A debris flow early warning and adaptive protection system

Abstract

The present application provides a kind of debris flow early warning and adaptive protection system, it is related to disaster warning technical field, system includes: drainage basin stereoscopic monitoring network, for obtaining the multi-source monitoring data of monitoring area;Early warning and analysis platform, for early warning analysis according to the multi-source monitoring data, generates early warning level;Also for when the early warning level is action level, generate debris flow prediction scale parameter, and according to the debris flow prediction scale parameter and the operating state of the monitoring area, simulation is carried out, generates debris flow influence simulation parameter;Adaptive protection decision and execution subsystem, for generating and executing protection strategy according to protection plan base and the debris flow influence simulation parameter, wherein, the protection plan base is based on the construction of special research results.The present application can comprehensively collect the multi-dimensional monitoring information of debris flow prevention and control area, simulation result is accurate, also solves the pain point that present technical special research results are idle, protection decision lacks quantitative basis and is passive response.

Description

Technical Field

[0001] This invention relates to the field of disaster early warning technology, and more specifically, to a debris flow early warning and adaptive protection system. Background Technology

[0002] Debris flows are sudden geological disasters unique to mountainous areas. They are triggered by water sources such as torrential rains and snowmelt, forming viscous, high-speed torrents carrying large amounts of solid materials such as mud, sand, and rocks. They are characterized by their suddenness, high velocity, great destructive power, and short duration, often destroying buildings, burying villages and towns, and silting up reservoirs and river channels, seriously threatening the safety of mountain residents and the operation of water conservancy projects and transportation facilities. Especially during reservoir operation, debris flows erupting in tributaries upstream of hydropower dams pose a significant safety hazard, rapidly silting up reservoir capacity, raising water levels, and blocking intakes, threatening the safety of the dam. Furthermore, the sudden entry of debris flows carrying large amounts of solid material into the reservoir can quickly silt up the effective reservoir capacity (especially in medium and small reservoirs or river-type reservoirs), raise local or even overall reservoir water levels, and may block power station intakes or spillway structures, directly affecting the operational safety and efficiency of the dam.

[0003] In related technologies, for debris flow prevention in the upstream area of ​​reservoirs of water conservancy and hydropower projects, the traditional process of first surveying, then designing, and then constructing is followed. Special studies require large investments and have long cycles. The results are archived in the form of paper reports or static databases, which are completely disconnected from the reservoir scheduling system. At the same time, there are five major defects: passive engineering management, reliance on experience for operational avoidance, isolated early warning system, lagging decision-making tools, and idle special study results. Overall, it presents problems of passive defense, delayed response, and qualitative decision-making. Summary of the Invention

[0004] The present invention aims to solve at least one of the above-mentioned problems.

[0005] To address the above problems, this invention provides a debris flow early warning and adaptive protection system, comprising: A three-dimensional watershed monitoring network is used to acquire multi-source monitoring data for the monitoring area; The early warning and analysis platform is used to perform early warning analysis based on the multi-source monitoring data and generate early warning levels; it is also used to generate debris flow prediction scale parameters when the early warning level is action level, and to perform simulation based on the debris flow prediction scale parameters and the operating status of the monitoring area to generate debris flow impact simulation parameters. An adaptive protection decision-making and execution subsystem is used to generate and execute protection strategies based on the protection plan library and the debris flow impact simulation parameters, wherein the protection plan library is constructed based on the results of special research.

[0006] Optionally, the watershed three-dimensional monitoring network includes: The space-based monitoring unit is used to acquire satellite remote sensing data from the multi-source monitoring data. An airborne monitoring unit is used to acquire terrain image data from the multi-source monitoring data via a drone. The ground monitoring unit is used to acquire rainfall data, ground acoustic data, video data, and radar data from the multi-source monitoring data.

[0007] Optionally, the ground monitoring unit is deployed based on the findings of the thematic research and includes: An array of rain gauges deployed in the upper and middle reaches of the gullies in the monitoring area is used to acquire the rainfall data; Ground acoustic sensors deployed in the circulation area of ​​the monitoring area are used to acquire the ground acoustic data; A video and radar flow measurement device is deployed at the entrance of the monitoring area to acquire the video data and the radar data.

[0008] Optionally, the early warning and analysis platform includes: The integrated early warning module is used to perform early warning analysis based on the multi-source monitoring data, generate the early warning level, and generate the debris flow prediction scale parameter when the early warning level is action level. The rapid simulation module is used to simulate the debris flow impact parameters based on the debris flow prediction scale parameters and the operational status of the monitoring area when the warning level is action level.

[0009] Optionally, the debris flow prediction scale parameters include: peak debris flow rate, total debris flow volume, and debris flow unit weight. The fusion early warning module is specifically used for: Based on the multi-source monitoring data and the disaster thresholds in the thematic research results, an early warning analysis is performed to generate the early warning level; When the warning level is action level, the peak flow rate of the debris flow is generated based on the multi-source monitoring data and regression model, the total debris flow volume is generated based on the multi-source monitoring data and relationship model, and the bulk density value of the debris flow is generated based on the multi-source monitoring data and / or the bulk density benchmark value of the debris flow. The regression model, the relationship model, and the bulk density value of the debris flow are all determined by the results of the special research.

[0010] Optionally, the fast simulation module includes: A terrain model is used to generate a three-dimensional terrain mesh based on the watershed terrain data of the monitoring area described in the thematic research results when the warning level is action level. A hydrodynamic model is used to generate hydrodynamic parameters for the monitoring area based on the three-dimensional terrain grid, the debris flow prediction scale parameters, and the operational status of the monitoring area. A sediment transport model is used to generate sedimentation morphology parameters based on the aforementioned hydrodynamic conditions. A structural impact model is used to generate simulation parameters of the debris flow impact based on the sedimentation morphology parameters.

[0011] Optionally, the adaptive protection decision and execution subsystem includes: The protection plan database is used to store digital protection plans from the research findings of the aforementioned topic; The decision-making module is used to generate the protection strategy based on the digital protection plan and the debris flow impact simulation parameters; The execution module is used to convert the protection strategy into control commands and send them to the control system of the monitoring area.

[0012] Optionally, the decision module is specifically used for: The risk level is determined based on the safety thresholds in the aforementioned research findings and the debris flow impact simulation parameters. When the risk level is low, the first plan in the digital protection plan will be used as the protection strategy.

[0013] Optionally, the decision module is further configured to: When the risk level is medium risk, the protection strategy is generated by performing multi-objective optimization calculations based on the second plan in the digital protection plan and according to the optimization objectives. When the risk level is high, the protection strategy is generated based on the third plan in the digital protection plan and multi-objective optimization calculation according to the optimization objectives.

[0014] Optionally, the watershed three-dimensional monitoring network is also used for: Obtain the actual status data of the monitoring area after the protection strategy is implemented; The early warning and analysis platform is also used for: When the actual state data and the debris flow impact simulation parameters exceed a preset threshold, new debris flow impact simulation parameters are generated. The adaptive protection decision and execution subsystem is also used for: Based on the new debris flow impact simulation parameters, the protection strategy is adjusted, and a new protection strategy is generated and implemented.

[0015] The beneficial effects of the debris flow early warning and adaptive protection system of the present invention are: The watershed three-dimensional monitoring network acquires multi-source monitoring data from the monitoring area. Compared with the single and isolated monitoring methods of existing technologies, it can comprehensively collect multi-dimensional monitoring information of the debris flow prevention and control area, laying a comprehensive and accurate data foundation for subsequent early warning analysis and simulation work. The early warning and analysis platform conducts early warning analysis based on multi-source monitoring data to generate early warning levels and debris flow prediction scale parameters. Then, it combines the early warning level, debris flow prediction scale parameters, and the operational status of the monitoring area to complete the simulation and generate debris flow impact simulation parameters. This solves the problems of existing technologies such as single early warning models, delayed simulation response, and inability to quantitatively extrapolate disaster impacts based on real-time operational status, achieving precise linkage between early warning analysis and impact simulation. The adaptive protection decision and execution subsystem builds a protection plan library based on the results of special research, and generates and executes protection strategies based on debris flow impact simulation parameters. This solves the pain points of existing technologies such as idle special research results, lack of quantitative basis for protection decisions, and passive response. It makes the generation of protection strategies more targeted and the execution more effective, realizing precise protection decision-making and implementation based on special research results and real-time simulation data. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the debris flow early warning and adaptive protection system provided in an embodiment of the present invention. Detailed Implementation

[0017] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0018] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0019] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; and the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first," "second," etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0020] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0021] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0022] like Figure 1 As shown in the figure, an embodiment of the present invention provides a debris flow early warning and adaptive protection system, comprising: A three-dimensional watershed monitoring network is used to acquire multi-source monitoring data for the monitoring area.

[0023] Specifically, the basin-wide three-dimensional monitoring network, as the front-end data acquisition component of the debris flow early warning and adaptive protection system, conducts comprehensive and real-time data acquisition across the debris flow monitoring area. It acquires multi-dimensional, multi-type, and multi-source monitoring data, providing fundamental data support for subsequent early warning analysis, simulation prediction, and protection strategy execution. The deployment and data acquisition of the monitoring network are both centered on the core needs of debris flow disaster prevention and control in the monitoring area, ensuring the integrity and real-time nature of the collected data. For example, the monitoring area can broadly cover the entire basin of tributaries upstream of hydropower hubs, including the sediment source formation area, midstream flow area, and reservoir accumulation area at the gully mouth, as well as the core safety control areas of the hub, such as the area in front of the reservoir dam, the power station intake, and the area surrounding the spillway structures. Simultaneously, it can be extended to adapt to the upstream debris flow gully basins of small and medium-sized reservoirs, river-type reservoirs, and tailings ponds in high mountain and canyon areas. It can also be applied to various reservoirs and hydropower station reservoir areas and surrounding tributary basins with the risk of debris flow into the reservoir, comprehensively covering debris flow disaster monitoring scenarios with different topographical features, reservoir capacity, and engineering types.

[0024] The early warning and analysis platform is used to perform early warning analysis based on the multi-source monitoring data and generate early warning levels; it is also used to generate debris flow prediction scale parameters when the early warning level is action level, and to perform simulation based on the debris flow prediction scale parameters and the operating status of the monitoring area to generate debris flow impact simulation parameters.

[0025] Specifically, the early warning and analysis platform receives multi-source monitoring data transmitted from the basin's three-dimensional monitoring network, processes and analyzes the data based on its built-in analysis logic, completes early warning analysis and generates corresponding early warning levels, and calculates debris flow prediction scale parameters by combining monitoring data with a disaster correlation model when the early warning level is action level. The platform retrieves the current real-time operating status data of the monitoring area, uses the debris flow prediction scale parameters and operating status data as simulation input conditions, completes debris flow impact simulation through simulation calculations, and finally outputs debris flow impact simulation parameters that reflect the disaster impact.

[0026] An adaptive protection decision-making and execution subsystem is used to generate and execute protection strategies based on the protection plan library and the debris flow impact simulation parameters, wherein the protection plan library is constructed based on the results of special research.

[0027] Specifically, the adaptive protection decision and execution subsystem calls a protection plan library built in advance based on the research results of debris flow. It compares the debris flow impact simulation parameters output by the early warning and analysis platform with the plan matching rules in the protection plan library. Through intelligent matching and calculation, it generates a protection strategy that is suitable for the current disaster scenario. Then, it converts the protection strategy into an executable control command and sends it to the corresponding control equipment in the monitoring area to complete the protection action, thereby realizing adaptive protection against debris flow disasters.

[0028] In this embodiment, the watershed three-dimensional monitoring network acquires multi-source monitoring data of the monitoring area. Compared with the single and isolated monitoring methods of existing technologies, it can comprehensively collect multi-dimensional monitoring information of the debris flow prevention and control area, laying a comprehensive and accurate data foundation for subsequent early warning analysis and simulation work. The early warning and analysis platform conducts early warning analysis based on multi-source monitoring data to generate early warning levels and debris flow prediction scale parameters. Then, it combines the early warning level, debris flow prediction scale parameters, and the operational status of the monitoring area to complete the simulation and generate debris flow impact simulation parameters. This solves the problems of existing technologies having single early warning models, lagging simulation response, and the inability to quantitatively extrapolate disaster impacts based on real-time operational status, and achieves precise linkage between early warning analysis and impact simulation. The adaptive protection decision and execution subsystem builds a protection plan library based on the results of special research, and generates and executes protection strategies based on debris flow impact simulation parameters. This solves the pain points of existing technologies such as idle special research results, lack of quantitative basis for protection decisions, and passive response. It makes the generation of protection strategies more targeted and the execution more effective, and achieves precise protection decision-making and implementation based on special research results and real-time simulation data.

[0029] Optionally, such as Figure 1 As shown, the watershed three-dimensional monitoring network includes: The space-based monitoring unit is used to acquire satellite remote sensing data from the multi-source monitoring data. An airborne monitoring unit is used to acquire terrain image data from the multi-source monitoring data via a drone. The ground monitoring unit is used to acquire rainfall data, ground acoustic data, video data, and radar data from the multi-source monitoring data.

[0030] Specifically, the basin-wide integrated monitoring network is composed of space-based monitoring units, airborne monitoring units, and ground-based monitoring units working together. The space-based monitoring units are responsible for collecting satellite remote sensing data from multi-source monitoring data, obtaining comprehensive environmental data such as vegetation cover and soil moisture in the monitored area through satellite remote sensing. The airborne monitoring units use drones equipped with image acquisition equipment to collect topographic image data from multi-source monitoring data, obtaining high-precision topographic and image information of gullies and loose debris source areas. The ground-based monitoring units collect rainfall data, ground acoustic data, video data, and radar data from multi-source monitoring data. The three types of units achieve three-dimensional acquisition of multi-source monitoring data from space, air, and ground, with strong data complementarity, comprehensively covering key monitoring elements of debris flow initiation and disaster formation.

[0031] Optionally, such as Figure 1 As shown, the ground monitoring unit is deployed based on the findings of the aforementioned thematic research and includes: An array of rain gauges deployed in the upper and middle reaches of the gullies in the monitoring area is used to acquire the rainfall data; Ground acoustic sensors deployed in the circulation area of ​​the monitoring area are used to acquire the ground acoustic data; A video and radar flow measurement device is deployed at the entrance of the monitoring area to acquire the video data and the radar data.

[0032] Specifically, the deployment location, equipment selection, and threshold settings of the ground monitoring units are all based on the findings of the debris flow research project. Rain gauge arrays are deployed in key sections of the upper and middle reaches of the gullies in the monitoring area to collect rainfall data of the gully basin in real time. The deployment density and location of the rain gauge arrays are determined in conjunction with the source distribution and critical rainfall intensity influence range in the research project. Ground acoustic sensors or infrasound sensors are deployed in the debris flow flow area of ​​the monitoring area to accurately collect ground acoustic or infrasound data generated by debris flow movement. The sensor identification parameters are set according to the debris flow movement spectrum in the research project. Video and radar flow measurement devices are deployed at the debris flow inlet in the monitoring area to collect video data of fluid movement at the inlet and radar data such as flow rate and velocity in real time. The ground monitoring units are deeply integrated with the research project results to ensure that the collected data can accurately reflect the core characteristics of debris flow disasters.

[0033] Optionally, such as Figure 1 As shown, the early warning and analysis platform includes: The integrated early warning module is used to perform early warning analysis based on the multi-source monitoring data, generate the early warning level, and generate the debris flow prediction scale parameter when the early warning level is action level. The rapid simulation module is used to simulate the debris flow impact parameters based on the debris flow prediction scale parameters and the operational status of the monitoring area when the warning level is action level.

[0034] Specifically, the early warning and analysis platform consists of a fusion early warning module and a rapid simulation module. The fusion early warning module receives multi-source monitoring data and performs early warning analysis, generating three early warning levels: attention level, alert level, and action level. Only when the early warning level is action level does the fusion early warning module initiate calculations to generate debris flow prediction parameters. The rapid simulation module is activated only when the early warning level is action level. It receives the debris flow prediction parameters output by the fusion early warning module, simultaneously retrieves real-time operational status data of the monitored area, performs rapid simulation calculations, and generates debris flow impact simulation parameters. The two modules have clearly defined roles and share data, achieving an orderly connection between early warning and simulation, and improving the system's emergency response efficiency.

[0035] Optionally, the debris flow prediction scale parameters include: peak debris flow rate, total debris flow volume, and debris flow unit weight. The fusion early warning module is specifically used for: Based on the multi-source monitoring data and the disaster thresholds in the thematic research results, an early warning analysis is performed to generate the early warning level; When the warning level is action level, the peak flow rate of the debris flow is generated based on the multi-source monitoring data and regression model, the total debris flow volume is generated based on the multi-source monitoring data and relationship model, and the bulk density value of the debris flow is generated based on the multi-source monitoring data and / or the bulk density benchmark value of the debris flow. The regression model, the relationship model, and the bulk density value of the debris flow are all determined by the results of the special research.

[0036] Specifically, the debris flow prediction scale parameters include peak debris flow rate, total debris flow volume, and debris flow bulk density. The fusion early warning module compares multi-source monitoring data with disaster thresholds in the thematic research results to complete early warning analysis and generate corresponding early warning levels. When only a single monitoring data point is close to the disaster threshold, for example, rainfall is close to the rainfall disaster threshold, a level of concern is generated, and the response strategy is to strengthen monitoring. When multiple monitoring data points are close to the threshold, for example, rainfall exceeds the rainfall threshold and the ground sound signal feature matching degree is greater than the ground sound disaster threshold, a level of alert is generated, and the response strategy is to prepare for emergency response. When multiple monitoring data points reach critical conditions, for example, rainfall exceeds the rainfall disaster threshold, the ground sound signal feature matching degree is greater than the ground sound disaster threshold, and the previous effective rainfall is greater than the rainfall disaster threshold, an action-level early warning level is generated. When the early warning level is action-level, the fusion early warning module calculates the peak debris flow rate based on the regression model calibrated in the thematic research results. For example, a peak flow rate-rainfall intensity-ground sound signal intensity regression model is used, which includes: ; in, This represents the peak flow rate of the debris flow (m³ / s). The rainfall intensity is measured over a 10-minute period (mm / min). Let be the ground acoustic signal intensity (dimensionless, usually normalized amplitude or spectral energy); a, b, and c are model parameters calibrated in the special study, and b for I powers of, c for S The powers of , their values, and calibration methods are shown in the following table:

[0037] The total debris flow volume is calculated based on the relationship model determined by the special research results. For example, the total volume-peak flow-duration relationship model is used. The total volume-peak flow-duration relationship model includes: ; in, T represents the total debris flow volume, T represents the estimated duration of the debris flow (determined based on weather forecasts), and k and m are model parameters calibrated in the special study (for example, the value of k is generally in the range of 0.5~2.0, and the value of m is generally in the range of 0.8~1.5, which can be obtained by nonlinear regression fitting using measured total volume, peak flow and duration data of historical debris flow events). m for T The power of the value; the bulk density value of debris flow is directly adopted from the benchmark value of debris flow bulk density determined by the special research results, or dynamically corrected by combining real-time mud level data in multi-source monitoring data. The parameter calculation relies on the localized special research results to ensure the accuracy of prediction.

[0038] Optionally, such as Figure 1 As shown, the fast simulation module includes: A terrain model is used to generate a three-dimensional terrain mesh based on the watershed terrain data of the monitoring area described in the thematic research results when the warning level is action level. A hydrodynamic model is used to generate hydrodynamic parameters for the monitoring area based on the three-dimensional terrain grid, the debris flow prediction scale parameters, and the operational status of the monitoring area. A sediment transport model is used to generate sedimentation morphology parameters based on the aforementioned hydrodynamic conditions. A structural impact model is used to generate simulation parameters of the debris flow impact based on the sedimentation morphology parameters.

[0039] Specifically, the rapid simulation module consists of a terrain model, a hydrodynamic model, a sediment transport model, and a structural impact model, which are interconnected at each level. When the warning level is action level, the terrain model uses watershed terrain data from thematic research results to generate a three-dimensional terrain grid, providing a computational platform for subsequent simulations. The hydrodynamic model, based on the three-dimensional terrain grid, debris flow prediction scale parameters, and the operational status of the monitoring area, generates hydrodynamic parameters such as velocity field and water level field by solving two-dimensional shallow water equations. The operational status of the monitoring area includes the real-time reservoir water level. The sediment transport model, based on the hydrodynamic parameters, calculates and generates sedimentation morphology parameters, including sediment concentration field and sedimentation thickness, through non-uniform sediment transport equations. The structural impact model calculates and generates debris flow impact simulation parameters, including sedimentation distance in front of the intake and flow velocity in front of the spillway, based on the sedimentation morphology parameters. The data from the four models are passed down and calculated collaboratively at each level to achieve minute-level high-precision simulation of the impact of debris flow into the reservoir.

[0040] Optionally, such as Figure 1 As shown, the adaptive protection decision and execution subsystem includes: The protection plan database is used to store digital protection plans from the research findings of the aforementioned topic; The decision-making module is used to generate the protection strategy based on the digital protection plan and the debris flow impact simulation parameters; The execution module is used to convert the protection strategy into control commands and send them to the control system of the monitoring area.

[0041] Specifically, the adaptive protection decision-making and execution subsystem includes a protection plan library, a decision-making module, and an execution module. The protection plan library stores digital protection plans compiled from thematic research results, covering protection schemes under different disaster scenarios, such as plans to open floodgates to form diversion and sand flushing channels, plans to reduce unit load to prevent blockage, plans to activate emergency interception devices in front of the dam, and plans to combine unconventional gates with artificial circulation sand flushing. The decision-making module combines digital protection plans with debris flow impact simulation parameters and generates suitable protection strategies through analysis and matching. The execution module transforms the protection strategies into standardized control commands and issues them to the control systems of floodgates, power plants, and emergency facilities in the monitoring area to complete the automatic / semi-automatic execution of protection actions. The three components work together to complete the entire process of plan matching, strategy generation, and command execution.

[0042] Optionally, the decision module is specifically used for: The risk level is determined based on the safety thresholds in the aforementioned research findings and the debris flow impact simulation parameters. When the risk level is low, the first plan in the digital protection plan will be used as the protection strategy.

[0043] Specifically, the decision-making module first compares the simulated parameters of debris flow impact with the safety thresholds in the special research results to determine the current risk level of debris flow disaster. When the risk level is low, the decision-making module directly selects the first plan in the digital protection plan as the final protection strategy. The first plan is the basic protection plan under low-risk scenarios, with low execution cost, fast response speed, and can effectively suppress the impact of minor disasters.

[0044] For example, the first contingency plan could be: opening one floodgate to a 5m opening and running it for 4-6 hours to utilize the main stream to flush the ditch opening and suppress siltation.

[0045] Optionally, the decision module is further configured to: When the risk level is medium risk, the protection strategy is generated by performing multi-objective optimization calculations based on the second plan in the digital protection plan and according to the optimization objectives. When the risk level is high, the protection strategy is generated based on the third plan in the digital protection plan and multi-objective optimization calculation according to the optimization objectives.

[0046] Specifically, when the decision-making module determines the risk level to be medium risk, it uses the second contingency plan in the digital protection plan as a basis, and constructs an objective function using a linear weighted summation method, focusing on the optimization objectives of minimizing reservoir capacity loss, ensuring flood discharge capacity, and reducing power generation losses. The objective function is as follows: ;in, , , These are weighting coefficients and can be adjusted according to the importance of the project. =0.4、 =0.3、 =0.3, This is the normalized value of storage capacity loss. This is the normalized value of power generation loss. This is the normalized value for flood discharge risk.

[0047] Then, a multi-objective optimization calculation is carried out using a genetic algorithm or a particle swarm optimization algorithm to solve the objective function and generate an optimized protection strategy that is suitable for medium risk. When the risk level is high risk, the third plan in the digital protection plan is used as a basis to carry out multi-objective optimization calculation based on the same optimization objective to generate an enhanced protection strategy that is suitable for high risk. The hierarchical optimization and matching takes into account both prevention and control safety and reservoir operation efficiency.

[0048] For example, the second contingency plan could be: opening the central spillway gate to a 10m opening to create a guiding flow; automatically reducing the load of units #2 and #3 to 70%; lowering the alarm threshold for differential pressure monitoring of the intake trash rack; and initiating underwater topographic scanning in front of the dam. The third contingency plan could be: dynamically adjusting the opening and closing combination of the multi-gate system to create artificial circulation, guiding the high-concentration debris flow to a pre-set corner of the reservoir area; reducing the load of all units in the plant to 50%; and preparing to activate the emergency floating guide device in front of the dam. For example, the protection strategy generated according to the second contingency plan includes: immediately opening the #2 central spillway gate to an 8m opening; automatically reducing the load of units #2 and #3 to 80%; increasing the frame rate of the intake video monitoring and marking it as a key area of ​​concern.

[0049] Optionally, the watershed three-dimensional monitoring network is also used for: Obtain the actual status data of the monitoring area after the protection strategy is implemented; The early warning and analysis platform is also used for: When the actual state data and the debris flow impact simulation parameters exceed a preset threshold, new debris flow impact simulation parameters are generated. The adaptive protection decision and execution subsystem is also used for: Based on the new debris flow impact simulation parameters, the protection strategy is adjusted, and a new protection strategy is generated and implemented.

[0050] Specifically, after the protection strategy is implemented, the basin's three-dimensional monitoring network continuously collects actual status data such as reservoir water level, sedimentation morphology, fluid movement, and facility operation in the monitoring area. The early warning and analysis platform compares the actual status data with the debris flow impact simulation parameters. When the deviation exceeds a preset threshold, new debris flow impact simulation parameters are regenerated. The adaptive protection decision and execution subsystem adjusts the original protection strategy based on the new simulation parameters, generates and executes a new protection strategy, forming a closed-loop adaptive control of monitoring-simulation-decision-execution-feedback-adjustment, continuously optimizing the protection effect until the disaster risk is eliminated.

[0051] For example, this embodiment provides an adaptive protection method for debris flow entering the reservoir, corresponding to a debris flow early warning and adaptive protection system. The specific implementation steps are as follows: S0, Debris Flow Thematic Investigation and Research Stage: Conduct field surveys, experiments, and evaluations of the target debris flow gully to obtain thematic research results such as watershed topography, loose sediment sources, dynamic parameters, critical thresholds, and safety thresholds, forming a digital parameter database; S1, System Construction Stage: Deploy a watershed three-dimensional monitoring network based on thematic research results, calibrate a digital twin water and sediment model, and compile a protection plan database; S2, Routine Operation Stage: The three-dimensional monitoring network continuously collects data, integrates the early warning module to conduct real-time risk assessment, and outputs attention-level or alert-level signals; S3, Emergency Trigger Stage: Monitoring data reaches the thematic research... When critical conditions are investigated, the integrated early warning module issues an action-level early warning, and the system switches to emergency response mode; S4, rapid simulation and prediction stage, the rapid simulation module starts the digital twin model, combines real-time operating conditions and predicted scale parameters, and completes the simulation of the impact of debris flow into the reservoir within minutes; S5, intelligent decision generation stage, the decision module compares the simulation parameters with the safety threshold, and generates an adaptive protection instruction set through multi-objective optimization; S6, instruction execution and closed-loop control stage, the execution module issues protection instructions, the monitoring network provides real-time feedback on the actual status, the system continuously simulates and dynamically fine-tunes the strategy until the debris flow process ends, the risk is eliminated, and the system returns to normal operation. This method realizes the full-process closed-loop control of the activation of special research results, the precision of early warning simulation, and the adaptive protection decision.

[0052] This embodiment uses the Xingergou debris flow upstream of the Dahejia Hydropower Station on the Yellow River as a practical application scenario, and adopts a debris flow early warning and adaptive protection system for adaptive protection, specifically including: First, based on the special study on debris flow in Xing'ergou, core parameters were obtained, including a drainage area of ​​168.8 km², a main channel length of 29.02 km, a channel gradient of 68.4‰, a total loose sediment reserve of 198.15 million m³, an unstable sediment reserve of 15.98 million m³, a debris flow bulk density of 1.55 t / m³, a 10-minute critical rainfall intensity of 8 mm (yellow) / 10 mm (red), and a warning siltation distance of 50 m at the inlet. All results were converted into a digital parameter database. Based on the special study results, a three-dimensional monitoring network was deployed, consisting of space-based satellite remote sensing, UAV inspection, three upstream rain gauges, two midstream ground acoustic / infrasound composite instruments, radar flow measurement at the inlet, and high-definition video. Two-dimensional water and sediment measurements were calibrated using measured debris flow data from 1998. The model ensures that the sedimentation prediction error is less than 15%, and three-level digital protection plans (A, B, and C) are developed. In an emergency scenario, when short-term heavy rainfall in the Xingergou watershed reaches the critical condition, the integrated early warning module issues an action-level warning, estimating the peak flow of debris flow at approximately 400 m³ / s and the total solid volume at approximately 200,000 cubic meters. The rapid simulation module completes the simulation of the impact of the inflow within 3 minutes, and the decision-making module determines it as a medium risk and optimizes the execution of plan B. After the instruction is executed, the system uses the monitoring data at the inflow point to provide feedback for rolling simulation and fine-tuning of the gate opening. The debris flow process ends after 40 minutes, and the system automatically pushes the recovery instruction, restoring the unit and gate to normal operation. This fully verifies the accuracy, efficiency, and practicality of this system and method in actual debris flow prevention and control in reservoir areas.

[0053] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. In this application, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention according to actual needs. Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units can be implemented in hardware or as software functional units.

[0054] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A debris flow early warning and adaptive protection system, characterized in that, include: A three-dimensional watershed monitoring network is used to acquire multi-source monitoring data for the monitoring area; The early warning and analysis platform is used to perform early warning analysis based on the multi-source monitoring data and generate early warning levels; It is also used to generate debris flow prediction scale parameters when the warning level is action level, and to simulate the debris flow impact based on the debris flow prediction scale parameters and the operating status of the monitoring area to generate debris flow impact simulation parameters. An adaptive protection decision-making and execution subsystem is used to generate and execute protection strategies based on the protection plan library and the debris flow impact simulation parameters, wherein the protection plan library is constructed based on the results of special research.

2. The debris flow early warning and adaptive protection system according to claim 1, characterized in that, The basin-wide three-dimensional monitoring network includes: The space-based monitoring unit is used to acquire satellite remote sensing data from the multi-source monitoring data. An airborne monitoring unit is used to acquire terrain image data from the multi-source monitoring data via a drone. The ground monitoring unit is used to acquire rainfall data, ground acoustic data, video data, and radar data from the multi-source monitoring data.

3. The debris flow early warning and adaptive protection system according to claim 2, characterized in that, The ground monitoring unit is deployed based on the findings of the aforementioned thematic research and includes: An array of rain gauges deployed in the upper and middle reaches of the gullies in the monitoring area is used to acquire the rainfall data; Ground acoustic sensors deployed in the circulation area of ​​the monitoring area are used to acquire the ground acoustic data; A video and radar flow measurement device is deployed at the entrance of the monitoring area to acquire the video data and the radar data.

4. The debris flow early warning and adaptive protection system according to claim 1, characterized in that, The early warning and analysis platform includes: The integrated early warning module is used to perform early warning analysis based on the multi-source monitoring data, generate the early warning level, and generate the debris flow prediction scale parameter when the early warning level is action level. The rapid simulation module is used to simulate the debris flow impact parameters based on the debris flow prediction scale parameters and the operational status of the monitoring area when the warning level is action level.

5. The debris flow early warning and adaptive protection system according to claim 4, characterized in that, The debris flow prediction scale parameters include: peak debris flow rate, total debris flow volume, and debris flow unit weight. The fusion early warning module is specifically used for: Based on the multi-source monitoring data and the disaster thresholds in the thematic research results, an early warning analysis is performed to generate the early warning level; When the warning level is action level, the peak flow rate of the debris flow is generated based on the multi-source monitoring data and regression model, the total debris flow volume is generated based on the multi-source monitoring data and relationship model, and the bulk density value of the debris flow is generated based on the multi-source monitoring data and / or the bulk density benchmark value of the debris flow. The regression model, the relationship model, and the bulk density value of the debris flow are all determined by the results of the special research.

6. The debris flow early warning and adaptive protection system according to claim 4, characterized in that, The fast simulation module includes: A terrain model is used to generate a three-dimensional terrain mesh based on the watershed terrain data of the monitoring area described in the thematic research results when the warning level is action level. A hydrodynamic model is used to generate hydrodynamic parameters for the monitoring area based on the three-dimensional terrain grid, the debris flow prediction scale parameters, and the operational status of the monitoring area. A sediment transport model is used to generate sedimentation morphology parameters based on the aforementioned hydrodynamic conditions. A structural impact model is used to generate simulation parameters of the debris flow impact based on the sedimentation morphology parameters.

7. The debris flow early warning and adaptive protection system according to claim 1, characterized in that, The adaptive protection decision and execution subsystem includes: The protection plan database is used to store digital protection plans from the research findings of the aforementioned topic; The decision-making module is used to generate the protection strategy based on the digital protection plan and the debris flow impact simulation parameters; The execution module is used to convert the protection strategy into control commands and send them to the control system of the monitoring area.

8. The debris flow early warning and adaptive protection system according to claim 7, characterized in that, The decision-making module is specifically used for: The risk level is determined based on the safety thresholds in the aforementioned research findings and the debris flow impact simulation parameters. When the risk level is low, the first plan in the digital protection plan will be used as the protection strategy.

9. The debris flow early warning and adaptive protection system according to claim 8, characterized in that, The decision module is also used for: When the risk level is medium risk, the protection strategy is generated by performing multi-objective optimization calculations based on the second plan in the digital protection plan and according to the optimization objectives. When the risk level is high, the protection strategy is generated based on the third plan in the digital protection plan and multi-objective optimization calculation according to the optimization objectives.

10. The debris flow early warning and adaptive protection system according to any one of claims 1-9, characterized in that, The watershed three-dimensional monitoring network is also used for: Obtain the actual status data of the monitoring area after the protection strategy is implemented; The early warning and analysis platform is also used for: When the actual state data and the debris flow impact simulation parameters exceed a preset threshold, new debris flow impact simulation parameters are generated. The adaptive protection decision and execution subsystem is also used for: Based on the new debris flow impact simulation parameters, the protection strategy is adjusted, and a new protection strategy is generated and implemented.

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