Water conservancy informatization management method and management system based on digital twinborn technology

Abstract

The invention relates to the technical field of water conservancy management, in particular to a water conservancy informatization management method and management system based on a digital twinborn technology. The method comprises the following steps: constructing a digital twin model covering a target area; multi-source data are collected in real time and synchronized with the model through an Internet of Things sensing network, remote sensing and other means; calculating regional flood storage capacity formed by soil water storage capacity, river channel tank storage capacity and surface water body regulation and storage capacity by utilizing the multi-source data; performing flood routing simulation deduction based on regional weather forecast and the flood storage capacity; and generating and issuing multi-level early warning according to prospective indexes such as the predicted flood storage capacity breakthrough time and the flooding range. According to the method, the problem that the prior art depends on static capacity evaluation and the early warning response is delayed is solved, the accuracy of flood forecasting and the advance of early warning are remarkably improved by dynamically and integrally quantifying the real flood receiving capacity of the region, and powerful scientific support is provided for accurate flood control decision making.

Description

Technical Field

[0001] This invention relates to the field of water conservancy management technology, specifically to a water conservancy information management method and system based on digital twin technology. Background Technology

[0002] Against the backdrop of global climate change and accelerated urbanization, extreme rainfall events are becoming more frequent, and floods have become one of the most widespread and devastating natural disasters. Therefore, establishing a precise and efficient flood early warning system is crucial. Traditional flood control systems mainly rely on physical engineering projects such as reservoirs and dikes to regulate surface water, combined with forecasts based on historical data or simplified models. However, these traditional methods have significant technical shortcomings: First, the assessment of a basin's flood storage capacity only considers fixed parameters such as reservoir design capacity and standard river flow capacity, neglecting key dynamic factors such as soil moisture content, leading to significant discrepancies between the assessment results and actual conditions. Second, early warning mechanisms often employ "threshold triggering," meaning that warnings are only issued after water levels at monitoring points exceed warning levels, resulting in a delayed response and extremely limited time windows for emergency response and evacuation.

[0003] To address these challenges, digital twin technology, as a cutting-edge method for mapping the physical world to the digital space, offers a new solution. Digital twins integrate technologies such as the Internet of Things (IoT), big data, and artificial intelligence to create a high-fidelity virtual copy of a physical entity. This virtual copy can reflect the real-time state of the physical entity and simulate and predict its behavior throughout its entire lifecycle. Combined with digital twin technology, it is possible to achieve real-time, dynamic, and holistic quantification of the comprehensive flood storage capacity of an entire catchment area, thereby enabling the issuance of more accurate and timely flood warnings. Summary of the Invention

[0004] To overcome the aforementioned deficiencies in the existing technology, this invention provides a water conservancy information management method and system based on digital twin technology.

[0005] This invention provides a water conservancy information management method based on digital twin technology, comprising the following steps: Acquire historical geographic information data, hydrological parameters, and infrastructure models for the target area; Based on the historical geographic information data, hydrological parameters, and infrastructure models, a digital twin model that is mapped to the target area in real time is constructed. By deploying a sensor network in the target area, real-time monitoring data of the target area is collected, and the real-time monitoring data is bidirectionally synchronized with the digital twin model; Based on the synchronized real-time monitoring data, the flood storage capacity of the target area at the current moment is calculated; Acquire rainfall forecast data for the region and use this rainfall forecast data as input. On the digital twin model, with the current flood storage capacity as the initial condition, drive the hydrological and hydrodynamic model to perform simulation and predict the hydrological state in the future time series. Based on the prediction results obtained from the simulation, a corresponding flood warning signal is generated according to a set of predefined predictive triggering criteria, and then released to the target users through multiple channels. The flood storage capacity is calculated using the following formula: ; In the formula, for The flood storage capacity of the target area at all times. for The remaining rain-holding capacity of the soil in the target area at any given time. for The remaining water level in the river channel safety reservoir in the target area at any given time. for Available flood storage capacity in the target area at any given time.

[0006] Preferably, the real-time monitoring data includes: river water level and flow velocity data collected by IoT sensors, soil saturation data collected by soil moisture sensors, and vegetation cover and surface water range data interpreted from remote sensing satellite images.

[0007] Preferably, the method for calculating the remaining rainwater carrying capacity of the soil is as follows: Acquire soil type data within the target area and determine the saturated water content of different soil types; The soil plots in the target area are discretized into multiple soil units, and the soil moisture data of each soil unit is determined based on the soil saturation data collected by the soil moisture sensor. Based on the soil moisture data and saturated water content data of each soil unit, the remaining rainwater carrying capacity of the soil in the area is calculated. The formula for calculating the remaining rainwater carrying capacity of the soil is as follows: ; In the formula, Number the discretized soil units within the target area. The number of soil units within the target area. For unit saturated water content, for Time unit The moisture content, For unit Soil layer thickness, For unit The area.

[0008] Preferably, the soil plots in the target area are discretized into multiple soil units, each soil unit belonging to the same soil type.

[0009] Preferably, the method for calculating the remaining capacity of the river safety channel is as follows: Discretize the river network system of the target area into a sequence of multiple river segments; For each individual river segment, obtain its levee safety water level and cross-sectional geometry information; The safe water passage cross-sectional area corresponding to the water level is determined based on the safe water level and cross-sectional geometric information of the dike. Based on the river water level data collected by IoT sensors, the real-time water level data of each river section is determined. Based on the real-time water level of each river section and the cross-sectional geometric information, the real-time cross-sectional area of ​​the water passage at the current moment is calculated. The difference between the safe cross-sectional area and the real-time cross-sectional area of ​​each river section is taken as the safe storage capacity of that river section. The safe storage capacity of the river channel in the target area is determined based on the safe storage capacity of each river section. The formula for calculating the remaining capacity of the river safety channel is as follows: ; In the formula, Number the discrete river segments within the target area. The number of river sections For river section The safe cross-sectional area for water passage. For river section In time The real-time cross-sectional area of ​​the water flow. For river section The length.

[0010] Preferably, the method for calculating the available flood storage capacity is as follows: Acquire information on all natural and artificial water bodies with water storage functions within the target area, including water level-storage capacity relationship curves, flood control limit water levels and their corresponding flood control storage capacities; For each water storage body, the real-time reservoir capacity at the current moment is obtained based on its real-time water level and the water level-reservoir capacity relationship curve. The difference between the flood control capacity and the real-time capacity of a water body is taken as the available flood storage capacity of that water body. The available flood storage capacity of all regulating water bodies is summed to obtain the available flood storage capacity within the target area.

[0011] Preferably, the step of using the current flood storage capacity as the initial condition to drive the hydrological and hydrodynamic model to simulate and extrapolate the flood evolution process and predict the hydrological state of the catchment area in future time series specifically includes: The rainfall forecast data is used as input to the hydrological and hydrodynamic model; Based on the flood storage capacity, the initial soil moisture content of each surface unit and the initial water level of each river section and water body are determined as the initial boundary conditions of the hydrological and hydrodynamic model. Using the hydrological and hydrodynamic model, the water balance equation and fluid dynamics equation are solved step by step within the forecast period to obtain the hydrological state parameters of each computational grid or cross section in the future time series. The parameters include water level, flow velocity, inundation range and inundation depth.

[0012] Preferably, the predefined predictive triggering criteria include: the remaining time before the basin's comprehensive dynamic flood storage capacity is completely exhausted, and the predicted flood inundation range and depth.

[0013] In another aspect, the present invention provides a water conservancy information management system based on digital twin technology, including a data acquisition and synchronization module, a digital twin model module, an evaluation and simulation module, and an early warning generation module; The data acquisition and synchronization module is used to acquire real-time monitoring data from the target area and synchronize it bidirectionally with a digital twin model. The digital twin model module is used to store a digital twin model that is mapped to the target area in real time; The evaluation and simulation module is connected to the data acquisition and synchronization module and the digital twin model module, and includes: The assessment unit is used to calculate the flood storage capacity of the target area at the current moment based on the synchronized real-time monitoring data; The simulation and deduction unit is used to drive the hydrological and hydrodynamic model to simulate the flood evolution process on the digital twin model, using rainfall forecast data as input and the flood storage capacity as initial conditions. The early warning generation module is connected to the evaluation and simulation module and is used to generate and issue multi-level flood early warning signals based on the prediction results of the simulation and a set of predefined predictive triggering criteria.

[0014] Compared with the prior art, the advantages of this invention are: By integrating the capacities of multiple dynamically changing subsystems such as soil and river channels in real time, the assessment of the current flood carrying capacity of the basin is transformed from post-hoc statistics and static estimation to real-time, dynamic, and precise quantification, thereby improving the accuracy of the initial conditions for flood forecasting.

[0015] By extrapolating from a digital twin model, this invention can not only predict the probability of flooding but also display the evolution of floods, including key information such as inundation extent, water depth, and arrival time. This visualized risk assessment provides a scientific and intuitive decision support platform for the development of emergency plans.

[0016] Furthermore, the scheme employs an early warning mechanism combining "predictive simulation" and "proactive triggering criteria," which simulates the entire flood process before rainfall occurs, based on forecasts and the actual flood storage capacity of the basin. This significantly shortens the early warning issuance time, providing valuable time for disaster prevention and mitigation decisions and the safe evacuation of people. Attached Figure Description

[0017] Figure 1 This is a flowchart of a water conservancy information management method based on digital twin technology proposed in this invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0019] refer to Figure 1 This invention describes a water conservancy information management method based on digital twin technology.

[0020] S1. Obtain historical geographic information data, hydrological parameters, and infrastructure models of the target area, and construct a digital twin model that is mapped to the target area in real time based on the historical geographic information data, hydrological parameters, and infrastructure models.

[0021] The historical geographic information data includes high-precision digital elevation models (DEM), digital surface models (DSM), as well as river network vector data, soil type distribution maps, geological structure maps, etc.

[0022] The infrastructure model is a building information model, which includes information such as the geometric dimensions, materials, design parameters, and control operation rules of key water conservancy projects such as reservoirs, dikes, gates, pumping stations, and bridges.

[0023] The constructed digital twin model includes: Geometric Model: Based on data such as DEM, BIM, and oblique photography, a three-dimensional visualization scene of the watershed is constructed to achieve a 1:1 realistic reproduction of the physical world.

[0024] Physical model: Encapsulate the mechanistic models describing hydrophysical processes (such as runoff generation and confluence models and soil erosion models) into digital components and assign the correct physical parameters (such as roughness and infiltration rate) to the models.

[0025] Behavioral Model: Defines the scheduling and operation rules of water conservancy projects (such as reservoirs and gates), such as the automatic gate opening logic based on upstream water inflow and downstream water level.

[0026] S2. Collect real-time monitoring data of the target area through a sensor network deployed in the target area, and synchronize the real-time monitoring data bidirectionally with the digital twin model.

[0027] The sensor network includes, but is not limited to, ultrasonic or radar water level gauges and flow meters installed at key sections of rivers and reservoirs; automatic rain gauges distributed throughout the watershed; and soil moisture sensors buried at different depths and under different land use types. These sensors transmit data to the data center in real time via wireless communication technologies such as 5G and NB-IoT.

[0028] In addition, the monitoring data also includes high-resolution satellite remote sensing images (optical and radar) used to interpret the extent of surface water bodies and invert regional soil moisture.

[0029] S3. Based on the synchronized real-time monitoring data, calculate the flood storage capacity of the target area at the current moment, specifically as follows: S301. Calculate the remaining rainwater carrying capacity of the soil in the area: Based on the soil type distribution map, determine the soil type data within the region and determine the saturated water content of different soil types.

[0030] The soil plots in the area were discretized into multiple soil units, and the soil moisture data of each soil unit was determined based on the soil saturation data collected by the soil moisture sensor.

[0031] Based on the soil moisture data and saturated water content data of each soil unit, the remaining rainwater carrying capacity of the soil in this area is calculated: ; In the formula, Number the discrete soil units within this region. This represents the number of soil units within the region. For unit saturated water content, for Time unit The moisture content, For unit Soil layer thickness, For unit The area.

[0032] It should be noted that each soil unit in the above division belongs to the same soil type.

[0033] S302. Calculate the remaining capacity of the safety channel in the river area: The river network system in this region is discretized into a sequence of multiple river segments.

[0034] For each individual river segment, obtain its levee safety water level and cross-sectional geometry information.

[0035] The safe water passage area corresponding to the water level is determined based on the safe water level and cross-sectional geometry information of the dike.

[0036] Based on the river water level data collected by IoT sensors, the real-time water level data of each river section is determined.

[0037] Based on the real-time water level of each river section and the cross-sectional geometric information, the real-time cross-sectional area of ​​the water passage at the current moment is calculated.

[0038] The difference between the safe cross-sectional area and the real-time cross-sectional area of ​​each river section is taken as the safe storage capacity of that river section.

[0039] The safety channel reserve in this area is determined based on the safety channel reserve of each river section: ; In the formula, The discrete river segments within this region are numbered. The number of river sections For river section The safe cross-sectional area for water passage. For river section In time The real-time cross-sectional area of ​​the water flow. For river section The length.

[0040] It should be noted that the specific method for calculating the cross-sectional area of ​​the water passage is as follows: Obtain the geometric data of the river channel cross-section, defined by a digital elevation model and consisting of a series of "horizontal station-elevation" coordinate points; then, combining the water level data, calculate the area below the water surface line and above the cross-sectional outline using numerical integration methods (such as the trapezoidal rule). This area is the cross-sectional area of ​​the water passage. The specific calculation formula is as follows: ; In the formula, For river section The cross-sectional area of ​​the water passage, and The horizontal station coordinates of two adjacent measurement points. and These represent the current underwater depths of these two points.

[0041] S303. Available flood storage capacity within the calculation area: Acquire information on all natural and artificial water bodies with water storage functions within the region. This information includes water level-storage capacity curves, flood control limit water levels, and their corresponding flood control storage capacities.

[0042] For each water storage body, the real-time reservoir capacity is obtained based on its current real-time water level and the water level-reservoir capacity relationship curve.

[0043] The difference between the flood control capacity and the real-time capacity of a water body is taken as the available flood storage capacity of that water body.

[0044] The available flood storage capacity of the region is obtained by summing the available flood storage capacity of all regulating water bodies.

[0045] S304. Based on the above calculations of the remaining rainwater carrying capacity of the soil in the region, the remaining capacity of the river safety channel, and the available flood storage capacity, calculate the region's flood storage capacity: ; In the formula, for The flood storage capacity of the area at any given time. for At any given time, the remaining rainwater carrying capacity of the soil in this area for The current water level in the river channel safety reservoir in this area. for The available flood storage capacity in the area at any given time.

[0046] S4. Obtain rainfall forecast data for the region, and use this rainfall forecast data as input. On the digital twin model, with the current flood storage capacity as the initial condition, drive the hydrological and hydrodynamic model to perform simulation and predict the hydrological state in the future time series. Specifically: First, a hydrological and hydrodynamic model is integrated or coupled into the digital twin model. Then, quantitative precipitation forecasts from meteorological departments are used as input to the hydrological and hydrodynamic model, while the calculated flood storage capacity is decomposed into initial conditions for each computational unit (such as initial soil moisture content and initial river level), serving as the initial boundary conditions for the model. Next, the coupled model is driven to perform calculations simulating the generation and confluence of rainfall at the surface, as well as the evolution of floods in the river channel. Finally, the predicted hydrological status of the entire basin at a series of future time points is output, including but not limited to water levels and discharges at key cross-sections, as well as the extent and depth of potential inundation zones.

[0047] S5. Based on the prediction results obtained from the simulation, generate corresponding flood warning signals according to a set of predefined predictive triggering criteria, and release them to target users through multiple channels.

[0048] For example, if the simulation results show that "the comprehensive dynamic flood storage capacity of the basin will be exceeded within 12 hours, and the predicted inundation area will affect residential area A," the system will automatically trigger an orange alert. The alert information (including the alert level, expected impact time, impact area, and defense recommendations) will be pushed to emergency management personnel and the public in the affected area through a unified release gateway in various forms such as SMS, mobile APP push, social media, and emergency broadcasts.

[0049] To realize the above-mentioned water conservancy information management method based on digital twin technology, a water conservancy information management system based on digital twin technology is provided, including a data acquisition module and synchronization module, a digital twin model module, an evaluation and simulation module, and an early warning generation module; The data acquisition and synchronization module is used to acquire real-time monitoring data from the target area and synchronize it bidirectionally with a digital twin model. The digital twin model module is used to store a digital twin model that is mapped to the target area in real time; The evaluation and simulation module is connected to the data acquisition and synchronization module and the digital twin model module, and includes: The assessment unit is used to calculate the flood storage capacity of the target area at the current moment based on the synchronized real-time monitoring data; The simulation and deduction unit is used to drive the hydrological and hydrodynamic model to simulate the flood evolution process on the digital twin model, using rainfall forecast data as input and the flood storage capacity as initial conditions. The early warning generation module is connected to the evaluation and simulation module and is used to generate and issue multi-level flood early warning signals based on the prediction results of the simulation and a set of predefined predictive triggering criteria.

[0050] In a preferred embodiment, the method further includes a model self-optimization step, specifically: after the conclusion of an actual flood event, automatically collect the entire process of measured data (such as water level hydrographs at various monitoring points, final inundation range, etc.). Then, compare these measured data with the predictions made in advance by simulation, and calculate the error. Finally, using artificial intelligence algorithms (such as genetic algorithms, deep reinforcement learning, etc.), with the goal of minimizing the prediction error, automatically adjust the key parameters in the hydrological and hydrodynamic model (such as the Manning roughness coefficient, soil infiltration parameters, etc.), and update the optimized parameters in the model library for use in the next prediction.

[0051] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0052] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A water conservancy informatization management method based on digital twin technology, characterized in that, The method comprises the following steps: obtaining historical geographic information data, hydrological parameters and infrastructure models of a target area; constructing a digital twin model mapped in real time with the target area based on the historical geographic information data, hydrological parameters and infrastructure models; collecting real-time monitoring data of the target area through a sensing network deployed in the target area, and synchronizing the real-time monitoring data with the digital twin model bidirectionally; calculating the flood storage capacity of the target area at the current time based on the synchronized real-time monitoring data; obtaining rainfall forecast data of the area, and inputting the rainfall forecast data to drive a hydrological and hydrodynamic model on the digital twin model to simulate and deduce the hydrological state at a future time sequence with the flood storage capacity at the current time as an initial condition; generating a corresponding flood warning signal based on a set of predefined predictive trigger criteria according to the prediction result obtained through the simulation and deduction, and publishing the flood warning signal to target users through multiple channels; the flood storage capacity is calculated by the following formula: ； wherein, is the flood storage capacity of the target area at the time, is the soil residual rainwater storage capacity of the target area at the time, is the riverway safety groove residual storage of the target area at the time, is the available flood storage capacity of the target area at the time.

2. The water conservancy informatization management method based on digital twin technology according to claim 1, characterized in that, the real-time monitoring data includes river water level and flow rate data collected by Internet of Things sensors, soil saturation data collected by soil moisture sensors, and vegetation coverage and surface water range data interpreted from remote sensing satellite images.

3. The water conservancy informatization management method based on digital twin technology according to claim 1, characterized in that, The calculation method of the residual rainfall capacity of the soil is as follows: obtaining soil type data in the target area and determining the saturated water content of different soil types; discretizing the soil plots of the target area into a plurality of soil units, and determining the soil moisture data of each soil unit according to the soil saturation data collected by the soil moisture sensors; calculating the residual rainfall capacity of the soil in the target area based on the soil moisture data of each soil unit and the saturated water content data of the soil unit; the calculation formula of the residual rainfall capacity of the soil is as follows: ； In the formula, Number the discretized soil units within the target area. The number of soil units within the target area. For unit saturated water content, for Time unit The moisture content, For unit Soil layer thickness, For unit The area.

4. The water conservancy informatization management method based on digital twin technology according to claim 3, characterized in that, the soil plots of the target area are discretized into a plurality of soil units, and each soil unit belongs to the same type of soil.

5. The water conservancy informatization management method based on digital twin technology according to claim 1, characterized in that, The calculation method of the residual storage capacity of the river safety tank is as follows: discretizing the river network system of the target area into a sequence composed of a plurality of river sections; for each individual river section, obtaining its dike safety water level and cross section geometric information; determining the safety cross section area corresponding to the water level according to the dike safety water level and cross section geometric information; determining the real-time water level data of each river section according to the river water level data collected by the Internet of Things sensors; calculating the real-time cross section area at the current time according to the real-time water level of each river section and the cross section geometric information; taking the difference between the safety cross section area and the real-time cross section area of each river section as the safety tank residual storage capacity of the river section; determining the river safety tank residual storage capacity of the target area based on the safety tank residual storage capacities of the river sections; the calculation formula of the river safety tank residual storage capacity is as follows: ； In the formula, Number the discrete river segments within the target area. The number of river sections River section The safe cross-sectional area for water passage. River section In time The real-time cross-sectional area of ​​the water flow. River section The length.

6. The water conservancy informatization management method based on digital twin technology according to claim 1, characterized in that, The calculation method of the available flood storage capacity is as follows: obtaining information of all natural and artificial water bodies with storage function in the target area, the information including water level-storage capacity relationship curve, flood control limiting water level and corresponding flood control storage capacity; for each storage water body, obtaining the real-time storage capacity at the current time according to the real-time water level at the current time and the water level-storage capacity relationship curve; The difference between the flood control capacity of the water body and the real-time capacity is used as the available flood storage capacity of the water body. The available flood storage capacities of all the water bodies are summed up to obtain the available flood storage capacity in the target region.

7. The water conservancy informatization management method based on digital twin technology according to claim 1, characterized in that, The flood storage capacity at the current time is used as an initial condition to drive a hydrological and hydrodynamic model to simulate and deduce the flood evolution process, and to predict the hydrological state of the catchment area at a future time sequence, which specifically includes: The rainfall prediction data is used as the input of the hydrological and hydrodynamic model; Based on the flood storage capacity, the initial soil moisture content of each surface unit and the initial water level of each river section and water body are determined as the initial boundary conditions of the hydrological and hydrodynamic model; The hydrological and hydrodynamic model is used to solve the water balance equation and the fluid dynamics equation at each time step in the prediction period to obtain the hydrological state parameters of each calculation grid or section at a future time sequence, including water level, flow rate, flooded area and flooded water depth.

8. The water conservancy informatization management method based on digital twin technology according to claim 1, characterized in that, The predefined predictive trigger criteria include the remaining time for the predicted comprehensive dynamic flood storage capacity of the basin to be completely exhausted, and the predicted flood inundation area and depth.

9. A water conservancy informatization management system based on digital twin technology, used to implement a water conservancy informatization management method based on digital twin technology as claimed in claims 1-8, characterized in that, The system comprises a data acquisition and synchronization module, a digital twin model module, an evaluation and simulation module, and an early warning generation module. The data acquisition and synchronization module is used to acquire real-time monitoring data from the target region and to synchronize with a digital twin model in both directions. The digital twin model module is used to store a digital twin model that is real-time mapped with the target region. The evaluation and simulation module is connected with the data acquisition and synchronization module and the digital twin model module, and comprises: An evaluation unit is configured to calculate the flood storage capacity of the target region at the current time based on the synchronized real-time monitoring data. A simulation and deduction unit is configured to drive a hydrological and hydrodynamic model on the digital twin model to simulate the flood evolution process based on rainfall prediction data as input and the flood storage capacity as an initial condition. The early warning generation module is connected with the evaluation and simulation module and is configured to generate and issue multi-level flood warning signals based on a set of predefined predictive trigger criteria according to the prediction results of the simulation and deduction.

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