering status indicators and flood time sequence evolution process, generate graded risk assessment table, intuitively present the flood impact range and risk level, and provide accurate and timely decision support for flood control emergency response. Attached Figure Description

[0010] Figure 1 A flowchart illustrating the steps involved in constructing a digital twin scenario for watershed flood control; Figure 2 This is a schematic diagram of the watershed river system research area in an embodiment of the present invention; Figure 3 This is a rendering of a digital twin scenario for flood control in a watershed, as described in this embodiment of the invention. The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0011] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0012] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0013] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated items listed.

[0014] To achieve the above objectives, please refer to Figures 1 to 3 A method for constructing a digital twin scenario for watershed flood control, the method comprising the following steps: Preferably, step S1: collect watershed topographic data, hydrological data and flood control engineering data, and generate a watershed flood control basic dataset after correlation verification and standardization integration; Optionally, step S1 includes the following steps: Collect topographic data of the watershed segment by segment along the river network direction and record the latitude and longitude coordinates of the collection points; Hydrological data is collected quarterly by category from hydrological monitoring stations, including rainfall, river water level and flow data, and the specific locations of the monitoring stations are marked to form hydrological data. Collect location data and crest elevation of dikes in the watershed, as well as reservoir capacity and dam height, to form flood control engineering data; Using the latitude and longitude coordinates of topographic data as a benchmark, the spatial matching between hydrological data and flood control engineering data is compared, data exceeding the preset latitude and longitude coordinate range is eliminated, and the data recording format and precision unit are standardized to form a basic dataset for watershed flood control.

[0015] Please see Figure 2 This is a schematic diagram of the river basin study area. Using latitude and longitude grids and a compass (N) for positioning, it clearly presents the spatial distribution of the Yellow River basin (Inner Mongolia section), the Liao River basin (mainly the West Liao River system), and other river basins in Northwest China. The main streams and tributaries of major rivers are marked with blue lines, and the basin boundaries are outlined with pink lines. This visually demonstrates the river network, basin division, and administrative geographical pattern within the study area, providing a clear geographical and river system foundation for constructing a digital twin scenario for flood control in the basin.

[0016] In this embodiment, the Yellow River Basin and the West Liao River system of the Liao River Basin in Inner Mongolia Autonomous Region are taken as the research objects, but it is not limited to this region. Other river basins can refer to and implement the relevant technical operations.

[0017] Along the main channels and major tributaries of the river network in the aforementioned target watershed, a surveying method combining GNSS real-time dynamic positioning technology and total station was employed. Topographic data collection points were deployed at 100-meter intervals, advancing from the river source to the river mouth or lake. Simultaneously, the latitude and longitude coordinates (format DD°MM′SS.SS″, accurate to 0.01 seconds), topographic elevation (accurate to centimeters), and slope value (accurate to 0.1°) of each point were recorded. The coordinate system adopted was the China Geodetic Coordinate System 2000 (CGCS2000), and the elevation was based on the 1985 National Elevation Datum. The base map scale for flood protection areas, small and medium-sized rivers, and reservoirs was used. The scale of the base map should be no less than 1:10000, and the scale of the urban base map should be no less than 1:2000. Data is collected through 23 fixed hydrological monitoring stations already deployed in the basin, categorized by the four seasons: spring (March-May), summer (June-August), autumn (September-November), and winter (December-February). Rainfall (accurate to 0.1 mm), river water level (measurement range 0-30 m, accuracy ±0.01 m), and river flow (measurement range 0.1-100 m³ / s, accuracy ±1%) are recorded hourly. The basin sub-zone number, river station number, and specific geographical coordinates of each monitoring station are marked, forming standardized hydrological data containing 28 fields.

[0018] Using a combination of handheld laser rangefinders and electronic levels, the planar coordinates (accurate to centimeters) of the starting point, ending point, and turning point of the dikes were collected segment by segment according to the management scope of the dikes. An elevation measuring point was set up every 50 meters along the top of the dike, and the elevation of the top of the dike was continuously measured and recorded. The total storage capacity (accurate to 10,000 m³) and maximum dam height (accurate to 0.1 m) of 48 key small and medium-sized reservoirs, including Meidai Reservoir, were extracted from the reservoir project completion archives. Combined with UAV aerial imagery (resolution not less than 2 m, not less than 0.8 m in urban areas), the outline coordinates of the dam were verified. The elevation data of the top, middle and bottom of the dam were measured on-site using the three-point verification method. The difference between the data and the archived data was controlled within ±0.3 m. The measurement data and parameter information of the dikes and reservoirs were integrated to form flood control engineering data containing 16 core indicators.

[0019] A unified spatial reference system was constructed based on the latitude and longitude coordinates of topographic data. Hydrological data and flood control engineering data were imported into ArcGIS spatial data processing software, and the spatial overlay analysis function was enabled. The matching error threshold was set to ±5 meters, and the coordinate overlap of the three types of data was compared. Data that exceeded the latitude and longitude range of the basin boundary (E107°12′-112°18′E and N37°24′-40°15′N in some areas of the Yellow River Basin) were removed. All valid data were uniformly converted into SHP format, with elevation data retained to 2 decimal places, flow data retained to 1 decimal place, and coordinate data retained to 6 decimal places. After the data format was verified to be correct, it was classified and archived into three categories: topographic data, hydrological data, and flood control engineering data, forming a structured basin flood control basic dataset.

[0020] Preferably, step S2: extract topographic correlation parameters and engineering layout information from the watershed flood control basic dataset, divide the flood control simulation units, and construct a watershed digital twin model; Optionally, step S2 includes the following steps: Topographic correlation parameters, including topographic elevation difference, topographic contour lines, and river network distribution density, are extracted from the basic flood control dataset of the watershed. Extract the spatial coordinates and protection coverage of flood control projects from the basic flood control dataset of the watershed, and establish a protection priority sequence for different flood control projects; Taking a single reservoir or continuous levee section in the engineering layout information as the core, and combining the direction of topographic contour lines, flood control simulation units are delineated, and each flood control simulation unit is set to contain at least one core flood control project. Using flood control simulation units as the basic unit, three-dimensional modeling technology is used to restore the geomorphic features corresponding to the terrain-related parameters. A watershed digital twin model is constructed according to the actual size ratio in the engineering layout information, and flood flow and water level parameters between flood control simulation units are set.

[0021] In this embodiment, topographic parameters are extracted from the basic dataset of watershed flood control. An elevation difference calculation tool is used to obtain the elevation difference between adjacent topographic collection points (accurate to 0.1m). A contour line generation tool is used to extract topographic contour lines at 10m contour intervals. A river network density analysis tool is used to calculate the river network distribution density (unit: km / km²) using a 10km×10km grid as the statistical unit. All topographic parameters are extracted and processed based on the CGCS2000 coordinate system and the 1985 National Elevation Datum.

[0022] Spatial data filtering tools were used to extract spatial coordinates (accurate to the centimeter level) and protection coverage (determined according to the protection boundary of the engineering design) of flood control projects from the basic flood control dataset of the basin. Based on indicators such as the protected population size, protected farmland area, and river class of the flood control projects, weight coefficients were determined through the analytic hierarchy process (AHP) to establish a priority sequence for flood control project protection. For example, 48 key small and medium-sized reservoirs, such as the Meidai Reservoir in the Yellow River Basin and the Xiliao River system of the Liao River Basin in Inner Mongolia Autonomous Region, as well as the Yellow River main stream dikes, were classified as first-level protection priority, while dikes of small and medium-sized rivers were classified as second-level protection priority.

[0023] Taking a single reservoir or continuous levee section with primary protection priority as the core, and combining the topographic contour lines, the boundary of the flood control simulation unit is delineated using a polygon clipping tool to ensure that the boundary of each unit is basically consistent with the contour line direction, and that each unit contains at least one core flood control project. The unit area is controlled between 50-100 km². Units that cross administrative regions are adjusted according to the natural boundary of the watershed to avoid administrative boundaries from disrupting the integrity of the unit.

[0024] Using 3D modeling technology, with flood control simulation units as the basic units, elevation data, contour data, and river network distribution data from the terrain-related parameters are imported to restore the watershed geomorphological features. A digital twin scene of the watershed is constructed according to the actual size scale in the engineering layout information (scale not less than 1:10000). The flood flow transmission threshold between units is set through hydrological connection tools (minimum transmission flow of 0.5 m³ / s), and the water level parameter connection relationship between units is set to ensure that the water level difference at the boundary of adjacent units does not exceed 0.2 m, so as to realize the continuous simulation of flood evolution between units.

[0025] Preferably, step S3: Based on the engineering design parameters and hydrological measurement data in the basin flood control basic dataset, determine the corresponding flood magnitude and engineering scheduling scenario; perform flood evolution coupling calculation on the flood control simulation unit of the basin digital twin model based on the flood magnitude and engineering scheduling scenario; Optionally, step S3, based on the engineering design parameters and hydrological measurement data in the basin flood control basic dataset, determines the corresponding flood magnitude and engineering scheduling scenario, including: The engineering design parameters of the design flood control height of the dikes and the maximum flood storage capacity of the reservoirs were extracted from the basic flood control dataset of the watershed, as well as the measured hydrological data of the peak flow and duration of historical floods. Based on the design flood control height of the engineering design parameters and combined with the peak flow of historical floods in the hydrological measurement data, different levels of flood volume are classified. Based on the maximum flood storage capacity of the reservoir according to the engineering design parameters, and combined with the number of days of historical floods in the hydrological measurement data, the engineering scheduling scenarios corresponding to different flood levels are determined.

[0026] In this embodiment, engineering design parameters and hydrological measurement data are extracted from the basic dataset of watershed flood control. The engineering design parameters include the design flood control height of the dikes of 8 flood control protection areas, such as the Yalu River flood protection area (accurate to 0.1m), and the maximum flood storage capacity of 48 key small and medium-sized reservoirs (accurate to 10,000 m³). The hydrological measurement data includes the peak flow of historical floods in the past 30 years (accurate to 0.1 m³ / s) and the duration of historical floods (accurate to 1 day). All data are associated with the corresponding watershed zoning number and engineering identifier.

[0027] Based on the design flood control height of the dikes and combined with the peak flow distribution characteristics of historical floods, five flood magnitude levels are defined. Specifically, a peak flow less than 50% of the flow corresponding to the design flood control height is classified as a 5-year flood; a peak flow between 50% and 80% of the flow corresponding to the design flood control height is classified as a 10-year flood; a peak flow between 80% and 100% of the flow corresponding to the design flood control height is classified as a 20-year flood; a peak flow between 100% and 120% of the flow corresponding to the design flood control height is classified as a 50-year flood; and a peak flow greater than 120% of the flow corresponding to the design flood control height is classified as a 100-year flood. The flow corresponding to the design flood control height of the dikes is obtained through analysis of river cross-sectional parameters and hydraulic characteristics.

[0028] Using the maximum flood storage capacity of the reservoir as a constraint, and combining the duration of historical floods, the engineering scheduling scenarios corresponding to each flood level are determined. For floods of 5-year and 10-year return periods, when the historical flood duration is less than 7 days, a normal reservoir discharge scheduling scenario is set, with the discharge flow controlled at 30%-50% of the maximum discharge flow; when the duration is between 7 and 15 days, a tiered reservoir discharge scheduling scenario is set, with the discharge flow gradually increased to 60%-80% of the maximum discharge flow. For floods of 20-year and 50-year return periods, when the historical flood duration is less than 10 days, a full-load reservoir discharge + routine dike protection scheduling scenario is set; when the duration is greater than or equal to 10 days, a full-load reservoir discharge + flood diversion channel activation scheduling scenario is set, with the flood diversion channel opening degree adjusted in a gradient of 50%-80%. For floods of 100-year return periods, regardless of the historical flood duration, an emergency reservoir discharge + key dike section reinforcement + full-area flood diversion scheduling scenario is set, with the discharge flow executed at 100% of the maximum discharge flow, and all flood diversion channels opened.

[0029] Optionally, the specific flood magnitude can be determined as follows: The statistical data of flood control in the basin is pre-set with historical flood measurement data, and the number of floods and peak flow are counted separately for spring, summer and autumn. Based on the engineering design parameters of the dike's designed flood control height and the reservoir's maximum flood storage capacity, the engineering bearing capacity corresponding to different flood peaks in each season is defined. The flood magnitude is divided into different levels according to the engineering load-bearing capacity from high to low, and the corresponding flood peak range and duration range are defined for each magnitude.

[0030] In this embodiment, the Yellow River Basin and the Xiliao River system of the Liao River Basin in Inner Mongolia Autonomous Region are used as the research objects, but it is not limited to this region. Other river basins can refer to the relevant technical operations. Nearly 30 years of measured flood data are extracted from the basic flood control dataset of the river basins. Statistics are categorized by three seasons: spring (March-May), summer (June-August), and autumn (September-November). In spring, the number of floods in the Yalu River, Guiliu River, and other river basins is counted (accurate to 1), and the peak flow of each flood is recorded simultaneously (accurate to 0.1 m³ / s). In summer, the number of floods and corresponding peak flows in major rivers such as the Yellow River main stream and the Xiliao River are counted. In autumn, flood data in the Hailar River, Dahei River, and other river basins are counted, forming a seasonal measured flood dataset.

[0031] Seasonal flood data were matched with engineering design parameters, including the design flood control height of the dikes in eight flood protection zones (accurate to 0.1m) and the maximum flood storage capacity of 48 key small and medium-sized reservoirs (accurate to 10,000 m³). Through hydraulic characteristic calculations, the critical flow value corresponding to the design flood control height of the dikes (accurate to 0.1 m³ / s) was obtained. Combined with the maximum flood storage capacity of the reservoirs, the upper limit of the flood peak that the dikes could withstand was calculated. The engineering load-bearing state corresponding to different flood peaks in each season was defined: a flood peak less than 80% of the critical flow value is considered a low-load load-bearing state; between 80% and 100% is a medium-load load-bearing state; between 100% and 120% is a high-load load-bearing state; and greater than 120% is an overload load-bearing state.

[0032] Based on the engineering carrying capacity, flood levels are divided into five categories from high to low. The overload carrying capacity corresponds to a 100-year flood, with a peak flow exceeding 120% of the critical flow and a duration of 10-15 days. The high load carrying capacity corresponds to a 50-year flood, with a peak flow between 100% and 120% of the critical flow and a duration of 7-10 days. The medium load carrying capacity corresponds to a 20-year flood, with a peak flow between 80% and 100% of the critical flow and a duration of 5-7 days. The low load carrying capacity is further divided into two categories: a peak flow between 50% and 80% of the critical flow corresponds to a 10-year flood, with a duration of 3-5 days; and a peak flow less than 50% of the critical flow corresponds to a 5-year flood, with a duration of 1-3 days. All category classifications are also marked with the corresponding season and the watershed sub-region number.

[0033] Optionally, the specific engineering scheduling scenario can be determined as follows: Analyze the engineering operation records under different flood scenarios in the basic flood control data of the watershed, and extract the correspondence between the opening degree of the dam and the river flow, and between the reservoir storage and the downstream water level; For each flood level, the initial opening angle of the dam and the initial discharge volume of the reservoir are set; According to the time sequence of flood evolution, the adjustment nodes of dam opening degree, the increase or decrease of reservoir discharge, and the conditions for the activation of flood diversion outlets are defined. The system detects the mutual influence between different scheduling projects, formulates linkage scheduling rules, and triggers the corresponding operations of related scheduling projects when the operating status of a certain scheduling project reaches a preset scheduling threshold, thus forming a complete project scheduling scenario process.

[0034] In this embodiment, the correlation between the dam opening degree and river flow, reservoir storage and downstream water level of 8 flood protection areas and 48 key small and medium-sized reservoirs under different flood scenarios is extracted from the engineering operation records of the basin flood control basic dataset. The dam opening degree is recorded in grades from 0° to 90°, the river flow is accurate to 0.1 m³ / s, the reservoir storage is accurate to 10,000 m³, and the downstream water level is accurate to 0.01 m. For flood events of 5 years, 10 years, 20 years, 50 years, and 100 years, the initial opening angle of the dam and the initial discharge volume of the reservoir are set as follows: For flood events of 5 years and 10 years, the initial opening angle of the dam is set at 30°, the initial discharge volume of medium-sized reservoirs is controlled at 30% of the maximum discharge volume, and the initial discharge volume of small reservoirs is controlled at 20% of the maximum discharge volume; For flood events of 20 years and 50 years, the initial opening angle of the dam is set at 60°, the initial discharge volume of medium-sized reservoirs is set at 50% of the maximum discharge volume, and the initial discharge volume of small reservoirs is set at 40% of the maximum discharge volume; For flood events of 100 years, the initial opening angle of the dam is set at 90°, the initial discharge volume of medium-sized reservoirs is set at 70% of the maximum discharge volume, and the initial discharge volume of small reservoirs is set at 60% of the maximum discharge volume.

[0035] Based on the time sequence of flood evolution, the adjustment nodes for the opening degree of sluice gates and dams are defined with a 24-hour time interval. For floods of the 5-year and 10-year return periods, the opening degree of sluice gates and dams increases by 10° every 24 hours, and the reservoir discharge increases by 10% every 24 hours. The flood diversion outlet is activated when the river flow reaches 120% of the design flow. For floods of the 20-year and 50-year return periods, the opening degree of sluice gates and dams increases by 15° every 12 hours, and the reservoir discharge increases by 15% every 12 hours. The flood diversion outlet is activated when the river flow reaches 100% of the design flow. For floods of the 100-year return period, the opening degree of sluice gates and dams increases by 20° every 8 hours, and the reservoir discharge increases by 20% every 8 hours. The flood diversion outlet is activated when the river flow reaches 80% of the design flow. The opening degree of the flood diversion outlet is increased in a gradient from 50% to 100%.

[0036] Real-time monitoring of the mutual influence between different scheduling projects and formulation of linkage scheduling rules: when the opening degree of a dam reaches 90° or the water storage of a reservoir reaches 80% of the total storage capacity (preset scheduling threshold), a linkage operation is triggered to increase the flood discharge of the upstream adjacent reservoir by 10% and increase the opening degree of the downstream dam by 10° in advance; when the opening degree of the flood diversion outlet reaches 80%, an early warning linkage is triggered for the reinforcement projects of the surrounding dikes.

[0037] Optionally, step S3, which involves performing flood evolution coupling calculations on the flood control simulation units of the watershed digital twin model based on flood magnitude and engineering scheduling scenarios, includes: For different combinations of flood magnitude and engineering scheduling scenarios, the corresponding peak flood discharge and initial water level are input as boundary conditions into the watershed digital twin model; Based on the time sequence of flood evolution, the flood overflow process in the terrain is simulated. Combined with the opening of dams and the flood discharge operation of reservoirs in the engineering scheduling scenario, the changes in flood velocity and water depth in different areas are calculated. The flooding status of each flood control simulation unit is obtained by flood evolution calculation through the watershed digital twin model, and the flow and transfer of flood between different flood control simulation units is realized by flood exchange calculation through the watershed digital twin model, thus coupling the results of flood evolution coupling calculation.

[0038] In this embodiment, five flood magnitudes—one in 5 years, one in 10 years, one in 20 years, one in 50 years, and one in 100 years—are combined with corresponding engineering scheduling scenarios such as reservoir discharge, dam regulation, and flood diversion point activation. In the basin digital twin scenario, the peak flood flow (accurate to 0.1 m³ / s) and initial water level (accurate to 0.01 m) corresponding to each combination are input as boundary conditions.

[0039] Taking the Zhalantun urban section of the Yalu River flood control protection area as an example, the peak flow input corresponding to a 5-year flood is 180.5 m³ / s, and the initial water level input is 312.45 m; the peak flow input corresponding to a 100-year flood is 620.3 m³ / s, and the initial water level input is 315.78 m. All boundary condition values ​​are determined based on historical flood measurement data and engineering design parameters in the basin flood control basic dataset. The coordinate system is uniformly adopted as CGCS2000, and the elevation adopts the 1985 National Elevation Datum.

[0040] Following the chronological order of flood evolution, the flood overflow process in the terrain is simulated with a time step of 1 hour. Combined with operational parameters such as dam opening angle, reservoir discharge, and flood diversion outlet opening degree in the engineering scheduling scenario, the variations in flood velocity (accurate to 0.01 m / s) and water depth (accurate to 0.01 m) in different areas are calculated. During the calculation, the river channel roughness is selected based on the river channel morphology and riverbed composition. The roughness of the main channel of the Yalu River is 0.028, and the roughness of the floodplain is 0.042. For areas outside the river channel, the roughness of the calculation grid is determined according to land use type: 0.035 for cultivated land, 0.062 for forest land, and 0.018 for urban built-up areas. For grids containing multiple land use types, the area-weighted method is used to calculate the comprehensive roughness.

[0041] Taking the flood control protection zone in the urban area of ​​Zhalantun City as an example, when the dam opening angle is 60° and the reservoir discharge is 50% of the maximum discharge, the calculated flood velocity in the main channel is 1.85 m / s, the flood velocity on the beach is 0.72 m / s, and the inundation depth in the urban edge area is 0.95 m.

[0042] By calculating flood evolution in a digital twin scenario of the watershed, inundation data such as the inundation range (accurate to 10m), maximum inundation depth, and inundation duration (accurate to 1 hour) within each flood control simulation unit were obtained. The calculation scope covers simulation units corresponding to 8 flood control protection zones, including the Yalu River flood protection zone, 84 small and medium-sized rivers, and 48 key small and medium-sized reservoirs. Taking the downstream simulation unit as an example, under a 50-year flood event, the inundation range is 18.6 km², the maximum inundation depth is 2.35m, and the inundation duration is 72 hours.

[0043] The transmission flow threshold (minimum transmission flow of 0.5 m³ / s) is determined based on the topographic elevation difference between units and the width of the connecting channel. The Manning formula is used to calculate the flood exchange flow between units, and the water level difference at the boundary of adjacent units is controlled within 0.2 m. Taking two adjacent simulated units in the Daheihe River flood control protection area as an example, the topographic elevation difference between unit A and unit B is 0.8 m, and the width of the connecting channel is 30 m. The calculated flood exchange flow between units is 12.6 m³ / s, and the water level difference at the boundary is 0.15 m. By superimposing the flood evolution calculation results within the unit with the flood exchange calculation results between units, the flood evolution coupling calculation is completed, ensuring that the relative error between the difference in water volume flowing into and out of the calculation range and the water storage within the calculation range is less than 1 × 10⁻. 6 It outputs flood evolution data with a unified time series for the entire basin.

[0044] Most importantly, the flood evolution coupling operation is specifically as follows: The flood evolution calculation of the watershed digital twin model proceeds in the order of first low-lying areas and then high-lying areas, and the step-by-step calculation method is used to simulate the flood filling process in the terrain segment by segment; A dedicated computing node is set up at the location of the flood control project to calculate the number of times the flood control project intercepts the flood based on the operation parameters in the project scheduling scenario; When calculating flood exchange in the digital twin model of the watershed, the flow rate and velocity of flood exchange are defined based on the topographic elevation difference between flood control simulation units; During the calculation process, the total flood volume and inflow / outflow within the flood control simulation unit are compared in real time. If any deviation occurs, the flood evolution coupling calculation parameters are adjusted promptly.

[0045] In this embodiment, the Yellow River Basin and the Xiliao River system of the Liao River Basin in Inner Mongolia Autonomous Region are taken as the research objects. The flood evolution calculation of the basin digital twin scenario proceeds in the order of low-lying areas first and then high-lying areas, and the flood filling process in the terrain is simulated segment by segment with a time step of 1 hour. The definition of low-lying areas is areas where the terrain elevation is 1.5m or more lower than the surrounding average elevation. Flood filling calculations are first performed on low-lying areas such as the urban section of Zhalantun City in the Yalu River flood control protection area and the urban section of Hohhot City in the Dahei River flood control protection area. Then, the calculations are gradually advanced to the rural sections and mountainous sections with higher elevations. After the filling calculation of each terrain elevation gradient is completed, the real-time water depth and flow velocity data of the area are recorded.

[0046] Dedicated calculation nodes were set up at key sections of 48 major small and medium-sized reservoirs and dams, including the Meidai Reservoir, and at eight flood control protection zones, including the Yalu River and Guiliu River. Each calculation node was bound to the corresponding engineering scheduling scenario operation parameters. For example, when the engineering scheduling scenario was set to emergency flood discharge for a 50-year design flood, the number of times the reservoir dam intercepted the flood was calculated in real time based on the operation parameters of a flood discharge flow of 300 m³ / s and a dam opening angle of 60°. Each interception recorded the peak flood reduction and water level change. The number of interceptions was counted as one effective interception if the flood flow was higher than the node's set threshold (200 m³ / s) for 30 consecutive minutes.

[0047] When calculating flood exchange in the digital twin scenario of the watershed, the flow rate and velocity of flood exchange are defined based on the topographic elevation difference between flood control simulation units. Taking two adjacent simulation units in the Daheihe River flood control protection area as an example, the topographic elevation of unit A is 1020.3m and the topographic elevation of unit B is 1018.7m, with a topographic elevation difference of 1.6m. According to the conversion standard that every 1m of elevation difference corresponds to an exchange flow rate of 15m³ / s and an exchange velocity of 0.8m / s, the flood exchange flow rate between the two units is determined to be 24m³ / s and the exchange velocity is 1.28m / s. During the exchange process, the actual exchange flow rate and velocity data are recorded every 30 minutes.

[0048] During the calculation process, a real-time data comparison module compares the total flood volume and inflow / outflow within each flood control simulation unit every 15 minutes. The total flood volume is calculated as the sum of the products of the water depth and the grid area of ​​all calculation grids within the unit, while the inflow / outflow is calculated as the sum of the products of the flow velocity and the cross-sectional area at the unit boundary. If the comparison result shows a relative error (|total flood volume - difference in inflow / outflow| / total flood volume) greater than 1×10⁻ 6 In such cases, adjust the coupled calculation parameters for flood evolution promptly, such as increasing or decreasing the channel roughness by 0.005, or adjusting the topographic elevation correction factor, until the relative error is controlled within 1×10⁻⁻⁶. 6 Within this range, ensure the accuracy of the calculation results.

[0049] Preferably, step S4 involves: collecting real-time watershed rainfall monitoring data and flood control project monitoring data; dynamically adjusting the flood evolution calculation parameters of each flood control simulation unit based on the watershed rainfall monitoring data and flood control project monitoring data; performing scene rendering processing on the watershed digital twin model after parameter adjustment; and outputting dynamic twin scene analysis results.

[0050] Particularly important is that step S4 involves real-time collection of watershed rainfall monitoring data and flood control project monitoring data, and dynamic adjustment of flood evolution calculation parameters for each flood control simulation unit based on these data. Rainfall intensity data is collected once at preset intervals by rain gauges distributed throughout the basin, and river level and flow data are collected in real time by water level and flow sensors in the river channel. By installing stress sensors at key sections of the dike, dam opening sensors, and reservoir water level sensors, the system can collect real-time data on the stress changes of the dike, the actual opening degree of the dam, and the real-time water storage of the reservoir. Establish a table showing the correspondence between monitoring data and calculation parameters. When the monitored rainfall increases by a certain value, the runoff coefficient of the corresponding unit is adjusted according to a preset ratio. When the engineering operation status data of the dam opening degree and reservoir discharge change, the corresponding water blocking coefficient and discharge coefficient in the digital twin model are updated synchronously.

[0051] This embodiment focuses on the Yellow River Basin and the Xiliao River system of the Liao River Basin in Inner Mongolia Autonomous Region, but is not limited to this region; other river basins can refer to the relevant technical operations. Rainfall intensity data is collected every 5 minutes using rainfall sensors distributed in 8 flood protection zones, including the Yalu River and Dahei River flood protection zones, and in 84 small and medium-sized river basins. The measurement range is 0-200 mm / h, with an accuracy of ±0.1 mm. Water level and flow rate data are collected in real time every 10 minutes using water level and flow rate sensors deployed in the river channels. The water level measurement range is 0-30 m, with an accuracy of ±0.01 m, and the flow rate measurement range is 0.1-1000 m³ / s, with an accuracy of ±1%. All hydrological monitoring data are associated with the latitude and longitude coordinates of the corresponding monitoring sections and the basin zoning number.

[0052] Stress sensors installed at key sections of dikes in various flood control protection areas collect dike stress change data at 15-minute intervals, with a measurement range of 0-50MPa and an accuracy of ±0.1MPa. Opening degree sensors installed at dam opening and closing mechanisms collect the actual opening degree of dams in real time, with a measurement range of 0°-90° and an accuracy of ±1°. Water level sensors installed on the dam bodies of 48 key small and medium-sized reservoirs, including Meidai Reservoir, collect real-time water level data at 5-minute intervals. Combined with the reservoir water level-volume curve, the real-time water storage is calculated, with a water level measurement accuracy of ±0.01m and a water storage calculation accuracy to the tens of thousands of cubic meters. All engineering monitoring data are bound to a unique identification code corresponding to the project.

[0053] A table mapping monitoring data to computational parameters was established, clarifying the linkage rules between rainfall intensity and runoff coefficient: for every 10mm increase in monitored rainfall, the runoff coefficient of the corresponding flood control simulation unit increases by 0.05, with an upper limit of 0.8; for every 8mm decrease in rainfall, the runoff coefficient decreases by 0.04, with a lower limit of 0.1. Taking the flood control simulation unit of the Zhalantun urban section of the Yalu River as an example, the initial runoff coefficient was 0.3. When the cumulative increase in rainfall from two consecutive collections reached 12mm, the runoff coefficient of this unit was adjusted to 0.36.

[0054] When the engineering operation data of dam opening degree and reservoir discharge change, the corresponding water resistance coefficient and discharge coefficient are updated synchronously: when the dam opening degree is adjusted from 30° to 60°, the water resistance coefficient decreases linearly from 0.7 to 0.3; when the opening degree is adjusted from 60° to 90°, the water resistance coefficient decreases linearly from 0.3 to 0.1. For every 100 m³ / s increase in reservoir discharge, the discharge coefficient increases by 0.1, and when the discharge reaches 100% of the maximum discharge capacity, the discharge coefficient is fixed at 1.0; for every 80 m³ / s decrease in discharge, the discharge coefficient decreases by 0.08, down to a minimum of 0.2; the data update delay time is controlled within 30 seconds to ensure that the calculated parameters are consistent with the actual operation status of the project.

[0055] Optionally, in step S4, the watershed digital twin model with adjusted parameters undergoes scene rendering processing, and the output dynamic twin scene analysis results include: Three-dimensional visualization technology is used to draw the scene of the watershed digital twin model after parameter adjustment, and the corresponding color gradient is set according to different inundation depth ranges to present the distribution of floods in the watershed; The system overlays real-time operational status indicators of flood control projects, using different icons to distinguish the opening and closing status of dams and the water storage capacity level of reservoirs. The system dynamically demonstrates the evolution of a flood at different points in time, marking the arrival time of the flood and the duration of inundation for each unit. By integrating the inundation range, water depth, and flow velocity of each flood control simulation unit, a flood risk level assessment table is generated.

[0056] This embodiment takes the Yellow River Basin and the Xiliao River system of the Liao River Basin in Inner Mongolia Autonomous Region as the research object, but it is not limited to this region. Other basins can refer to the relevant technical operations. Three-dimensional visualization drawing technology is used to draw the digital twin scene of the basin after parameter adjustment. Based on the results of flood evolution coupling calculation, a four-level color gradient is set according to the inundation depth range: areas with inundation depth less than 0.5m are marked in blue, areas with inundation depth of 0.5-1.0m are marked in yellow, areas with inundation depth of 1.0-2.0m are marked in orange, and areas with inundation depth greater than 2.0m are marked in red. The color transparency is uniformly set to 80%. The drawing accuracy is consistent with the scale of the base map, with a scale of no less than 1:10000 for flood protection areas, small and medium-sized rivers, and reservoir areas, and no less than 1:2000 for urban areas of Baotou City.

[0057] The system overlays real-time operational status indicators for flood control projects, using vector icons to label flood control projects such as dams and reservoirs: when the opening angle of a dam is greater than 0° and less than 90°, a blue triangle icon is used to indicate the open status, with the icon size set at a scale of 1:5000 based on the actual scale of the project; when the opening angle of a dam is 0°, a red circle icon is used to indicate the closed status; when the reservoir's water storage is less than 30% of its total capacity, a green square icon is used to indicate the low water storage level; when it is 30%-70%, a yellow square icon is used to indicate the medium water storage level; and when it is greater than 70%, an orange square icon is used to indicate the high water storage level. All icons are labeled with the project name and core operational parameters, with the dam's opening angle labeled (accurate to 1°) and the reservoir's real-time water storage labeled (accurate to 10,000 m³).

[0058] The simulation dynamically demonstrates the evolution of a flood at different time points, with a timeline control that switches between showing the flood's spread from the river source to the downstream area. The arrival time of the flood (accurate to the hour) and the duration of inundation (accurate to the hour) are marked at the boundaries of each flood control simulation unit. The timeline progress bar is synchronized with the flood's evolution sequence, and dragging allows for viewing the flood distribution at any given moment. For example, in the downstream simulation unit, the arrival time of a 50-year flood is marked as the 6th hour, and the duration of inundation is 72 hours. The water depth change curves at different locations within the unit are displayed synchronously.

[0059] By integrating core data such as the inundation range (accurate to 10m), maximum inundation depth (accurate to 0.01m), and average flow velocity (accurate to 0.01m / s) of each flood control simulation unit, a flood risk level assessment table is generated. The assessment form is sorted by watershed zoning number and includes eight fields: simulation unit number, watershed, inundation range, maximum inundation depth, average flow velocity, flood arrival time, inundation duration, and risk level. The risk level is determined based on a combination of maximum inundation depth and average flow velocity: low risk for maximum inundation depth less than 0.5m and average flow velocity less than 0.3m / s; medium risk for maximum inundation depth 0.5-1.0m and average flow velocity 0.3-0.5m / s; relatively high risk for maximum inundation depth 1.0-2.0m and average flow velocity 0.5-1.0m / s; and high risk for maximum inundation depth greater than 2.0m and average flow velocity greater than 1.0m / s. The final result is a dynamic twin scenario analysis that includes a dynamic demonstration video, a 3D visualization scene file, and a flood risk level assessment form.

[0060] Please see Figure 3 This is a digital twin rendering of a watershed flood control scenario. The central concrete dam (reservoir embankment) serves as the core flood control project, divided into different flood control simulation units by white borders. The blue area represents the reservoir water body and main river channel, the core carrier for hydrological data collection and flood evolution simulation; the red area represents high-risk inundation zones and core flood evolution channels, reflecting the simulation results of flood overflow and inter-unit transmission; the orange area represents flood protection zones and engineering scheduling impact zones, corresponding to the coverage of engineering scheduling under different flood levels; the yellow area represents low-risk protection zones and basic topographic areas, the basis for topographic parameter extraction and model construction; the green area represents the watershed ecology and non-flood control core areas, restoring the real topography; the overall design, through color-coded partitions and core projects, intuitively demonstrates the entire process from data collection and unit division to flood evolution simulation and risk visualization, achieving accurate simulation and risk classification of watershed flood control.

[0061] Preferably, the present invention also provides a digital twin scenario construction system for watershed flood control, used to execute the above-described digital twin scenario construction method for watershed flood control, the digital twin scenario construction system for watershed flood control comprising: The data acquisition module is used to collect watershed topographic data, hydrological data, and flood control engineering data. After correlation verification and standardization integration, it generates a basic dataset for watershed flood control. The digital twin modeling module is used to extract topographic correlation parameters and engineering layout information from the basic flood control dataset of the watershed, divide the flood control simulation units, and construct a digital twin model of the watershed. The flood scenario matching module is used to determine the corresponding flood magnitude and engineering scheduling scenario based on the engineering design parameters and hydrological measurement data in the basin flood control basic dataset; and to perform flood evolution coupling calculations on the flood control simulation units of the basin digital twin model based on the flood magnitude and engineering scheduling scenario. The watershed flood control adjustment module is used to collect watershed rainfall monitoring data and flood control project monitoring data in real time, dynamically adjust the flood evolution calculation parameters of each flood control simulation unit based on the watershed rainfall monitoring data and flood control project monitoring data, perform scene rendering processing on the watershed digital twin model after parameter adjustment, and output dynamic twin scene analysis results.

[0062] Preferably, a computer-readable storage medium stores a computer program thereon, which, when executed, implements the above-described method for constructing a digital twin scenario for watershed flood control.

[0063] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0064] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for constructing a digital twin scenario for watershed flood control, characterized in that, Includes the following steps: Step S1: Collect watershed topographic data, hydrological data, and flood control engineering data, and generate a basic dataset for watershed flood control through correlation verification and standardization integration; Step S2: Extract topographic correlation parameters and engineering layout information from the basic flood control dataset of the watershed, divide the flood control simulation units, and construct a digital twin model of the watershed; Step S3: Based on the engineering design parameters and hydrological measurement data in the basin flood control basic dataset, determine the corresponding flood magnitude and engineering scheduling scenario; perform flood evolution coupling calculation on the flood control simulation unit of the basin digital twin model based on the flood magnitude and engineering scheduling scenario; Step S4: Collect watershed rainfall monitoring data and flood control project monitoring data in real time, and dynamically adjust the flood evolution calculation parameters of each flood control simulation unit based on the watershed rainfall monitoring data and flood control project monitoring data; perform scene rendering processing on the watershed digital twin model after parameter adjustment, and output dynamic twin scene analysis results.

2. The method for constructing a digital twin scenario for watershed flood control according to claim 1, characterized in that, Step S1 includes the following steps: Collect topographic data of the watershed segment by segment along the river network direction and record the latitude and longitude coordinates of the collection points; Hydrological data is collected quarterly by category from hydrological monitoring stations, including rainfall, river water level and flow data, and the specific locations of the monitoring stations are marked to form hydrological data. Collect location data and crest elevation of dikes in the watershed, as well as reservoir capacity and dam height, to form flood control engineering data; Using the latitude and longitude coordinates of topographic data as a benchmark, the spatial matching between hydrological data and flood control engineering data is compared, data exceeding the preset latitude and longitude coordinate range is eliminated, and the data recording format and precision unit are standardized to form a basic dataset for watershed flood control.

3. The method for constructing a digital twin scenario for watershed flood control according to claim 1, characterized in that, Step S2 includes the following steps: Topographic correlation parameters, including topographic elevation difference, topographic contour lines, and river network distribution density, are extracted from the basic flood control dataset of the watershed. Extract the spatial coordinates and protection coverage of flood control projects from the basic flood control dataset of the watershed, and establish a protection priority sequence for different flood control projects; Taking a single reservoir or continuous levee section in the engineering layout information as the core, and combining the direction of topographic contour lines, flood control simulation units are delineated, and each flood control simulation unit is set to contain at least one core flood control project. Using flood control simulation units as the basic unit, three-dimensional modeling technology is used to restore the geomorphic features corresponding to the terrain-related parameters. A watershed digital twin model is constructed according to the actual size ratio in the engineering layout information, and flood flow and water level parameters between flood control simulation units are set.

4. The method for constructing a digital twin scenario for watershed flood control according to claim 1, characterized in that, Step S3, based on the engineering design parameters and hydrological measurement data in the basin flood control basic dataset, determines the corresponding flood magnitude and engineering scheduling scenario, including: The engineering design parameters of the design flood control height of the dikes and the maximum flood storage capacity of the reservoirs were extracted from the basic flood control dataset of the watershed, as well as the measured hydrological data of the peak flow and duration of historical floods. Based on the design flood control height of the engineering design parameters and combined with the peak flow of historical floods in the hydrological measurement data, different levels of flood volume are classified. Based on the maximum flood storage capacity of the reservoir according to the engineering design parameters, and combined with the number of days of historical floods in the hydrological measurement data, the engineering scheduling scenarios corresponding to different flood levels are determined.

5. The method for constructing a digital twin scenario for watershed flood control according to claim 4, characterized in that, When determining the corresponding flood magnitude: The statistical data of flood control in the basin is pre-set with historical flood measurement data, and the number of floods and peak flow are counted separately for spring, summer and autumn. Based on the engineering design parameters of the dike's designed flood control height and the reservoir's maximum flood storage capacity, the engineering bearing capacity corresponding to different flood peaks in each season is defined. The flood magnitude is divided into different levels according to the engineering load-bearing capacity from high to low, and the corresponding flood peak range and duration range are defined for each magnitude.

6. The method for constructing a digital twin scenario for watershed flood control according to claim 5, characterized in that, The specific engineering scheduling scenario is as follows: Analyze the engineering operation records under different flood scenarios in the basic flood control data of the watershed, and extract the correspondence between the opening degree of the dam and the river flow, and between the reservoir storage and the downstream water level; For each flood level, the initial opening angle of the dam and the initial discharge volume of the reservoir are set; According to the time sequence of flood evolution, the adjustment nodes of dam opening degree, the increase or decrease of reservoir discharge, and the conditions for the activation of flood diversion outlets are defined. The system detects the mutual influence between different scheduling projects, formulates linkage scheduling rules, and triggers the corresponding operations of related scheduling projects when the operating status of a certain scheduling project reaches a preset scheduling threshold, thus forming a complete project scheduling scenario process.

7. The method for constructing a digital twin scenario for watershed flood control according to claim 6, characterized in that, Step S3 involves performing flood evolution coupling calculations on the flood control simulation units of the watershed digital twin model based on flood magnitude and engineering scheduling scenarios, including: For different combinations of flood magnitude and engineering scheduling scenarios, the corresponding peak flood discharge and initial water level are input as boundary conditions into the watershed digital twin model; Based on the time sequence of flood evolution, the flood overflow process in the terrain is simulated. Combined with the opening of dams and the flood discharge operation of reservoirs in the engineering scheduling scenario, the changes in flood velocity and water depth in different areas are calculated. The flooding status of each flood control simulation unit is obtained by flood evolution calculation through the watershed digital twin model, and the flow and transfer of flood between different flood control simulation units is realized by flood exchange calculation through the watershed digital twin model, thus coupling the results of flood evolution coupling calculation.

8. The method for constructing a digital twin scenario for watershed flood control according to claim 1, characterized in that, In step S4, the watershed digital twin model with adjusted parameters is subjected to scene rendering processing, and the output dynamic twin scene analysis results include: Three-dimensional visualization technology is used to draw the scene of the watershed digital twin model after parameter adjustment, and the corresponding color gradient is set according to different inundation depth ranges to present the distribution of floods in the watershed; The system overlays real-time operational status indicators of flood control projects, using different icons to distinguish the opening and closing status of dams and the water storage capacity level of reservoirs. The system dynamically demonstrates the evolution of a flood at different points in time, marking the arrival time of the flood and the duration of inundation for each unit. By integrating the inundation range, water depth, and flow velocity of each flood control simulation unit, a flood risk level assessment table is generated.

9. A digital twin scenario construction system for watershed flood control, characterized in that, For implementing the digital twin scenario construction method for watershed flood control as described in claim 1, the digital twin scenario construction system for watershed flood control includes: The data acquisition module is used to collect watershed topographic data, hydrological data, and flood control engineering data. After correlation verification and standardization integration, it generates a basic dataset for watershed flood control. The digital twin modeling module is used to extract topographic correlation parameters and engineering layout information from the basic flood control dataset of the watershed, divide the flood control simulation units, and construct a digital twin model of the watershed. The flood scenario matching module is used to determine the corresponding flood magnitude and engineering scheduling scenario based on the engineering design parameters and hydrological measurement data in the basin flood control basic dataset; and to perform flood evolution coupling calculations on the flood control simulation units of the basin digital twin model based on the flood magnitude and engineering scheduling scenario. The watershed flood control adjustment module is used to collect watershed rainfall monitoring data and flood control project monitoring data in real time, dynamically adjust the flood evolution calculation parameters of each flood control simulation unit based on the watershed rainfall monitoring data and flood control project monitoring data, perform scene rendering processing on the watershed digital twin model after parameter adjustment, and output dynamic twin scene analysis results.

10. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed, implements the digital twin scenario construction method for watershed flood control as described in any one of claims 1-8.

Images